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from copy import deepcopy
from io import BytesIO
from urllib import request
import numpy
import os
from PIL import Image
import pytest
from pytest import fixture
import time
import torch
from typing import Union
import json
import subprocess
import websocket #NOTE: websocket-client (https://github.com/websocket-client/websocket-client)
import uuid
import urllib.request
import urllib.parse
from comfy.samplers import KSampler
"""
These tests generate and save images through a range of parameters
"""
class ComfyGraph:
def __init__(self,
graph: dict,
sampler_nodes: list[str],
):
self.graph = graph
self.sampler_nodes = sampler_nodes
def set_prompt(self, prompt, negative_prompt=None):
# Sets the prompt for the sampler nodes (eg. base and refiner)
for node in self.sampler_nodes:
prompt_node = self.graph[node]['inputs']['positive'][0]
self.graph[prompt_node]['inputs']['text'] = prompt
if negative_prompt:
negative_prompt_node = self.graph[node]['inputs']['negative'][0]
self.graph[negative_prompt_node]['inputs']['text'] = negative_prompt
def set_sampler_name(self, sampler_name:str, ):
# sets the sampler name for the sampler nodes (eg. base and refiner)
for node in self.sampler_nodes:
self.graph[node]['inputs']['sampler_name'] = sampler_name
def set_scheduler(self, scheduler:str):
# sets the sampler name for the sampler nodes (eg. base and refiner)
for node in self.sampler_nodes:
self.graph[node]['inputs']['scheduler'] = scheduler
def set_filename_prefix(self, prefix:str):
# sets the filename prefix for the save nodes
for node in self.graph:
if self.graph[node]['class_type'] == 'SaveImage':
self.graph[node]['inputs']['filename_prefix'] = prefix
class ComfyClient:
# From examples/websockets_api_example.py
def connect(self,
listen:str = '127.0.0.1',
port:Union[str,int] = 8188,
client_id: str = str(uuid.uuid4())
):
self.client_id = client_id
self.server_address = f"{listen}:{port}"
ws = websocket.WebSocket()
ws.connect("ws://{}/ws?clientId={}".format(self.server_address, self.client_id))
self.ws = ws
def queue_prompt(self, prompt):
p = {"prompt": prompt, "client_id": self.client_id}
data = json.dumps(p).encode('utf-8')
req = urllib.request.Request("http://{}/prompt".format(self.server_address), data=data)
return json.loads(urllib.request.urlopen(req).read())
def get_image(self, filename, subfolder, folder_type):
data = {"filename": filename, "subfolder": subfolder, "type": folder_type}
url_values = urllib.parse.urlencode(data)
with urllib.request.urlopen("http://{}/view?{}".format(self.server_address, url_values)) as response:
return response.read()
def get_history(self, prompt_id):
with urllib.request.urlopen("http://{}/history/{}".format(self.server_address, prompt_id)) as response:
return json.loads(response.read())
def get_images(self, graph, save=True):
prompt = graph
if not save:
# Replace save nodes with preview nodes
prompt_str = json.dumps(prompt)
prompt_str = prompt_str.replace('SaveImage', 'PreviewImage')
prompt = json.loads(prompt_str)
prompt_id = self.queue_prompt(prompt)['prompt_id']
output_images = {}
while True:
out = self.ws.recv()
if isinstance(out, str):
message = json.loads(out)
if message['type'] == 'executing':
data = message['data']
if data['node'] is None and data['prompt_id'] == prompt_id:
break #Execution is done
else:
continue #previews are binary data
history = self.get_history(prompt_id)[prompt_id]
for node_id in history['outputs']:
node_output = history['outputs'][node_id]
images_output = []
if 'images' in node_output:
for image in node_output['images']:
image_data = self.get_image(image['filename'], image['subfolder'], image['type'])
images_output.append(image_data)
output_images[node_id] = images_output
return output_images
#
# Initialize graphs
#
default_graph_file = 'tests/inference/graphs/default_graph_sdxl1_0.json'
with open(default_graph_file, 'r') as file:
default_graph = json.loads(file.read())
DEFAULT_COMFY_GRAPH = ComfyGraph(graph=default_graph, sampler_nodes=['10','14'])
DEFAULT_COMFY_GRAPH_ID = os.path.splitext(os.path.basename(default_graph_file))[0]
#
# Loop through these variables
#
comfy_graph_list = [DEFAULT_COMFY_GRAPH]
comfy_graph_ids = [DEFAULT_COMFY_GRAPH_ID]
prompt_list = [
'a painting of a cat',
]
sampler_list = KSampler.SAMPLERS
scheduler_list = KSampler.SCHEDULERS
@pytest.mark.inference
@pytest.mark.parametrize("sampler", sampler_list)
@pytest.mark.parametrize("scheduler", scheduler_list)
@pytest.mark.parametrize("prompt", prompt_list)
class TestInference:
#
# Initialize server and client
#
@fixture(scope="class", autouse=True)
def _server(self, args_pytest):
# Start server
p = subprocess.Popen([
'python','main.py',
'--output-directory', args_pytest["output_dir"],
'--listen', args_pytest["listen"],
'--port', str(args_pytest["port"]),
])
yield
p.kill()
torch.cuda.empty_cache()
def start_client(self, listen:str, port:int):
# Start client
comfy_client = ComfyClient()
# Connect to server (with retries)
n_tries = 5
for i in range(n_tries):
time.sleep(4)
try:
comfy_client.connect(listen=listen, port=port)
except ConnectionRefusedError as e:
print(e)
print(f"({i+1}/{n_tries}) Retrying...")
else:
break
return comfy_client
#
# Client and graph fixtures with server warmup
#
# Returns a "_client_graph", which is client-graph pair corresponding to an initialized server
# The "graph" is the default graph
@fixture(scope="class", params=comfy_graph_list, ids=comfy_graph_ids, autouse=True)
def _client_graph(self, request, args_pytest, _server) -> (ComfyClient, ComfyGraph):
comfy_graph = request.param
# Start client
comfy_client = self.start_client(args_pytest["listen"], args_pytest["port"])
# Warm up pipeline
comfy_client.get_images(graph=comfy_graph.graph, save=False)
yield comfy_client, comfy_graph
del comfy_client
del comfy_graph
torch.cuda.empty_cache()
@fixture
def client(self, _client_graph):
client = _client_graph[0]
yield client
@fixture
def comfy_graph(self, _client_graph):
# avoid mutating the graph
graph = deepcopy(_client_graph[1])
yield graph
def test_comfy(
self,
client,
comfy_graph,
sampler,
scheduler,
prompt,
request
):
test_info = request.node.name
comfy_graph.set_filename_prefix(test_info)
# Settings for comfy graph
comfy_graph.set_sampler_name(sampler)
comfy_graph.set_scheduler(scheduler)
comfy_graph.set_prompt(prompt)
# Generate
images = client.get_images(comfy_graph.graph)
assert len(images) != 0, "No images generated"
# assert all images are not blank
for images_output in images.values():
for image_data in images_output:
pil_image = Image.open(BytesIO(image_data))
assert numpy.array(pil_image).any() != 0, "Image is blank"
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