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import torch
import asyncio
from typing import Dict
from comfy.utils import ProgressBar
from comfy_execution.graph_utils import GraphBuilder
from comfy.comfy_types.node_typing import ComfyNodeABC
from comfy.comfy_types import IO
class TestAsyncValidation(ComfyNodeABC):
"""Test node with async VALIDATE_INPUTS."""
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"value": ("FLOAT", {"default": 5.0}),
"threshold": ("FLOAT", {"default": 10.0}),
},
}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "process"
CATEGORY = "_for_testing/async"
@classmethod
async def VALIDATE_INPUTS(cls, value, threshold):
# Simulate async validation (e.g., checking remote service)
await asyncio.sleep(0.05)
if value > threshold:
return f"Value {value} exceeds threshold {threshold}"
return True
def process(self, value, threshold):
# Create image based on value
intensity = value / 10.0
image = torch.ones([1, 512, 512, 3]) * intensity
return (image,)
class TestAsyncError(ComfyNodeABC):
"""Test node that errors during async execution."""
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"value": (IO.ANY, {}),
"error_after": ("FLOAT", {"default": 0.1, "min": 0.0, "max": 10.0}),
},
}
RETURN_TYPES = (IO.ANY,)
FUNCTION = "error_execution"
CATEGORY = "_for_testing/async"
async def error_execution(self, value, error_after):
await asyncio.sleep(error_after)
raise RuntimeError("Intentional async execution error for testing")
class TestAsyncValidationError(ComfyNodeABC):
"""Test node with async validation that always fails."""
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"value": ("FLOAT", {"default": 5.0}),
"max_value": ("FLOAT", {"default": 10.0}),
},
}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "process"
CATEGORY = "_for_testing/async"
@classmethod
async def VALIDATE_INPUTS(cls, value, max_value):
await asyncio.sleep(0.05)
# Always fail validation for values > max_value
if value > max_value:
return f"Async validation failed: {value} > {max_value}"
return True
def process(self, value, max_value):
# This won't be reached if validation fails
image = torch.ones([1, 512, 512, 3]) * (value / max_value)
return (image,)
class TestAsyncTimeout(ComfyNodeABC):
"""Test node that simulates timeout scenarios."""
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"value": (IO.ANY, {}),
"timeout": ("FLOAT", {"default": 1.0, "min": 0.1, "max": 10.0}),
"operation_time": ("FLOAT", {"default": 2.0, "min": 0.1, "max": 10.0}),
},
}
RETURN_TYPES = (IO.ANY,)
FUNCTION = "timeout_execution"
CATEGORY = "_for_testing/async"
async def timeout_execution(self, value, timeout, operation_time):
try:
# This will timeout if operation_time > timeout
await asyncio.wait_for(asyncio.sleep(operation_time), timeout=timeout)
return (value,)
except asyncio.TimeoutError:
raise RuntimeError(f"Operation timed out after {timeout} seconds")
class TestSyncError(ComfyNodeABC):
"""Test node that errors synchronously (for mixed sync/async testing)."""
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"value": (IO.ANY, {}),
},
}
RETURN_TYPES = (IO.ANY,)
FUNCTION = "sync_error"
CATEGORY = "_for_testing/async"
def sync_error(self, value):
raise RuntimeError("Intentional sync execution error for testing")
class TestAsyncLazyCheck(ComfyNodeABC):
"""Test node with async check_lazy_status."""
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"input1": (IO.ANY, {"lazy": True}),
"input2": (IO.ANY, {"lazy": True}),
"condition": ("BOOLEAN", {"default": True}),
},
}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "process"
CATEGORY = "_for_testing/async"
async def check_lazy_status(self, condition, input1, input2):
# Simulate async checking (e.g., querying remote service)
await asyncio.sleep(0.05)
needed = []
if condition and input1 is None:
needed.append("input1")
if not condition and input2 is None:
needed.append("input2")
return needed
def process(self, input1, input2, condition):
# Return a simple image
return (torch.ones([1, 512, 512, 3]),)
class TestDynamicAsyncGeneration(ComfyNodeABC):
"""Test node that dynamically generates async nodes."""
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"image1": ("IMAGE",),
"image2": ("IMAGE",),
"num_async_nodes": ("INT", {"default": 3, "min": 1, "max": 10}),
"sleep_duration": ("FLOAT", {"default": 0.2, "min": 0.1, "max": 1.0}),
},
}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "generate_async_workflow"
CATEGORY = "_for_testing/async"
def generate_async_workflow(self, image1, image2, num_async_nodes, sleep_duration):
g = GraphBuilder()
# Create multiple async sleep nodes
sleep_nodes = []
for i in range(num_async_nodes):
image = image1 if i % 2 == 0 else image2
sleep_node = g.node("TestSleep", value=image, seconds=sleep_duration)
sleep_nodes.append(sleep_node)
# Average all results
if len(sleep_nodes) == 1:
final_node = sleep_nodes[0]
else:
avg_inputs = {"input1": sleep_nodes[0].out(0)}
for i, node in enumerate(sleep_nodes[1:], 2):
avg_inputs[f"input{i}"] = node.out(0)
final_node = g.node("TestVariadicAverage", **avg_inputs)
return {
"result": (final_node.out(0),),
"expand": g.finalize(),
}
class TestAsyncResourceUser(ComfyNodeABC):
"""Test node that uses resources during async execution."""
# Class-level resource tracking for testing
_active_resources: Dict[str, bool] = {}
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"value": (IO.ANY, {}),
"resource_id": ("STRING", {"default": "resource_0"}),
"duration": ("FLOAT", {"default": 0.1, "min": 0.0, "max": 1.0}),
},
}
RETURN_TYPES = (IO.ANY,)
FUNCTION = "use_resource"
CATEGORY = "_for_testing/async"
async def use_resource(self, value, resource_id, duration):
# Check if resource is already in use
if self._active_resources.get(resource_id, False):
raise RuntimeError(f"Resource {resource_id} is already in use!")
# Mark resource as in use
self._active_resources[resource_id] = True
try:
# Simulate resource usage
await asyncio.sleep(duration)
return (value,)
finally:
# Always clean up resource
self._active_resources[resource_id] = False
class TestAsyncBatchProcessing(ComfyNodeABC):
"""Test async processing of batched inputs."""
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"images": ("IMAGE",),
"process_time_per_item": ("FLOAT", {"default": 0.1, "min": 0.01, "max": 1.0}),
},
"hidden": {
"unique_id": "UNIQUE_ID",
},
}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "process_batch"
CATEGORY = "_for_testing/async"
async def process_batch(self, images, process_time_per_item, unique_id):
batch_size = images.shape[0]
pbar = ProgressBar(batch_size, node_id=unique_id)
# Process each image in the batch
processed = []
for i in range(batch_size):
# Simulate async processing
await asyncio.sleep(process_time_per_item)
# Simple processing: invert the image
processed_image = 1.0 - images[i:i+1]
processed.append(processed_image)
pbar.update(1)
# Stack processed images
result = torch.cat(processed, dim=0)
return (result,)
class TestAsyncConcurrentLimit(ComfyNodeABC):
"""Test concurrent execution limits for async nodes."""
_semaphore = asyncio.Semaphore(2) # Only allow 2 concurrent executions
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"value": (IO.ANY, {}),
"duration": ("FLOAT", {"default": 0.5, "min": 0.1, "max": 2.0}),
"node_id": ("INT", {"default": 0}),
},
}
RETURN_TYPES = (IO.ANY,)
FUNCTION = "limited_execution"
CATEGORY = "_for_testing/async"
async def limited_execution(self, value, duration, node_id):
async with self._semaphore:
# Node {node_id} acquired semaphore
await asyncio.sleep(duration)
# Node {node_id} releasing semaphore
return (value,)
# Add node mappings
ASYNC_TEST_NODE_CLASS_MAPPINGS = {
"TestAsyncValidation": TestAsyncValidation,
"TestAsyncError": TestAsyncError,
"TestAsyncValidationError": TestAsyncValidationError,
"TestAsyncTimeout": TestAsyncTimeout,
"TestSyncError": TestSyncError,
"TestAsyncLazyCheck": TestAsyncLazyCheck,
"TestDynamicAsyncGeneration": TestDynamicAsyncGeneration,
"TestAsyncResourceUser": TestAsyncResourceUser,
"TestAsyncBatchProcessing": TestAsyncBatchProcessing,
"TestAsyncConcurrentLimit": TestAsyncConcurrentLimit,
}
ASYNC_TEST_NODE_DISPLAY_NAME_MAPPINGS = {
"TestAsyncValidation": "Test Async Validation",
"TestAsyncError": "Test Async Error",
"TestAsyncValidationError": "Test Async Validation Error",
"TestAsyncTimeout": "Test Async Timeout",
"TestSyncError": "Test Sync Error",
"TestAsyncLazyCheck": "Test Async Lazy Check",
"TestDynamicAsyncGeneration": "Test Dynamic Async Generation",
"TestAsyncResourceUser": "Test Async Resource User",
"TestAsyncBatchProcessing": "Test Async Batch Processing",
"TestAsyncConcurrentLimit": "Test Async Concurrent Limit",
}
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