ComfyUI/tests/inference/test_execution.py

500 lines
22 KiB
Python

from io import BytesIO
import numpy
from PIL import Image
import pytest
from pytest import fixture
import time
import torch
from typing import Union, Dict
import json
import subprocess
import websocket #NOTE: websocket-client (https://github.com/websocket-client/websocket-client)
import uuid
import urllib.request
import urllib.parse
import urllib.error
from comfy_execution.graph_utils import GraphBuilder, Node
class RunResult:
def __init__(self, prompt_id: str):
self.outputs: Dict[str,Dict] = {}
self.runs: Dict[str,bool] = {}
self.prompt_id: str = prompt_id
def get_output(self, node: Node):
return self.outputs.get(node.id, None)
def did_run(self, node: Node):
return self.runs.get(node.id, False)
def get_images(self, node: Node):
output = self.get_output(node)
if output is None:
return []
return output.get('image_objects', [])
def get_prompt_id(self):
return self.prompt_id
class ComfyClient:
def __init__(self):
self.test_name = ""
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 set_test_name(self, name):
self.test_name = name
def run(self, graph):
prompt = graph.finalize()
for node in graph.nodes.values():
if node.class_type == 'SaveImage':
node.inputs['filename_prefix'] = self.test_name
prompt_id = self.queue_prompt(prompt)['prompt_id']
result = RunResult(prompt_id)
while True:
out = self.ws.recv()
if isinstance(out, str):
message = json.loads(out)
if message['type'] == 'executing':
data = message['data']
if data['prompt_id'] != prompt_id:
continue
if data['node'] is None:
break
result.runs[data['node']] = True
elif message['type'] == 'execution_error':
raise Exception(message['data'])
elif message['type'] == 'execution_cached':
pass # Probably want to store this off for testing
history = self.get_history(prompt_id)[prompt_id]
for o in history['outputs']:
for node_id in history['outputs']:
node_output = history['outputs'][node_id]
result.outputs[node_id] = node_output
if 'images' in node_output:
images_output = []
for image in node_output['images']:
image_data = self.get_image(image['filename'], image['subfolder'], image['type'])
image_obj = Image.open(BytesIO(image_data))
images_output.append(image_obj)
node_output['image_objects'] = images_output
return result
#
# Loop through these variables
#
@pytest.mark.execution
class TestExecution:
#
# Initialize server and client
#
@fixture(scope="class", autouse=True, params=[
# (use_lru, lru_size)
(False, 0),
(True, 0),
(True, 100),
])
def _server(self, args_pytest, request):
# Start server
pargs = [
'python','main.py',
'--output-directory', args_pytest["output_dir"],
'--listen', args_pytest["listen"],
'--port', str(args_pytest["port"]),
'--extra-model-paths-config', 'tests/inference/extra_model_paths.yaml',
]
use_lru, lru_size = request.param
if use_lru:
pargs += ['--cache-lru', str(lru_size)]
print("Running server with args:", pargs)
p = subprocess.Popen(pargs)
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
@fixture(scope="class", autouse=True)
def shared_client(self, args_pytest, _server):
client = self.start_client(args_pytest["listen"], args_pytest["port"])
yield client
del client
torch.cuda.empty_cache()
@fixture
def client(self, shared_client, request):
shared_client.set_test_name(f"execution[{request.node.name}]")
yield shared_client
@fixture
def builder(self, request):
yield GraphBuilder(prefix=request.node.name)
def test_lazy_input(self, client: ComfyClient, builder: GraphBuilder):
g = builder
input1 = g.node("StubImage", content="BLACK", height=512, width=512, batch_size=1)
input2 = g.node("StubImage", content="WHITE", height=512, width=512, batch_size=1)
mask = g.node("StubMask", value=0.0, height=512, width=512, batch_size=1)
lazy_mix = g.node("TestLazyMixImages", image1=input1.out(0), image2=input2.out(0), mask=mask.out(0))
output = g.node("SaveImage", images=lazy_mix.out(0))
result = client.run(g)
result_image = result.get_images(output)[0]
assert numpy.array(result_image).any() == 0, "Image should be black"
assert result.did_run(input1)
assert not result.did_run(input2)
assert result.did_run(mask)
assert result.did_run(lazy_mix)
def test_full_cache(self, client: ComfyClient, builder: GraphBuilder):
g = builder
input1 = g.node("StubImage", content="BLACK", height=512, width=512, batch_size=1)
input2 = g.node("StubImage", content="NOISE", height=512, width=512, batch_size=1)
mask = g.node("StubMask", value=0.5, height=512, width=512, batch_size=1)
lazy_mix = g.node("TestLazyMixImages", image1=input1.out(0), image2=input2.out(0), mask=mask.out(0))
g.node("SaveImage", images=lazy_mix.out(0))
client.run(g)
result2 = client.run(g)
for node_id, node in g.nodes.items():
assert not result2.did_run(node), f"Node {node_id} ran, but should have been cached"
def test_partial_cache(self, client: ComfyClient, builder: GraphBuilder):
g = builder
input1 = g.node("StubImage", content="BLACK", height=512, width=512, batch_size=1)
input2 = g.node("StubImage", content="NOISE", height=512, width=512, batch_size=1)
mask = g.node("StubMask", value=0.5, height=512, width=512, batch_size=1)
lazy_mix = g.node("TestLazyMixImages", image1=input1.out(0), image2=input2.out(0), mask=mask.out(0))
g.node("SaveImage", images=lazy_mix.out(0))
client.run(g)
mask.inputs['value'] = 0.4
result2 = client.run(g)
assert not result2.did_run(input1), "Input1 should have been cached"
assert not result2.did_run(input2), "Input2 should have been cached"
def test_error(self, client: ComfyClient, builder: GraphBuilder):
g = builder
input1 = g.node("StubImage", content="BLACK", height=512, width=512, batch_size=1)
# Different size of the two images
input2 = g.node("StubImage", content="NOISE", height=256, width=256, batch_size=1)
mask = g.node("StubMask", value=0.5, height=512, width=512, batch_size=1)
lazy_mix = g.node("TestLazyMixImages", image1=input1.out(0), image2=input2.out(0), mask=mask.out(0))
g.node("SaveImage", images=lazy_mix.out(0))
try:
client.run(g)
assert False, "Should have raised an error"
except Exception as e:
assert 'prompt_id' in e.args[0], f"Did not get back a proper error message: {e}"
@pytest.mark.parametrize("test_value, expect_error", [
(5, True),
("foo", True),
(5.0, False),
])
def test_validation_error_literal(self, test_value, expect_error, client: ComfyClient, builder: GraphBuilder):
g = builder
validation1 = g.node("TestCustomValidation1", input1=test_value, input2=3.0)
g.node("SaveImage", images=validation1.out(0))
if expect_error:
with pytest.raises(urllib.error.HTTPError):
client.run(g)
else:
client.run(g)
@pytest.mark.parametrize("test_type, test_value", [
("StubInt", 5),
("StubFloat", 5.0)
])
def test_validation_error_edge1(self, test_type, test_value, client: ComfyClient, builder: GraphBuilder):
g = builder
stub = g.node(test_type, value=test_value)
validation1 = g.node("TestCustomValidation1", input1=stub.out(0), input2=3.0)
g.node("SaveImage", images=validation1.out(0))
with pytest.raises(urllib.error.HTTPError):
client.run(g)
@pytest.mark.parametrize("test_type, test_value, expect_error", [
("StubInt", 5, True),
("StubFloat", 5.0, False)
])
def test_validation_error_edge2(self, test_type, test_value, expect_error, client: ComfyClient, builder: GraphBuilder):
g = builder
stub = g.node(test_type, value=test_value)
validation2 = g.node("TestCustomValidation2", input1=stub.out(0), input2=3.0)
g.node("SaveImage", images=validation2.out(0))
if expect_error:
with pytest.raises(urllib.error.HTTPError):
client.run(g)
else:
client.run(g)
@pytest.mark.parametrize("test_type, test_value, expect_error", [
("StubInt", 5, True),
("StubFloat", 5.0, False)
])
def test_validation_error_edge3(self, test_type, test_value, expect_error, client: ComfyClient, builder: GraphBuilder):
g = builder
stub = g.node(test_type, value=test_value)
validation3 = g.node("TestCustomValidation3", input1=stub.out(0), input2=3.0)
g.node("SaveImage", images=validation3.out(0))
if expect_error:
with pytest.raises(urllib.error.HTTPError):
client.run(g)
else:
client.run(g)
@pytest.mark.parametrize("test_type, test_value, expect_error", [
("StubInt", 5, True),
("StubFloat", 5.0, False)
])
def test_validation_error_edge4(self, test_type, test_value, expect_error, client: ComfyClient, builder: GraphBuilder):
g = builder
stub = g.node(test_type, value=test_value)
validation4 = g.node("TestCustomValidation4", input1=stub.out(0), input2=3.0)
g.node("SaveImage", images=validation4.out(0))
if expect_error:
with pytest.raises(urllib.error.HTTPError):
client.run(g)
else:
client.run(g)
@pytest.mark.parametrize("test_value1, test_value2, expect_error", [
(0.0, 0.5, False),
(0.0, 5.0, False),
(0.0, 7.0, True)
])
def test_validation_error_kwargs(self, test_value1, test_value2, expect_error, client: ComfyClient, builder: GraphBuilder):
g = builder
validation5 = g.node("TestCustomValidation5", input1=test_value1, input2=test_value2)
g.node("SaveImage", images=validation5.out(0))
if expect_error:
with pytest.raises(urllib.error.HTTPError):
client.run(g)
else:
client.run(g)
def test_cycle_error(self, client: ComfyClient, builder: GraphBuilder):
g = builder
input1 = g.node("StubImage", content="BLACK", height=512, width=512, batch_size=1)
input2 = g.node("StubImage", content="WHITE", height=512, width=512, batch_size=1)
mask = g.node("StubMask", value=0.5, height=512, width=512, batch_size=1)
lazy_mix1 = g.node("TestLazyMixImages", image1=input1.out(0), mask=mask.out(0))
lazy_mix2 = g.node("TestLazyMixImages", image1=lazy_mix1.out(0), image2=input2.out(0), mask=mask.out(0))
g.node("SaveImage", images=lazy_mix2.out(0))
# When the cycle exists on initial submission, it should raise a validation error
with pytest.raises(urllib.error.HTTPError):
client.run(g)
def test_dynamic_cycle_error(self, client: ComfyClient, builder: GraphBuilder):
g = builder
input1 = g.node("StubImage", content="BLACK", height=512, width=512, batch_size=1)
input2 = g.node("StubImage", content="WHITE", height=512, width=512, batch_size=1)
generator = g.node("TestDynamicDependencyCycle", input1=input1.out(0), input2=input2.out(0))
g.node("SaveImage", images=generator.out(0))
# When the cycle is in a graph that is generated dynamically, it should raise a runtime error
try:
client.run(g)
assert False, "Should have raised an error"
except Exception as e:
assert 'prompt_id' in e.args[0], f"Did not get back a proper error message: {e}"
assert e.args[0]['node_id'] == generator.id, "Error should have been on the generator node"
def test_missing_node_error(self, client: ComfyClient, builder: GraphBuilder):
g = builder
input1 = g.node("StubImage", content="BLACK", height=512, width=512, batch_size=1)
input2 = g.node("StubImage", id="removeme", content="WHITE", height=512, width=512, batch_size=1)
input3 = g.node("StubImage", content="WHITE", height=512, width=512, batch_size=1)
mask = g.node("StubMask", value=0.5, height=512, width=512, batch_size=1)
mix1 = g.node("TestLazyMixImages", image1=input1.out(0), image2=input2.out(0), mask=mask.out(0))
mix2 = g.node("TestLazyMixImages", image1=input1.out(0), image2=input3.out(0), mask=mask.out(0))
# We have multiple outputs. The first is invalid, but the second is valid
g.node("SaveImage", images=mix1.out(0))
g.node("SaveImage", images=mix2.out(0))
g.remove_node("removeme")
client.run(g)
# Add back in the missing node to make sure the error doesn't break the server
input2 = g.node("StubImage", id="removeme", content="WHITE", height=512, width=512, batch_size=1)
client.run(g)
def test_custom_is_changed(self, client: ComfyClient, builder: GraphBuilder):
g = builder
# Creating the nodes in this specific order previously caused a bug
save = g.node("SaveImage")
is_changed = g.node("TestCustomIsChanged", should_change=False)
input1 = g.node("StubImage", content="BLACK", height=512, width=512, batch_size=1)
save.set_input('images', is_changed.out(0))
is_changed.set_input('image', input1.out(0))
result1 = client.run(g)
result2 = client.run(g)
is_changed.set_input('should_change', True)
result3 = client.run(g)
result4 = client.run(g)
assert result1.did_run(is_changed), "is_changed should have been run"
assert not result2.did_run(is_changed), "is_changed should have been cached"
assert result3.did_run(is_changed), "is_changed should have been re-run"
assert result4.did_run(is_changed), "is_changed should not have been cached"
def test_undeclared_inputs(self, client: ComfyClient, builder: GraphBuilder):
g = builder
input1 = g.node("StubImage", content="BLACK", height=512, width=512, batch_size=1)
input2 = g.node("StubImage", content="WHITE", height=512, width=512, batch_size=1)
input3 = g.node("StubImage", content="BLACK", height=512, width=512, batch_size=1)
input4 = g.node("StubImage", content="BLACK", height=512, width=512, batch_size=1)
average = g.node("TestVariadicAverage", input1=input1.out(0), input2=input2.out(0), input3=input3.out(0), input4=input4.out(0))
output = g.node("SaveImage", images=average.out(0))
result = client.run(g)
result_image = result.get_images(output)[0]
expected = 255 // 4
assert numpy.array(result_image).min() == expected and numpy.array(result_image).max() == expected, "Image should be grey"
def test_for_loop(self, client: ComfyClient, builder: GraphBuilder):
g = builder
iterations = 4
input1 = g.node("StubImage", content="BLACK", height=512, width=512, batch_size=1)
input2 = g.node("StubImage", content="WHITE", height=512, width=512, batch_size=1)
is_changed = g.node("TestCustomIsChanged", should_change=True, image=input2.out(0))
for_open = g.node("TestForLoopOpen", remaining=iterations, initial_value1=is_changed.out(0))
average = g.node("TestVariadicAverage", input1=input1.out(0), input2=for_open.out(2))
for_close = g.node("TestForLoopClose", flow_control=for_open.out(0), initial_value1=average.out(0))
output = g.node("SaveImage", images=for_close.out(0))
for iterations in range(1, 5):
for_open.set_input('remaining', iterations)
result = client.run(g)
result_image = result.get_images(output)[0]
expected = 255 // (2 ** iterations)
assert numpy.array(result_image).min() == expected and numpy.array(result_image).max() == expected, "Image should be grey"
assert result.did_run(is_changed)
def test_mixed_expansion_returns(self, client: ComfyClient, builder: GraphBuilder):
g = builder
val_list = g.node("TestMakeListNode", value1=0.1, value2=0.2, value3=0.3)
mixed = g.node("TestMixedExpansionReturns", input1=val_list.out(0))
output_dynamic = g.node("SaveImage", images=mixed.out(0))
output_literal = g.node("SaveImage", images=mixed.out(1))
result = client.run(g)
images_dynamic = result.get_images(output_dynamic)
assert len(images_dynamic) == 3, "Should have 2 images"
assert numpy.array(images_dynamic[0]).min() == 25 and numpy.array(images_dynamic[0]).max() == 25, "First image should be 0.1"
assert numpy.array(images_dynamic[1]).min() == 51 and numpy.array(images_dynamic[1]).max() == 51, "Second image should be 0.2"
assert numpy.array(images_dynamic[2]).min() == 76 and numpy.array(images_dynamic[2]).max() == 76, "Third image should be 0.3"
images_literal = result.get_images(output_literal)
assert len(images_literal) == 3, "Should have 2 images"
for i in range(3):
assert numpy.array(images_literal[i]).min() == 255 and numpy.array(images_literal[i]).max() == 255, "All images should be white"
def test_mixed_lazy_results(self, client: ComfyClient, builder: GraphBuilder):
g = builder
val_list = g.node("TestMakeListNode", value1=0.0, value2=0.5, value3=1.0)
mask = g.node("StubMask", value=val_list.out(0), height=512, width=512, batch_size=1)
input1 = g.node("StubImage", content="BLACK", height=512, width=512, batch_size=1)
input2 = g.node("StubImage", content="WHITE", height=512, width=512, batch_size=1)
mix = g.node("TestLazyMixImages", image1=input1.out(0), image2=input2.out(0), mask=mask.out(0))
rebatch = g.node("RebatchImages", images=mix.out(0), batch_size=3)
output = g.node("SaveImage", images=rebatch.out(0))
result = client.run(g)
images = result.get_images(output)
assert len(images) == 3, "Should have 3 image"
assert numpy.array(images[0]).min() == 0 and numpy.array(images[0]).max() == 0, "First image should be 0.0"
assert numpy.array(images[1]).min() == 127 and numpy.array(images[1]).max() == 127, "Second image should be 0.5"
assert numpy.array(images[2]).min() == 255 and numpy.array(images[2]).max() == 255, "Third image should be 1.0"
def test_output_reuse(self, client: ComfyClient, builder: GraphBuilder):
g = builder
input1 = g.node("StubImage", content="BLACK", height=512, width=512, batch_size=1)
output1 = g.node("SaveImage", images=input1.out(0))
output2 = g.node("SaveImage", images=input1.out(0))
result = client.run(g)
images1 = result.get_images(output1)
images2 = result.get_images(output2)
assert len(images1) == 1, "Should have 1 image"
assert len(images2) == 1, "Should have 1 image"
# This tests that only constant outputs are used in the call to `IS_CHANGED`
def test_is_changed_with_outputs(self, client: ComfyClient, builder: GraphBuilder):
g = builder
input1 = g.node("StubConstantImage", value=0.5, height=512, width=512, batch_size=1)
test_node = g.node("TestIsChangedWithConstants", image=input1.out(0), value=0.5)
output = g.node("PreviewImage", images=test_node.out(0))
result = client.run(g)
images = result.get_images(output)
assert len(images) == 1, "Should have 1 image"
assert numpy.array(images[0]).min() == 63 and numpy.array(images[0]).max() == 63, "Image should have value 0.25"
result = client.run(g)
images = result.get_images(output)
assert len(images) == 1, "Should have 1 image"
assert numpy.array(images[0]).min() == 63 and numpy.array(images[0]).max() == 63, "Image should have value 0.25"
assert not result.did_run(test_node), "The execution should have been cached"