Spaces:
Running
Running
ZeroCommand
commited on
Commit
•
6e92592
1
Parent(s):
8dc0e4d
fix uid reload and show log files
Browse files- app.py +3 -0
- app_debug.py +37 -0
- app_text_classification.py +19 -11
- text_classification_ui_helpers.py +1 -1
app.py
CHANGED
@@ -3,6 +3,7 @@ import gradio as gr
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from app_leaderboard import get_demo as get_demo_leaderboard
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from app_text_classification import get_demo as get_demo_text_classification
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from run_jobs import start_process_run_job, stop_thread
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try:
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@@ -11,6 +12,8 @@ try:
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get_demo_text_classification(demo)
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with gr.Tab("Leaderboard"):
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get_demo_leaderboard()
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start_process_run_job()
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from app_leaderboard import get_demo as get_demo_leaderboard
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from app_text_classification import get_demo as get_demo_text_classification
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from app_debug import get_demo as get_demo_debug
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from run_jobs import start_process_run_job, stop_thread
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try:
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get_demo_text_classification(demo)
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with gr.Tab("Leaderboard"):
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get_demo_leaderboard()
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with gr.Tab("Logs(Debug)"):
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get_demo_debug(demo)
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start_process_run_job()
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app_debug.py
ADDED
@@ -0,0 +1,37 @@
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import gradio as gr
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import pipe
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from os import listdir
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from os.path import isfile, join
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LOG_PATH = "./tmp"
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CONFIG_PATH = "./cicd/configs"
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def get_accordions_of_files(path, files):
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components = []
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for file in files:
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with gr.Row():
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with gr.Accordion(label=file, open=False):
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with gr.Row():
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with open(join(path, file), "r") as f:
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gr.Markdown(f.read())
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return components
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def get_accordions_of_log_files():
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log_files = [f for f in listdir(LOG_PATH) if isfile(join(LOG_PATH, f)) and f.endswith("_log")]
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return get_accordions_of_files(LOG_PATH, log_files)
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def get_accordions_of_config_files():
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config_files = config_files = [f for f in listdir(CONFIG_PATH) if isfile(join(CONFIG_PATH, f)) and f.endswith(".yaml")]
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return get_accordions_of_files(CONFIG_PATH, config_files)
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def get_demo(demo):
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with gr.Row():
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# check if jobs is an attribute of pipe
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if hasattr(pipe, "jobs"):
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gr.Markdown(f"current jobs in queue: {len(pipe.jobs)}")
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with gr.Accordion(label="Config Files", open=False):
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config_accordion = get_accordions_of_config_files()
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demo.load(get_accordions_of_config_files, outputs=config_accordion, every=1)
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with gr.Accordion(label="Log Files", open=False):
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log_accordions = get_accordions_of_log_files()
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demo.load(get_accordions_of_log_files, outputs=log_accordions, every=1)
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app_text_classification.py
CHANGED
@@ -27,11 +27,10 @@ CONFIG_PATH = "./config.yaml"
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def get_demo(demo):
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uid = uuid.uuid4()
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with gr.Row():
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gr.Markdown(INTRODUCTION_MD)
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uid_label = gr.Textbox(
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label="Evaluation ID:", value=
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)
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with gr.Row():
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model_id_input = gr.Textbox(
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@@ -70,19 +69,28 @@ def get_demo(demo):
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with gr.Accordion(label="Model Wrap Advance Config (optional)", open=False):
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run_local = gr.Checkbox(value=True, label="Run in this Space")
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inference_token = gr.Textbox(value="", label="HF Token for Inference API", visible=False, interactive=True)
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with gr.Accordion(label="Scanner Advance Config (optional)", open=False):
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selected = read_scanners(uid)
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# currently we remove data_leakage from the default scanners
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# Reason: data_leakage barely raises any issues and takes too many requests
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# when using inference API, causing rate limit error
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scan_config = selected + ["data_leakage"]
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scanners = gr.CheckboxGroup(
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)
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with gr.Row():
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run_btn = gr.Button(
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@@ -98,7 +106,7 @@ def get_demo(demo):
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dataset_id_input.change(
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check_dataset_and_get_config,
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inputs=[dataset_id_input
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)
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dataset_config_input.change(
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def get_demo(demo):
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with gr.Row():
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gr.Markdown(INTRODUCTION_MD)
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uid_label = gr.Textbox(
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label="Evaluation ID:", value=uuid.uuid4, visible=False, interactive=False
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)
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with gr.Row():
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model_id_input = gr.Textbox(
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with gr.Accordion(label="Model Wrap Advance Config (optional)", open=False):
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run_local = gr.Checkbox(value=True, label="Run in this Space")
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run_inference = gr.Checkbox(value="False", label="Run with Inference API")
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@gr.on(triggers=[uid_label.change], inputs=[uid_label], outputs=[run_inference])
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def get_run_mode(uid):
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return (
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gr.update(value=read_inference_type(uid) == "hf_inference_api" and not run_local.value)
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)
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inference_token = gr.Textbox(value="", label="HF Token for Inference API", visible=False, interactive=True)
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with gr.Accordion(label="Scanner Advance Config (optional)", open=False):
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scanners = gr.CheckboxGroup(
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label="Scan Settings", visible=True
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)
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@gr.on(triggers=[uid_label.change], inputs=[uid_label], outputs=[scanners])
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def get_scanners(uid):
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selected = read_scanners(uid)
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# currently we remove data_leakage from the default scanners
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# Reason: data_leakage barely raises any issues and takes too many requests
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# when using inference API, causing rate limit error
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scan_config = selected + ["data_leakage"]
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return (gr.update(
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choices=scan_config, value=selected, label="Scan Settings", visible=True
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))
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with gr.Row():
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run_btn = gr.Button(
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dataset_id_input.change(
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check_dataset_and_get_config,
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inputs=[dataset_id_input], outputs=[dataset_config_input]
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)
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dataset_config_input.change(
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text_classification_ui_helpers.py
CHANGED
@@ -23,7 +23,7 @@ HF_SPACE_ID = "SPACE_ID"
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HF_WRITE_TOKEN = "HF_WRITE_TOKEN"
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def check_dataset_and_get_config(dataset_id
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try:
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# write_column_mapping(None, uid) # reset column mapping
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configs = datasets.get_dataset_config_names(dataset_id)
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HF_WRITE_TOKEN = "HF_WRITE_TOKEN"
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def check_dataset_and_get_config(dataset_id):
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try:
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# write_column_mapping(None, uid) # reset column mapping
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configs = datasets.get_dataset_config_names(dataset_id)
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