Working version

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+soundfonts/FluidR3_GM.sf2 filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -0,0 +1,160 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/

Dockerfile

@@ -0,0 +1,13 @@
+FROM python:3.7
+
+RUN useradd -m -u 1000 user
+USER user
+ENV HOME=/home/user \
+	PATH=/home/user/.local/bin:$PATH
+
+WORKDIR $HOME/app
+COPY --chown=user . $HOME/app
+
+RUN pip install --no-cache-dir --upgrade -r $HOME/app/requirements.txt
+
+CMD ["flask", "run", "--host=0.0.0.0", "--port=7860"]

app.py

@@ -0,0 +1,53 @@
+from flask import Flask, render_template, jsonify, request
+import json
+import subprocess
+
+app = Flask(__name__)
+
+
+@app.route('/')
+def index():
+    return render_template('index.html')
+
+
+@app.route('/generate_midi', methods=['POST'])
+def generate_midi():
+    data = request.json
+    keep_tonality = data.get('keepTonality', False)
+    use_grid = data.get('useGrid', True)
+
+    arguments = ['python3', 'generate.py', 'models/LMD2/', 'static/',
+                 '--n', '1', '--no_audio']
+
+    if keep_tonality:
+        arguments.extend(['--z_file', 'static/0/z'])
+
+    if use_grid:
+        arguments.extend(['--s_file', 'static/0/structure.json'])
+
+    subprocess.run(arguments, capture_output=True, text=True)
+
+    filename = "generated.mid"
+    return jsonify({"filename": filename})
+
+
+@app.route('/save_json', methods=['POST'])
+def save_json():
+    data = request.json
+    filepath = 'static/0/structure.json'
+
+    with open(filepath, 'w') as file:
+        json.dump(data, file)
+
+    return jsonify(message="JSON saved successfully!")
+
+
+@app.route('/load_grid')
+def load_grid():
+    with open('static/0/structure.json', 'r') as file:
+        data = json.load(file)
+    return jsonify(data)
+
+
+if __name__ == '__main__':
+    app.run(debug=True)

constants.py

@@ -0,0 +1,60 @@
+from enum import Enum
+
+
+N_TRACKS = 4
+TRACKS = ['Drums', 'Bass', 'Guitar', 'Strings']
+
+# These defaults, which should not be changed, are set when the related 
+# variables in the YAML config file are not set. 
+DEFAULT_MIDI_PROGRAMS = {
+    'Drums': -1,
+    'Bass': 34,
+    'Guitar': 1,
+    'Strings': 83,
+}
+DEFAULT_SOUNDFONT_PATH = '/usr/share/soundfonts/FluidR3_GM.sf2'
+
+
+# Pitch tokens have values in the range [0, 130]. Tokens from 0 to 127 represent
+# MIDI pitches. Token 60 represents middle C (C4).
+# See https://www.inspiredacoustics.com/en/MIDI_note_numbers_and_center_frequencies
+# for the complete list of MIDI pitches.
+class PitchToken(Enum):
+    SOS = 128
+    EOS = 129
+    PAD = 130
+
+
+N_PITCH_TOKENS = 131
+MAX_PITCH_TOKEN = 127
+
+
+# Duration tokens have values in the range [0, 98]. Tokens from 0 to 95 have to
+# be interpreted as durations from 1 to 96 timesteps.
+class DurationToken(Enum):
+    SOS = 96
+    EOS = 97
+    PAD = 98
+
+
+N_DUR_TOKENS = 99
+MAX_DUR_TOKEN = 95
+
+
+# Dimension of (pitch, duration) token pair
+D_TOKEN_PAIR = N_PITCH_TOKENS + N_DUR_TOKENS
+
+# Number of maximum tokens stored in each timestep (14 + SOS and EOS)
+MAX_SIMU_TOKENS = 16
+
+
+# This enum contains edge type indices for each edge type
+class EdgeTypes(Enum):
+    TRACK = 0 # This has to be interpreted as the starting index
+    ONSET = N_TRACKS
+    NEXT = N_TRACKS + 1
+
+# N_TRACKS track types + 1 onset edge type + 1 next edge type
+N_EDGE_TYPES = N_TRACKS + 2
+
+

data.py

@@ -0,0 +1,271 @@
+import itertools
+import os
+
+import torch
+import numpy as np
+from torch_geometric.data import Dataset
+from torch_geometric.data import Data
+from torch_geometric.data.collate import collate
+
+import constants
+from constants import EdgeTypes
+
+
+def get_node_labels(s_tensor, ones_idxs):
+    # Build a tensor which has node labels in place of each activation in the
+    # stucture tensor
+    labels = torch.zeros_like(s_tensor, dtype=torch.long, 
+                              device=s_tensor.device)
+    n_nodes = len(ones_idxs[0])
+    labels[ones_idxs] = torch.arange(n_nodes, device=s_tensor.device)
+    return labels
+
+
+def get_track_edges(s_tensor, ones_idxs=None, node_labels=None):
+
+    track_edges = []
+
+    if ones_idxs is None:
+        # Indices where the binary structure tensor is active
+        ones_idxs = torch.nonzero(s_tensor, as_tuple=True)
+
+    if node_labels is None:
+        node_labels = get_node_labels(s_tensor, ones_idxs)
+
+    # For each track, add direct and inverse edges between consecutive nodes
+    for track in range(s_tensor.size(0)):
+        # List of active timesteps in the current track
+        tss = list(ones_idxs[1][ones_idxs[0] == track])
+        edge_type = EdgeTypes.TRACK.value + track
+        edges = [
+            # Edge tuple: (u, v, type, ts_distance). Zip is used to obtain
+            # consecutive active timesteps. Edges in different tracks have
+            # different types.
+            (node_labels[track, t1],
+             node_labels[track, t2], edge_type, t2 - t1)
+            for t1, t2 in zip(tss[:-1], tss[1:])
+        ]
+        inverse_edges = [(u, v, t, d) for (v, u, t, d) in edges]
+        track_edges.extend(edges + inverse_edges)
+
+    return torch.tensor(track_edges, dtype=torch.long)
+
+
+def get_onset_edges(s_tensor, ones_idxs=None, node_labels=None):
+
+    onset_edges = []
+    edge_type = EdgeTypes.ONSET.value
+
+    if ones_idxs is None:
+        # Indices where the binary structure tensor is active
+        ones_idxs = torch.nonzero(s_tensor, as_tuple=True)
+
+    if node_labels is None:
+        node_labels = get_node_labels(s_tensor, ones_idxs)
+
+    # Add direct and inverse edges between nodes played in the same timestep
+    for ts in range(s_tensor.size(1)):
+        # List of active tracks in the current timestep
+        tracks = list(ones_idxs[0][ones_idxs[1] == ts])
+        # Obtain all possible pairwise combinations of active tracks
+        combinations = list(itertools.combinations(tracks, 2))
+        edges = [
+            # Edge tuple: (u, v, type, ts_distance(=0)).
+            (node_labels[track1, ts], node_labels[track2, ts], edge_type, 0)
+            for track1, track2 in combinations
+        ]
+        inverse_edges = [(u, v, t, d) for (v, u, t, d) in edges]
+        onset_edges.extend(edges + inverse_edges)
+
+    return torch.tensor(onset_edges, dtype=torch.long)
+
+
+def get_next_edges(s_tensor, ones_idxs=None, node_labels=None):
+
+    next_edges = []
+    edge_type = EdgeTypes.NEXT.value
+
+    if ones_idxs is None:
+        # Indices where the binary structure tensor is active
+        ones_idxs = torch.nonzero(s_tensor, as_tuple=True)
+
+    if node_labels is None:
+        node_labels = get_node_labels(s_tensor, ones_idxs)
+
+    # List of active timesteps
+    tss = torch.nonzero(torch.any(s_tensor.bool(), dim=0)).squeeze()
+    if tss.dim() == 0:
+        return torch.tensor([], dtype=torch.long)
+
+    for i in range(tss.size(0)-1):
+        # Get consecutive active timesteps
+        t1, t2 = tss[i], tss[i+1]
+        # Get all the active tracks in the two timesteps
+        t1_tracks = ones_idxs[0][ones_idxs[1] == t1]
+        t2_tracks = ones_idxs[0][ones_idxs[1] == t2]
+
+        # Combine the source and destination tracks, removing combinations with
+        # the same source and destination track (since these represent track
+        # edges).
+        tracks_product = list(itertools.product(t1_tracks, t2_tracks))
+        tracks_product = [(track1, track2)
+                          for (track1, track2) in tracks_product
+                          if track1 != track2]
+        # Edge tuple: (u, v, type, ts_distance).
+        edges = [(node_labels[track1, t1], node_labels[track2, t2],
+                  edge_type, t2 - t1)
+                 for track1, track2 in tracks_product]
+
+        next_edges.extend(edges)
+
+    return torch.tensor(next_edges, dtype=torch.long)
+
+
+def get_track_features(s_tensor):
+
+    # Indices where the binary structure tensor is active
+    ones_idxs = torch.nonzero(s_tensor)
+
+    n_nodes = len(ones_idxs)
+    tracks = ones_idxs[:, 0]
+    n_tracks = s_tensor.size(0)
+
+    # The feature n_nodes x n_tracks tensor contains one-hot tracks
+    # representations for each node
+    features = torch.zeros((n_nodes, n_tracks))
+    features[torch.arange(n_nodes), tracks] = 1
+
+    return features
+
+
+def graph_from_tensor(s_tensor):
+
+    bars = []
+
+    # Iterate over bars and construct a graph for each bar
+    for i in range(s_tensor.size(0)):
+
+        bar = s_tensor[i]
+
+        # If the bar contains no activations, add a fake one to avoid having 
+        # to deal with empty graphs
+        if not torch.any(bar):
+            bar[0, 0] = 1
+
+        # Get edges from boolean activations
+        track_edges = get_track_edges(bar)
+        onset_edges = get_onset_edges(bar)
+        next_edges = get_next_edges(bar)
+        edges = [track_edges, onset_edges, next_edges]
+
+        # Concatenate edge tensors (N x 4) (if any)
+        is_edgeless = (len(track_edges) == 0 and
+                       len(onset_edges) == 0 and
+                       len(next_edges) == 0)
+        if not is_edgeless:
+            edge_list = torch.cat([x for x in edges
+                                   if torch.numel(x) > 0])
+
+        # Adapt tensor to torch_geometric's Data
+        # If no edges, add fake self-edge
+        # edge_list[:, :2] contains source and destination node labels
+        # edge_list[:, 2:] contains edge types and timestep distances
+        edge_index = (edge_list[:, :2].t().contiguous() if not is_edgeless else
+                      torch.LongTensor([[0], [0]]))
+        attrs = (edge_list[:, 2:] if not is_edgeless else
+                 torch.Tensor([[0, 0]]))
+
+        # Add one hot timestep distance to edge attributes
+        edge_attrs = torch.zeros(attrs.size(0), s_tensor.shape[-1] + 1)
+        edge_attrs[:, 0] = attrs[:, 0]
+        edge_attrs[torch.arange(edge_attrs.size(0)),
+                   attrs.long()[:, 1] + 1] = 1
+
+        node_features = get_track_features(bar)
+        is_drum = node_features[:, 0].bool()
+        num_nodes = torch.sum(bar, dtype=torch.long)
+
+        bars.append(Data(edge_index=edge_index, edge_attrs=edge_attrs,
+                         num_nodes=num_nodes, node_features=node_features,
+                         is_drum=is_drum).to(s_tensor.device))
+
+    # Merge the graphs corresponding to different bars into a single big graph
+    graph, _, _ = collate(
+        Data,
+        data_list=bars,
+        increment=True,
+        add_batch=True
+    )
+
+    # Change bars assignment vector name (otherwise, Dataloader's collate
+    # would overwrite graphs.batch)
+    graph.bars = graph.batch
+
+    return graph
+
+
+class PolyphemusDataset(Dataset):
+
+    def __init__(self, dir, n_bars=2):
+        self.dir = dir
+        self.files = list(os.scandir(self.dir))
+        self.len = len(self.files)
+        self.n_bars = n_bars
+
+    def __len__(self):
+        return self.len
+
+    def __getitem__(self, idx):
+
+        # Load tensors
+        sample_path = os.path.join(self.dir, self.files[idx].name)
+        data = np.load(sample_path)
+        c_tensor = torch.tensor(data["c_tensor"], dtype=torch.long)
+        s_tensor = torch.tensor(data["s_tensor"], dtype=torch.bool)
+
+        # From (n_tracks x n_timesteps x ...)
+        # to (n_bars x n_tracks x n_timesteps x ...)
+        c_tensor = c_tensor.reshape(c_tensor.shape[0], self.n_bars, -1,
+                                    c_tensor.shape[2], c_tensor.shape[3])
+        c_tensor = c_tensor.permute(1, 0, 2, 3, 4)
+        s_tensor = s_tensor.reshape(s_tensor.shape[0], self.n_bars, -1)
+        s_tensor = s_tensor.permute(1, 0, 2)
+
+        # From decimals to onehot (pitches)
+        pitches = c_tensor[..., 0]
+        onehot_p = torch.zeros(
+            (pitches.shape[0]*pitches.shape[1]*pitches.shape[2]*pitches.shape[3],
+             constants.N_PITCH_TOKENS),
+            dtype=torch.float32
+        )
+        onehot_p[torch.arange(0, onehot_p.shape[0]), pitches.reshape(-1)] = 1.
+        onehot_p = onehot_p.reshape(pitches.shape[0], pitches.shape[1],
+                                    pitches.shape[2], pitches.shape[3],
+                                    constants.N_PITCH_TOKENS)
+
+        # From decimals to onehot (durations)
+        durs = c_tensor[..., 1]
+        onehot_d = torch.zeros(
+            (durs.shape[0]*durs.shape[1]*durs.shape[2]*durs.shape[3],
+             constants.N_DUR_TOKENS),
+            dtype=torch.float32
+        )
+        onehot_d[torch.arange(0, onehot_d.shape[0]), durs.reshape(-1)] = 1.
+        onehot_d = onehot_d.reshape(durs.shape[0], durs.shape[1],
+                                    durs.shape[2], durs.shape[3],
+                                    constants.N_DUR_TOKENS)
+
+        # Concatenate pitches and durations
+        c_tensor = torch.cat((onehot_p, onehot_d), dim=-1)
+
+        # Build graph structure from structure tensor
+        graph = graph_from_tensor(s_tensor)
+
+        # Filter silences in order to get a sparse representation
+        c_tensor = c_tensor.reshape(-1, c_tensor.shape[-2], c_tensor.shape[-1])
+        c_tensor = c_tensor[s_tensor.reshape(-1).bool()]
+
+        graph.c_tensor = c_tensor
+        graph.s_tensor = s_tensor.float()
+
+        return graph

download_models.py

@@ -0,0 +1,30 @@
+import argparse
+import os
+
+from huggingface_hub import snapshot_download
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        description="Downloads Polyphemus' pretrained models from Hugging "
+        "Face."
+    )
+    parser.add_argument(
+        'models_dir',
+        type=str, help='Directory to store the pretrained models.'
+    )
+    
+    args = parser.parse_args()
+    
+    repo_id = 'EmanueleCosenza/polyphemus'
+
+    r = snapshot_download(
+        repo_id=repo_id,
+        local_dir=args.models_dir,
+        local_dir_use_symlinks=False    
+    )
+    print("Models successfully downloaded in {}".format(r))
+
+
+if __name__ == '__main__':
+    main()

download_soundfont.sh

@@ -0,0 +1,67 @@
+#!/bin/bash
+
+# Check if the target directory is specified
+if [ "$#" -ne 1 ]; then
+    echo "Usage: $0 <target_directory>"
+    exit 1
+fi
+
+# Set the target directory
+TARGET_DIR="$1"
+
+# Check if the target directory exists. If not, create it.
+if [ ! -d "$TARGET_DIR" ]; then
+    echo "Target directory $TARGET_DIR does not exist. Creating..."
+    mkdir -p "$TARGET_DIR"
+    if [ $? -ne 0 ]; then
+        echo "Error creating target directory $TARGET_DIR"
+        exit 1
+    fi
+fi
+
+# Check https://packages.ubuntu.com/jammy/all/fluid-soundfont-gm/download for a
+# complete list of mirrors
+URL="http://mirrors.kernel.org/ubuntu/pool/universe/f/fluid-soundfont/fluid-soundfont-gm_3.1-5.3_all.deb"
+
+# Download the deb package
+echo "Downloading the deb package..."
+wget -q $URL -O fluid-soundfont-gm.deb
+
+if [ $? -ne 0 ]; then
+    echo "Error downloading the deb package"
+    exit 1
+fi
+
+# Create a temporary directory
+TMP_DIR=$(mktemp -d)
+
+# Extract the data.tar.zst component from the deb package using ar
+echo "Extracting the data.tar.zst from the deb package..."
+ar -p fluid-soundfont-gm.deb data.tar.zst > $TMP_DIR/data.tar.zst
+
+if [ $? -ne 0 ]; then
+    echo "Error extracting the data.tar.zst component from the deb package"
+    rm -rf $TMP_DIR
+    exit 1
+fi
+
+echo "Extracting the contents of data.tar.zst..."
+unzstd -o $TMP_DIR/data.tar $TMP_DIR/data.tar.zst
+tar -xf $TMP_DIR/data.tar -C $TMP_DIR
+
+if [ $? -ne 0 ]; then
+    echo "Error extracting the contents of data.tar.zst"
+    rm -rf $TMP_DIR
+    exit 1
+fi
+
+# Find the .sf2 file and move it to the target directory
+echo "Moving the .sf2 file to $TARGET_DIR"
+find $TMP_DIR -type f -name '*.sf2' -exec mv {} $TARGET_DIR \;
+
+# Clean up
+rm -rf $TMP_DIR
+rm fluid-soundfont-gm.deb
+
+echo "Done."
+

generate.py

@@ -0,0 +1,284 @@
+import argparse
+import os
+import json
+import time
+import math
+
+import torch
+import os
+from matplotlib import pyplot as plt
+
+import generation_config
+import constants
+from model import VAE
+from utils import set_seed
+from utils import mtp_from_logits, muspy_from_mtp, set_seed
+from utils import print_divider
+from utils import loop_muspy_music, save_midi, save_audio
+from plots import plot_pianoroll, plot_structure
+
+
+def generate_music(vae, z, s_cond=None, s_tensor_cond=None):
+
+    # Decoder pass to get structure and content logits
+    s_logits, c_logits = vae.decoder(z, s_cond)
+
+    if s_tensor_cond is not None:
+        s_tensor = s_tensor_cond
+    else:
+        # Compute binary structure tensor from logits
+        s_tensor = vae.decoder._binary_from_logits(s_logits)
+
+    # Build (n_batches x n_bars x n_tracks x n_timesteps x Sigma x d_token)
+    # multitrack pianoroll tensor containing logits for each activation and
+    # hard silences elsewhere
+    mtp = mtp_from_logits(c_logits, s_tensor)
+
+    return mtp, s_tensor
+
+
+def save(mtp, dir, s_tensor=None, n_loops=1, audio=True, z=None,
+         looped_only=False, plot_proll=False, plot_struct=False):
+
+    n_bars = mtp.size(1)
+    resolution = mtp.size(3) // 4
+    # Clear matplotlib cache (this solves formatting problems with first plot)
+    plt.clf()
+
+    # Iterate over batches
+    for i in range(mtp.size(0)):
+
+        # Create the directory if it does not exist
+        save_dir = os.path.join(dir, str(i))
+        os.makedirs(save_dir, exist_ok=True)
+
+        if not looped_only:
+            # Generate MIDI song from multitrack pianoroll and save
+            muspy_song = muspy_from_mtp(mtp[i])
+            print("Saving MIDI sequence {} in {}...".format(str(i + 1), 
+                                                            save_dir))
+            save_midi(muspy_song, save_dir, name='generated')
+            if audio:
+                print("Saving audio sequence {} in {}...".format(str(i + 1),
+                                                                 save_dir))
+                save_audio(muspy_song, save_dir, name='generated')
+
+        if plot_proll:
+            plot_pianoroll(muspy_song, save_dir)
+
+        if plot_struct:
+            plot_structure(s_tensor[i].cpu(), save_dir)
+
+        if n_loops > 1:
+            # Copy the generated sequence n_loops times and save the looped
+            # MIDI and audio files
+            print("Saving MIDI sequence "
+                  "{} looped {} times in {}...".format(str(i + 1), n_loops,
+                                                       save_dir))
+            extended = loop_muspy_music(muspy_song, n_loops, 
+                                         n_bars, resolution)
+            save_midi(extended, save_dir, name='extended')
+            if audio:
+                print("Saving audio sequence "
+                      "{} looped {} times in {}...".format(str(i + 1), n_loops,
+                                                           save_dir))
+                save_audio(extended, save_dir, name='extended')
+        
+        # Save structure
+        with open(os.path.join(save_dir, 'structure.json'), 'wb') as file:
+            file.write(json.dumps(s_tensor[i].tolist()).encode('utf-8'))
+        
+        # Save z
+        if z[i] is not None:
+            torch.save(z[i], os.path.join(save_dir, 'z'))
+
+        print()
+
+
+def generate_z(bs, d_model, device):
+    shape = (bs, d_model)
+
+    z_norm = torch.normal(
+        torch.zeros(shape, device=device),
+        torch.ones(shape, device=device)
+    )
+
+    return z_norm
+
+
+def load_model(model_dir, device):
+
+    checkpoint = torch.load(os.path.join(model_dir, 'checkpoint'),
+                            map_location='cpu')
+    configuration = torch.load(os.path.join(model_dir, 'configuration'),
+                               map_location='cpu')
+
+    state_dict = checkpoint['model_state_dict']
+
+    model = VAE(**configuration['model'], device=device).to(device)
+    model.load_state_dict(state_dict)
+    model.eval()
+
+    return model, configuration
+
+
+def main():
+
+    parser = argparse.ArgumentParser(
+        description='Generates MIDI music with a trained model.'
+    )
+    parser.add_argument(
+        'model_dir',
+        type=str, help='Directory of the model.'
+    )
+    parser.add_argument(
+        'output_dir',
+        type=str,
+        help='Directory to save the generated MIDI files.'
+    )
+    parser.add_argument(
+        '--n',
+        type=int,
+        default=5,
+        help='Number of sequences to be generated. Default is 5.'
+    )
+    parser.add_argument(
+        '--n_loops',
+        type=int,
+        default=1,
+        help="If greater than 1, outputs an additional MIDI file containing "
+        "the sequence looped n_loops times."
+    )
+    parser.add_argument(
+        '--no_audio',
+        action='store_true',
+        default=False,
+        help="Flag to disable audio files generation."
+    )
+    parser.add_argument(
+        '--s_file',
+        type=str,
+        help='Path to the JSON file containing the binary structure tensor.'
+    )
+    parser.add_argument(
+        '--z_file',
+        type=str,
+        help=''
+    )
+    parser.add_argument(
+        '--z_change',
+        action='store_true',
+        default=False,
+        help=''
+    )
+    parser.add_argument(
+        '--use_gpu',
+        action='store_true',
+        default=False,
+        help='Flag to enable GPU usage.'
+    )
+    parser.add_argument(
+        '--gpu_id',
+        type=int,
+        default='0',
+        help='Index of the GPU to be used. Default is 0.'
+    )
+    parser.add_argument(
+        '--seed',
+        type=int
+    )
+
+    args = parser.parse_args()
+
+    if args.seed is not None:
+        set_seed(args.seed)
+    
+    audio = not args.no_audio
+
+    device = torch.device("cuda") if args.use_gpu else torch.device("cpu")
+    if args.use_gpu:
+        torch.cuda.set_device(args.gpu_id)
+
+    print_divider()
+    print("Loading the model on {} device...".format(device))
+
+    model, configuration = load_model(args.model_dir, device)
+
+    d_model = configuration['model']['d']
+    n_bars = configuration['model']['n_bars']
+    n_tracks = constants.N_TRACKS
+    n_timesteps = 4 * configuration['model']['resolution']
+    output_dir = args.output_dir
+
+    s, s_tensor = None, None
+
+    if args.s_file is not None:
+
+        print("Loading the structure tensor "
+              "from {}...".format(args.model_dir))
+
+        # Load structure tensor from file
+        with open(args.s_file, 'r') as f:
+            s_tensor = json.load(f)
+
+        s_tensor = torch.tensor(s_tensor, dtype=bool)
+
+        # Check structure dimensions
+        dims = list(s_tensor.size())
+        expected = [n_bars, n_tracks, n_timesteps]
+        if dims != expected:
+            if (len(dims) != len(expected) or dims[1:] != expected[1:]
+                    or dims[0] > n_bars):
+                raise ValueError(f"Loaded structure tensor dimensions {dims} "
+                                 f"do not match expected dimensions {expected}")
+            elif dims[0] > n_bars:
+                raise ValueError(f"First structure tensor dimension {dims[0]} "
+                                 f"is higher than {n_bars}")
+            else:
+                # Repeat partial structure tensor
+                r = math.ceil(n_bars / dims[0])
+                s_tensor = s_tensor.repeat(r, 1, 1)
+                s_tensor = s_tensor[:n_bars, ...]
+        
+        # Avoid empty bars by creating a fake activation for each empty
+        # (n_tracks x n_timesteps) bar matrix in position [0, 0]
+        empty_mask = ~s_tensor.any(dim=-1).any(dim=-1)
+        if empty_mask.any():
+            print("The provided structure tensor contains empty bars. Fake "
+                  "track activations will be created to avoid processing "
+                  "empty bars.")
+        idxs = torch.nonzero(empty_mask, as_tuple=True)
+        s_tensor[idxs + (0, 0)] = True
+        
+        # Repeat structure along new batch dimension
+        s_tensor = s_tensor.unsqueeze(0).repeat(args.n, 1, 1, 1)
+        
+        s = model.decoder._structure_from_binary(s_tensor)
+
+    print()
+    if args.z_file is not None:
+        print("Loading z...")
+        z = torch.load(args.z_file)
+        z = z.unsqueeze(0)
+        if args.z_change:
+            #e = 0.5
+            e = 0.5
+            z = z + e*(torch.rand(list(z.size())) - 0.5)
+    else:
+        print("Generating z...")
+        z = generate_z(args.n, d_model, device)
+
+    print("Generating music with the model...")
+    s_t = time.time()
+    mtp, s_tensor = generate_music(model, z, s, s_tensor)
+    print("Inference time: {:.3f} s".format(time.time() - s_t))
+
+    print()
+    print("Saving MIDI files in {}...\n".format(output_dir))
+    save(mtp, output_dir, s_tensor, args.n_loops, audio, z)
+    print("Finished saving MIDI files.")
+    print_divider()
+
+
+if __name__ == '__main__':
+    main()

generation_config.py

@@ -0,0 +1,19 @@
+import yaml
+from constants import DEFAULT_MIDI_PROGRAMS, DEFAULT_SOUNDFONT_PATH
+
+
+CONFIG_FILENAME = 'generation_config.yaml'
+
+
+def load_config(filename):
+    with open(filename, 'r') as f:
+        config = yaml.safe_load(f)
+        
+    return config
+
+
+config = load_config(CONFIG_FILENAME)
+
+
+MIDI_PROGRAMS = config.get('MIDI_PROGRAMS', DEFAULT_MIDI_PROGRAMS)
+SOUNDFONT_PATH = config.get('SOUNDFONT_PATH', DEFAULT_SOUNDFONT_PATH)

generation_config.yaml

@@ -0,0 +1,18 @@
+
+# These values indicate the MIDI programs used for each track. 
+# Possible values: [0, 127]
+# Check https://en.wikipedia.org/wiki/General_MIDI for a complete list 
+# of MIDI programs (remember to map values to the [0, 127] range).
+# The `drums` value is ignored (drums have a dedicated MIDI channel and each
+# program corresponds to a different drum sound). The guitar track typically 
+# plays accompaniment chords and it can also be intepreted as a 
+# piano/accompaniment track. The strings track typically contains a 
+# lead melody.
+MIDI_PROGRAMS:
+  Drums: -1
+  Bass: 34 # Electric Bass (picked)
+  Guitar: 4 # Electric Piano 1
+  Strings: 54 # Synth Voice
+
+# The path of the soundfont file needed to convert MIDI to audio
+SOUNDFONT_PATH: "soundfonts/FluidR3_GM.sf2"

model.py

@@ -0,0 +1,678 @@
+from typing import Union, Tuple
+
+import torch
+import torch.nn.functional as F
+from torch import nn, Tensor
+from torch_sparse import SparseTensor, masked_select_nnz
+from torch_geometric.typing import OptTensor, Adj
+from torch_geometric.nn.inits import reset
+from torch_geometric.nn.norm import BatchNorm
+from torch_geometric.nn.glob import GlobalAttention
+from torch_geometric.data import Batch
+from torch_geometric.nn.conv import RGCNConv
+
+import constants
+from data import graph_from_tensor
+
+
+@torch.jit._overload
+def masked_edge_index(edge_index, edge_mask):
+    # type: (Tensor, Tensor) -> Tensor
+    pass
+
+
+@torch.jit._overload
+def masked_edge_index(edge_index, edge_mask):
+    # type: (SparseTensor, Tensor) -> SparseTensor
+    pass
+
+
+def masked_edge_index(edge_index, edge_mask):
+    if isinstance(edge_index, Tensor):
+        return edge_index[:, edge_mask]
+    else:
+        return masked_select_nnz(edge_index, edge_mask, layout='coo')
+
+
+def masked_edge_attrs(edge_attrs, edge_mask):
+    return edge_attrs[edge_mask, :]
+
+
+class GCL(RGCNConv):
+
+    def __init__(self, in_channels, out_channels, num_relations, nn,
+                 dropout=0.1, **kwargs):
+        super().__init__(in_channels=in_channels, out_channels=out_channels,
+                         num_relations=num_relations, **kwargs)
+        self.nn = nn
+        self.dropout = dropout
+
+        self.reset_edge_nn()
+
+    def reset_edge_nn(self):
+        reset(self.nn)
+
+    def forward(self, x: Union[OptTensor, Tuple[OptTensor, Tensor]],
+                edge_index: Adj, edge_type: OptTensor = None,
+                edge_attr: OptTensor = None):
+
+        # Convert input features to a pair of node features or node indices.
+        x_l: OptTensor = None
+        if isinstance(x, tuple):
+            x_l = x[0]
+        else:
+            x_l = x
+        if x_l is None:
+            x_l = torch.arange(self.in_channels_l, device=self.weight.device)
+
+        x_r: Tensor = x_l
+        if isinstance(x, tuple):
+            x_r = x[1]
+
+        size = (x_l.size(0), x_r.size(0))
+
+        if isinstance(edge_index, SparseTensor):
+            edge_type = edge_index.storage.value()
+        assert edge_type is not None
+
+        # propagate_type: (x: Tensor)
+        out = torch.zeros(x_r.size(0), self.out_channels, device=x_r.device)
+        weight = self.weight
+
+        # Basis-decomposition
+        if self.num_bases is not None:
+            weight = (self.comp @ weight.view(self.num_bases, -1)).view(
+                self.num_relations, self.in_channels_l, self.out_channels)
+
+        # Block-diagonal-decomposition
+        if self.num_blocks is not None:
+
+            if x_l.dtype == torch.long and self.num_blocks is not None:
+                raise ValueError('Block-diagonal decomposition not supported '
+                                 'for non-continuous input features.')
+
+            for i in range(self.num_relations):
+                tmp = masked_edge_index(edge_index, edge_type == i)
+                h = self.propagate(tmp, x=x_l, size=size)
+                h = h.view(-1, weight.size(1), weight.size(2))
+                h = torch.einsum('abc,bcd->abd', h, weight[i])
+                out += h.contiguous().view(-1, self.out_channels)
+
+        else:
+            # No regularization/Basis-decomposition
+            for i in range(self.num_relations):
+                tmp = masked_edge_index(edge_index, edge_type == i)
+                attr = masked_edge_attrs(edge_attr, edge_type == i)
+
+                if x_l.dtype == torch.long:
+                    out += self.propagate(tmp, x=weight[i, x_l], size=size)
+                else:
+                    h = self.propagate(tmp, x=x_l, size=size,
+                                       edge_attr=attr)
+                    out = out + (h @ weight[i])
+
+        root = self.root
+        if root is not None:
+            out += root[x_r] if x_r.dtype == torch.long else x_r @ root
+
+        if self.bias is not None:
+            out += self.bias
+
+        return out
+
+    def message(self, x_j: Tensor, edge_attr: Tensor) -> Tensor:
+
+        # Use edge nn to compute weight tensor from edge attributes
+        # (=onehot timestep distances between nodes)
+        weights = self.nn(edge_attr)
+        weights = weights[..., :self.in_channels_l]
+        weights = weights.view(-1, self.in_channels_l)
+
+        out = x_j * weights
+        out = F.relu(out)
+        out = F.dropout(out, p=self.dropout, training=self.training)
+
+        return out
+
+
+class MLP(nn.Module):
+
+    def __init__(self, input_dim=256, hidden_dim=256, output_dim=256,
+                 num_layers=2, activation=True, dropout=0.1):
+        super().__init__()
+
+        self.layers = nn.ModuleList()
+
+        if num_layers == 1:
+            self.layers.append(nn.Linear(input_dim, output_dim))
+        else:
+            # Input layer (1) + Intermediate layers (n-2) + Output layer (1)
+            self.layers.append(nn.Linear(input_dim, hidden_dim))
+            for _ in range(num_layers - 2):
+                self.layers.append(nn.Linear(hidden_dim, hidden_dim))
+            self.layers.append(nn.Linear(hidden_dim, output_dim))
+
+        self.activation = activation
+        self.p = dropout
+
+    def forward(self, x):
+        for layer in self.layers:
+            x = F.dropout(x, p=self.p, training=self.training)
+            x = layer(x)
+            if self.activation:
+                x = F.relu(x)
+        return x
+
+
+class GCN(nn.Module):
+
+    def __init__(self, input_dim=256, hidden_dim=256, n_layers=3,
+                 num_relations=3, num_dists=32, batch_norm=False, dropout=0.1):
+        super().__init__()
+
+        self.layers = nn.ModuleList()
+        self.norm_layers = nn.ModuleList()
+        edge_nn = nn.Linear(num_dists, input_dim)
+        self.batch_norm = batch_norm
+
+        self.layers.append(GCL(input_dim, hidden_dim, num_relations, edge_nn))
+        if self.batch_norm:
+            self.norm_layers.append(BatchNorm(hidden_dim))
+
+        for i in range(n_layers-1):
+            self.layers.append(GCL(hidden_dim, hidden_dim,
+                                   num_relations, edge_nn))
+            if self.batch_norm:
+                self.norm_layers.append(BatchNorm(hidden_dim))
+
+        self.p = dropout
+
+    def forward(self, data):
+
+        x, edge_index, edge_attrs = data.x, data.edge_index, data.edge_attrs
+        edge_type = edge_attrs[:, 0]
+        edge_attr = edge_attrs[:, 1:]
+
+        for i in range(len(self.layers)):
+
+            residual = x
+            x = F.dropout(x, p=self.p, training=self.training)
+            x = self.layers[i](x, edge_index, edge_type, edge_attr)
+
+            if self.batch_norm:
+                x = self.norm_layers[i](x)
+
+            x = F.relu(x)
+            x = residual + x
+
+        return x
+
+
+class CNNEncoder(nn.Module):
+
+    def __init__(self, output_dim=256, dense_dim=256, batch_norm=False,
+                 dropout=0.1):
+        super().__init__()
+
+        # Convolutional layers
+        if batch_norm:
+            self.conv = nn.Sequential(
+                # From (4 x 32) to (8 x 4 x 32)
+                nn.Conv2d(1, 8, 3, padding=1),
+                nn.BatchNorm2d(8),
+                nn.ReLU(True),
+                # From (8 x 4 x 32) to (8 x 4 x 8)
+                nn.MaxPool2d((1, 4), stride=(1, 4)),
+                # From (8 x 4 x 8) to (16 x 4 x 8)
+                nn.Conv2d(8, 16, 3, padding=1),
+                nn.BatchNorm2d(16),
+                nn.ReLU(True)
+            )
+        else:
+            self.conv = nn.Sequential(
+                nn.Conv2d(1, 8, 3, padding=1),
+                nn.ReLU(True),
+                nn.MaxPool2d((1, 4), stride=(1, 4)),
+                nn.Conv2d(8, 16, 3, padding=1),
+                nn.ReLU(True)
+            )
+
+        self.flatten = nn.Flatten(start_dim=1)
+
+        # Linear layers
+        self.lin = nn.Sequential(
+            nn.Dropout(dropout),
+            nn.Linear(16 * 4 * 8, dense_dim),
+            nn.ReLU(True),
+            nn.Dropout(dropout),
+            nn.Linear(dense_dim, output_dim)
+        )
+
+    def forward(self, x):
+        x = x.unsqueeze(1)
+        x = self.conv(x)
+        x = self.flatten(x)
+        x = self.lin(x)
+        return x
+
+
+class CNNDecoder(nn.Module):
+
+    def __init__(self, input_dim=256, dense_dim=256, batch_norm=False,
+                 dropout=0.1):
+        super().__init__()
+
+        # Linear decompressors
+        self.lin = nn.Sequential(
+            nn.Dropout(dropout),
+            nn.Linear(input_dim, dense_dim),
+            nn.ReLU(True),
+            nn.Dropout(dropout),
+            nn.Linear(dense_dim, 16 * 4 * 8),
+            nn.ReLU(True)
+        )
+
+        self.unflatten = nn.Unflatten(dim=1, unflattened_size=(16, 4, 8))
+
+        # Upsample and convolutional layers
+        if batch_norm:
+            self.conv = nn.Sequential(
+                nn.Upsample(scale_factor=(1, 4), mode='nearest'),
+                nn.Conv2d(16, 8, 3, padding=1),
+                nn.BatchNorm2d(8),
+                nn.ReLU(True),
+                nn.Conv2d(8, 1, 3, padding=1)
+            )
+        else:
+            self.conv = nn.Sequential(
+                nn.Upsample(scale_factor=(1, 4), mode='nearest'),
+                nn.Conv2d(16, 8, 3, padding=1),
+                nn.ReLU(True),
+                nn.Conv2d(8, 1, 3, padding=1)
+            )
+
+    def forward(self, x):
+        x = self.lin(x)
+        x = self.unflatten(x)
+        x = self.conv(x)
+        x = x.unsqueeze(1)
+        return x
+
+
+class ContentEncoder(nn.Module):
+
+    def __init__(self, **kwargs):
+        super().__init__()
+        self.__dict__.update(kwargs)
+
+        self.dropout_layer = nn.Dropout(p=self.dropout)
+
+        # Pitch and duration embedding layers (separate layers for drums
+        # and non drums)
+        self.non_drums_pitch_emb = nn.Linear(constants.N_PITCH_TOKENS, 
+                                             self.d//2)
+        self.drums_pitch_emb = nn.Linear(constants.N_PITCH_TOKENS, self.d//2)
+        self.dur_emb = nn.Linear(constants.N_DUR_TOKENS, self.d//2)
+
+        # Batch norm layers
+        self.bn_non_drums = nn.BatchNorm1d(num_features=self.d//2)
+        self.bn_drums = nn.BatchNorm1d(num_features=self.d//2)
+        self.bn_dur = nn.BatchNorm1d(num_features=self.d//2)
+
+        self.chord_encoder = nn.Linear(
+            self.d * (constants.MAX_SIMU_TOKENS-1), self.d)
+
+        self.graph_encoder = GCN(
+            dropout=self.dropout,
+            input_dim=self.d,
+            hidden_dim=self.d,
+            n_layers=self.gnn_n_layers,
+            num_relations=constants.N_EDGE_TYPES,
+            batch_norm=self.batch_norm
+        )
+
+        # Soft attention node-aggregation layer
+        gate_nn = nn.Sequential(
+            MLP(input_dim=self.d, output_dim=1, num_layers=1,
+                activation=False, dropout=self.dropout),
+            nn.BatchNorm1d(1)
+        )
+        self.graph_attention = GlobalAttention(gate_nn)
+
+        self.bars_encoder = nn.Linear(self.n_bars * self.d, self.d)
+    
+    def forward(self, graph):
+        
+        c_tensor = graph.c_tensor
+
+        # Discard SOS token
+        c_tensor = c_tensor[:, 1:, :]
+
+        # Get drums and non drums tensors
+        drums = c_tensor[graph.is_drum]
+        non_drums = c_tensor[torch.logical_not(graph.is_drum)]
+
+        # Compute drums embeddings
+        sz = drums.size()
+        drums_pitch = self.drums_pitch_emb(
+            drums[..., :constants.N_PITCH_TOKENS])
+        drums_pitch = self.bn_drums(drums_pitch.view(-1, self.d//2))
+        drums_pitch = drums_pitch.view(sz[0], sz[1], self.d//2)
+        drums_dur = self.dur_emb(drums[..., constants.N_PITCH_TOKENS:])
+        drums_dur = self.bn_dur(drums_dur.view(-1, self.d//2))
+        drums_dur = drums_dur.view(sz[0], sz[1], self.d//2)
+        drums = torch.cat((drums_pitch, drums_dur), dim=-1)
+        # n_nodes x MAX_SIMU_TOKENS x d
+
+        # Compute non drums embeddings
+        sz = non_drums.size()
+        non_drums_pitch = self.non_drums_pitch_emb(
+            non_drums[..., :constants.N_PITCH_TOKENS]
+        )
+        non_drums_pitch = self.bn_non_drums(non_drums_pitch.view(-1, self.d//2))
+        non_drums_pitch = non_drums_pitch.view(sz[0], sz[1], self.d//2)
+        non_drums_dur = self.dur_emb(non_drums[..., constants.N_PITCH_TOKENS:])
+        non_drums_dur = self.bn_dur(non_drums_dur.view(-1, self.d//2))
+        non_drums_dur = non_drums_dur.view(sz[0], sz[1], self.d//2)
+        non_drums = torch.cat((non_drums_pitch, non_drums_dur), dim=-1)
+        # n_nodes x MAX_SIMU_TOKENS x d
+
+        # Compute chord embeddings (drums and non drums)
+        drums = self.chord_encoder(
+            drums.view(-1, self.d * (constants.MAX_SIMU_TOKENS-1))
+        )
+        non_drums = self.chord_encoder(
+            non_drums.view(-1, self.d * (constants.MAX_SIMU_TOKENS-1))
+        )
+        drums = F.relu(drums)
+        non_drums = F.relu(non_drums)
+        drums = self.dropout_layer(drums)
+        non_drums = self.dropout_layer(non_drums)
+        # n_nodes x d
+
+        # Merge drums and non drums
+        out = torch.zeros((c_tensor.size(0), self.d), device=self.device,
+                          dtype=drums.dtype)
+        out[graph.is_drum] = drums
+        out[torch.logical_not(graph.is_drum)] = non_drums
+        # n_nodes x d
+
+        # Set initial graph node states to intermediate chord representations 
+        # and pass through GCN
+        graph.x = out
+        graph.distinct_bars = graph.bars + self.n_bars*graph.batch
+        out = self.graph_encoder(graph)
+        # n_nodes x d
+
+        # Aggregate final node states into bar encodings with soft attention
+        with torch.cuda.amp.autocast(enabled=False):
+            out = self.graph_attention(out, batch=graph.distinct_bars)
+        # bs x n_bars x d
+
+        out = out.view(-1, self.n_bars * self.d)
+        # bs x (n_bars*d)
+        z_c = self.bars_encoder(out)
+        # bs x d
+        
+        return z_c
+
+
+class StructureEncoder(nn.Module):
+
+    def __init__(self, **kwargs):
+        super().__init__()
+        self.__dict__.update(kwargs)
+
+        self.cnn_encoder = CNNEncoder(
+            dense_dim=self.d,
+            output_dim=self.d,
+            dropout=self.dropout,
+            batch_norm=self.batch_norm
+        )
+        self.bars_encoder = nn.Linear(self.n_bars * self.d, self.d)
+    
+    def forward(self, graph):
+        
+        s_tensor = graph.s_tensor
+        out = self.cnn_encoder(s_tensor.view(-1, constants.N_TRACKS,
+                                             self.resolution * 4))
+        # (bs*n_bars) x d
+        out = out.view(-1, self.n_bars * self.d)
+        # bs x (n_bars*d)
+        z_s = self.bars_encoder(out)
+        # bs x d
+
+        return z_s
+    
+
+class Encoder(nn.Module):
+
+    def __init__(self, **kwargs):
+        super().__init__()
+        self.__dict__.update(kwargs)
+
+        self.s_encoder = StructureEncoder(**kwargs)
+        self.c_encoder = ContentEncoder(**kwargs)
+
+        self.dropout_layer = nn.Dropout(p=self.dropout)
+
+        # Linear layer that merges content and structure representations
+        self.linear_merge = nn.Linear(2*self.d, self.d)
+        self.bn_linear_merge = nn.BatchNorm1d(num_features=self.d)
+
+        self.linear_mu = nn.Linear(self.d, self.d)
+        self.linear_log_var = nn.Linear(self.d, self.d)
+
+    def forward(self, graph):
+        
+        z_s = self.s_encoder(graph)
+        z_c = self.c_encoder(graph)
+        
+        # Merge content and structure representations
+        z_g = torch.cat((z_c, z_s), dim=1)
+        z_g = self.dropout_layer(z_g)
+        z_g = self.linear_merge(z_g)
+        z_g = self.bn_linear_merge(z_g)
+        z_g = F.relu(z_g)
+
+        # Compute mu and log(std^2)
+        z_g = self.dropout_layer(z_g)
+        mu = self.linear_mu(z_g)
+        log_var = self.linear_log_var(z_g)
+
+        return mu, log_var
+
+
+class StructureDecoder(nn.Module):
+
+    def __init__(self, **kwargs):
+        super().__init__()
+        self.__dict__.update(kwargs)
+
+        self.bars_decoder = nn.Linear(self.d, self.d * self.n_bars)
+        self.cnn_decoder = CNNDecoder(
+            input_dim=self.d,
+            dense_dim=self.d,
+            dropout=self.dropout,
+            batch_norm=self.batch_norm
+        )
+
+    def forward(self, z_s):
+        # z_s: bs x d
+        out = self.bars_decoder(z_s)  # bs x (n_bars*d)
+        out = self.cnn_decoder(out.reshape(-1, self.d))
+        out = out.view(z_s.size(0), self.n_bars, constants.N_TRACKS, -1)
+        return out
+
+
+class ContentDecoder(nn.Module):
+
+    def __init__(self, **kwargs):
+        super().__init__()
+        self.__dict__.update(kwargs)
+
+        self.bars_decoder = nn.Linear(self.d, self.d * self.n_bars)
+
+        self.graph_decoder = GCN(
+            dropout=self.dropout,
+            input_dim=self.d,
+            hidden_dim=self.d,
+            n_layers=self.gnn_n_layers,
+            num_relations=constants.N_EDGE_TYPES,
+            batch_norm=self.batch_norm
+        )
+
+        self.chord_decoder = nn.Linear(
+            self.d, self.d*(constants.MAX_SIMU_TOKENS-1))
+
+        # Pitch and duration (un)embedding linear layers
+        self.drums_pitch_emb = nn.Linear(self.d//2, constants.N_PITCH_TOKENS)
+        self.non_drums_pitch_emb = nn.Linear(
+            self.d//2, constants.N_PITCH_TOKENS)
+        self.dur_emb = nn.Linear(self.d//2, constants.N_DUR_TOKENS)
+
+        self.dropout_layer = nn.Dropout(p=self.dropout)
+
+    def forward(self, z_c, s):
+
+        out = self.bars_decoder(z_c)  # bs x (n_bars*d)
+
+        # Initialize node features with corresponding z_bar
+        # and propagate with GNN
+        s.distinct_bars = s.bars + self.n_bars*s.batch
+        _, counts = torch.unique(s.distinct_bars, return_counts=True)
+        out = out.view(-1, self.d)
+        out = torch.repeat_interleave(out, counts, axis=0)  # n_nodes x d
+        s.x = out
+        out = self.graph_decoder(s)  # n_nodes x d
+
+        out = self.chord_decoder(out)  # n_nodes x (MAX_SIMU_TOKENS*d)
+        out = out.view(-1, constants.MAX_SIMU_TOKENS-1, self.d)
+
+        drums = out[s.is_drum]  # n_nodes_drums x MAX_SIMU_TOKENS x d
+        non_drums = out[torch.logical_not(s.is_drum)]
+        # n_nodes_non_drums x MAX_SIMU_TOKENS x d
+
+        # Obtain final pitch and dur logits (softmax will be applied
+        # outside forward)
+        non_drums = self.dropout_layer(non_drums)
+        drums = self.dropout_layer(drums)
+
+        drums_pitch = self.drums_pitch_emb(drums[..., :self.d//2])
+        drums_dur = self.dur_emb(drums[..., self.d//2:])
+        drums = torch.cat((drums_pitch, drums_dur), dim=-1)
+        # n_nodes_drums x MAX_SIMU_TOKENS x d_token
+
+        non_drums_pitch = self.non_drums_pitch_emb(non_drums[..., :self.d//2])
+        non_drums_dur = self.dur_emb(non_drums[..., self.d//2:])
+        non_drums = torch.cat((non_drums_pitch, non_drums_dur), dim=-1)
+        # n_nodes_non_drums x MAX_SIMU_TOKENS x d_token
+
+        # Merge drums and non-drums in the final output tensor
+        d_token = constants.D_TOKEN_PAIR
+        out = torch.zeros((s.num_nodes, constants.MAX_SIMU_TOKENS-1, d_token),
+                          device=self.device, dtype=drums.dtype)
+        out[s.is_drum] = drums
+        out[torch.logical_not(s.is_drum)] = non_drums
+
+        return out
+
+
+class Decoder(nn.Module):
+
+    def __init__(self, **kwargs):
+        super().__init__()
+        self.__dict__.update(kwargs)
+
+        self.lin_decoder = nn.Linear(self.d, 2 * self.d)
+        self.batch_norm = nn.BatchNorm1d(num_features=2*self.d)
+        self.dropout = nn.Dropout(p=self.dropout)
+
+        self.s_decoder = StructureDecoder(**kwargs)
+        self.c_decoder = ContentDecoder(**kwargs)
+
+        self.sigmoid_thresh = 0.5
+
+    def _structure_from_binary(self, s_tensor):
+
+        # Create graph structures for each batch
+        s = []
+        for i in range(s_tensor.size(0)):
+            s.append(graph_from_tensor(s_tensor[i]))
+
+        # Create batch of graphs from single graphs
+        s = Batch.from_data_list(s, exclude_keys=['batch'])
+        s = s.to(next(self.parameters()).device)
+
+        return s
+
+    def _binary_from_logits(self, s_logits):
+
+        # Hard threshold instead of sampling gives more pleasant results
+        s_tensor = torch.sigmoid(s_logits)
+        s_tensor[s_tensor >= self.sigmoid_thresh] = 1
+        s_tensor[s_tensor < self.sigmoid_thresh] = 0
+        s_tensor = s_tensor.bool()
+        
+        # Avoid empty bars by creating a fake activation for each empty
+        # (n_tracks x n_timesteps) bar matrix in position [0, 0]
+        empty_mask = ~s_tensor.any(dim=-1).any(dim=-1)
+        idxs = torch.nonzero(empty_mask, as_tuple=True)
+        s_tensor[idxs + (0, 0)] = True
+
+        return s_tensor
+
+    def _structure_from_logits(self, s_logits):
+
+        # Compute binary structure tensor from logits and build torch geometric
+        # structure from binary tensor
+        s_tensor = self._binary_from_logits(s_logits)
+        s = self._structure_from_binary(s_tensor)
+
+        return s
+
+    def forward(self, z, s=None):
+
+        # Obtain z_s and z_c from z
+        z = self.lin_decoder(z)
+        z = self.batch_norm(z)
+        z = F.relu(z)
+        z = self.dropout(z)  # bs x (2*d)
+        z_s, z_c = z[:, :self.d], z[:, self.d:]
+
+        # Obtain the tensor containing structure logits
+        s_logits = self.s_decoder(z_s)
+
+        if s is None:
+            # Build torch geometric graph structure from structure logits.
+            # This step involves non differentiable operations.
+            # No gradients pass through here.
+            s = self._structure_from_logits(s_logits.detach())
+
+        # Obtain the tensor containing content logits
+        c_logits = self.c_decoder(z_c, s)
+
+        return s_logits, c_logits
+
+
+class VAE(nn.Module):
+
+    def __init__(self, **kwargs):
+        super().__init__()
+        self.encoder = Encoder(**kwargs)
+        self.decoder = Decoder(**kwargs)
+
+    def forward(self, graph):
+
+        # Encoder pass
+        mu, log_var = self.encoder(graph)
+
+        # Reparameterization trick
+        z = torch.exp(0.5 * log_var)
+        z = z * torch.randn_like(z)
+        z = z + mu
+
+        # Decoder pass
+        out = self.decoder(z, graph)
+
+        return out, mu, log_var

models/.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+LMD16/checkpoint filter=lfs diff=lfs merge=lfs -text
+LMD2/checkpoint filter=lfs diff=lfs merge=lfs -text

models/LMD2/checkpoint

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+version https://git-lfs.github.com/spec/v1
+oid sha256:657b1de2d4de3a4dc94c63616784bd9142ee55db1e5f33912d0ea263c2aa973e
+size 661667674

models/README.md

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+---
+license: mit
+tags:
+- music
+- generation
+- symbolic music
+---
+
+# polyphemus
+
+A graph-based deep MIDI music generator. Official model repository of the [paper](https://arxiv.org/abs/2307.14928) "Graph-based Polyphonic Multitrack Music Generation".
+
+You can listen to the samples generated in the experimental phase in the dedicated [site](https://emanuelecosenza.github.io/polyphemus/).
+
+The repository contains two models: `LMD2`, a model that generates short 2-bar of music, and `LMD16`, a model that generates longer 16-bar sequences.
+Refer to the GitHub [repo](https://github.com/EmanueleCosenza/polyphemus) for instructions on how to use these models.

plots.py

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+import os
+
+from matplotlib import pyplot as plt
+import matplotlib as mpl
+import muspy
+import torch
+
+import constants
+
+
+def plot_pianoroll(muspy_song, save_dir=None, name='pianoroll'):
+
+    lines_linewidth = 4
+    axes_linewidth = 4
+    font_size = 34
+    fformat = 'png'
+    xticklabel = False
+    label = 'y'
+    figsize = (20, 10)
+    dpi = 200
+
+    with mpl.rc_context({'lines.linewidth': lines_linewidth,
+                         'axes.linewidth': axes_linewidth,
+                         'font.size': font_size}):
+
+        fig, axs_ = plt.subplots(constants.N_TRACKS, sharex=True,
+                                 figsize=figsize)
+        fig.subplots_adjust(hspace=0)
+        axs = axs_.tolist()
+        muspy.show_pianoroll(music=muspy_song, yticklabel='off', xtick='off',
+                             label=label, xticklabel=xticklabel,
+                             grid_axis='off', axs=axs, preset='full')
+
+        if save_dir:
+            plt.savefig(os.path.join(save_dir, name + "." + fformat),
+                        format=fformat, dpi=dpi)
+
+
+def plot_structure(s_tensor, save_dir=None, name='structure'):
+
+    lines_linewidth = 1
+    axes_linewidth = 1
+    font_size = 14
+    fformat = 'svg'
+    dpi = 200
+
+    n_bars = s_tensor.shape[0]
+    figsize = (3 * n_bars, 3)
+
+    n_timesteps = s_tensor.size(2)
+    resolution = n_timesteps // 4
+    s_tensor = s_tensor.permute(1, 0, 2)
+    s_tensor = s_tensor.reshape(s_tensor.shape[0], -1)
+
+    with mpl.rc_context({'lines.linewidth': lines_linewidth,
+                         'axes.linewidth': axes_linewidth,
+                         'font.size': font_size}):
+
+        plt.figure(figsize=figsize)
+        plt.pcolormesh(s_tensor, edgecolors='k', linewidth=1)
+        ax = plt.gca()
+
+        plt.xticks(range(0, s_tensor.shape[1], resolution),
+                   range(1, 4*n_bars + 1))
+        plt.yticks(range(0, s_tensor.shape[0]), constants.TRACKS)
+
+        ax.invert_yaxis()
+
+        if save_dir:
+            plt.savefig(os.path.join(save_dir, name + "." + fformat),
+                        format=fformat, dpi=dpi)
+    
+    
+def plot_stats(stat_names, stats_tr, stats_val=None, eval_every=None, 
+               labels=None, rx=None, ry=None):
+
+    for i, stat in enumerate(stat_names):
+
+        label = stat if not labels else labels[i]
+
+        plt.plot(range(1, len(stats_tr[stat])+1), stats_tr[stat],
+                label=label+' (TR)')
+
+        if stats_val:
+            plt.plot(range(eval_every, len(stats_tr[stat])+1, eval_every),
+                    stats_val[stat], '.', label=label+' (VL)')
+
+    plt.grid()
+
+    plt.ylim(ry) if ry else plt.ylim(0)
+    plt.xlim(rx) if rx else plt.xlim(0)
+
+    plt.legend()
+
+
+# Dictionary that maps loss statistic name to plot label 
+loss_labels = {
+    'tot': 'Total Loss',
+    'structure': 'Structure',
+    'pitch': 'Pitches',
+    'dur': 'Duration',
+    'reconstruction': 'Reconstruction Term',
+    'kld': 'KLD',
+    'beta*kld': 'beta * KLD'
+}
+
+
+def plot_losses(model_dir, losses, plot_val=False):
+    
+    checkpoint_path = os.path.join(model_dir, 'checkpoint')
+    checkpoint = torch.load(checkpoint_path, map_location='cpu')
+    labels = [loss_labels[loss] for loss in losses]
+    
+    tr_losses = checkpoint['tr_losses']
+    val_losses = checkpoint['val_losses'] if plot_val == True else None
+    eval_every = checkpoint['eval_every'] if plot_val == True else None
+
+    plot_stats(losses, tr_losses, stats_val=val_losses,
+               eval_every=eval_every, labels=labels, rx=(0))
+    
+
+# Dictionary that maps accuracy statistic name to plot label 
+accuracy_labels = {
+    's_acc': 'Struct. Accuracy',
+    's_precision': 'Struct. Precision',
+    's_recall': 'Struct. Recall',
+    's_f1': 'Struct. F1',
+    'pitch': 'Pitch Accuracy',
+    'pitch_drums': 'Pitch Accuracy (Drums)',
+    'pitch_non_drums': 'Pitch Accuracy (Non Drums)',
+    'dur': 'Duration Accuracy',
+    'note': 'Note Accuracy'
+}
+
+
+def plot_accuracies(model_dir, accuracies, plot_val=False):
+    
+    checkpoint_path = os.path.join(model_dir, 'checkpoint')
+    checkpoint = torch.load(checkpoint_path, map_location='cpu')
+    labels = [accuracy_labels[accuracy] for accuracy in accuracies]
+    
+    tr_accuracies = checkpoint['tr_accuracies']
+    val_accuracies = checkpoint['val_accuracies'] if plot_val == True else None
+    eval_every = checkpoint['eval_every'] if plot_val == True else None
+
+    plot_stats(accuracies, tr_accuracies, stats_val=val_accuracies,
+               eval_every=eval_every, labels=labels, ry=(0, 1))

preprocess.py

@@ -0,0 +1,294 @@
+import os
+import time
+import sys
+import multiprocessing
+import itertools
+import argparse
+from itertools import product
+
+import numpy as np
+import tqdm
+import pypianoroll as pproll
+import muspy
+
+import constants
+from constants import PitchToken, DurationToken
+
+
+def preprocess_midi_file(filepath, dest_dir, n_bars, resolution):
+
+    print("Preprocessing file {}".format(filepath))
+
+    filename = os.path.basename(filepath)
+    saved_samples = 0
+
+    # Load the file both as a pypianoroll song and a muspy song
+    # (Need to load both since muspy.to_pypianoroll() is expensive)
+    try:
+        pproll_song = pproll.read(filepath, resolution=resolution)
+        muspy_song = muspy.read(filepath)
+    except Exception as e:
+        print("Song skipped (Invalid song format)")
+        return 0
+
+    # Only accept songs that have a time signature of 4/4 and no time changes
+    for t in muspy_song.time_signatures:
+        if t.numerator != 4 or t.denominator != 4:
+            print("Song skipped ({}/{} time signature)".
+                  format(t.numerator, t.denominator))
+            return 0
+
+    # Gather tracks of pypianoroll song based on MIDI program number
+    drum_tracks = []
+    bass_tracks = []
+    guitar_tracks = []
+    strings_tracks = []
+
+    for track in pproll_song.tracks:
+        if track.is_drum:
+            track.name = 'Drums'
+            drum_tracks.append(track)
+        elif 0 <= track.program <= 31:
+            track.name = 'Guitar'
+            guitar_tracks.append(track)
+        elif 32 <= track.program <= 39:
+            track.name = 'Bass'
+            bass_tracks.append(track)
+        else:
+            # Tracks with program > 39 are all considered as strings tracks
+            # and will be merged into a single track later on
+            strings_tracks.append(track)
+
+    # Filter song if it does not contain drum, guitar, bass or strings tracks
+    # if not guitar_tracks \
+    if not drum_tracks or not guitar_tracks \
+            or not bass_tracks or not strings_tracks:
+        print("Song skipped (does not contain drum or "
+              "guitar or bass or strings tracks)")
+        return 0
+
+    # Merge strings tracks into a single pypianoroll track
+    strings = pproll.Multitrack(tracks=strings_tracks)
+    strings_track = pproll.Track(pianoroll=strings.blend(mode='max'),
+                                 program=48, name='Strings')
+
+    combinations = list(product(drum_tracks, bass_tracks, guitar_tracks))
+
+    # Single instruments can have multiple tracks.
+    # Consider all possible combinations of drum, bass, and guitar tracks
+    for i, combination in enumerate(combinations):
+
+        print("Processing combination {} of {}".format(i + 1, 
+                                                       len(combinations)))
+
+        # Process combination (called 'subsong' from now on)
+        drum_track, bass_track, guitar_track = combination
+        tracks = [drum_track, bass_track, guitar_track, strings_track]
+
+        pproll_subsong = pproll.Multitrack(
+            tracks=tracks,
+            tempo=pproll_song.tempo,
+            resolution=resolution
+        )
+        muspy_subsong = muspy.from_pypianoroll(pproll_subsong)
+
+        tracks_notes = [track.notes for track in muspy_subsong.tracks]
+
+        # Obtain length of subsong (maximum of each track's length)
+        length = 0
+        for notes in tracks_notes:
+            track_length = max(note.end for note in notes) if notes else 0
+            length = max(length, track_length)
+        length += 1
+
+        # Add timesteps until length is a multiple of resolution
+        length = length if length % (4*resolution) == 0 \
+            else length + (4*resolution-(length % (4*resolution)))
+
+        tracks_content = []
+        tracks_structure = []
+
+        for notes in tracks_notes:
+
+            # track_content: length x MAX_SIMU_TOKENS x 2
+            # This is used as a basis to build the final content tensors for
+            # each sequence.
+            # The last dimension contains pitches and durations. int16 is enough
+            # to encode small to medium duration values.
+            track_content = np.zeros((length, constants.MAX_SIMU_TOKENS, 2), 
+                                    np.int16)
+
+            track_content[:, :, 0] = PitchToken.PAD.value
+            track_content[:, 0, 0] = PitchToken.SOS.value
+            track_content[:, :, 1] = DurationToken.PAD.value
+            track_content[:, 0, 1] = DurationToken.SOS.value
+
+            # Keeps track of how many notes have been stored in each timestep
+            # (int8 imposes MAX_SIMU_TOKENS < 256)
+            notes_counter = np.ones(length, dtype=np.int8)
+
+            # Todo: np.put_along_axis?
+            for note in notes:
+                # Insert note in the lowest position available in the timestep
+
+                t = note.time
+
+                if notes_counter[t] >= constants.MAX_SIMU_TOKENS-1:
+                    # Skip note if there is no more space
+                    continue
+
+                pitch = max(min(note.pitch, constants.MAX_PITCH_TOKEN), 0)
+                track_content[t, notes_counter[t], 0] = pitch
+                dur = max(min(note.duration, constants.MAX_DUR_TOKEN + 1), 1)
+                track_content[t, notes_counter[t], 1] = dur-1
+                notes_counter[t] += 1
+
+            # Add EOS token
+            t_range = np.arange(0, length)
+            track_content[t_range, notes_counter, 0] = PitchToken.EOS.value
+            track_content[t_range, notes_counter, 1] = DurationToken.EOS.value
+
+            # Get track activations, a boolean tensor indicating whether notes
+            # are being played in a timestep (sustain does not count)
+            # (needed for graph rep.)
+            activations = np.array(notes_counter-1, dtype=bool)
+
+            tracks_content.append(track_content)
+            tracks_structure.append(activations)
+
+        # n_tracks x length x MAX_SIMU_TOKENS x 2
+        subsong_content = np.stack(tracks_content, axis=0)
+
+        # n_tracks x length
+        subsong_structure = np.stack(tracks_structure, axis=0)
+
+        # Slide window over 'subsong_content' and 'subsong_structure' along the
+        # time axis (2nd dimension) with the stride of a bar
+        # Todo: np.lib.stride_tricks.as_strided(song_proll)?
+        for i in range(0, length-n_bars*4*resolution+1, 4*resolution):
+
+            # Get the content and structure tensors of a single sequence
+            c_tensor = subsong_content[:, i:i+n_bars*4*resolution, :]
+            s_tensor = subsong_structure[:, i:i+n_bars*4*resolution]
+            c_tensor = np.copy(c_tensor)
+            s_tensor = np.copy(s_tensor)
+
+            if n_bars > 1:
+                # Skip sequence if it contains more than one bar of consecutive
+                # silence in at least one track
+                bars = s_tensor.reshape(s_tensor.shape[0], n_bars, -1)
+                bars_acts = np.any(bars, axis=2)
+
+                if 1 in np.diff(np.where(bars_acts == 0)[1]):
+                    continue
+
+                # Skip sequence if it contains one bar of complete silence
+                silences = np.logical_not(np.any(bars_acts, axis=0))
+                if np.any(silences):
+                    continue
+
+            else:
+                # Skip if all tracks are silenced
+                bar_acts = np.any(s_tensor, axis=1)
+                if not np.any(bar_acts):
+                    continue
+
+            # Randomly transpose the pitches of the sequence (-5 to 6 semitones)
+            # Not considering SOS, EOS or PAD tokens. Not transposing drums.
+            shift = np.random.choice(np.arange(-5, 7), 1)
+            cond = (c_tensor[1:, :, :, 0] != PitchToken.PAD.value) &           \
+                   (c_tensor[1:, :, :, 0] != PitchToken.SOS.value) &           \
+                   (c_tensor[1:, :, :, 0] != PitchToken.EOS.value)
+            non_drums = c_tensor[1:, ...]
+            non_drums[cond, 0] += shift
+            non_drums[cond, 0] = np.clip(non_drums[cond, 0], a_min=0, 
+                                         a_max=constants.MAX_PITCH_TOKEN)
+
+            # Save sample (content and structure) to file
+            sample_filepath = os.path.join(
+                dest_dir, filename+str(saved_samples))
+            np.savez(sample_filepath, c_tensor=c_tensor, s_tensor=s_tensor)
+
+            saved_samples += 1
+
+
+def preprocess_midi_dataset(midi_dataset_dir, preprocessed_dir, n_bars, 
+                            resolution, n_files=None, n_workers=1):
+
+    print("Starting preprocessing")
+    start = time.time()
+
+    # Visit recursively the directories inside the dataset directory
+    with multiprocessing.Pool(n_workers) as pool:
+
+        walk = os.walk(midi_dataset_dir)
+        fn_gen = itertools.chain.from_iterable(
+            ((os.path.join(dirpath, file), preprocessed_dir, n_bars, resolution)
+                for file in files)
+                for dirpath, dirs, files in walk
+        )
+
+        r = list(tqdm.tqdm(pool.starmap(preprocess_midi_file, fn_gen),
+                           total=n_files))
+
+    end = time.time()
+    hours, rem = divmod(end-start, 3600)
+    minutes, seconds = divmod(rem, 60)
+    print("Preprocessing completed in (h:m:s): {:0>2}:{:0>2}:{:05.2f}"
+          .format(int(hours), int(minutes), seconds))
+
+
+if __name__ == "__main__":
+
+    parser = argparse.ArgumentParser(
+        description="Preprocesses a MIDI dataset. MIDI files can be arranged " 
+            "hierarchically in subdirectories, similarly to the Lakh MIDI "
+            "Dataset (lmd_matched) and the MetaMIDI Dataset."
+    )
+    parser.add_argument(
+        'midi_dataset_dir',
+        type=str, 
+        help='Directory of the MIDI dataset.'
+    )
+    parser.add_argument(
+        'preprocessed_dir',
+        type=str,
+        help='Directory to save the preprocessed dataset.'
+    )
+    parser.add_argument(
+        '--n_bars',
+        type=int,
+        default=2,
+        help="Number of bars for each sequence of the resulting preprocessed "
+            "dataset. Defaults to 2 bars."
+    )
+    parser.add_argument(
+        '--resolution',
+        type=int,
+        default=8,
+        help="Number of timesteps per beat. When set to r, given that only "
+            "4/4 songs are preprocessed, there will be 4*r timesteps in a bar. "
+            "Defaults to 8."
+    )
+    parser.add_argument(
+        '--n_files',
+        type=int,
+        help="Number of files in the MIDI dataset. If set, the script "
+            "will provide statistics on the time remaining."
+    )
+    parser.add_argument(
+        '--n_workers',
+        type=int,
+        default=1,
+        help="Number of parallel workers. Defaults to 1."
+    )
+
+    args = parser.parse_args()
+    
+    # Create the output directory if it does not exist
+    if not os.path.exists(args.preprocessed_dir):
+        os.makedirs(args.preprocessed_dir)
+
+    preprocess_midi_dataset(args.midi_dataset_dir, args.preprocessed_dir, 
+                            args.n_bars, args.resolution, args.n_files,
+                            n_workers=args.n_workers)

requirements.txt

@@ -0,0 +1,25 @@
+--find-links https://download.pytorch.org/whl/torch_stable.html
+--find-links https://data.pyg.org/whl/torch-1.7.0+cu101.html
+
+# PyTorch related
+torch==1.7.0+cu101
+torchvision==0.8.0
+torch-geometric==2.0.2
+torch-cluster==1.5.9
+torch-scatter==2.0.7
+torch-sparse==0.6.9
+torch-spline-conv==1.2.1
+
+# Music packages
+pretty-midi==0.2.9
+muspy==0.4.0
+pypianoroll==1.0.4
+
+# Various
+prettytable==2.4.0
+tqdm==4.62.3
+huggingface-hub==0.16.4
+
+# Hugging Face
+flask==2.1.*
+requests==2.27.*

soundfonts/FluidR3_GM.sf2

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:74594e8f4250680adf590507a306655a299935343583256f3b722c48a1bc1cb0
+size 148398306

static/0/structure.json

@@ -0,0 +1 @@
+[[[true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, true, false, true, false, false, false], [true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false], [true, false, false, false, true, false, false, false, true, false, false, false, false, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false], [true, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, true, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false]], [[true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, true, false, true, false, false, false], [true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false], [true, false, false, false, true, false, false, false, true, false, false, false, false, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false], [true, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, true, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false]]]

static/assets/FontAwesome/LICENSE.txt

@@ -0,0 +1,165 @@
+Fonticons, Inc. (https://fontawesome.com)
+
+--------------------------------------------------------------------------------
+
+Font Awesome Free License
+
+Font Awesome Free is free, open source, and GPL friendly. You can use it for
+commercial projects, open source projects, or really almost whatever you want.
+Full Font Awesome Free license: https://fontawesome.com/license/free.
+
+--------------------------------------------------------------------------------
+
+# Icons: CC BY 4.0 License (https://creativecommons.org/licenses/by/4.0/)
+
+The Font Awesome Free download is licensed under a Creative Commons
+Attribution 4.0 International License and applies to all icons packaged
+as SVG and JS file types.
+
+--------------------------------------------------------------------------------
+
+# Fonts: SIL OFL 1.1 License
+
+In the Font Awesome Free download, the SIL OFL license applies to all icons
+packaged as web and desktop font files.
+
+Copyright (c) 2023 Fonticons, Inc. (https://fontawesome.com)
+with Reserved Font Name: "Font Awesome".
+
+This Font Software is licensed under the SIL Open Font License, Version 1.1.
+This license is copied below, and is also available with a FAQ at:
+http://scripts.sil.org/OFL
+
+SIL OPEN FONT LICENSE
+Version 1.1 - 26 February 2007
+
+PREAMBLE
+The goals of the Open Font License (OFL) are to stimulate worldwide
+development of collaborative font projects, to support the font creation
+efforts of academic and linguistic communities, and to provide a free and
+open framework in which fonts may be shared and improved in partnership
+with others.
+
+The OFL allows the licensed fonts to be used, studied, modified and
+redistributed freely as long as they are not sold by themselves. The
+fonts, including any derivative works, can be bundled, embedded,
+redistributed and/or sold with any software provided that any reserved
+names are not used by derivative works. The fonts and derivatives,
+however, cannot be released under any other type of license. The
+requirement for fonts to remain under this license does not apply
+to any document created using the fonts or their derivatives.
+
+DEFINITIONS
+"Font Software" refers to the set of files released by the Copyright
+Holder(s) under this license and clearly marked as such. This may
+include source files, build scripts and documentation.
+
+"Reserved Font Name" refers to any names specified as such after the
+copyright statement(s).
+
+"Original Version" refers to the collection of Font Software components as
+distributed by the Copyright Holder(s).
+
+"Modified Version" refers to any derivative made by adding to, deleting,
+or substituting — in part or in whole — any of the components of the
+Original Version, by changing formats or by porting the Font Software to a
+new environment.
+
+"Author" refers to any designer, engineer, programmer, technical
+writer or other person who contributed to the Font Software.
+
+PERMISSION & CONDITIONS
+Permission is hereby granted, free of charge, to any person obtaining
+a copy of the Font Software, to use, study, copy, merge, embed, modify,
+redistribute, and sell modified and unmodified copies of the Font
+Software, subject to the following conditions:
+
+1) Neither the Font Software nor any of its individual components,
+in Original or Modified Versions, may be sold by itself.
+
+2) Original or Modified Versions of the Font Software may be bundled,
+redistributed and/or sold with any software, provided that each copy
+contains the above copyright notice and this license. These can be
+included either as stand-alone text files, human-readable headers or
+in the appropriate machine-readable metadata fields within text or
+binary files as long as those fields can be easily viewed by the user.
+
+3) No Modified Version of the Font Software may use the Reserved Font
+Name(s) unless explicit written permission is granted by the corresponding
+Copyright Holder. This restriction only applies to the primary font name as
+presented to the users.
+
+4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font
+Software shall not be used to promote, endorse or advertise any
+Modified Version, except to acknowledge the contribution(s) of the
+Copyright Holder(s) and the Author(s) or with their explicit written
+permission.
+
+5) The Font Software, modified or unmodified, in part or in whole,
+must be distributed entirely under this license, and must not be
+distributed under any other license. The requirement for fonts to
+remain under this license does not apply to any document created
+using the Font Software.
+
+TERMINATION
+This license becomes null and void if any of the above conditions are
+not met.
+
+DISCLAIMER
+THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF
+MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT
+OF COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. IN NO EVENT SHALL THE
+COPYRIGHT HOLDER BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+INCLUDING ANY GENERAL, SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL
+DAMAGES, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+FROM, OUT OF THE USE OR INABILITY TO USE THE FONT SOFTWARE OR FROM
+OTHER DEALINGS IN THE FONT SOFTWARE.
+
+--------------------------------------------------------------------------------
+
+# Code: MIT License (https://opensource.org/licenses/MIT)
+
+In the Font Awesome Free download, the MIT license applies to all non-font and
+non-icon files.
+
+Copyright 2023 Fonticons, Inc.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of
+this software and associated documentation files (the "Software"), to deal in the
+Software without restriction, including without limitation the rights to use, copy,
+modify, merge, publish, distribute, sublicense, and/or sell copies of the Software,
+and to permit persons to whom the Software is furnished to do so, subject to the
+following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED,
+INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
+PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
+OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
+SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+
+--------------------------------------------------------------------------------
+
+# Attribution
+
+Attribution is required by MIT, SIL OFL, and CC BY licenses. Downloaded Font
+Awesome Free files already contain embedded comments with sufficient
+attribution, so you shouldn't need to do anything additional when using these
+files normally.
+
+We've kept attribution comments terse, so we ask that you do not actively work
+to remove them from files, especially code. They're a great way for folks to
+learn about Font Awesome.
+
+--------------------------------------------------------------------------------
+
+# Brand Icons
+
+All brand icons are trademarks of their respective owners. The use of these
+trademarks does not indicate endorsement of the trademark holder by Font
+Awesome, nor vice versa. **Please do not use brand logos for any purpose except
+to represent the company, product, or service to which they refer.**

static/assets/FontAwesome/css/brands.css

@@ -0,0 +1,1537 @@
+/*!
+ * Font Awesome Free 6.4.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */
+:root, :host {
+  --fa-style-family-brands: 'Font Awesome 6 Brands';
+  --fa-font-brands: normal 400 1em/1 'Font Awesome 6 Brands'; }
+
+@font-face {
+  font-family: 'Font Awesome 6 Brands';
+  font-style: normal;
+  font-weight: 400;
+  font-display: block;
+  src: url("../webfonts/fa-brands-400.woff2") format("woff2"), url("../webfonts/fa-brands-400.ttf") format("truetype"); }
+
+.fab,
+.fa-brands {
+  font-weight: 400; }
+
+.fa-monero:before {
+  content: "\f3d0"; }
+
+.fa-hooli:before {
+  content: "\f427"; }
+
+.fa-yelp:before {
+  content: "\f1e9"; }
+
+.fa-cc-visa:before {
+  content: "\f1f0"; }
+
+.fa-lastfm:before {
+  content: "\f202"; }
+
+.fa-shopware:before {
+  content: "\f5b5"; }
+
+.fa-creative-commons-nc:before {
+  content: "\f4e8"; }
+
+.fa-aws:before {
+  content: "\f375"; }
+
+.fa-redhat:before {
+  content: "\f7bc"; }
+
+.fa-yoast:before {
+  content: "\f2b1"; }
+
+.fa-cloudflare:before {
+  content: "\e07d"; }
+
+.fa-ups:before {
+  content: "\f7e0"; }
+
+.fa-wpexplorer:before {
+  content: "\f2de"; }
+
+.fa-dyalog:before {
+  content: "\f399"; }
+
+.fa-bity:before {
+  content: "\f37a"; }
+
+.fa-stackpath:before {
+  content: "\f842"; }
+
+.fa-buysellads:before {
+  content: "\f20d"; }
+
+.fa-first-order:before {
+  content: "\f2b0"; }
+
+.fa-modx:before {
+  content: "\f285"; }
+
+.fa-guilded:before {
+  content: "\e07e"; }
+
+.fa-vnv:before {
+  content: "\f40b"; }
+
+.fa-square-js:before {
+  content: "\f3b9"; }
+
+.fa-js-square:before {
+  content: "\f3b9"; }
+
+.fa-microsoft:before {
+  content: "\f3ca"; }
+
+.fa-qq:before {
+  content: "\f1d6"; }
+
+.fa-orcid:before {
+  content: "\f8d2"; }
+
+.fa-java:before {
+  content: "\f4e4"; }
+
+.fa-invision:before {
+  content: "\f7b0"; }
+
+.fa-creative-commons-pd-alt:before {
+  content: "\f4ed"; }
+
+.fa-centercode:before {
+  content: "\f380"; }
+
+.fa-glide-g:before {
+  content: "\f2a6"; }
+
+.fa-drupal:before {
+  content: "\f1a9"; }
+
+.fa-hire-a-helper:before {
+  content: "\f3b0"; }
+
+.fa-creative-commons-by:before {
+  content: "\f4e7"; }
+
+.fa-unity:before {
+  content: "\e049"; }
+
+.fa-whmcs:before {
+  content: "\f40d"; }
+
+.fa-rocketchat:before {
+  content: "\f3e8"; }
+
+.fa-vk:before {
+  content: "\f189"; }
+
+.fa-untappd:before {
+  content: "\f405"; }
+
+.fa-mailchimp:before {
+  content: "\f59e"; }
+
+.fa-css3-alt:before {
+  content: "\f38b"; }
+
+.fa-square-reddit:before {
+  content: "\f1a2"; }
+
+.fa-reddit-square:before {
+  content: "\f1a2"; }
+
+.fa-vimeo-v:before {
+  content: "\f27d"; }
+
+.fa-contao:before {
+  content: "\f26d"; }
+
+.fa-square-font-awesome:before {
+  content: "\e5ad"; }
+
+.fa-deskpro:before {
+  content: "\f38f"; }
+
+.fa-sistrix:before {
+  content: "\f3ee"; }
+
+.fa-square-instagram:before {
+  content: "\e055"; }
+
+.fa-instagram-square:before {
+  content: "\e055"; }
+
+.fa-battle-net:before {
+  content: "\f835"; }
+
+.fa-the-red-yeti:before {
+  content: "\f69d"; }
+
+.fa-square-hacker-news:before {
+  content: "\f3af"; }
+
+.fa-hacker-news-square:before {
+  content: "\f3af"; }
+
+.fa-edge:before {
+  content: "\f282"; }
+
+.fa-threads:before {
+  content: "\e618"; }
+
+.fa-napster:before {
+  content: "\f3d2"; }
+
+.fa-square-snapchat:before {
+  content: "\f2ad"; }
+
+.fa-snapchat-square:before {
+  content: "\f2ad"; }
+
+.fa-google-plus-g:before {
+  content: "\f0d5"; }
+
+.fa-artstation:before {
+  content: "\f77a"; }
+
+.fa-markdown:before {
+  content: "\f60f"; }
+
+.fa-sourcetree:before {
+  content: "\f7d3"; }
+
+.fa-google-plus:before {
+  content: "\f2b3"; }
+
+.fa-diaspora:before {
+  content: "\f791"; }
+
+.fa-foursquare:before {
+  content: "\f180"; }
+
+.fa-stack-overflow:before {
+  content: "\f16c"; }
+
+.fa-github-alt:before {
+  content: "\f113"; }
+
+.fa-phoenix-squadron:before {
+  content: "\f511"; }
+
+.fa-pagelines:before {
+  content: "\f18c"; }
+
+.fa-algolia:before {
+  content: "\f36c"; }
+
+.fa-red-river:before {
+  content: "\f3e3"; }
+
+.fa-creative-commons-sa:before {
+  content: "\f4ef"; }
+
+.fa-safari:before {
+  content: "\f267"; }
+
+.fa-google:before {
+  content: "\f1a0"; }
+
+.fa-square-font-awesome-stroke:before {
+  content: "\f35c"; }
+
+.fa-font-awesome-alt:before {
+  content: "\f35c"; }
+
+.fa-atlassian:before {
+  content: "\f77b"; }
+
+.fa-linkedin-in:before {
+  content: "\f0e1"; }
+
+.fa-digital-ocean:before {
+  content: "\f391"; }
+
+.fa-nimblr:before {
+  content: "\f5a8"; }
+
+.fa-chromecast:before {
+  content: "\f838"; }
+
+.fa-evernote:before {
+  content: "\f839"; }
+
+.fa-hacker-news:before {
+  content: "\f1d4"; }
+
+.fa-creative-commons-sampling:before {
+  content: "\f4f0"; }
+
+.fa-adversal:before {
+  content: "\f36a"; }
+
+.fa-creative-commons:before {
+  content: "\f25e"; }
+
+.fa-watchman-monitoring:before {
+  content: "\e087"; }
+
+.fa-fonticons:before {
+  content: "\f280"; }
+
+.fa-weixin:before {
+  content: "\f1d7"; }
+
+.fa-shirtsinbulk:before {
+  content: "\f214"; }
+
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+  content: "\f1cb"; }
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+  content: "\e5ac"; }
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+  content: "\f4ea"; }
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+  content: "\f265"; }
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+  content: "\e340"; }
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+  content: "\f7c6"; }
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+  content: "\f09b"; }
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+  content: "\e078"; }
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+  content: "\f198"; }
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+  content: "\f198"; }
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+  content: "\f3c8"; }
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+  content: "\f287"; }
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+  content: "\f173"; }
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+  content: "\f408"; }
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+  content: "\f2c4"; }
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+  content: "\e61a"; }
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+  content: "\f75d"; }
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+  content: "\f23a"; }
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+  content: "\f23a"; }
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+  content: "\f36d"; }
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+  content: "\f289"; }
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+.fa-flipboard:before {
+  content: "\f44d"; }
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+.fa-viacoin:before {
+  content: "\f237"; }
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+.fa-critical-role:before {
+  content: "\f6c9"; }
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+  content: "\e44a"; }
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+  content: "\f393"; }
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+.fa-joomla:before {
+  content: "\f1aa"; }
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+.fa-mastodon:before {
+  content: "\f4f6"; }
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+.fa-airbnb:before {
+  content: "\f834"; }
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+.fa-wolf-pack-battalion:before {
+  content: "\f514"; }
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+.fa-buy-n-large:before {
+  content: "\f8a6"; }
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+.fa-gulp:before {
+  content: "\f3ae"; }
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+.fa-creative-commons-sampling-plus:before {
+  content: "\f4f1"; }
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+.fa-strava:before {
+  content: "\f428"; }
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+.fa-ember:before {
+  content: "\f423"; }
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+.fa-canadian-maple-leaf:before {
+  content: "\f785"; }
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+.fa-teamspeak:before {
+  content: "\f4f9"; }
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+.fa-pushed:before {
+  content: "\f3e1"; }
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+.fa-wordpress-simple:before {
+  content: "\f411"; }
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+.fa-nutritionix:before {
+  content: "\f3d6"; }
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+.fa-wodu:before {
+  content: "\e088"; }
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+.fa-google-pay:before {
+  content: "\e079"; }
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+.fa-intercom:before {
+  content: "\f7af"; }
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+.fa-zhihu:before {
+  content: "\f63f"; }
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+.fa-korvue:before {
+  content: "\f42f"; }
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+.fa-pix:before {
+  content: "\e43a"; }
+
+.fa-steam-symbol:before {
+  content: "\f3f6"; }

static/assets/FontAwesome/css/brands.min.css

@@ -0,0 +1,6 @@
+/*!
+ * Font Awesome Free 6.4.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */
+:host,:root{--fa-style-family-brands:"Font Awesome 6 Brands";--fa-font-brands:normal 400 1em/1 "Font Awesome 6 Brands"}@font-face{font-family:"Font Awesome 6 Brands";font-style:normal;font-weight:400;font-display:block;src:url(../webfonts/fa-brands-400.woff2) format("woff2"),url(../webfonts/fa-brands-400.ttf) 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+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */
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static/assets/FontAwesome/css/solid.css

@@ -0,0 +1,19 @@
+/*!
+ * Font Awesome Free 6.4.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */
+:root, :host {
+  --fa-style-family-classic: 'Font Awesome 6 Free';
+  --fa-font-solid: normal 900 1em/1 'Font Awesome 6 Free'; }
+
+@font-face {
+  font-family: 'Font Awesome 6 Free';
+  font-style: normal;
+  font-weight: 900;
+  font-display: block;
+  src: url("../webfonts/fa-solid-900.woff2") format("woff2"), url("../webfonts/fa-solid-900.ttf") format("truetype"); }
+
+.fas,
+.fa-solid {
+  font-weight: 900; }

static/assets/FontAwesome/css/solid.min.css

@@ -0,0 +1,6 @@
+/*!
+ * Font Awesome Free 6.4.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */
+:host,:root{--fa-style-family-classic:"Font Awesome 6 Free";--fa-font-solid:normal 900 1em/1 "Font Awesome 6 Free"}@font-face{font-family:"Font Awesome 6 Free";font-style:normal;font-weight:900;font-display:block;src:url(../webfonts/fa-solid-900.woff2) format("woff2"),url(../webfonts/fa-solid-900.ttf) format("truetype")}.fa-solid,.fas{font-weight:900}

static/assets/FontAwesome/css/svg-with-js.css

@@ -0,0 +1,639 @@
+/*!
+ * Font Awesome Free 6.4.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */
+:root, :host {
+  --fa-font-solid: normal 900 1em/1 'Font Awesome 6 Solid';
+  --fa-font-regular: normal 400 1em/1 'Font Awesome 6 Regular';
+  --fa-font-light: normal 300 1em/1 'Font Awesome 6 Light';
+  --fa-font-thin: normal 100 1em/1 'Font Awesome 6 Thin';
+  --fa-font-duotone: normal 900 1em/1 'Font Awesome 6 Duotone';
+  --fa-font-sharp-solid: normal 900 1em/1 'Font Awesome 6 Sharp';
+  --fa-font-sharp-regular: normal 400 1em/1 'Font Awesome 6 Sharp';
+  --fa-font-sharp-light: normal 300 1em/1 'Font Awesome 6 Sharp';
+  --fa-font-brands: normal 400 1em/1 'Font Awesome 6 Brands'; }
+
+svg:not(:root).svg-inline--fa, svg:not(:host).svg-inline--fa {
+  overflow: visible;
+  box-sizing: content-box; }
+
+.svg-inline--fa {
+  display: var(--fa-display, inline-block);
+  height: 1em;
+  overflow: visible;
+  vertical-align: -.125em; }
+  .svg-inline--fa.fa-2xs {
+    vertical-align: 0.1em; }
+  .svg-inline--fa.fa-xs {
+    vertical-align: 0em; }
+  .svg-inline--fa.fa-sm {
+    vertical-align: -0.07143em; }
+  .svg-inline--fa.fa-lg {
+    vertical-align: -0.2em; }
+  .svg-inline--fa.fa-xl {
+    vertical-align: -0.25em; }
+  .svg-inline--fa.fa-2xl {
+    vertical-align: -0.3125em; }
+  .svg-inline--fa.fa-pull-left {
+    margin-right: var(--fa-pull-margin, 0.3em);
+    width: auto; }
+  .svg-inline--fa.fa-pull-right {
+    margin-left: var(--fa-pull-margin, 0.3em);
+    width: auto; }
+  .svg-inline--fa.fa-li {
+    width: var(--fa-li-width, 2em);
+    top: 0.25em; }
+  .svg-inline--fa.fa-fw {
+    width: var(--fa-fw-width, 1.25em); }
+
+.fa-layers svg.svg-inline--fa {
+  bottom: 0;
+  left: 0;
+  margin: auto;
+  position: absolute;
+  right: 0;
+  top: 0; }
+
+.fa-layers-text, .fa-layers-counter {
+  display: inline-block;
+  position: absolute;
+  text-align: center; }
+
+.fa-layers {
+  display: inline-block;
+  height: 1em;
+  position: relative;
+  text-align: center;
+  vertical-align: -.125em;
+  width: 1em; }
+  .fa-layers svg.svg-inline--fa {
+    -webkit-transform-origin: center center;
+            transform-origin: center center; }
+
+.fa-layers-text {
+  left: 50%;
+  top: 50%;
+  -webkit-transform: translate(-50%, -50%);
+          transform: translate(-50%, -50%);
+  -webkit-transform-origin: center center;
+          transform-origin: center center; }
+
+.fa-layers-counter {
+  background-color: var(--fa-counter-background-color, #ff253a);
+  border-radius: var(--fa-counter-border-radius, 1em);
+  box-sizing: border-box;
+  color: var(--fa-inverse, #fff);
+  line-height: var(--fa-counter-line-height, 1);
+  max-width: var(--fa-counter-max-width, 5em);
+  min-width: var(--fa-counter-min-width, 1.5em);
+  overflow: hidden;
+  padding: var(--fa-counter-padding, 0.25em 0.5em);
+  right: var(--fa-right, 0);
+  text-overflow: ellipsis;
+  top: var(--fa-top, 0);
+  -webkit-transform: scale(var(--fa-counter-scale, 0.25));
+          transform: scale(var(--fa-counter-scale, 0.25));
+  -webkit-transform-origin: top right;
+          transform-origin: top right; }
+
+.fa-layers-bottom-right {
+  bottom: var(--fa-bottom, 0);
+  right: var(--fa-right, 0);
+  top: auto;
+  -webkit-transform: scale(var(--fa-layers-scale, 0.25));
+          transform: scale(var(--fa-layers-scale, 0.25));
+  -webkit-transform-origin: bottom right;
+          transform-origin: bottom right; }
+
+.fa-layers-bottom-left {
+  bottom: var(--fa-bottom, 0);
+  left: var(--fa-left, 0);
+  right: auto;
+  top: auto;
+  -webkit-transform: scale(var(--fa-layers-scale, 0.25));
+          transform: scale(var(--fa-layers-scale, 0.25));
+  -webkit-transform-origin: bottom left;
+          transform-origin: bottom left; }
+
+.fa-layers-top-right {
+  top: var(--fa-top, 0);
+  right: var(--fa-right, 0);
+  -webkit-transform: scale(var(--fa-layers-scale, 0.25));
+          transform: scale(var(--fa-layers-scale, 0.25));
+  -webkit-transform-origin: top right;
+          transform-origin: top right; }
+
+.fa-layers-top-left {
+  left: var(--fa-left, 0);
+  right: auto;
+  top: var(--fa-top, 0);
+  -webkit-transform: scale(var(--fa-layers-scale, 0.25));
+          transform: scale(var(--fa-layers-scale, 0.25));
+  -webkit-transform-origin: top left;
+          transform-origin: top left; }
+
+.fa-1x {
+  font-size: 1em; }
+
+.fa-2x {
+  font-size: 2em; }
+
+.fa-3x {
+  font-size: 3em; }
+
+.fa-4x {
+  font-size: 4em; }
+
+.fa-5x {
+  font-size: 5em; }
+
+.fa-6x {
+  font-size: 6em; }
+
+.fa-7x {
+  font-size: 7em; }
+
+.fa-8x {
+  font-size: 8em; }
+
+.fa-9x {
+  font-size: 9em; }
+
+.fa-10x {
+  font-size: 10em; }
+
+.fa-2xs {
+  font-size: 0.625em;
+  line-height: 0.1em;
+  vertical-align: 0.225em; }
+
+.fa-xs {
+  font-size: 0.75em;
+  line-height: 0.08333em;
+  vertical-align: 0.125em; }
+
+.fa-sm {
+  font-size: 0.875em;
+  line-height: 0.07143em;
+  vertical-align: 0.05357em; }
+
+.fa-lg {
+  font-size: 1.25em;
+  line-height: 0.05em;
+  vertical-align: -0.075em; }
+
+.fa-xl {
+  font-size: 1.5em;
+  line-height: 0.04167em;
+  vertical-align: -0.125em; }
+
+.fa-2xl {
+  font-size: 2em;
+  line-height: 0.03125em;
+  vertical-align: -0.1875em; }
+
+.fa-fw {
+  text-align: center;
+  width: 1.25em; }
+
+.fa-ul {
+  list-style-type: none;
+  margin-left: var(--fa-li-margin, 2.5em);
+  padding-left: 0; }
+  .fa-ul > li {
+    position: relative; }
+
+.fa-li {
+  left: calc(var(--fa-li-width, 2em) * -1);
+  position: absolute;
+  text-align: center;
+  width: var(--fa-li-width, 2em);
+  line-height: inherit; }
+
+.fa-border {
+  border-color: var(--fa-border-color, #eee);
+  border-radius: var(--fa-border-radius, 0.1em);
+  border-style: var(--fa-border-style, solid);
+  border-width: var(--fa-border-width, 0.08em);
+  padding: var(--fa-border-padding, 0.2em 0.25em 0.15em); }
+
+.fa-pull-left {
+  float: left;
+  margin-right: var(--fa-pull-margin, 0.3em); }
+
+.fa-pull-right {
+  float: right;
+  margin-left: var(--fa-pull-margin, 0.3em); }
+
+.fa-beat {
+  -webkit-animation-name: fa-beat;
+          animation-name: fa-beat;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, ease-in-out);
+          animation-timing-function: var(--fa-animation-timing, ease-in-out); }
+
+.fa-bounce {
+  -webkit-animation-name: fa-bounce;
+          animation-name: fa-bounce;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.28, 0.84, 0.42, 1));
+          animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.28, 0.84, 0.42, 1)); }
+
+.fa-fade {
+  -webkit-animation-name: fa-fade;
+          animation-name: fa-fade;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1));
+          animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1)); }
+
+.fa-beat-fade {
+  -webkit-animation-name: fa-beat-fade;
+          animation-name: fa-beat-fade;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1));
+          animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1)); }
+
+.fa-flip {
+  -webkit-animation-name: fa-flip;
+          animation-name: fa-flip;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, ease-in-out);
+          animation-timing-function: var(--fa-animation-timing, ease-in-out); }
+
+.fa-shake {
+  -webkit-animation-name: fa-shake;
+          animation-name: fa-shake;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, linear);
+          animation-timing-function: var(--fa-animation-timing, linear); }
+
+.fa-spin {
+  -webkit-animation-name: fa-spin;
+          animation-name: fa-spin;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 2s);
+          animation-duration: var(--fa-animation-duration, 2s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, linear);
+          animation-timing-function: var(--fa-animation-timing, linear); }
+
+.fa-spin-reverse {
+  --fa-animation-direction: reverse; }
+
+.fa-pulse,
+.fa-spin-pulse {
+  -webkit-animation-name: fa-spin;
+          animation-name: fa-spin;
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, steps(8));
+          animation-timing-function: var(--fa-animation-timing, steps(8)); }
+
+@media (prefers-reduced-motion: reduce) {
+  .fa-beat,
+  .fa-bounce,
+  .fa-fade,
+  .fa-beat-fade,
+  .fa-flip,
+  .fa-pulse,
+  .fa-shake,
+  .fa-spin,
+  .fa-spin-pulse {
+    -webkit-animation-delay: -1ms;
+            animation-delay: -1ms;
+    -webkit-animation-duration: 1ms;
+            animation-duration: 1ms;
+    -webkit-animation-iteration-count: 1;
+            animation-iteration-count: 1;
+    -webkit-transition-delay: 0s;
+            transition-delay: 0s;
+    -webkit-transition-duration: 0s;
+            transition-duration: 0s; } }
+
+@-webkit-keyframes fa-beat {
+  0%, 90% {
+    -webkit-transform: scale(1);
+            transform: scale(1); }
+  45% {
+    -webkit-transform: scale(var(--fa-beat-scale, 1.25));
+            transform: scale(var(--fa-beat-scale, 1.25)); } }
+
+@keyframes fa-beat {
+  0%, 90% {
+    -webkit-transform: scale(1);
+            transform: scale(1); }
+  45% {
+    -webkit-transform: scale(var(--fa-beat-scale, 1.25));
+            transform: scale(var(--fa-beat-scale, 1.25)); } }
+
+@-webkit-keyframes fa-bounce {
+  0% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); }
+  10% {
+    -webkit-transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0);
+            transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0); }
+  30% {
+    -webkit-transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em));
+            transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em)); }
+  50% {
+    -webkit-transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0);
+            transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0); }
+  57% {
+    -webkit-transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em));
+            transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em)); }
+  64% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); }
+  100% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); } }
+
+@keyframes fa-bounce {
+  0% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); }
+  10% {
+    -webkit-transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0);
+            transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0); }
+  30% {
+    -webkit-transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em));
+            transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em)); }
+  50% {
+    -webkit-transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0);
+            transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0); }
+  57% {
+    -webkit-transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em));
+            transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em)); }
+  64% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); }
+  100% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); } }
+
+@-webkit-keyframes fa-fade {
+  50% {
+    opacity: var(--fa-fade-opacity, 0.4); } }
+
+@keyframes fa-fade {
+  50% {
+    opacity: var(--fa-fade-opacity, 0.4); } }
+
+@-webkit-keyframes fa-beat-fade {
+  0%, 100% {
+    opacity: var(--fa-beat-fade-opacity, 0.4);
+    -webkit-transform: scale(1);
+            transform: scale(1); }
+  50% {
+    opacity: 1;
+    -webkit-transform: scale(var(--fa-beat-fade-scale, 1.125));
+            transform: scale(var(--fa-beat-fade-scale, 1.125)); } }
+
+@keyframes fa-beat-fade {
+  0%, 100% {
+    opacity: var(--fa-beat-fade-opacity, 0.4);
+    -webkit-transform: scale(1);
+            transform: scale(1); }
+  50% {
+    opacity: 1;
+    -webkit-transform: scale(var(--fa-beat-fade-scale, 1.125));
+            transform: scale(var(--fa-beat-fade-scale, 1.125)); } }
+
+@-webkit-keyframes fa-flip {
+  50% {
+    -webkit-transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg));
+            transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg)); } }
+
+@keyframes fa-flip {
+  50% {
+    -webkit-transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg));
+            transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg)); } }
+
+@-webkit-keyframes fa-shake {
+  0% {
+    -webkit-transform: rotate(-15deg);
+            transform: rotate(-15deg); }
+  4% {
+    -webkit-transform: rotate(15deg);
+            transform: rotate(15deg); }
+  8%, 24% {
+    -webkit-transform: rotate(-18deg);
+            transform: rotate(-18deg); }
+  12%, 28% {
+    -webkit-transform: rotate(18deg);
+            transform: rotate(18deg); }
+  16% {
+    -webkit-transform: rotate(-22deg);
+            transform: rotate(-22deg); }
+  20% {
+    -webkit-transform: rotate(22deg);
+            transform: rotate(22deg); }
+  32% {
+    -webkit-transform: rotate(-12deg);
+            transform: rotate(-12deg); }
+  36% {
+    -webkit-transform: rotate(12deg);
+            transform: rotate(12deg); }
+  40%, 100% {
+    -webkit-transform: rotate(0deg);
+            transform: rotate(0deg); } }
+
+@keyframes fa-shake {
+  0% {
+    -webkit-transform: rotate(-15deg);
+            transform: rotate(-15deg); }
+  4% {
+    -webkit-transform: rotate(15deg);
+            transform: rotate(15deg); }
+  8%, 24% {
+    -webkit-transform: rotate(-18deg);
+            transform: rotate(-18deg); }
+  12%, 28% {
+    -webkit-transform: rotate(18deg);
+            transform: rotate(18deg); }
+  16% {
+    -webkit-transform: rotate(-22deg);
+            transform: rotate(-22deg); }
+  20% {
+    -webkit-transform: rotate(22deg);
+            transform: rotate(22deg); }
+  32% {
+    -webkit-transform: rotate(-12deg);
+            transform: rotate(-12deg); }
+  36% {
+    -webkit-transform: rotate(12deg);
+            transform: rotate(12deg); }
+  40%, 100% {
+    -webkit-transform: rotate(0deg);
+            transform: rotate(0deg); } }
+
+@-webkit-keyframes fa-spin {
+  0% {
+    -webkit-transform: rotate(0deg);
+            transform: rotate(0deg); }
+  100% {
+    -webkit-transform: rotate(360deg);
+            transform: rotate(360deg); } }
+
+@keyframes fa-spin {
+  0% {
+    -webkit-transform: rotate(0deg);
+            transform: rotate(0deg); }
+  100% {
+    -webkit-transform: rotate(360deg);
+            transform: rotate(360deg); } }
+
+.fa-rotate-90 {
+  -webkit-transform: rotate(90deg);
+          transform: rotate(90deg); }
+
+.fa-rotate-180 {
+  -webkit-transform: rotate(180deg);
+          transform: rotate(180deg); }
+
+.fa-rotate-270 {
+  -webkit-transform: rotate(270deg);
+          transform: rotate(270deg); }
+
+.fa-flip-horizontal {
+  -webkit-transform: scale(-1, 1);
+          transform: scale(-1, 1); }
+
+.fa-flip-vertical {
+  -webkit-transform: scale(1, -1);
+          transform: scale(1, -1); }
+
+.fa-flip-both,
+.fa-flip-horizontal.fa-flip-vertical {
+  -webkit-transform: scale(-1, -1);
+          transform: scale(-1, -1); }
+
+.fa-rotate-by {
+  -webkit-transform: rotate(var(--fa-rotate-angle, none));
+          transform: rotate(var(--fa-rotate-angle, none)); }
+
+.fa-stack {
+  display: inline-block;
+  vertical-align: middle;
+  height: 2em;
+  position: relative;
+  width: 2.5em; }
+
+.fa-stack-1x,
+.fa-stack-2x {
+  bottom: 0;
+  left: 0;
+  margin: auto;
+  position: absolute;
+  right: 0;
+  top: 0;
+  z-index: var(--fa-stack-z-index, auto); }
+
+.svg-inline--fa.fa-stack-1x {
+  height: 1em;
+  width: 1.25em; }
+
+.svg-inline--fa.fa-stack-2x {
+  height: 2em;
+  width: 2.5em; }
+
+.fa-inverse {
+  color: var(--fa-inverse, #fff); }
+
+.sr-only,
+.fa-sr-only {
+  position: absolute;
+  width: 1px;
+  height: 1px;
+  padding: 0;
+  margin: -1px;
+  overflow: hidden;
+  clip: rect(0, 0, 0, 0);
+  white-space: nowrap;
+  border-width: 0; }
+
+.sr-only-focusable:not(:focus),
+.fa-sr-only-focusable:not(:focus) {
+  position: absolute;
+  width: 1px;
+  height: 1px;
+  padding: 0;
+  margin: -1px;
+  overflow: hidden;
+  clip: rect(0, 0, 0, 0);
+  white-space: nowrap;
+  border-width: 0; }
+
+.svg-inline--fa .fa-primary {
+  fill: var(--fa-primary-color, currentColor);
+  opacity: var(--fa-primary-opacity, 1); }
+
+.svg-inline--fa .fa-secondary {
+  fill: var(--fa-secondary-color, currentColor);
+  opacity: var(--fa-secondary-opacity, 0.4); }
+
+.svg-inline--fa.fa-swap-opacity .fa-primary {
+  opacity: var(--fa-secondary-opacity, 0.4); }
+
+.svg-inline--fa.fa-swap-opacity .fa-secondary {
+  opacity: var(--fa-primary-opacity, 1); }
+
+.svg-inline--fa mask .fa-primary,
+.svg-inline--fa mask .fa-secondary {
+  fill: black; }
+
+.fad.fa-inverse,
+.fa-duotone.fa-inverse {
+  color: var(--fa-inverse, #fff); }

static/assets/FontAwesome/css/svg-with-js.min.css

@@ -0,0 +1,6 @@
+/*!
+ * Font Awesome Free 6.4.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */
+:host,:root{--fa-font-solid:normal 900 1em/1 "Font Awesome 6 Solid";--fa-font-regular:normal 400 1em/1 "Font Awesome 6 Regular";--fa-font-light:normal 300 1em/1 "Font Awesome 6 Light";--fa-font-thin:normal 100 1em/1 "Font Awesome 6 Thin";--fa-font-duotone:normal 900 1em/1 "Font Awesome 6 Duotone";--fa-font-sharp-solid:normal 900 1em/1 "Font Awesome 6 Sharp";--fa-font-sharp-regular:normal 400 1em/1 "Font Awesome 6 Sharp";--fa-font-sharp-light:normal 300 1em/1 "Font Awesome 6 Sharp";--fa-font-brands:normal 400 1em/1 "Font Awesome 6 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.15em)}.fa-pull-left{float:left;margin-right:var(--fa-pull-margin,.3em)}.fa-pull-right{float:right;margin-left:var(--fa-pull-margin,.3em)}.fa-beat{-webkit-animation-name:fa-beat;animation-name:fa-beat;-webkit-animation-delay:var(--fa-animation-delay,0s);animation-delay:var(--fa-animation-delay,0s);-webkit-animation-direction:var(--fa-animation-direction,normal);animation-direction:var(--fa-animation-direction,normal);-webkit-animation-duration:var(--fa-animation-duration,1s);animation-duration:var(--fa-animation-duration,1s);-webkit-animation-iteration-count:var(--fa-animation-iteration-count,infinite);animation-iteration-count:var(--fa-animation-iteration-count,infinite);-webkit-animation-timing-function:var(--fa-animation-timing,ease-in-out);animation-timing-function:var(--fa-animation-timing,ease-in-out)}.fa-bounce{-webkit-animation-name:fa-bounce;animation-name:fa-bounce;-webkit-animation-delay:var(--fa-animation-delay,0s);animation-delay:var(--fa-animation-delay,0s);-webkit-animation-direction:var(--fa-animation-direction,normal);animation-direction:var(--fa-animation-direction,normal);-webkit-animation-duration:var(--fa-animation-duration,1s);animation-duration:var(--fa-animation-duration,1s);-webkit-animation-iteration-count:var(--fa-animation-iteration-count,infinite);animation-iteration-count:var(--fa-animation-iteration-count,infinite);-webkit-animation-timing-function:var(--fa-animation-timing,cubic-bezier(.28,.84,.42,1));animation-timing-function:var(--fa-animation-timing,cubic-bezier(.28,.84,.42,1))}.fa-fade{-webkit-animation-name:fa-fade;animation-name:fa-fade;-webkit-animation-iteration-count:var(--fa-animation-iteration-count,infinite);animation-iteration-count:var(--fa-animation-iteration-count,infinite);-webkit-animation-timing-function:var(--fa-animation-timing,cubic-bezier(.4,0,.6,1));animation-timing-function:var(--fa-animation-timing,cubic-bezier(.4,0,.6,1))}.fa-beat-fade,.fa-fade{-webkit-animation-delay:var(--fa-animation-delay,0s);animation-delay:var(--fa-animation-delay,0s);-webkit-animation-direction:var(--fa-animation-direction,normal);animation-direction:var(--fa-animation-direction,normal);-webkit-animation-duration:var(--fa-animation-duration,1s);animation-duration:var(--fa-animation-duration,1s)}.fa-beat-fade{-webkit-animation-name:fa-beat-fade;animation-name:fa-beat-fade;-webkit-animation-iteration-count:var(--fa-animation-iteration-count,infinite);animation-iteration-count:var(--fa-animation-iteration-count,infinite);-webkit-animation-timing-function:var(--fa-animation-timing,cubic-bezier(.4,0,.6,1));animation-timing-function:var(--fa-animation-timing,cubic-bezier(.4,0,.6,1))}.fa-flip{-webkit-animation-name:fa-flip;animation-name:fa-flip;-webkit-animation-delay:var(--fa-animation-delay,0s);animation-delay:var(--fa-animation-delay,0s);-webkit-animation-direction:var(--fa-animation-direction,normal);animation-direction:var(--fa-animation-direction,normal);-webkit-animation-duration:var(--fa-animation-duration,1s);animation-duration:var(--fa-animation-duration,1s);-webkit-animation-iteration-count:var(--fa-animation-iteration-count,infinite);animation-iteration-count:var(--fa-animation-iteration-count,infinite);-webkit-animation-timing-function:var(--fa-animation-timing,ease-in-out);animation-timing-function:var(--fa-animation-timing,ease-in-out)}.fa-shake{-webkit-animation-name:fa-shake;animation-name:fa-shake;-webkit-animation-duration:var(--fa-animation-duration,1s);animation-duration:var(--fa-animation-duration,1s);-webkit-animation-iteration-count:var(--fa-animation-iteration-count,infinite);animation-iteration-count:var(--fa-animation-iteration-count,infinite);-webkit-animation-timing-function:var(--fa-animation-timing,linear);animation-timing-function:var(--fa-animation-timing,linear)}.fa-shake,.fa-spin{-webkit-animation-delay:var(--fa-animation-delay,0s);animation-delay:var(--fa-animation-delay,0s);-webkit-animation-direction:var(--fa-animation-direction,normal);animation-direction:var(--fa-animation-direction,normal)}.fa-spin{-webkit-animation-name:fa-spin;animation-name:fa-spin;-webkit-animation-duration:var(--fa-animation-duration,2s);animation-duration:var(--fa-animation-duration,2s);-webkit-animation-iteration-count:var(--fa-animation-iteration-count,infinite);animation-iteration-count:var(--fa-animation-iteration-count,infinite);-webkit-animation-timing-function:var(--fa-animation-timing,linear);animation-timing-function:var(--fa-animation-timing,linear)}.fa-spin-reverse{--fa-animation-direction:reverse}.fa-pulse,.fa-spin-pulse{-webkit-animation-name:fa-spin;animation-name:fa-spin;-webkit-animation-direction:var(--fa-animation-direction,normal);animation-direction:var(--fa-animation-direction,normal);-webkit-animation-duration:var(--fa-animation-duration,1s);animation-duration:var(--fa-animation-duration,1s);-webkit-animation-iteration-count:var(--fa-animation-iteration-count,infinite);animation-iteration-count:var(--fa-animation-iteration-count,infinite);-webkit-animation-timing-function:var(--fa-animation-timing,steps(8));animation-timing-function:var(--fa-animation-timing,steps(8))}@media 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fa-spin{0%{-webkit-transform:rotate(0deg);transform:rotate(0deg)}to{-webkit-transform:rotate(1turn);transform:rotate(1turn)}}.fa-rotate-90{-webkit-transform:rotate(90deg);transform:rotate(90deg)}.fa-rotate-180{-webkit-transform:rotate(180deg);transform:rotate(180deg)}.fa-rotate-270{-webkit-transform:rotate(270deg);transform:rotate(270deg)}.fa-flip-horizontal{-webkit-transform:scaleX(-1);transform:scaleX(-1)}.fa-flip-vertical{-webkit-transform:scaleY(-1);transform:scaleY(-1)}.fa-flip-both,.fa-flip-horizontal.fa-flip-vertical{-webkit-transform:scale(-1);transform:scale(-1)}.fa-rotate-by{-webkit-transform:rotate(var(--fa-rotate-angle,none));transform:rotate(var(--fa-rotate-angle,none))}.fa-stack{display:inline-block;vertical-align:middle;height:2em;position:relative;width:2.5em}.fa-stack-1x,.fa-stack-2x{bottom:0;left:0;margin:auto;position:absolute;right:0;top:0;z-index:var(--fa-stack-z-index,auto)}.svg-inline--fa.fa-stack-1x{height:1em;width:1.25em}.svg-inline--fa.fa-stack-2x{height:2em;width:2.5em}.fa-inverse{color:var(--fa-inverse,#fff)}.fa-sr-only,.fa-sr-only-focusable:not(:focus),.sr-only,.sr-only-focusable:not(:focus){position:absolute;width:1px;height:1px;padding:0;margin:-1px;overflow:hidden;clip:rect(0,0,0,0);white-space:nowrap;border-width:0}.svg-inline--fa .fa-primary{fill:var(--fa-primary-color,currentColor);opacity:var(--fa-primary-opacity,1)}.svg-inline--fa .fa-secondary{fill:var(--fa-secondary-color,currentColor)}.svg-inline--fa .fa-secondary,.svg-inline--fa.fa-swap-opacity .fa-primary{opacity:var(--fa-secondary-opacity,.4)}.svg-inline--fa.fa-swap-opacity .fa-secondary{opacity:var(--fa-primary-opacity,1)}.svg-inline--fa mask .fa-primary,.svg-inline--fa mask .fa-secondary{fill:#000}.fa-duotone.fa-inverse,.fad.fa-inverse{color:var(--fa-inverse,#fff)}

static/assets/FontAwesome/css/v4-font-face.css

@@ -0,0 +1,26 @@
+/*!
+ * Font Awesome Free 6.4.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */
+@font-face {
+  font-family: 'FontAwesome';
+  font-display: block;
+  src: url("../webfonts/fa-solid-900.woff2") format("woff2"), url("../webfonts/fa-solid-900.ttf") format("truetype"); }
+
+@font-face {
+  font-family: 'FontAwesome';
+  font-display: block;
+  src: url("../webfonts/fa-brands-400.woff2") format("woff2"), url("../webfonts/fa-brands-400.ttf") format("truetype"); }
+
+@font-face {
+  font-family: 'FontAwesome';
+  font-display: block;
+  src: url("../webfonts/fa-regular-400.woff2") format("woff2"), url("../webfonts/fa-regular-400.ttf") format("truetype");
+  unicode-range: U+F003,U+F006,U+F014,U+F016-F017,U+F01A-F01B,U+F01D,U+F022,U+F03E,U+F044,U+F046,U+F05C-F05D,U+F06E,U+F070,U+F087-F088,U+F08A,U+F094,U+F096-F097,U+F09D,U+F0A0,U+F0A2,U+F0A4-F0A7,U+F0C5,U+F0C7,U+F0E5-F0E6,U+F0EB,U+F0F6-F0F8,U+F10C,U+F114-F115,U+F118-F11A,U+F11C-F11D,U+F133,U+F147,U+F14E,U+F150-F152,U+F185-F186,U+F18E,U+F190-F192,U+F196,U+F1C1-F1C9,U+F1D9,U+F1DB,U+F1E3,U+F1EA,U+F1F7,U+F1F9,U+F20A,U+F247-F248,U+F24A,U+F24D,U+F255-F25B,U+F25D,U+F271-F274,U+F278,U+F27B,U+F28C,U+F28E,U+F29C,U+F2B5,U+F2B7,U+F2BA,U+F2BC,U+F2BE,U+F2C0-F2C1,U+F2C3,U+F2D0,U+F2D2,U+F2D4,U+F2DC; }
+
+@font-face {
+  font-family: 'FontAwesome';
+  font-display: block;
+  src: url("../webfonts/fa-v4compatibility.woff2") format("woff2"), url("../webfonts/fa-v4compatibility.ttf") format("truetype");
+  unicode-range: U+F041,U+F047,U+F065-F066,U+F07D-F07E,U+F080,U+F08B,U+F08E,U+F090,U+F09A,U+F0AC,U+F0AE,U+F0B2,U+F0D0,U+F0D6,U+F0E4,U+F0EC,U+F10A-F10B,U+F123,U+F13E,U+F148-F149,U+F14C,U+F156,U+F15E,U+F160-F161,U+F163,U+F175-F178,U+F195,U+F1F8,U+F219,U+F27A; }

static/assets/FontAwesome/css/v4-font-face.min.css

@@ -0,0 +1,6 @@
+/*!
+ * Font Awesome Free 6.4.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */
+@font-face{font-family:"FontAwesome";font-display:block;src:url(../webfonts/fa-solid-900.woff2) format("woff2"),url(../webfonts/fa-solid-900.ttf) format("truetype")}@font-face{font-family:"FontAwesome";font-display:block;src:url(../webfonts/fa-brands-400.woff2) format("woff2"),url(../webfonts/fa-brands-400.ttf) format("truetype")}@font-face{font-family:"FontAwesome";font-display:block;src:url(../webfonts/fa-regular-400.woff2) format("woff2"),url(../webfonts/fa-regular-400.ttf) format("truetype");unicode-range:u+f003,u+f006,u+f014,u+f016-f017,u+f01a-f01b,u+f01d,u+f022,u+f03e,u+f044,u+f046,u+f05c-f05d,u+f06e,u+f070,u+f087-f088,u+f08a,u+f094,u+f096-f097,u+f09d,u+f0a0,u+f0a2,u+f0a4-f0a7,u+f0c5,u+f0c7,u+f0e5-f0e6,u+f0eb,u+f0f6-f0f8,u+f10c,u+f114-f115,u+f118-f11a,u+f11c-f11d,u+f133,u+f147,u+f14e,u+f150-f152,u+f185-f186,u+f18e,u+f190-f192,u+f196,u+f1c1-f1c9,u+f1d9,u+f1db,u+f1e3,u+f1ea,u+f1f7,u+f1f9,u+f20a,u+f247-f248,u+f24a,u+f24d,u+f255-f25b,u+f25d,u+f271-f274,u+f278,u+f27b,u+f28c,u+f28e,u+f29c,u+f2b5,u+f2b7,u+f2ba,u+f2bc,u+f2be,u+f2c0-f2c1,u+f2c3,u+f2d0,u+f2d2,u+f2d4,u+f2dc}@font-face{font-family:"FontAwesome";font-display:block;src:url(../webfonts/fa-v4compatibility.woff2) format("woff2"),url(../webfonts/fa-v4compatibility.ttf) format("truetype");unicode-range:u+f041,u+f047,u+f065-f066,u+f07d-f07e,u+f080,u+f08b,u+f08e,u+f090,u+f09a,u+f0ac,u+f0ae,u+f0b2,u+f0d0,u+f0d6,u+f0e4,u+f0ec,u+f10a-f10b,u+f123,u+f13e,u+f148-f149,u+f14c,u+f156,u+f15e,u+f160-f161,u+f163,u+f175-f178,u+f195,u+f1f8,u+f219,u+f27a}

static/assets/FontAwesome/css/v4-shims.css

@@ -0,0 +1,2194 @@
+/*!
+ * Font Awesome Free 6.4.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */
+.fa.fa-glass:before {
+  content: "\f000"; }
+
+.fa.fa-envelope-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-envelope-o:before {
+  content: "\f0e0"; }
+
+.fa.fa-star-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-star-o:before {
+  content: "\f005"; }
+
+.fa.fa-remove:before {
+  content: "\f00d"; }
+
+.fa.fa-close:before {
+  content: "\f00d"; }
+
+.fa.fa-gear:before {
+  content: "\f013"; }
+
+.fa.fa-trash-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-trash-o:before {
+  content: "\f2ed"; }
+
+.fa.fa-home:before {
+  content: "\f015"; }
+
+.fa.fa-file-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-file-o:before {
+  content: "\f15b"; }
+
+.fa.fa-clock-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-clock-o:before {
+  content: "\f017"; }
+
+.fa.fa-arrow-circle-o-down {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-arrow-circle-o-down:before {
+  content: "\f358"; }
+
+.fa.fa-arrow-circle-o-up {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-arrow-circle-o-up:before {
+  content: "\f35b"; }
+
+.fa.fa-play-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-play-circle-o:before {
+  content: "\f144"; }
+
+.fa.fa-repeat:before {
+  content: "\f01e"; }
+
+.fa.fa-rotate-right:before {
+  content: "\f01e"; }
+
+.fa.fa-refresh:before {
+  content: "\f021"; }
+
+.fa.fa-list-alt {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-list-alt:before {
+  content: "\f022"; }
+
+.fa.fa-dedent:before {
+  content: "\f03b"; }
+
+.fa.fa-video-camera:before {
+  content: "\f03d"; }
+
+.fa.fa-picture-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-picture-o:before {
+  content: "\f03e"; }
+
+.fa.fa-photo {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-photo:before {
+  content: "\f03e"; }
+
+.fa.fa-image {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-image:before {
+  content: "\f03e"; }
+
+.fa.fa-map-marker:before {
+  content: "\f3c5"; }
+
+.fa.fa-pencil-square-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-pencil-square-o:before {
+  content: "\f044"; }
+
+.fa.fa-edit {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-edit:before {
+  content: "\f044"; }
+
+.fa.fa-share-square-o:before {
+  content: "\f14d"; }
+
+.fa.fa-check-square-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-check-square-o:before {
+  content: "\f14a"; }
+
+.fa.fa-arrows:before {
+  content: "\f0b2"; }
+
+.fa.fa-times-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-times-circle-o:before {
+  content: "\f057"; }
+
+.fa.fa-check-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-check-circle-o:before {
+  content: "\f058"; }
+
+.fa.fa-mail-forward:before {
+  content: "\f064"; }
+
+.fa.fa-expand:before {
+  content: "\f424"; }
+
+.fa.fa-compress:before {
+  content: "\f422"; }
+
+.fa.fa-eye {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-eye-slash {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-warning:before {
+  content: "\f071"; }
+
+.fa.fa-calendar:before {
+  content: "\f073"; }
+
+.fa.fa-arrows-v:before {
+  content: "\f338"; }
+
+.fa.fa-arrows-h:before {
+  content: "\f337"; }
+
+.fa.fa-bar-chart:before {
+  content: "\e0e3"; }
+
+.fa.fa-bar-chart-o:before {
+  content: "\e0e3"; }
+
+.fa.fa-twitter-square {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-twitter-square:before {
+  content: "\f081"; }
+
+.fa.fa-facebook-square {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-facebook-square:before {
+  content: "\f082"; }
+
+.fa.fa-gears:before {
+  content: "\f085"; }
+
+.fa.fa-thumbs-o-up {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-thumbs-o-up:before {
+  content: "\f164"; }
+
+.fa.fa-thumbs-o-down {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-thumbs-o-down:before {
+  content: "\f165"; }
+
+.fa.fa-heart-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-heart-o:before {
+  content: "\f004"; }
+
+.fa.fa-sign-out:before {
+  content: "\f2f5"; }
+
+.fa.fa-linkedin-square {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-linkedin-square:before {
+  content: "\f08c"; }
+
+.fa.fa-thumb-tack:before {
+  content: "\f08d"; }
+
+.fa.fa-external-link:before {
+  content: "\f35d"; }
+
+.fa.fa-sign-in:before {
+  content: "\f2f6"; }
+
+.fa.fa-github-square {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-github-square:before {
+  content: "\f092"; }
+
+.fa.fa-lemon-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-lemon-o:before {
+  content: "\f094"; }
+
+.fa.fa-square-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-square-o:before {
+  content: "\f0c8"; }
+
+.fa.fa-bookmark-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-bookmark-o:before {
+  content: "\f02e"; }
+
+.fa.fa-twitter {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-facebook {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-facebook:before {
+  content: "\f39e"; }
+
+.fa.fa-facebook-f {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-facebook-f:before {
+  content: "\f39e"; }
+
+.fa.fa-github {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-credit-card {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-feed:before {
+  content: "\f09e"; }
+
+.fa.fa-hdd-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hdd-o:before {
+  content: "\f0a0"; }
+
+.fa.fa-hand-o-right {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-o-right:before {
+  content: "\f0a4"; }
+
+.fa.fa-hand-o-left {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-o-left:before {
+  content: "\f0a5"; }
+
+.fa.fa-hand-o-up {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-o-up:before {
+  content: "\f0a6"; }
+
+.fa.fa-hand-o-down {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-o-down:before {
+  content: "\f0a7"; }
+
+.fa.fa-globe:before {
+  content: "\f57d"; }
+
+.fa.fa-tasks:before {
+  content: "\f828"; }
+
+.fa.fa-arrows-alt:before {
+  content: "\f31e"; }
+
+.fa.fa-group:before {
+  content: "\f0c0"; }
+
+.fa.fa-chain:before {
+  content: "\f0c1"; }
+
+.fa.fa-cut:before {
+  content: "\f0c4"; }
+
+.fa.fa-files-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-files-o:before {
+  content: "\f0c5"; }
+
+.fa.fa-floppy-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-floppy-o:before {
+  content: "\f0c7"; }
+
+.fa.fa-save {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-save:before {
+  content: "\f0c7"; }
+
+.fa.fa-navicon:before {
+  content: "\f0c9"; }
+
+.fa.fa-reorder:before {
+  content: "\f0c9"; }
+
+.fa.fa-magic:before {
+  content: "\e2ca"; }
+
+.fa.fa-pinterest {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-pinterest-square {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-pinterest-square:before {
+  content: "\f0d3"; }
+
+.fa.fa-google-plus-square {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-google-plus-square:before {
+  content: "\f0d4"; }
+
+.fa.fa-google-plus {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-google-plus:before {
+  content: "\f0d5"; }
+
+.fa.fa-money:before {
+  content: "\f3d1"; }
+
+.fa.fa-unsorted:before {
+  content: "\f0dc"; }
+
+.fa.fa-sort-desc:before {
+  content: "\f0dd"; }
+
+.fa.fa-sort-asc:before {
+  content: "\f0de"; }
+
+.fa.fa-linkedin {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-linkedin:before {
+  content: "\f0e1"; }
+
+.fa.fa-rotate-left:before {
+  content: "\f0e2"; }
+
+.fa.fa-legal:before {
+  content: "\f0e3"; }
+
+.fa.fa-tachometer:before {
+  content: "\f625"; }
+
+.fa.fa-dashboard:before {
+  content: "\f625"; }
+
+.fa.fa-comment-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-comment-o:before {
+  content: "\f075"; }
+
+.fa.fa-comments-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-comments-o:before {
+  content: "\f086"; }
+
+.fa.fa-flash:before {
+  content: "\f0e7"; }
+
+.fa.fa-clipboard:before {
+  content: "\f0ea"; }
+
+.fa.fa-lightbulb-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-lightbulb-o:before {
+  content: "\f0eb"; }
+
+.fa.fa-exchange:before {
+  content: "\f362"; }
+
+.fa.fa-cloud-download:before {
+  content: "\f0ed"; }
+
+.fa.fa-cloud-upload:before {
+  content: "\f0ee"; }
+
+.fa.fa-bell-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-bell-o:before {
+  content: "\f0f3"; }
+
+.fa.fa-cutlery:before {
+  content: "\f2e7"; }
+
+.fa.fa-file-text-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-file-text-o:before {
+  content: "\f15c"; }
+
+.fa.fa-building-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-building-o:before {
+  content: "\f1ad"; }
+
+.fa.fa-hospital-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hospital-o:before {
+  content: "\f0f8"; }
+
+.fa.fa-tablet:before {
+  content: "\f3fa"; }
+
+.fa.fa-mobile:before {
+  content: "\f3cd"; }
+
+.fa.fa-mobile-phone:before {
+  content: "\f3cd"; }
+
+.fa.fa-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-circle-o:before {
+  content: "\f111"; }
+
+.fa.fa-mail-reply:before {
+  content: "\f3e5"; }
+
+.fa.fa-github-alt {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-folder-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-folder-o:before {
+  content: "\f07b"; }
+
+.fa.fa-folder-open-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-folder-open-o:before {
+  content: "\f07c"; }
+
+.fa.fa-smile-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-smile-o:before {
+  content: "\f118"; }
+
+.fa.fa-frown-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-frown-o:before {
+  content: "\f119"; }
+
+.fa.fa-meh-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-meh-o:before {
+  content: "\f11a"; }
+
+.fa.fa-keyboard-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-keyboard-o:before {
+  content: "\f11c"; }
+
+.fa.fa-flag-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-flag-o:before {
+  content: "\f024"; }
+
+.fa.fa-mail-reply-all:before {
+  content: "\f122"; }
+
+.fa.fa-star-half-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-star-half-o:before {
+  content: "\f5c0"; }
+
+.fa.fa-star-half-empty {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-star-half-empty:before {
+  content: "\f5c0"; }
+
+.fa.fa-star-half-full {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-star-half-full:before {
+  content: "\f5c0"; }
+
+.fa.fa-code-fork:before {
+  content: "\f126"; }
+
+.fa.fa-chain-broken:before {
+  content: "\f127"; }
+
+.fa.fa-unlink:before {
+  content: "\f127"; }
+
+.fa.fa-calendar-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-calendar-o:before {
+  content: "\f133"; }
+
+.fa.fa-maxcdn {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-html5 {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-css3 {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-unlock-alt:before {
+  content: "\f09c"; }
+
+.fa.fa-minus-square-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-minus-square-o:before {
+  content: "\f146"; }
+
+.fa.fa-level-up:before {
+  content: "\f3bf"; }
+
+.fa.fa-level-down:before {
+  content: "\f3be"; }
+
+.fa.fa-pencil-square:before {
+  content: "\f14b"; }
+
+.fa.fa-external-link-square:before {
+  content: "\f360"; }
+
+.fa.fa-compass {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-caret-square-o-down {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-caret-square-o-down:before {
+  content: "\f150"; }
+
+.fa.fa-toggle-down {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-toggle-down:before {
+  content: "\f150"; }
+
+.fa.fa-caret-square-o-up {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-caret-square-o-up:before {
+  content: "\f151"; }
+
+.fa.fa-toggle-up {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-toggle-up:before {
+  content: "\f151"; }
+
+.fa.fa-caret-square-o-right {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-caret-square-o-right:before {
+  content: "\f152"; }
+
+.fa.fa-toggle-right {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-toggle-right:before {
+  content: "\f152"; }
+
+.fa.fa-eur:before {
+  content: "\f153"; }
+
+.fa.fa-euro:before {
+  content: "\f153"; }
+
+.fa.fa-gbp:before {
+  content: "\f154"; }
+
+.fa.fa-usd:before {
+  content: "\24"; }
+
+.fa.fa-dollar:before {
+  content: "\24"; }
+
+.fa.fa-inr:before {
+  content: "\e1bc"; }
+
+.fa.fa-rupee:before {
+  content: "\e1bc"; }
+
+.fa.fa-jpy:before {
+  content: "\f157"; }
+
+.fa.fa-cny:before {
+  content: "\f157"; }
+
+.fa.fa-rmb:before {
+  content: "\f157"; }
+
+.fa.fa-yen:before {
+  content: "\f157"; }
+
+.fa.fa-rub:before {
+  content: "\f158"; }
+
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+  content: "\f240"; }
+
+.fa.fa-battery:before {
+  content: "\f240"; }
+
+.fa.fa-battery-3:before {
+  content: "\f241"; }
+
+.fa.fa-battery-2:before {
+  content: "\f242"; }
+
+.fa.fa-battery-1:before {
+  content: "\f243"; }
+
+.fa.fa-battery-0:before {
+  content: "\f244"; }
+
+.fa.fa-object-group {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-object-ungroup {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-sticky-note-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-sticky-note-o:before {
+  content: "\f249"; }
+
+.fa.fa-cc-jcb {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-cc-diners-club {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-clone {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hourglass-o:before {
+  content: "\f254"; }
+
+.fa.fa-hourglass-1:before {
+  content: "\f251"; }
+
+.fa.fa-hourglass-2:before {
+  content: "\f252"; }
+
+.fa.fa-hourglass-3:before {
+  content: "\f253"; }
+
+.fa.fa-hand-rock-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-rock-o:before {
+  content: "\f255"; }
+
+.fa.fa-hand-grab-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-grab-o:before {
+  content: "\f255"; }
+
+.fa.fa-hand-paper-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-paper-o:before {
+  content: "\f256"; }
+
+.fa.fa-hand-stop-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-stop-o:before {
+  content: "\f256"; }
+
+.fa.fa-hand-scissors-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-scissors-o:before {
+  content: "\f257"; }
+
+.fa.fa-hand-lizard-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-lizard-o:before {
+  content: "\f258"; }
+
+.fa.fa-hand-spock-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-spock-o:before {
+  content: "\f259"; }
+
+.fa.fa-hand-pointer-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-pointer-o:before {
+  content: "\f25a"; }
+
+.fa.fa-hand-peace-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-hand-peace-o:before {
+  content: "\f25b"; }
+
+.fa.fa-registered {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-creative-commons {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-gg {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-gg-circle {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-odnoklassniki {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-odnoklassniki-square {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-odnoklassniki-square:before {
+  content: "\f264"; }
+
+.fa.fa-get-pocket {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wikipedia-w {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-safari {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-chrome {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-firefox {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-opera {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-internet-explorer {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-television:before {
+  content: "\f26c"; }
+
+.fa.fa-contao {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-500px {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-amazon {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-calendar-plus-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-calendar-plus-o:before {
+  content: "\f271"; }
+
+.fa.fa-calendar-minus-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-calendar-minus-o:before {
+  content: "\f272"; }
+
+.fa.fa-calendar-times-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-calendar-times-o:before {
+  content: "\f273"; }
+
+.fa.fa-calendar-check-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-calendar-check-o:before {
+  content: "\f274"; }
+
+.fa.fa-map-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-map-o:before {
+  content: "\f279"; }
+
+.fa.fa-commenting:before {
+  content: "\f4ad"; }
+
+.fa.fa-commenting-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-commenting-o:before {
+  content: "\f4ad"; }
+
+.fa.fa-houzz {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-vimeo {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-vimeo:before {
+  content: "\f27d"; }
+
+.fa.fa-black-tie {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-fonticons {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-reddit-alien {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-edge {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-credit-card-alt:before {
+  content: "\f09d"; }
+
+.fa.fa-codiepie {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-modx {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-fort-awesome {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-usb {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-product-hunt {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-mixcloud {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-scribd {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-pause-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-pause-circle-o:before {
+  content: "\f28b"; }
+
+.fa.fa-stop-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-stop-circle-o:before {
+  content: "\f28d"; }
+
+.fa.fa-bluetooth {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-bluetooth-b {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-gitlab {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wpbeginner {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wpforms {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-envira {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wheelchair-alt {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wheelchair-alt:before {
+  content: "\f368"; }
+
+.fa.fa-question-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-question-circle-o:before {
+  content: "\f059"; }
+
+.fa.fa-volume-control-phone:before {
+  content: "\f2a0"; }
+
+.fa.fa-asl-interpreting:before {
+  content: "\f2a3"; }
+
+.fa.fa-deafness:before {
+  content: "\f2a4"; }
+
+.fa.fa-hard-of-hearing:before {
+  content: "\f2a4"; }
+
+.fa.fa-glide {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-glide-g {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-signing:before {
+  content: "\f2a7"; }
+
+.fa.fa-viadeo {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-viadeo-square {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-viadeo-square:before {
+  content: "\f2aa"; }
+
+.fa.fa-snapchat {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-snapchat-ghost {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-snapchat-ghost:before {
+  content: "\f2ab"; }
+
+.fa.fa-snapchat-square {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-snapchat-square:before {
+  content: "\f2ad"; }
+
+.fa.fa-pied-piper {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-first-order {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-yoast {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-themeisle {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-google-plus-official {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-google-plus-official:before {
+  content: "\f2b3"; }
+
+.fa.fa-google-plus-circle {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-google-plus-circle:before {
+  content: "\f2b3"; }
+
+.fa.fa-font-awesome {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-fa {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-fa:before {
+  content: "\f2b4"; }
+
+.fa.fa-handshake-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-handshake-o:before {
+  content: "\f2b5"; }
+
+.fa.fa-envelope-open-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-envelope-open-o:before {
+  content: "\f2b6"; }
+
+.fa.fa-linode {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-address-book-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-address-book-o:before {
+  content: "\f2b9"; }
+
+.fa.fa-vcard:before {
+  content: "\f2bb"; }
+
+.fa.fa-address-card-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-address-card-o:before {
+  content: "\f2bb"; }
+
+.fa.fa-vcard-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-vcard-o:before {
+  content: "\f2bb"; }
+
+.fa.fa-user-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-user-circle-o:before {
+  content: "\f2bd"; }
+
+.fa.fa-user-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-user-o:before {
+  content: "\f007"; }
+
+.fa.fa-id-badge {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-drivers-license:before {
+  content: "\f2c2"; }
+
+.fa.fa-id-card-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-id-card-o:before {
+  content: "\f2c2"; }
+
+.fa.fa-drivers-license-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-drivers-license-o:before {
+  content: "\f2c2"; }
+
+.fa.fa-quora {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-free-code-camp {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-telegram {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-thermometer-4:before {
+  content: "\f2c7"; }
+
+.fa.fa-thermometer:before {
+  content: "\f2c7"; }
+
+.fa.fa-thermometer-3:before {
+  content: "\f2c8"; }
+
+.fa.fa-thermometer-2:before {
+  content: "\f2c9"; }
+
+.fa.fa-thermometer-1:before {
+  content: "\f2ca"; }
+
+.fa.fa-thermometer-0:before {
+  content: "\f2cb"; }
+
+.fa.fa-bathtub:before {
+  content: "\f2cd"; }
+
+.fa.fa-s15:before {
+  content: "\f2cd"; }
+
+.fa.fa-window-maximize {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-window-restore {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-times-rectangle:before {
+  content: "\f410"; }
+
+.fa.fa-window-close-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-window-close-o:before {
+  content: "\f410"; }
+
+.fa.fa-times-rectangle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-times-rectangle-o:before {
+  content: "\f410"; }
+
+.fa.fa-bandcamp {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-grav {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-etsy {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-imdb {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-ravelry {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-eercast {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-eercast:before {
+  content: "\f2da"; }
+
+.fa.fa-snowflake-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-snowflake-o:before {
+  content: "\f2dc"; }
+
+.fa.fa-superpowers {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wpexplorer {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-meetup {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }

static/assets/FontAwesome/css/v4-shims.min.css

@@ -0,0 +1,6 @@
+/*!
+ * Font Awesome Free 6.4.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */
+.fa.fa-glass:before{content:"\f000"}.fa.fa-envelope-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-envelope-o:before{content:"\f0e0"}.fa.fa-star-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-star-o:before{content:"\f005"}.fa.fa-close:before,.fa.fa-remove:before{content:"\f00d"}.fa.fa-gear:before{content:"\f013"}.fa.fa-trash-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-trash-o:before{content:"\f2ed"}.fa.fa-home:before{content:"\f015"}.fa.fa-file-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-file-o:before{content:"\f15b"}.fa.fa-clock-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-clock-o:before{content:"\f017"}.fa.fa-arrow-circle-o-down{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-arrow-circle-o-down:before{content:"\f358"}.fa.fa-arrow-circle-o-up{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-arrow-circle-o-up:before{content:"\f35b"}.fa.fa-play-circle-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-play-circle-o:before{content:"\f144"}.fa.fa-repeat:before,.fa.fa-rotate-right:before{content:"\f01e"}.fa.fa-refresh:before{content:"\f021"}.fa.fa-list-alt{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-list-alt:before{content:"\f022"}.fa.fa-dedent:before{content:"\f03b"}.fa.fa-video-camera:before{content:"\f03d"}.fa.fa-picture-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-picture-o:before{content:"\f03e"}.fa.fa-photo{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-photo:before{content:"\f03e"}.fa.fa-image{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-image:before{content:"\f03e"}.fa.fa-map-marker:before{content:"\f3c5"}.fa.fa-pencil-square-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-pencil-square-o:before{content:"\f044"}.fa.fa-edit{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-edit:before{content:"\f044"}.fa.fa-share-square-o:before{content:"\f14d"}.fa.fa-check-square-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-check-square-o:before{content:"\f14a"}.fa.fa-arrows:before{content:"\f0b2"}.fa.fa-times-circle-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-times-circle-o:before{content:"\f057"}.fa.fa-check-circle-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-check-circle-o:before{content:"\f058"}.fa.fa-mail-forward:before{content:"\f064"}.fa.fa-expand:before{content:"\f424"}.fa.fa-compress:before{content:"\f422"}.fa.fa-eye,.fa.fa-eye-slash{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-warning:before{content:"\f071"}.fa.fa-calendar:before{content:"\f073"}.fa.fa-arrows-v:before{content:"\f338"}.fa.fa-arrows-h:before{content:"\f337"}.fa.fa-bar-chart-o:before,.fa.fa-bar-chart:before{content:"\e0e3"}.fa.fa-twitter-square{font-family:"Font Awesome 6 Brands";font-weight:400}.fa.fa-twitter-square:before{content:"\f081"}.fa.fa-facebook-square{font-family:"Font Awesome 6 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Brands";font-weight:400}.fa.fa-credit-card-alt:before{content:"\f09d"}.fa.fa-codiepie,.fa.fa-fort-awesome,.fa.fa-mixcloud,.fa.fa-modx,.fa.fa-product-hunt,.fa.fa-scribd,.fa.fa-usb{font-family:"Font Awesome 6 Brands";font-weight:400}.fa.fa-pause-circle-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-pause-circle-o:before{content:"\f28b"}.fa.fa-stop-circle-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-stop-circle-o:before{content:"\f28d"}.fa.fa-bluetooth,.fa.fa-bluetooth-b,.fa.fa-envira,.fa.fa-gitlab,.fa.fa-wheelchair-alt,.fa.fa-wpbeginner,.fa.fa-wpforms{font-family:"Font Awesome 6 Brands";font-weight:400}.fa.fa-wheelchair-alt:before{content:"\f368"}.fa.fa-question-circle-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-question-circle-o:before{content:"\f059"}.fa.fa-volume-control-phone:before{content:"\f2a0"}.fa.fa-asl-interpreting:before{content:"\f2a3"}.fa.fa-deafness:before,.fa.fa-hard-of-hearing:before{content:"\f2a4"}.fa.fa-glide,.fa.fa-glide-g{font-family:"Font Awesome 6 Brands";font-weight:400}.fa.fa-signing:before{content:"\f2a7"}.fa.fa-viadeo,.fa.fa-viadeo-square{font-family:"Font Awesome 6 Brands";font-weight:400}.fa.fa-viadeo-square:before{content:"\f2aa"}.fa.fa-snapchat,.fa.fa-snapchat-ghost{font-family:"Font Awesome 6 Brands";font-weight:400}.fa.fa-snapchat-ghost:before{content:"\f2ab"}.fa.fa-snapchat-square{font-family:"Font Awesome 6 Brands";font-weight:400}.fa.fa-snapchat-square:before{content:"\f2ad"}.fa.fa-first-order,.fa.fa-google-plus-official,.fa.fa-pied-piper,.fa.fa-themeisle,.fa.fa-yoast{font-family:"Font Awesome 6 Brands";font-weight:400}.fa.fa-google-plus-official:before{content:"\f2b3"}.fa.fa-google-plus-circle{font-family:"Font Awesome 6 Brands";font-weight:400}.fa.fa-google-plus-circle:before{content:"\f2b3"}.fa.fa-fa,.fa.fa-font-awesome{font-family:"Font Awesome 6 Brands";font-weight:400}.fa.fa-fa:before{content:"\f2b4"}.fa.fa-handshake-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-handshake-o:before{content:"\f2b5"}.fa.fa-envelope-open-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-envelope-open-o:before{content:"\f2b6"}.fa.fa-linode{font-family:"Font Awesome 6 Brands";font-weight:400}.fa.fa-address-book-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-address-book-o:before{content:"\f2b9"}.fa.fa-vcard:before{content:"\f2bb"}.fa.fa-address-card-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-address-card-o:before{content:"\f2bb"}.fa.fa-vcard-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-vcard-o:before{content:"\f2bb"}.fa.fa-user-circle-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-user-circle-o:before{content:"\f2bd"}.fa.fa-user-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-user-o:before{content:"\f007"}.fa.fa-id-badge{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-drivers-license:before{content:"\f2c2"}.fa.fa-id-card-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-id-card-o:before{content:"\f2c2"}.fa.fa-drivers-license-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-drivers-license-o:before{content:"\f2c2"}.fa.fa-free-code-camp,.fa.fa-quora,.fa.fa-telegram{font-family:"Font Awesome 6 Brands";font-weight:400}.fa.fa-thermometer-4:before,.fa.fa-thermometer:before{content:"\f2c7"}.fa.fa-thermometer-3:before{content:"\f2c8"}.fa.fa-thermometer-2:before{content:"\f2c9"}.fa.fa-thermometer-1:before{content:"\f2ca"}.fa.fa-thermometer-0:before{content:"\f2cb"}.fa.fa-bathtub:before,.fa.fa-s15:before{content:"\f2cd"}.fa.fa-window-maximize,.fa.fa-window-restore{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-times-rectangle:before{content:"\f410"}.fa.fa-window-close-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-window-close-o:before{content:"\f410"}.fa.fa-times-rectangle-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-times-rectangle-o:before{content:"\f410"}.fa.fa-bandcamp,.fa.fa-eercast,.fa.fa-etsy,.fa.fa-grav,.fa.fa-imdb,.fa.fa-ravelry{font-family:"Font Awesome 6 Brands";font-weight:400}.fa.fa-eercast:before{content:"\f2da"}.fa.fa-snowflake-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-snowflake-o:before{content:"\f2dc"}.fa.fa-meetup,.fa.fa-superpowers,.fa.fa-wpexplorer{font-family:"Font Awesome 6 Brands";font-weight:400}

static/assets/FontAwesome/css/v5-font-face.css

@@ -0,0 +1,22 @@
+/*!
+ * Font Awesome Free 6.4.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */
+@font-face {
+  font-family: 'Font Awesome 5 Brands';
+  font-display: block;
+  font-weight: 400;
+  src: url("../webfonts/fa-brands-400.woff2") format("woff2"), url("../webfonts/fa-brands-400.ttf") format("truetype"); }
+
+@font-face {
+  font-family: 'Font Awesome 5 Free';
+  font-display: block;
+  font-weight: 900;
+  src: url("../webfonts/fa-solid-900.woff2") format("woff2"), url("../webfonts/fa-solid-900.ttf") format("truetype"); }
+
+@font-face {
+  font-family: 'Font Awesome 5 Free';
+  font-display: block;
+  font-weight: 400;
+  src: url("../webfonts/fa-regular-400.woff2") format("woff2"), url("../webfonts/fa-regular-400.ttf") format("truetype"); }

static/assets/FontAwesome/css/v5-font-face.min.css

@@ -0,0 +1,6 @@
+/*!
+ * Font Awesome Free 6.4.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */
+@font-face{font-family:"Font Awesome 5 Brands";font-display:block;font-weight:400;src:url(../webfonts/fa-brands-400.woff2) format("woff2"),url(../webfonts/fa-brands-400.ttf) format("truetype")}@font-face{font-family:"Font Awesome 5 Free";font-display:block;font-weight:900;src:url(../webfonts/fa-solid-900.woff2) format("woff2"),url(../webfonts/fa-solid-900.ttf) format("truetype")}@font-face{font-family:"Font Awesome 5 Free";font-display:block;font-weight:400;src:url(../webfonts/fa-regular-400.woff2) format("woff2"),url(../webfonts/fa-regular-400.ttf) format("truetype")}

static/assets/FontAwesome/js/conflict-detection.js

@@ -0,0 +1,1138 @@
+/*!
+ * Font Awesome Free 6.4.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */
+(function (global, factory) {
+  typeof exports === 'object' && typeof module !== 'undefined' ? factory() :
+  typeof define === 'function' && define.amd ? define(factory) :
+  (factory());
+}(this, (function () { 'use strict';
+
+  function ownKeys(object, enumerableOnly) {
+    var keys = Object.keys(object);
+
+    if (Object.getOwnPropertySymbols) {
+      var symbols = Object.getOwnPropertySymbols(object);
+      enumerableOnly && (symbols = symbols.filter(function (sym) {
+        return Object.getOwnPropertyDescriptor(object, sym).enumerable;
+      })), keys.push.apply(keys, symbols);
+    }
+
+    return keys;
+  }
+
+  function _objectSpread2(target) {
+    for (var i = 1; i < arguments.length; i++) {
+      var source = null != arguments[i] ? arguments[i] : {};
+      i % 2 ? ownKeys(Object(source), !0).forEach(function (key) {
+        _defineProperty(target, key, source[key]);
+      }) : Object.getOwnPropertyDescriptors ? Object.defineProperties(target, Object.getOwnPropertyDescriptors(source)) : ownKeys(Object(source)).forEach(function (key) {
+        Object.defineProperty(target, key, Object.getOwnPropertyDescriptor(source, key));
+      });
+    }
+
+    return target;
+  }
+
+  function _typeof(obj) {
+    "@babel/helpers - typeof";
+
+    return _typeof = "function" == typeof Symbol && "symbol" == typeof Symbol.iterator ? function (obj) {
+      return typeof obj;
+    } : function (obj) {
+      return obj && "function" == typeof Symbol && obj.constructor === Symbol && obj !== Symbol.prototype ? "symbol" : typeof obj;
+    }, _typeof(obj);
+  }
+
+  function _defineProperty(obj, key, value) {
+    if (key in obj) {
+      Object.defineProperty(obj, key, {
+        value: value,
+        enumerable: true,
+        configurable: true,
+        writable: true
+      });
+    } else {
+      obj[key] = value;
+    }
+
+    return obj;
+  }
+
+  function _toConsumableArray(arr) {
+    return _arrayWithoutHoles(arr) || _iterableToArray(arr) || _unsupportedIterableToArray(arr) || _nonIterableSpread();
+  }
+
+  function _arrayWithoutHoles(arr) {
+    if (Array.isArray(arr)) return _arrayLikeToArray(arr);
+  }
+
+  function _iterableToArray(iter) {
+    if (typeof Symbol !== "undefined" && iter[Symbol.iterator] != null || iter["@@iterator"] != null) return Array.from(iter);
+  }
+
+  function _unsupportedIterableToArray(o, minLen) {
+    if (!o) return;
+    if (typeof o === "string") return _arrayLikeToArray(o, minLen);
+    var n = Object.prototype.toString.call(o).slice(8, -1);
+    if (n === "Object" && o.constructor) n = o.constructor.name;
+    if (n === "Map" || n === "Set") return Array.from(o);
+    if (n === "Arguments" || /^(?:Ui|I)nt(?:8|16|32)(?:Clamped)?Array$/.test(n)) return _arrayLikeToArray(o, minLen);
+  }
+
+  function _arrayLikeToArray(arr, len) {
+    if (len == null || len > arr.length) len = arr.length;
+
+    for (var i = 0, arr2 = new Array(len); i < len; i++) arr2[i] = arr[i];
+
+    return arr2;
+  }
+
+  function _nonIterableSpread() {
+    throw new TypeError("Invalid attempt to spread non-iterable instance.\nIn order to be iterable, non-array objects must have a [Symbol.iterator]() method.");
+  }
+
+  var _WINDOW = {};
+  var _DOCUMENT = {};
+
+  try {
+    if (typeof window !== 'undefined') _WINDOW = window;
+    if (typeof document !== 'undefined') _DOCUMENT = document;
+  } catch (e) {}
+
+  var _ref = _WINDOW.navigator || {},
+      _ref$userAgent = _ref.userAgent,
+      userAgent = _ref$userAgent === void 0 ? '' : _ref$userAgent;
+  var WINDOW = _WINDOW;
+  var DOCUMENT = _DOCUMENT;
+  var IS_BROWSER = !!WINDOW.document;
+  var IS_DOM = !!DOCUMENT.documentElement && !!DOCUMENT.head && typeof DOCUMENT.addEventListener === 'function' && typeof DOCUMENT.createElement === 'function';
+  var IS_IE = ~userAgent.indexOf('MSIE') || ~userAgent.indexOf('Trident/');
+
+  var functions = [];
+
+  var listener = function listener() {
+    DOCUMENT.removeEventListener('DOMContentLoaded', listener);
+    loaded = 1;
+    functions.map(function (fn) {
+      return fn();
+    });
+  };
+
+  var loaded = false;
+
+  if (IS_DOM) {
+    loaded = (DOCUMENT.documentElement.doScroll ? /^loaded|^c/ : /^loaded|^i|^c/).test(DOCUMENT.readyState);
+    if (!loaded) DOCUMENT.addEventListener('DOMContentLoaded', listener);
+  }
+
+  function domready (fn) {
+    if (!IS_DOM) return;
+    loaded ? setTimeout(fn, 0) : functions.push(fn);
+  }
+
+  function report (_ref) {
+    var nodesTested = _ref.nodesTested,
+        nodesFound = _ref.nodesFound;
+    var timedOutTests = {};
+
+    for (var key in nodesFound) {
+      if (!(nodesTested.conflict[key] || nodesTested.noConflict[key])) {
+        timedOutTests[key] = nodesFound[key];
+      }
+    }
+
+    var conflictsCount = Object.keys(nodesTested.conflict).length;
+
+    if (conflictsCount > 0) {
+      console.info("%cConflict".concat(conflictsCount > 1 ? 's' : '', " found:"), 'color: darkred; font-size: large');
+      var data = {};
+
+      for (var _key in nodesTested.conflict) {
+        var item = nodesTested.conflict[_key];
+        data[_key] = {
+          'tagName': item.tagName,
+          'src/href': item.src || item.href || 'n/a',
+          'innerText excerpt': item.innerText && item.innerText !== '' ? item.innerText.slice(0, 200) + '...' : '(empty)'
+        };
+      }
+
+      console.table(data);
+    }
+
+    var noConflictsCount = Object.keys(nodesTested.noConflict).length;
+
+    if (noConflictsCount > 0) {
+      console.info("%cNo conflict".concat(noConflictsCount > 1 ? 's' : '', " found with ").concat(noConflictsCount === 1 ? 'this' : 'these', ":"), 'color: green; font-size: large');
+      var _data = {};
+
+      for (var _key2 in nodesTested.noConflict) {
+        var _item = nodesTested.noConflict[_key2];
+        _data[_key2] = {
+          'tagName': _item.tagName,
+          'src/href': _item.src || _item.href || 'n/a',
+          'innerText excerpt': _item.innerText && _item.innerText !== '' ? _item.innerText.slice(0, 200) + '...' : '(empty)'
+        };
+      }
+
+      console.table(_data);
+    }
+
+    var timeOutCount = Object.keys(timedOutTests).length;
+
+    if (timeOutCount > 0) {
+      console.info("%cLeftovers--we timed out before collecting test results for ".concat(timeOutCount === 1 ? 'this' : 'these', ":"), 'color: blue; font-size: large');
+      var _data2 = {};
+
+      for (var _key3 in timedOutTests) {
+        var _item2 = timedOutTests[_key3];
+        _data2[_key3] = {
+          'tagName': _item2.tagName,
+          'src/href': _item2.src || _item2.href || 'n/a',
+          'innerText excerpt': _item2.innerText && _item2.innerText !== '' ? _item2.innerText.slice(0, 200) + '...' : '(empty)'
+        };
+      }
+
+      console.table(_data2);
+    }
+  }
+
+  var commonjsGlobal = typeof window !== 'undefined' ? window : typeof global !== 'undefined' ? global : typeof self !== 'undefined' ? self : {};
+
+  function createCommonjsModule(fn, module) {
+  	return module = { exports: {} }, fn(module, module.exports), module.exports;
+  }
+
+  var md5 = createCommonjsModule(function (module) {
+
+    (function ($) {
+      /**
+       * Add integers, wrapping at 2^32.
+       * This uses 16-bit operations internally to work around bugs in interpreters.
+       *
+       * @param {number} x First integer
+       * @param {number} y Second integer
+       * @returns {number} Sum
+       */
+
+      function safeAdd(x, y) {
+        var lsw = (x & 0xffff) + (y & 0xffff);
+        var msw = (x >> 16) + (y >> 16) + (lsw >> 16);
+        return msw << 16 | lsw & 0xffff;
+      }
+      /**
+       * Bitwise rotate a 32-bit number to the left.
+       *
+       * @param {number} num 32-bit number
+       * @param {number} cnt Rotation count
+       * @returns {number} Rotated number
+       */
+
+
+      function bitRotateLeft(num, cnt) {
+        return num << cnt | num >>> 32 - cnt;
+      }
+      /**
+       * Basic operation the algorithm uses.
+       *
+       * @param {number} q q
+       * @param {number} a a
+       * @param {number} b b
+       * @param {number} x x
+       * @param {number} s s
+       * @param {number} t t
+       * @returns {number} Result
+       */
+
+
+      function md5cmn(q, a, b, x, s, t) {
+        return safeAdd(bitRotateLeft(safeAdd(safeAdd(a, q), safeAdd(x, t)), s), b);
+      }
+      /**
+       * Basic operation the algorithm uses.
+       *
+       * @param {number} a a
+       * @param {number} b b
+       * @param {number} c c
+       * @param {number} d d
+       * @param {number} x x
+       * @param {number} s s
+       * @param {number} t t
+       * @returns {number} Result
+       */
+
+
+      function md5ff(a, b, c, d, x, s, t) {
+        return md5cmn(b & c | ~b & d, a, b, x, s, t);
+      }
+      /**
+       * Basic operation the algorithm uses.
+       *
+       * @param {number} a a
+       * @param {number} b b
+       * @param {number} c c
+       * @param {number} d d
+       * @param {number} x x
+       * @param {number} s s
+       * @param {number} t t
+       * @returns {number} Result
+       */
+
+
+      function md5gg(a, b, c, d, x, s, t) {
+        return md5cmn(b & d | c & ~d, a, b, x, s, t);
+      }
+      /**
+       * Basic operation the algorithm uses.
+       *
+       * @param {number} a a
+       * @param {number} b b
+       * @param {number} c c
+       * @param {number} d d
+       * @param {number} x x
+       * @param {number} s s
+       * @param {number} t t
+       * @returns {number} Result
+       */
+
+
+      function md5hh(a, b, c, d, x, s, t) {
+        return md5cmn(b ^ c ^ d, a, b, x, s, t);
+      }
+      /**
+       * Basic operation the algorithm uses.
+       *
+       * @param {number} a a
+       * @param {number} b b
+       * @param {number} c c
+       * @param {number} d d
+       * @param {number} x x
+       * @param {number} s s
+       * @param {number} t t
+       * @returns {number} Result
+       */
+
+
+      function md5ii(a, b, c, d, x, s, t) {
+        return md5cmn(c ^ (b | ~d), a, b, x, s, t);
+      }
+      /**
+       * Calculate the MD5 of an array of little-endian words, and a bit length.
+       *
+       * @param {Array} x Array of little-endian words
+       * @param {number} len Bit length
+       * @returns {Array<number>} MD5 Array
+       */
+
+
+      function binlMD5(x, len) {
+        /* append padding */
+        x[len >> 5] |= 0x80 << len % 32;
+        x[(len + 64 >>> 9 << 4) + 14] = len;
+        var i;
+        var olda;
+        var oldb;
+        var oldc;
+        var oldd;
+        var a = 1732584193;
+        var b = -271733879;
+        var c = -1732584194;
+        var d = 271733878;
+
+        for (i = 0; i < x.length; i += 16) {
+          olda = a;
+          oldb = b;
+          oldc = c;
+          oldd = d;
+          a = md5ff(a, b, c, d, x[i], 7, -680876936);
+          d = md5ff(d, a, b, c, x[i + 1], 12, -389564586);
+          c = md5ff(c, d, a, b, x[i + 2], 17, 606105819);
+          b = md5ff(b, c, d, a, x[i + 3], 22, -1044525330);
+          a = md5ff(a, b, c, d, x[i + 4], 7, -176418897);
+          d = md5ff(d, a, b, c, x[i + 5], 12, 1200080426);
+          c = md5ff(c, d, a, b, x[i + 6], 17, -1473231341);
+          b = md5ff(b, c, d, a, x[i + 7], 22, -45705983);
+          a = md5ff(a, b, c, d, x[i + 8], 7, 1770035416);
+          d = md5ff(d, a, b, c, x[i + 9], 12, -1958414417);
+          c = md5ff(c, d, a, b, x[i + 10], 17, -42063);
+          b = md5ff(b, c, d, a, x[i + 11], 22, -1990404162);
+          a = md5ff(a, b, c, d, x[i + 12], 7, 1804603682);
+          d = md5ff(d, a, b, c, x[i + 13], 12, -40341101);
+          c = md5ff(c, d, a, b, x[i + 14], 17, -1502002290);
+          b = md5ff(b, c, d, a, x[i + 15], 22, 1236535329);
+          a = md5gg(a, b, c, d, x[i + 1], 5, -165796510);
+          d = md5gg(d, a, b, c, x[i + 6], 9, -1069501632);
+          c = md5gg(c, d, a, b, x[i + 11], 14, 643717713);
+          b = md5gg(b, c, d, a, x[i], 20, -373897302);
+          a = md5gg(a, b, c, d, x[i + 5], 5, -701558691);
+          d = md5gg(d, a, b, c, x[i + 10], 9, 38016083);
+          c = md5gg(c, d, a, b, x[i + 15], 14, -660478335);
+          b = md5gg(b, c, d, a, x[i + 4], 20, -405537848);
+          a = md5gg(a, b, c, d, x[i + 9], 5, 568446438);
+          d = md5gg(d, a, b, c, x[i + 14], 9, -1019803690);
+          c = md5gg(c, d, a, b, x[i + 3], 14, -187363961);
+          b = md5gg(b, c, d, a, x[i + 8], 20, 1163531501);
+          a = md5gg(a, b, c, d, x[i + 13], 5, -1444681467);
+          d = md5gg(d, a, b, c, x[i + 2], 9, -51403784);
+          c = md5gg(c, d, a, b, x[i + 7], 14, 1735328473);
+          b = md5gg(b, c, d, a, x[i + 12], 20, -1926607734);
+          a = md5hh(a, b, c, d, x[i + 5], 4, -378558);
+          d = md5hh(d, a, b, c, x[i + 8], 11, -2022574463);
+          c = md5hh(c, d, a, b, x[i + 11], 16, 1839030562);
+          b = md5hh(b, c, d, a, x[i + 14], 23, -35309556);
+          a = md5hh(a, b, c, d, x[i + 1], 4, -1530992060);
+          d = md5hh(d, a, b, c, x[i + 4], 11, 1272893353);
+          c = md5hh(c, d, a, b, x[i + 7], 16, -155497632);
+          b = md5hh(b, c, d, a, x[i + 10], 23, -1094730640);
+          a = md5hh(a, b, c, d, x[i + 13], 4, 681279174);
+          d = md5hh(d, a, b, c, x[i], 11, -358537222);
+          c = md5hh(c, d, a, b, x[i + 3], 16, -722521979);
+          b = md5hh(b, c, d, a, x[i + 6], 23, 76029189);
+          a = md5hh(a, b, c, d, x[i + 9], 4, -640364487);
+          d = md5hh(d, a, b, c, x[i + 12], 11, -421815835);
+          c = md5hh(c, d, a, b, x[i + 15], 16, 530742520);
+          b = md5hh(b, c, d, a, x[i + 2], 23, -995338651);
+          a = md5ii(a, b, c, d, x[i], 6, -198630844);
+          d = md5ii(d, a, b, c, x[i + 7], 10, 1126891415);
+          c = md5ii(c, d, a, b, x[i + 14], 15, -1416354905);
+          b = md5ii(b, c, d, a, x[i + 5], 21, -57434055);
+          a = md5ii(a, b, c, d, x[i + 12], 6, 1700485571);
+          d = md5ii(d, a, b, c, x[i + 3], 10, -1894986606);
+          c = md5ii(c, d, a, b, x[i + 10], 15, -1051523);
+          b = md5ii(b, c, d, a, x[i + 1], 21, -2054922799);
+          a = md5ii(a, b, c, d, x[i + 8], 6, 1873313359);
+          d = md5ii(d, a, b, c, x[i + 15], 10, -30611744);
+          c = md5ii(c, d, a, b, x[i + 6], 15, -1560198380);
+          b = md5ii(b, c, d, a, x[i + 13], 21, 1309151649);
+          a = md5ii(a, b, c, d, x[i + 4], 6, -145523070);
+          d = md5ii(d, a, b, c, x[i + 11], 10, -1120210379);
+          c = md5ii(c, d, a, b, x[i + 2], 15, 718787259);
+          b = md5ii(b, c, d, a, x[i + 9], 21, -343485551);
+          a = safeAdd(a, olda);
+          b = safeAdd(b, oldb);
+          c = safeAdd(c, oldc);
+          d = safeAdd(d, oldd);
+        }
+
+        return [a, b, c, d];
+      }
+      /**
+       * Convert an array of little-endian words to a string
+       *
+       * @param {Array<number>} input MD5 Array
+       * @returns {string} MD5 string
+       */
+
+
+      function binl2rstr(input) {
+        var i;
+        var output = '';
+        var length32 = input.length * 32;
+
+        for (i = 0; i < length32; i += 8) {
+          output += String.fromCharCode(input[i >> 5] >>> i % 32 & 0xff);
+        }
+
+        return output;
+      }
+      /**
+       * Convert a raw string to an array of little-endian words
+       * Characters >255 have their high-byte silently ignored.
+       *
+       * @param {string} input Raw input string
+       * @returns {Array<number>} Array of little-endian words
+       */
+
+
+      function rstr2binl(input) {
+        var i;
+        var output = [];
+        output[(input.length >> 2) - 1] = undefined;
+
+        for (i = 0; i < output.length; i += 1) {
+          output[i] = 0;
+        }
+
+        var length8 = input.length * 8;
+
+        for (i = 0; i < length8; i += 8) {
+          output[i >> 5] |= (input.charCodeAt(i / 8) & 0xff) << i % 32;
+        }
+
+        return output;
+      }
+      /**
+       * Calculate the MD5 of a raw string
+       *
+       * @param {string} s Input string
+       * @returns {string} Raw MD5 string
+       */
+
+
+      function rstrMD5(s) {
+        return binl2rstr(binlMD5(rstr2binl(s), s.length * 8));
+      }
+      /**
+       * Calculates the HMAC-MD5 of a key and some data (raw strings)
+       *
+       * @param {string} key HMAC key
+       * @param {string} data Raw input string
+       * @returns {string} Raw MD5 string
+       */
+
+
+      function rstrHMACMD5(key, data) {
+        var i;
+        var bkey = rstr2binl(key);
+        var ipad = [];
+        var opad = [];
+        var hash;
+        ipad[15] = opad[15] = undefined;
+
+        if (bkey.length > 16) {
+          bkey = binlMD5(bkey, key.length * 8);
+        }
+
+        for (i = 0; i < 16; i += 1) {
+          ipad[i] = bkey[i] ^ 0x36363636;
+          opad[i] = bkey[i] ^ 0x5c5c5c5c;
+        }
+
+        hash = binlMD5(ipad.concat(rstr2binl(data)), 512 + data.length * 8);
+        return binl2rstr(binlMD5(opad.concat(hash), 512 + 128));
+      }
+      /**
+       * Convert a raw string to a hex string
+       *
+       * @param {string} input Raw input string
+       * @returns {string} Hex encoded string
+       */
+
+
+      function rstr2hex(input) {
+        var hexTab = '0123456789abcdef';
+        var output = '';
+        var x;
+        var i;
+
+        for (i = 0; i < input.length; i += 1) {
+          x = input.charCodeAt(i);
+          output += hexTab.charAt(x >>> 4 & 0x0f) + hexTab.charAt(x & 0x0f);
+        }
+
+        return output;
+      }
+      /**
+       * Encode a string as UTF-8
+       *
+       * @param {string} input Input string
+       * @returns {string} UTF8 string
+       */
+
+
+      function str2rstrUTF8(input) {
+        return unescape(encodeURIComponent(input));
+      }
+      /**
+       * Encodes input string as raw MD5 string
+       *
+       * @param {string} s Input string
+       * @returns {string} Raw MD5 string
+       */
+
+
+      function rawMD5(s) {
+        return rstrMD5(str2rstrUTF8(s));
+      }
+      /**
+       * Encodes input string as Hex encoded string
+       *
+       * @param {string} s Input string
+       * @returns {string} Hex encoded string
+       */
+
+
+      function hexMD5(s) {
+        return rstr2hex(rawMD5(s));
+      }
+      /**
+       * Calculates the raw HMAC-MD5 for the given key and data
+       *
+       * @param {string} k HMAC key
+       * @param {string} d Input string
+       * @returns {string} Raw MD5 string
+       */
+
+
+      function rawHMACMD5(k, d) {
+        return rstrHMACMD5(str2rstrUTF8(k), str2rstrUTF8(d));
+      }
+      /**
+       * Calculates the Hex encoded HMAC-MD5 for the given key and data
+       *
+       * @param {string} k HMAC key
+       * @param {string} d Input string
+       * @returns {string} Raw MD5 string
+       */
+
+
+      function hexHMACMD5(k, d) {
+        return rstr2hex(rawHMACMD5(k, d));
+      }
+      /**
+       * Calculates MD5 value for a given string.
+       * If a key is provided, calculates the HMAC-MD5 value.
+       * Returns a Hex encoded string unless the raw argument is given.
+       *
+       * @param {string} string Input string
+       * @param {string} [key] HMAC key
+       * @param {boolean} [raw] Raw output switch
+       * @returns {string} MD5 output
+       */
+
+
+      function md5(string, key, raw) {
+        if (!key) {
+          if (!raw) {
+            return hexMD5(string);
+          }
+
+          return rawMD5(string);
+        }
+
+        if (!raw) {
+          return hexHMACMD5(key, string);
+        }
+
+        return rawHMACMD5(key, string);
+      }
+
+      if (module.exports) {
+        module.exports = md5;
+      } else {
+        $.md5 = md5;
+      }
+    })(commonjsGlobal);
+  });
+
+  function md5ForNode(node) {
+    if (null === node || 'object' !== _typeof(node)) return undefined;
+
+    if (node.src) {
+      return md5(node.src);
+    } else if (node.href) {
+      return md5(node.href);
+    } else if (node.innerText && '' !== node.innerText) {
+      // eslint-disable-line yoda
+      return md5(node.innerText);
+    } else {
+      return undefined;
+    }
+  }
+
+  var diagScriptId = 'fa-kits-diag';
+  var nodeUnderTestId = 'fa-kits-node-under-test';
+  var md5Attr = 'data-md5';
+  var detectionIgnoreAttr = 'data-fa-detection-ignore';
+  var timeoutAttr = 'data-fa-detection-timeout';
+  var resultsCollectionMaxWaitAttr = 'data-fa-detection-results-collection-max-wait';
+
+  var silenceErrors = function silenceErrors(e) {
+    e.preventDefault();
+    e.stopPropagation();
+  };
+
+  function pollUntil(_ref) {
+    var _ref$fn = _ref.fn,
+        fn = _ref$fn === void 0 ? function () {
+      return true;
+    } : _ref$fn,
+        _ref$initialDuration = _ref.initialDuration,
+        initialDuration = _ref$initialDuration === void 0 ? 1 : _ref$initialDuration,
+        _ref$maxDuration = _ref.maxDuration,
+        maxDuration = _ref$maxDuration === void 0 ? WINDOW.FontAwesomeDetection.timeout : _ref$maxDuration,
+        _ref$showProgress = _ref.showProgress,
+        showProgress = _ref$showProgress === void 0 ? false : _ref$showProgress,
+        progressIndicator = _ref.progressIndicator;
+    return new Promise(function (resolve, reject) {
+      // eslint-disable-line compat/compat
+      function poll(duration, cumulativeDuration) {
+        setTimeout(function () {
+          var result = fn();
+
+          if (showProgress) {
+            console.info(progressIndicator);
+          }
+
+          if (!!result) {
+            // eslint-disable-line no-extra-boolean-cast
+            resolve(result);
+          } else {
+            var nextDuration = 250;
+            var nextCumulativeDuration = nextDuration + cumulativeDuration;
+
+            if (nextCumulativeDuration <= maxDuration) {
+              poll(nextDuration, nextCumulativeDuration);
+            } else {
+              reject('timeout'); // eslint-disable-line prefer-promise-reject-errors
+            }
+          }
+        }, duration);
+      }
+
+      poll(initialDuration, 0);
+    });
+  }
+
+  function detectWebfontConflicts() {
+    var linkTags = Array.from(DOCUMENT.getElementsByTagName('link')).filter(function (t) {
+      return !t.hasAttribute(detectionIgnoreAttr);
+    });
+    var styleTags = Array.from(DOCUMENT.getElementsByTagName('style')).filter(function (t) {
+      if (t.hasAttribute(detectionIgnoreAttr)) {
+        return false;
+      } // If the browser has loaded the FA5 CSS, let's not test that <style> element.
+      // Its enough that we'll be testing for traces of the corresponding JS being loaded, and testing
+      // this <style> would only produce a false negative anyway.
+
+
+      if (WINDOW.FontAwesomeConfig && t.innerText.match(new RegExp("svg:not\\(:root\\)\\.".concat(WINDOW.FontAwesomeConfig.replacementClass)))) {
+        return false;
+      }
+
+      return true;
+    });
+
+    function runDiag(scriptOrLinkTag, md5) {
+      var diagFrame = DOCUMENT.createElement('iframe'); // Using "visibility: hidden; position: absolute" instead of "display: none;" because
+      // Firefox will not return the expected results for getComputedStyle if our iframe has display: none.
+
+      diagFrame.setAttribute('style', 'visibility: hidden; position: absolute; height: 0; width: 0;');
+      var testIconId = 'fa-test-icon-' + md5;
+      var iTag = DOCUMENT.createElement('i');
+      iTag.setAttribute('class', 'fa fa-coffee');
+      iTag.setAttribute('id', testIconId);
+      var diagScript = DOCUMENT.createElement('script');
+      diagScript.setAttribute('id', diagScriptId); // WARNING: this function will be toString()'d and assigned to innerText of the diag script
+      // element that we'll be putting into a diagnostic iframe.
+      // That means that this code won't compile until after the outer script has run and injected
+      // this code into the iframe. There are some compile time errors that might occur there.
+      // For example, using single line (double-slash) comments like this one inside that function
+      // will probably cause it to choke. Chrome will show an error like this:
+      // Uncaught SyntaxError: Unexpected end of input
+
+      var diagScriptFun = function diagScriptFun(nodeUnderTestId, testIconId, md5, parentOrigin) {
+        parent.FontAwesomeDetection.__pollUntil({
+          fn: function fn() {
+            var iEl = document.getElementById(testIconId);
+            var computedStyle = window.getComputedStyle(iEl);
+            var fontFamily = computedStyle.getPropertyValue('font-family');
+
+            if (!!fontFamily.match(/FontAwesome/) || !!fontFamily.match(/Font Awesome [56]/)) {
+              return true;
+            } else {
+              return false;
+            }
+          }
+        }).then(function () {
+          var node = document.getElementById(nodeUnderTestId);
+          parent.postMessage({
+            type: 'fontawesome-conflict',
+            technology: 'webfont',
+            href: node.href,
+            innerText: node.innerText,
+            tagName: node.tagName,
+            md5: md5
+          }, parentOrigin);
+        }).catch(function (e) {
+          var node = document.getElementById(nodeUnderTestId);
+
+          if (e === 'timeout') {
+            parent.postMessage({
+              type: 'no-conflict',
+              technology: 'webfont',
+              href: node.src,
+              innerText: node.innerText,
+              tagName: node.tagName,
+              md5: md5
+            }, parentOrigin);
+          } else {
+            console.error(e);
+          }
+        });
+      };
+
+      var parentOrigin = WINDOW.location.origin === 'file://' ? '*' : WINDOW.location.origin;
+      diagScript.innerText = "(".concat(diagScriptFun.toString(), ")('").concat(nodeUnderTestId, "', '").concat(testIconId || 'foo', "', '").concat(md5, "', '").concat(parentOrigin, "');");
+
+      diagFrame.onload = function () {
+        diagFrame.contentWindow.addEventListener('error', silenceErrors, true);
+        diagFrame.contentDocument.head.appendChild(diagScript);
+        diagFrame.contentDocument.head.appendChild(scriptOrLinkTag);
+        diagFrame.contentDocument.body.appendChild(iTag);
+      };
+
+      domready(function () {
+        return DOCUMENT.body.appendChild(diagFrame);
+      });
+    }
+
+    var cssByMD5 = {};
+
+    for (var i = 0; i < linkTags.length; i++) {
+      var linkUnderTest = DOCUMENT.createElement('link');
+      linkUnderTest.setAttribute('id', nodeUnderTestId);
+      linkUnderTest.setAttribute('href', linkTags[i].href);
+      linkUnderTest.setAttribute('rel', linkTags[i].rel);
+      var md5ForLink = md5ForNode(linkTags[i]);
+      linkUnderTest.setAttribute(md5Attr, md5ForLink);
+      cssByMD5[md5ForLink] = linkTags[i];
+      runDiag(linkUnderTest, md5ForLink);
+    }
+
+    for (var _i = 0; _i < styleTags.length; _i++) {
+      var styleUnderTest = DOCUMENT.createElement('style');
+      styleUnderTest.setAttribute('id', nodeUnderTestId);
+      var md5ForStyle = md5ForNode(styleTags[_i]);
+      styleUnderTest.setAttribute(md5Attr, md5ForStyle);
+      styleUnderTest.innerText = styleTags[_i].innerText;
+      cssByMD5[md5ForStyle] = styleTags[_i];
+      runDiag(styleUnderTest, md5ForStyle);
+    }
+
+    return cssByMD5;
+  }
+
+  function detectSvgConflicts(currentScript) {
+    var scripts = Array.from(DOCUMENT.scripts).filter(function (t) {
+      return !t.hasAttribute(detectionIgnoreAttr) && t !== currentScript;
+    });
+    var scriptsByMD5 = {};
+
+    var _loop = function _loop(scriptIdx) {
+      var diagFrame = DOCUMENT.createElement('iframe');
+      diagFrame.setAttribute('style', 'display:none;');
+      var scriptUnderTest = DOCUMENT.createElement('script');
+      scriptUnderTest.setAttribute('id', nodeUnderTestId);
+      var md5ForScript = md5ForNode(scripts[scriptIdx]);
+      scriptUnderTest.setAttribute(md5Attr, md5ForScript);
+      scriptsByMD5[md5ForScript] = scripts[scriptIdx];
+
+      if (scripts[scriptIdx].src !== '') {
+        scriptUnderTest.src = scripts[scriptIdx].src;
+      }
+
+      if (scripts[scriptIdx].innerText !== '') {
+        scriptUnderTest.innerText = scripts[scriptIdx].innerText;
+      }
+
+      scriptUnderTest.async = true;
+      var diagScript = DOCUMENT.createElement('script');
+      diagScript.setAttribute('id', diagScriptId);
+      var parentOrigin = WINDOW.location.origin === 'file://' ? '*' : WINDOW.location.origin;
+
+      var diagScriptFun = function diagScriptFun(nodeUnderTestId, md5, parentOrigin) {
+        parent.FontAwesomeDetection.__pollUntil({
+          fn: function fn() {
+            return !!window.FontAwesomeConfig || !!window.FontAwesomeKitConfig;
+          }
+        }).then(function () {
+          var scriptNode = document.getElementById(nodeUnderTestId);
+          parent.postMessage({
+            type: 'fontawesome-conflict',
+            technology: 'js',
+            src: scriptNode.src,
+            innerText: scriptNode.innerText,
+            tagName: scriptNode.tagName,
+            md5: md5
+          }, parentOrigin);
+        }).catch(function (e) {
+          var scriptNode = document.getElementById(nodeUnderTestId);
+
+          if (e === 'timeout') {
+            parent.postMessage({
+              type: 'no-conflict',
+              src: scriptNode.src,
+              innerText: scriptNode.innerText,
+              tagName: scriptNode.tagName,
+              md5: md5
+            }, parentOrigin);
+          } else {
+            console.error(e);
+          }
+        });
+      };
+
+      diagScript.innerText = "(".concat(diagScriptFun.toString(), ")('").concat(nodeUnderTestId, "', '").concat(md5ForScript, "', '").concat(parentOrigin, "');");
+
+      diagFrame.onload = function () {
+        diagFrame.contentWindow.addEventListener('error', silenceErrors, true);
+        diagFrame.contentDocument.head.appendChild(diagScript);
+        diagFrame.contentDocument.head.appendChild(scriptUnderTest);
+      };
+
+      domready(function () {
+        return DOCUMENT.body.appendChild(diagFrame);
+      });
+    };
+
+    for (var scriptIdx = 0; scriptIdx < scripts.length; scriptIdx++) {
+      _loop(scriptIdx);
+    }
+
+    return scriptsByMD5;
+  }
+
+  function setDoneResults(_ref2) {
+    var nodesTested = _ref2.nodesTested,
+        nodesFound = _ref2.nodesFound;
+    WINDOW.FontAwesomeDetection = WINDOW.FontAwesomeDetection || {};
+    WINDOW.FontAwesomeDetection.nodesTested = nodesTested;
+    WINDOW.FontAwesomeDetection.nodesFound = nodesFound;
+    WINDOW.FontAwesomeDetection.detectionDone = true;
+  }
+
+  function conflictDetection() {
+    var report$$1 = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : function () {};
+    var nodesTested = {
+      conflict: {},
+      noConflict: {}
+    };
+
+    WINDOW.onmessage = function (e) {
+      if (WINDOW.location.origin === 'file://' || e.origin === WINDOW.location.origin) {
+        if (e && e.data) {
+          if (e.data.type === 'fontawesome-conflict') {
+            nodesTested.conflict[e.data.md5] = e.data;
+          } else if (e.data.type === 'no-conflict') {
+            nodesTested.noConflict[e.data.md5] = e.data;
+          }
+        }
+      }
+    };
+
+    var scriptsToTest = detectSvgConflicts(DOCUMENT.currentScript);
+    var cssToTest = detectWebfontConflicts();
+
+    var nodesFound = _objectSpread2(_objectSpread2({}, scriptsToTest), cssToTest);
+
+    var testCount = Object.keys(scriptsToTest).length + Object.keys(cssToTest).length; // The resultsCollectionMaxWait allows for the time between when the tests running under
+    // child iframes call postMessage with their results, and when the parent window
+    // receives and handles those events with window.onmessage.
+    // Making it configurable allows us to test the scenario where this timeout is exceeded.
+    // Naming it something very different from "timeout" is to help avoid the potential ambiguity between
+    // these two timeout-related settings.
+
+    var masterTimeout = WINDOW.FontAwesomeDetection.timeout + WINDOW.FontAwesomeDetection.resultsCollectionMaxWait;
+    console.group('Font Awesome Detector');
+
+    if (testCount === 0) {
+      console.info('%cAll Good!', 'color: green; font-size: large');
+      console.info('We didn\'t find anything that needs testing for conflicts. Ergo, no conflicts.');
+    } else {
+      console.info("Testing ".concat(testCount, " possible conflicts."));
+      console.info("We'll wait about ".concat(Math.round(WINDOW.FontAwesomeDetection.timeout / 10) / 100, " seconds while testing these and\n") + "then up to another ".concat(Math.round(WINDOW.FontAwesomeDetection.resultsCollectionMaxWait / 10) / 100, " to allow the browser time\n") + "to accumulate the results. But we'll probably be outta here way before then.\n\n");
+      console.info("You can adjust those durations by assigning values to these attributes on the <script> element that loads this detection:");
+      console.info("\t%c".concat(timeoutAttr, "%c: milliseconds to wait for each test before deciding whether it's a conflict."), 'font-weight: bold;', 'font-size: normal;');
+      console.info("\t%c".concat(resultsCollectionMaxWaitAttr, "%c: milliseconds to wait for the browser to accumulate test results before giving up."), 'font-weight: bold;', 'font-size: normal;');
+      pollUntil({
+        // Give this overall timer a little extra cushion
+        maxDuration: masterTimeout,
+        showProgress: true,
+        progressIndicator: 'waiting...',
+        fn: function fn() {
+          return Object.keys(nodesTested.conflict).length + Object.keys(nodesTested.noConflict).length >= testCount;
+        }
+      }).then(function () {
+        console.info('DONE!');
+        setDoneResults({
+          nodesTested: nodesTested,
+          nodesFound: nodesFound
+        });
+        report$$1({
+          nodesTested: nodesTested,
+          nodesFound: nodesFound
+        });
+        console.groupEnd();
+      }).catch(function (e) {
+        if (e === 'timeout') {
+          console.info('TIME OUT! We waited until we got tired. Here\'s what we found:');
+          setDoneResults({
+            nodesTested: nodesTested,
+            nodesFound: nodesFound
+          });
+          report$$1({
+            nodesTested: nodesTested,
+            nodesFound: nodesFound
+          });
+        } else {
+          console.info('Whoops! We hit an error:', e);
+          console.info('Here\'s what we\'d found up until that error:');
+          setDoneResults({
+            nodesTested: nodesTested,
+            nodesFound: nodesFound
+          });
+          report$$1({
+            nodesTested: nodesTested,
+            nodesFound: nodesFound
+          });
+        }
+
+        console.groupEnd();
+      });
+    }
+  } // Allow clients to access, and in some cases, override some properties
+
+  var initialConfig = WINDOW.FontAwesomeDetection || {}; // These can be overridden
+
+  var _default = {
+    report: report,
+    timeout: +(DOCUMENT.currentScript.getAttribute(timeoutAttr) || "2000"),
+    resultsCollectionMaxWait: +(DOCUMENT.currentScript.getAttribute(resultsCollectionMaxWaitAttr) || "5000")
+  };
+
+  var _config = _objectSpread2(_objectSpread2(_objectSpread2({}, _default), initialConfig), {}, {
+    // These cannot be overridden
+    __pollUntil: pollUntil,
+    md5ForNode: md5ForNode,
+    detectionDone: false,
+    nodesTested: null,
+    nodesFound: null
+  });
+
+  WINDOW.FontAwesomeDetection = _config;
+
+  var _familyProxy, _familyProxy2, _familyProxy3, _familyProxy4, _familyProxy5;
+  var PRODUCTION = function () {
+    try {
+      return process.env.NODE_ENV === 'production';
+    } catch (e) {
+      return false;
+    }
+  }();
+  var FAMILY_CLASSIC = 'classic';
+  var FAMILY_SHARP = 'sharp';
+  var FAMILIES = [FAMILY_CLASSIC, FAMILY_SHARP];
+
+  function familyProxy(obj) {
+    // Defaults to the classic family if family is not available
+    return new Proxy(obj, {
+      get: function get(target, prop) {
+        return prop in target ? target[prop] : target[FAMILY_CLASSIC];
+      }
+    });
+  }
+  var PREFIX_TO_STYLE = familyProxy((_familyProxy = {}, _defineProperty(_familyProxy, FAMILY_CLASSIC, {
+    'fa': 'solid',
+    'fas': 'solid',
+    'fa-solid': 'solid',
+    'far': 'regular',
+    'fa-regular': 'regular',
+    'fal': 'light',
+    'fa-light': 'light',
+    'fat': 'thin',
+    'fa-thin': 'thin',
+    'fad': 'duotone',
+    'fa-duotone': 'duotone',
+    'fab': 'brands',
+    'fa-brands': 'brands',
+    'fak': 'kit',
+    'fa-kit': 'kit'
+  }), _defineProperty(_familyProxy, FAMILY_SHARP, {
+    'fa': 'solid',
+    'fass': 'solid',
+    'fa-solid': 'solid',
+    'fasr': 'regular',
+    'fa-regular': 'regular',
+    'fasl': 'light',
+    'fa-light': 'light'
+  }), _familyProxy));
+  var STYLE_TO_PREFIX = familyProxy((_familyProxy2 = {}, _defineProperty(_familyProxy2, FAMILY_CLASSIC, {
+    'solid': 'fas',
+    'regular': 'far',
+    'light': 'fal',
+    'thin': 'fat',
+    'duotone': 'fad',
+    'brands': 'fab',
+    'kit': 'fak'
+  }), _defineProperty(_familyProxy2, FAMILY_SHARP, {
+    'solid': 'fass',
+    'regular': 'fasr',
+    'light': 'fasl'
+  }), _familyProxy2));
+  var PREFIX_TO_LONG_STYLE = familyProxy((_familyProxy3 = {}, _defineProperty(_familyProxy3, FAMILY_CLASSIC, {
+    'fab': 'fa-brands',
+    'fad': 'fa-duotone',
+    'fak': 'fa-kit',
+    'fal': 'fa-light',
+    'far': 'fa-regular',
+    'fas': 'fa-solid',
+    'fat': 'fa-thin'
+  }), _defineProperty(_familyProxy3, FAMILY_SHARP, {
+    'fass': 'fa-solid',
+    'fasr': 'fa-regular',
+    'fasl': 'fa-light'
+  }), _familyProxy3));
+  var LONG_STYLE_TO_PREFIX = familyProxy((_familyProxy4 = {}, _defineProperty(_familyProxy4, FAMILY_CLASSIC, {
+    'fa-brands': 'fab',
+    'fa-duotone': 'fad',
+    'fa-kit': 'fak',
+    'fa-light': 'fal',
+    'fa-regular': 'far',
+    'fa-solid': 'fas',
+    'fa-thin': 'fat'
+  }), _defineProperty(_familyProxy4, FAMILY_SHARP, {
+    'fa-solid': 'fass',
+    'fa-regular': 'fasr',
+    'fa-light': 'fasl'
+  }), _familyProxy4));
+  var FONT_WEIGHT_TO_PREFIX = familyProxy((_familyProxy5 = {}, _defineProperty(_familyProxy5, FAMILY_CLASSIC, {
+    '900': 'fas',
+    '400': 'far',
+    'normal': 'far',
+    '300': 'fal',
+    '100': 'fat'
+  }), _defineProperty(_familyProxy5, FAMILY_SHARP, {
+    '900': 'fass',
+    '400': 'fasr',
+    '300': 'fasl'
+  }), _familyProxy5));
+  var oneToTen = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10];
+  var oneToTwenty = oneToTen.concat([11, 12, 13, 14, 15, 16, 17, 18, 19, 20]);
+  var DUOTONE_CLASSES = {
+    GROUP: 'duotone-group',
+    SWAP_OPACITY: 'swap-opacity',
+    PRIMARY: 'primary',
+    SECONDARY: 'secondary'
+  };
+  var prefixes = new Set();
+  Object.keys(STYLE_TO_PREFIX[FAMILY_CLASSIC]).map(prefixes.add.bind(prefixes));
+  Object.keys(STYLE_TO_PREFIX[FAMILY_SHARP]).map(prefixes.add.bind(prefixes));
+  var RESERVED_CLASSES = [].concat(FAMILIES, _toConsumableArray(prefixes), ['2xs', 'xs', 'sm', 'lg', 'xl', '2xl', 'beat', 'border', 'fade', 'beat-fade', 'bounce', 'flip-both', 'flip-horizontal', 'flip-vertical', 'flip', 'fw', 'inverse', 'layers-counter', 'layers-text', 'layers', 'li', 'pull-left', 'pull-right', 'pulse', 'rotate-180', 'rotate-270', 'rotate-90', 'rotate-by', 'shake', 'spin-pulse', 'spin-reverse', 'spin', 'stack-1x', 'stack-2x', 'stack', 'ul', DUOTONE_CLASSES.GROUP, DUOTONE_CLASSES.SWAP_OPACITY, DUOTONE_CLASSES.PRIMARY, DUOTONE_CLASSES.SECONDARY]).concat(oneToTen.map(function (n) {
+    return "".concat(n, "x");
+  })).concat(oneToTwenty.map(function (n) {
+    return "w-".concat(n);
+  }));
+
+  function bunker(fn) {
+    try {
+      for (var _len = arguments.length, args = new Array(_len > 1 ? _len - 1 : 0), _key = 1; _key < _len; _key++) {
+        args[_key - 1] = arguments[_key];
+      }
+
+      fn.apply(void 0, args);
+    } catch (e) {
+      if (!PRODUCTION) {
+        throw e;
+      }
+    }
+  }
+
+  bunker(function () {
+    if (IS_BROWSER && IS_DOM) {
+      conflictDetection(window.FontAwesomeDetection.report);
+    }
+  });
+
+})));

static/assets/FontAwesome/js/conflict-detection.min.js

@@ -0,0 +1,6 @@
+/*!
+ * Font Awesome Free 6.4.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */
+var t;t=function(){"use strict";function o(e,t){var n,o=Object.keys(e);return Object.getOwnPropertySymbols&&(n=Object.getOwnPropertySymbols(e),t&&(n=n.filter(function(t){return Object.getOwnPropertyDescriptor(e,t).enumerable})),o.push.apply(o,n)),o}function a(e){for(var t=1;t<arguments.length;t++){var n=null!=arguments[t]?arguments[t]:{};t%2?o(Object(n),!0).forEach(function(t){r(e,t,n[t])}):Object.getOwnPropertyDescriptors?Object.defineProperties(e,Object.getOwnPropertyDescriptors(n)):o(Object(n)).forEach(function(t){Object.defineProperty(e,t,Object.getOwnPropertyDescriptor(n,t))})}return e}function e(t){return(e="function"==typeof Symbol&&"symbol"==typeof Symbol.iterator?function(t){return typeof t}:function(t){return t&&"function"==typeof Symbol&&t.constructor===Symbol&&t!==Symbol.prototype?"symbol":typeof t})(t)}function r(t,e,n){return e in t?Object.defineProperty(t,e,{value:n,enumerable:!0,configurable:!0,writable:!0}):t[e]=n,t}function 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