Execution Model Inversion (#2666)
* Execution Model Inversion
This PR inverts the execution model -- from recursively calling nodes to
using a topological sort of the nodes. This change allows for
modification of the node graph during execution. This allows for two
major advantages:
1. The implementation of lazy evaluation in nodes. For example, if a
"Mix Images" node has a mix factor of exactly 0.0, the second image
input doesn't even need to be evaluated (and visa-versa if the mix
factor is 1.0).
2. Dynamic expansion of nodes. This allows for the creation of dynamic
"node groups". Specifically, custom nodes can return subgraphs that
replace the original node in the graph. This is an incredibly
powerful concept. Using this functionality, it was easy to
implement:
a. Components (a.k.a. node groups)
b. Flow control (i.e. while loops) via tail recursion
c. All-in-one nodes that replicate the WebUI functionality
d. and more
All of those were able to be implemented entirely via custom nodes,
so those features are *not* a part of this PR. (There are some
front-end changes that should occur before that functionality is
made widely available, particularly around variant sockets.)
The custom nodes associated with this PR can be found at:
https://github.com/BadCafeCode/execution-inversion-demo-comfyui
Note that some of them require that variant socket types ("*") be
enabled.
* Allow `input_info` to be of type `None`
* Handle errors (like OOM) more gracefully
* Add a command-line argument to enable variants
This allows the use of nodes that have sockets of type '*' without
applying a patch to the code.
* Fix an overly aggressive assertion.
This could happen when attempting to evaluate `IS_CHANGED` for a node
during the creation of the cache (in order to create the cache key).
* Fix Pyright warnings
* Add execution model unit tests
* Fix issue with unused literals
Behavior should now match the master branch with regard to undeclared
inputs. Undeclared inputs that are socket connections will be used while
undeclared inputs that are literals will be ignored.
* Make custom VALIDATE_INPUTS skip normal validation
Additionally, if `VALIDATE_INPUTS` takes an argument named `input_types`,
that variable will be a dictionary of the socket type of all incoming
connections. If that argument exists, normal socket type validation will
not occur. This removes the last hurdle for enabling variant types
entirely from custom nodes, so I've removed that command-line option.
I've added appropriate unit tests for these changes.
* Fix example in unit test
This wouldn't have caused any issues in the unit test, but it would have
bugged the UI if someone copy+pasted it into their own node pack.
* Use fstrings instead of '%' formatting syntax
* Use custom exception types.
* Display an error for dependency cycles
Previously, dependency cycles that were created during node expansion
would cause the application to quit (due to an uncaught exception). Now,
we'll throw a proper error to the UI. We also make an attempt to 'blame'
the most relevant node in the UI.
* Add docs on when ExecutionBlocker should be used
* Remove unused functionality
* Rename ExecutionResult.SLEEPING to PENDING
* Remove superfluous function parameter
* Pass None for uneval inputs instead of default
This applies to `VALIDATE_INPUTS`, `check_lazy_status`, and lazy values
in evaluation functions.
* Add a test for mixed node expansion
This test ensures that a node that returns a combination of expanded
subgraphs and literal values functions correctly.
* Raise exception for bad get_node calls.
* Minor refactor of IsChangedCache.get
* Refactor `map_node_over_list` function
* Fix ui output for duplicated nodes
* Add documentation on `check_lazy_status`
* Add file for execution model unit tests
* Clean up Javascript code as per review
* Improve documentation
Converted some comments to docstrings as per review
* Add a new unit test for mixed lazy results
This test validates that when an output list is fed to a lazy node, the
node will properly evaluate previous nodes that are needed by any inputs
to the lazy node.
No code in the execution model has been changed. The test already
passes.
* Allow kwargs in VALIDATE_INPUTS functions
When kwargs are used, validation is skipped for all inputs as if they
had been mentioned explicitly.
* List cached nodes in `execution_cached` message
This was previously just bugged in this PR.
2024-08-15 15:21:11 +00:00
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from io import BytesIO
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import numpy
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from PIL import Image
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import pytest
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from pytest import fixture
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import time
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import torch
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from typing import Union, Dict
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import json
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import subprocess
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import websocket #NOTE: websocket-client (https://github.com/websocket-client/websocket-client)
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import uuid
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import urllib.request
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import urllib.parse
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import urllib.error
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2024-08-15 13:37:30 +00:00
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from comfy_execution.graph_utils import GraphBuilder, Node
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Execution Model Inversion (#2666)
* Execution Model Inversion
This PR inverts the execution model -- from recursively calling nodes to
using a topological sort of the nodes. This change allows for
modification of the node graph during execution. This allows for two
major advantages:
1. The implementation of lazy evaluation in nodes. For example, if a
"Mix Images" node has a mix factor of exactly 0.0, the second image
input doesn't even need to be evaluated (and visa-versa if the mix
factor is 1.0).
2. Dynamic expansion of nodes. This allows for the creation of dynamic
"node groups". Specifically, custom nodes can return subgraphs that
replace the original node in the graph. This is an incredibly
powerful concept. Using this functionality, it was easy to
implement:
a. Components (a.k.a. node groups)
b. Flow control (i.e. while loops) via tail recursion
c. All-in-one nodes that replicate the WebUI functionality
d. and more
All of those were able to be implemented entirely via custom nodes,
so those features are *not* a part of this PR. (There are some
front-end changes that should occur before that functionality is
made widely available, particularly around variant sockets.)
The custom nodes associated with this PR can be found at:
https://github.com/BadCafeCode/execution-inversion-demo-comfyui
Note that some of them require that variant socket types ("*") be
enabled.
* Allow `input_info` to be of type `None`
* Handle errors (like OOM) more gracefully
* Add a command-line argument to enable variants
This allows the use of nodes that have sockets of type '*' without
applying a patch to the code.
* Fix an overly aggressive assertion.
This could happen when attempting to evaluate `IS_CHANGED` for a node
during the creation of the cache (in order to create the cache key).
* Fix Pyright warnings
* Add execution model unit tests
* Fix issue with unused literals
Behavior should now match the master branch with regard to undeclared
inputs. Undeclared inputs that are socket connections will be used while
undeclared inputs that are literals will be ignored.
* Make custom VALIDATE_INPUTS skip normal validation
Additionally, if `VALIDATE_INPUTS` takes an argument named `input_types`,
that variable will be a dictionary of the socket type of all incoming
connections. If that argument exists, normal socket type validation will
not occur. This removes the last hurdle for enabling variant types
entirely from custom nodes, so I've removed that command-line option.
I've added appropriate unit tests for these changes.
* Fix example in unit test
This wouldn't have caused any issues in the unit test, but it would have
bugged the UI if someone copy+pasted it into their own node pack.
* Use fstrings instead of '%' formatting syntax
* Use custom exception types.
* Display an error for dependency cycles
Previously, dependency cycles that were created during node expansion
would cause the application to quit (due to an uncaught exception). Now,
we'll throw a proper error to the UI. We also make an attempt to 'blame'
the most relevant node in the UI.
* Add docs on when ExecutionBlocker should be used
* Remove unused functionality
* Rename ExecutionResult.SLEEPING to PENDING
* Remove superfluous function parameter
* Pass None for uneval inputs instead of default
This applies to `VALIDATE_INPUTS`, `check_lazy_status`, and lazy values
in evaluation functions.
* Add a test for mixed node expansion
This test ensures that a node that returns a combination of expanded
subgraphs and literal values functions correctly.
* Raise exception for bad get_node calls.
* Minor refactor of IsChangedCache.get
* Refactor `map_node_over_list` function
* Fix ui output for duplicated nodes
* Add documentation on `check_lazy_status`
* Add file for execution model unit tests
* Clean up Javascript code as per review
* Improve documentation
Converted some comments to docstrings as per review
* Add a new unit test for mixed lazy results
This test validates that when an output list is fed to a lazy node, the
node will properly evaluate previous nodes that are needed by any inputs
to the lazy node.
No code in the execution model has been changed. The test already
passes.
* Allow kwargs in VALIDATE_INPUTS functions
When kwargs are used, validation is skipped for all inputs as if they
had been mentioned explicitly.
* List cached nodes in `execution_cached` message
This was previously just bugged in this PR.
2024-08-15 15:21:11 +00:00
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class RunResult:
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def __init__(self, prompt_id: str):
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self.outputs: Dict[str,Dict] = {}
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self.runs: Dict[str,bool] = {}
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self.prompt_id: str = prompt_id
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def get_output(self, node: Node):
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return self.outputs.get(node.id, None)
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def did_run(self, node: Node):
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return self.runs.get(node.id, False)
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def get_images(self, node: Node):
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output = self.get_output(node)
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if output is None:
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return []
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return output.get('image_objects', [])
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def get_prompt_id(self):
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return self.prompt_id
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class ComfyClient:
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def __init__(self):
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self.test_name = ""
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def connect(self,
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listen:str = '127.0.0.1',
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port:Union[str,int] = 8188,
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client_id: str = str(uuid.uuid4())
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):
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self.client_id = client_id
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self.server_address = f"{listen}:{port}"
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ws = websocket.WebSocket()
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ws.connect("ws://{}/ws?clientId={}".format(self.server_address, self.client_id))
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self.ws = ws
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def queue_prompt(self, prompt):
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p = {"prompt": prompt, "client_id": self.client_id}
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data = json.dumps(p).encode('utf-8')
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req = urllib.request.Request("http://{}/prompt".format(self.server_address), data=data)
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return json.loads(urllib.request.urlopen(req).read())
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def get_image(self, filename, subfolder, folder_type):
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data = {"filename": filename, "subfolder": subfolder, "type": folder_type}
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url_values = urllib.parse.urlencode(data)
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with urllib.request.urlopen("http://{}/view?{}".format(self.server_address, url_values)) as response:
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return response.read()
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def get_history(self, prompt_id):
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with urllib.request.urlopen("http://{}/history/{}".format(self.server_address, prompt_id)) as response:
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return json.loads(response.read())
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def set_test_name(self, name):
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self.test_name = name
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def run(self, graph):
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prompt = graph.finalize()
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for node in graph.nodes.values():
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if node.class_type == 'SaveImage':
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node.inputs['filename_prefix'] = self.test_name
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prompt_id = self.queue_prompt(prompt)['prompt_id']
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result = RunResult(prompt_id)
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while True:
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out = self.ws.recv()
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if isinstance(out, str):
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message = json.loads(out)
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if message['type'] == 'executing':
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data = message['data']
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if data['prompt_id'] != prompt_id:
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continue
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if data['node'] is None:
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break
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result.runs[data['node']] = True
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elif message['type'] == 'execution_error':
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raise Exception(message['data'])
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elif message['type'] == 'execution_cached':
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pass # Probably want to store this off for testing
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history = self.get_history(prompt_id)[prompt_id]
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2024-08-28 21:46:30 +00:00
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for node_id in history['outputs']:
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node_output = history['outputs'][node_id]
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result.outputs[node_id] = node_output
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images_output = []
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if 'images' in node_output:
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for image in node_output['images']:
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image_data = self.get_image(image['filename'], image['subfolder'], image['type'])
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image_obj = Image.open(BytesIO(image_data))
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images_output.append(image_obj)
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node_output['image_objects'] = images_output
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Execution Model Inversion (#2666)
* Execution Model Inversion
This PR inverts the execution model -- from recursively calling nodes to
using a topological sort of the nodes. This change allows for
modification of the node graph during execution. This allows for two
major advantages:
1. The implementation of lazy evaluation in nodes. For example, if a
"Mix Images" node has a mix factor of exactly 0.0, the second image
input doesn't even need to be evaluated (and visa-versa if the mix
factor is 1.0).
2. Dynamic expansion of nodes. This allows for the creation of dynamic
"node groups". Specifically, custom nodes can return subgraphs that
replace the original node in the graph. This is an incredibly
powerful concept. Using this functionality, it was easy to
implement:
a. Components (a.k.a. node groups)
b. Flow control (i.e. while loops) via tail recursion
c. All-in-one nodes that replicate the WebUI functionality
d. and more
All of those were able to be implemented entirely via custom nodes,
so those features are *not* a part of this PR. (There are some
front-end changes that should occur before that functionality is
made widely available, particularly around variant sockets.)
The custom nodes associated with this PR can be found at:
https://github.com/BadCafeCode/execution-inversion-demo-comfyui
Note that some of them require that variant socket types ("*") be
enabled.
* Allow `input_info` to be of type `None`
* Handle errors (like OOM) more gracefully
* Add a command-line argument to enable variants
This allows the use of nodes that have sockets of type '*' without
applying a patch to the code.
* Fix an overly aggressive assertion.
This could happen when attempting to evaluate `IS_CHANGED` for a node
during the creation of the cache (in order to create the cache key).
* Fix Pyright warnings
* Add execution model unit tests
* Fix issue with unused literals
Behavior should now match the master branch with regard to undeclared
inputs. Undeclared inputs that are socket connections will be used while
undeclared inputs that are literals will be ignored.
* Make custom VALIDATE_INPUTS skip normal validation
Additionally, if `VALIDATE_INPUTS` takes an argument named `input_types`,
that variable will be a dictionary of the socket type of all incoming
connections. If that argument exists, normal socket type validation will
not occur. This removes the last hurdle for enabling variant types
entirely from custom nodes, so I've removed that command-line option.
I've added appropriate unit tests for these changes.
* Fix example in unit test
This wouldn't have caused any issues in the unit test, but it would have
bugged the UI if someone copy+pasted it into their own node pack.
* Use fstrings instead of '%' formatting syntax
* Use custom exception types.
* Display an error for dependency cycles
Previously, dependency cycles that were created during node expansion
would cause the application to quit (due to an uncaught exception). Now,
we'll throw a proper error to the UI. We also make an attempt to 'blame'
the most relevant node in the UI.
* Add docs on when ExecutionBlocker should be used
* Remove unused functionality
* Rename ExecutionResult.SLEEPING to PENDING
* Remove superfluous function parameter
* Pass None for uneval inputs instead of default
This applies to `VALIDATE_INPUTS`, `check_lazy_status`, and lazy values
in evaluation functions.
* Add a test for mixed node expansion
This test ensures that a node that returns a combination of expanded
subgraphs and literal values functions correctly.
* Raise exception for bad get_node calls.
* Minor refactor of IsChangedCache.get
* Refactor `map_node_over_list` function
* Fix ui output for duplicated nodes
* Add documentation on `check_lazy_status`
* Add file for execution model unit tests
* Clean up Javascript code as per review
* Improve documentation
Converted some comments to docstrings as per review
* Add a new unit test for mixed lazy results
This test validates that when an output list is fed to a lazy node, the
node will properly evaluate previous nodes that are needed by any inputs
to the lazy node.
No code in the execution model has been changed. The test already
passes.
* Allow kwargs in VALIDATE_INPUTS functions
When kwargs are used, validation is skipped for all inputs as if they
had been mentioned explicitly.
* List cached nodes in `execution_cached` message
This was previously just bugged in this PR.
2024-08-15 15:21:11 +00:00
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return result
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#
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# Loop through these variables
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#
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@pytest.mark.execution
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class TestExecution:
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#
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# Initialize server and client
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#
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@fixture(scope="class", autouse=True, params=[
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# (use_lru, lru_size)
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(False, 0),
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(True, 0),
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(True, 100),
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])
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def _server(self, args_pytest, request):
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# Start server
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pargs = [
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'python','main.py',
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'--output-directory', args_pytest["output_dir"],
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'--listen', args_pytest["listen"],
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'--port', str(args_pytest["port"]),
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'--extra-model-paths-config', 'tests/inference/extra_model_paths.yaml',
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]
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use_lru, lru_size = request.param
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if use_lru:
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pargs += ['--cache-lru', str(lru_size)]
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print("Running server with args:", pargs)
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p = subprocess.Popen(pargs)
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yield
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p.kill()
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torch.cuda.empty_cache()
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def start_client(self, listen:str, port:int):
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# Start client
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comfy_client = ComfyClient()
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# Connect to server (with retries)
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n_tries = 5
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for i in range(n_tries):
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time.sleep(4)
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try:
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comfy_client.connect(listen=listen, port=port)
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except ConnectionRefusedError as e:
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print(e)
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print(f"({i+1}/{n_tries}) Retrying...")
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else:
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break
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return comfy_client
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@fixture(scope="class", autouse=True)
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def shared_client(self, args_pytest, _server):
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client = self.start_client(args_pytest["listen"], args_pytest["port"])
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yield client
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del client
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torch.cuda.empty_cache()
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@fixture
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def client(self, shared_client, request):
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shared_client.set_test_name(f"execution[{request.node.name}]")
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yield shared_client
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@fixture
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def builder(self, request):
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yield GraphBuilder(prefix=request.node.name)
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def test_lazy_input(self, client: ComfyClient, builder: GraphBuilder):
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g = builder
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input1 = g.node("StubImage", content="BLACK", height=512, width=512, batch_size=1)
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input2 = g.node("StubImage", content="WHITE", height=512, width=512, batch_size=1)
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mask = g.node("StubMask", value=0.0, height=512, width=512, batch_size=1)
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lazy_mix = g.node("TestLazyMixImages", image1=input1.out(0), image2=input2.out(0), mask=mask.out(0))
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output = g.node("SaveImage", images=lazy_mix.out(0))
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result = client.run(g)
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result_image = result.get_images(output)[0]
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assert numpy.array(result_image).any() == 0, "Image should be black"
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assert result.did_run(input1)
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assert not result.did_run(input2)
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assert result.did_run(mask)
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assert result.did_run(lazy_mix)
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def test_full_cache(self, client: ComfyClient, builder: GraphBuilder):
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g = builder
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input1 = g.node("StubImage", content="BLACK", height=512, width=512, batch_size=1)
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input2 = g.node("StubImage", content="NOISE", height=512, width=512, batch_size=1)
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mask = g.node("StubMask", value=0.5, height=512, width=512, batch_size=1)
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lazy_mix = g.node("TestLazyMixImages", image1=input1.out(0), image2=input2.out(0), mask=mask.out(0))
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g.node("SaveImage", images=lazy_mix.out(0))
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client.run(g)
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|
|
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"
|
|
|
|
|
2024-08-24 19:34:58 +00:00
|
|
|
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)
|
|
|
|
|
Execution Model Inversion (#2666)
* Execution Model Inversion
This PR inverts the execution model -- from recursively calling nodes to
using a topological sort of the nodes. This change allows for
modification of the node graph during execution. This allows for two
major advantages:
1. The implementation of lazy evaluation in nodes. For example, if a
"Mix Images" node has a mix factor of exactly 0.0, the second image
input doesn't even need to be evaluated (and visa-versa if the mix
factor is 1.0).
2. Dynamic expansion of nodes. This allows for the creation of dynamic
"node groups". Specifically, custom nodes can return subgraphs that
replace the original node in the graph. This is an incredibly
powerful concept. Using this functionality, it was easy to
implement:
a. Components (a.k.a. node groups)
b. Flow control (i.e. while loops) via tail recursion
c. All-in-one nodes that replicate the WebUI functionality
d. and more
All of those were able to be implemented entirely via custom nodes,
so those features are *not* a part of this PR. (There are some
front-end changes that should occur before that functionality is
made widely available, particularly around variant sockets.)
The custom nodes associated with this PR can be found at:
https://github.com/BadCafeCode/execution-inversion-demo-comfyui
Note that some of them require that variant socket types ("*") be
enabled.
* Allow `input_info` to be of type `None`
* Handle errors (like OOM) more gracefully
* Add a command-line argument to enable variants
This allows the use of nodes that have sockets of type '*' without
applying a patch to the code.
* Fix an overly aggressive assertion.
This could happen when attempting to evaluate `IS_CHANGED` for a node
during the creation of the cache (in order to create the cache key).
* Fix Pyright warnings
* Add execution model unit tests
* Fix issue with unused literals
Behavior should now match the master branch with regard to undeclared
inputs. Undeclared inputs that are socket connections will be used while
undeclared inputs that are literals will be ignored.
* Make custom VALIDATE_INPUTS skip normal validation
Additionally, if `VALIDATE_INPUTS` takes an argument named `input_types`,
that variable will be a dictionary of the socket type of all incoming
connections. If that argument exists, normal socket type validation will
not occur. This removes the last hurdle for enabling variant types
entirely from custom nodes, so I've removed that command-line option.
I've added appropriate unit tests for these changes.
* Fix example in unit test
This wouldn't have caused any issues in the unit test, but it would have
bugged the UI if someone copy+pasted it into their own node pack.
* Use fstrings instead of '%' formatting syntax
* Use custom exception types.
* Display an error for dependency cycles
Previously, dependency cycles that were created during node expansion
would cause the application to quit (due to an uncaught exception). Now,
we'll throw a proper error to the UI. We also make an attempt to 'blame'
the most relevant node in the UI.
* Add docs on when ExecutionBlocker should be used
* Remove unused functionality
* Rename ExecutionResult.SLEEPING to PENDING
* Remove superfluous function parameter
* Pass None for uneval inputs instead of default
This applies to `VALIDATE_INPUTS`, `check_lazy_status`, and lazy values
in evaluation functions.
* Add a test for mixed node expansion
This test ensures that a node that returns a combination of expanded
subgraphs and literal values functions correctly.
* Raise exception for bad get_node calls.
* Minor refactor of IsChangedCache.get
* Refactor `map_node_over_list` function
* Fix ui output for duplicated nodes
* Add documentation on `check_lazy_status`
* Add file for execution model unit tests
* Clean up Javascript code as per review
* Improve documentation
Converted some comments to docstrings as per review
* Add a new unit test for mixed lazy results
This test validates that when an output list is fed to a lazy node, the
node will properly evaluate previous nodes that are needed by any inputs
to the lazy node.
No code in the execution model has been changed. The test already
passes.
* Allow kwargs in VALIDATE_INPUTS functions
When kwargs are used, validation is skipped for all inputs as if they
had been mentioned explicitly.
* List cached nodes in `execution_cached` message
This was previously just bugged in this PR.
2024-08-15 15:21:11 +00:00
|
|
|
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"
|
|
|
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def test_mixed_lazy_results(self, client: ComfyClient, builder: GraphBuilder):
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g = builder
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val_list = g.node("TestMakeListNode", value1=0.0, value2=0.5, value3=1.0)
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mask = g.node("StubMask", value=val_list.out(0), height=512, width=512, batch_size=1)
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input1 = g.node("StubImage", content="BLACK", height=512, width=512, batch_size=1)
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input2 = g.node("StubImage", content="WHITE", height=512, width=512, batch_size=1)
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mix = g.node("TestLazyMixImages", image1=input1.out(0), image2=input2.out(0), mask=mask.out(0))
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rebatch = g.node("RebatchImages", images=mix.out(0), batch_size=3)
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output = g.node("SaveImage", images=rebatch.out(0))
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result = client.run(g)
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images = result.get_images(output)
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assert len(images) == 3, "Should have 3 image"
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assert numpy.array(images[0]).min() == 0 and numpy.array(images[0]).max() == 0, "First image should be 0.0"
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assert numpy.array(images[1]).min() == 127 and numpy.array(images[1]).max() == 127, "Second image should be 0.5"
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assert numpy.array(images[2]).min() == 255 and numpy.array(images[2]).max() == 255, "Third image should be 1.0"
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def test_output_reuse(self, client: ComfyClient, builder: GraphBuilder):
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g = builder
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input1 = g.node("StubImage", content="BLACK", height=512, width=512, batch_size=1)
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2024-08-24 19:34:58 +00:00
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output1 = g.node("SaveImage", images=input1.out(0))
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output2 = g.node("SaveImage", images=input1.out(0))
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Execution Model Inversion (#2666)
* Execution Model Inversion
This PR inverts the execution model -- from recursively calling nodes to
using a topological sort of the nodes. This change allows for
modification of the node graph during execution. This allows for two
major advantages:
1. The implementation of lazy evaluation in nodes. For example, if a
"Mix Images" node has a mix factor of exactly 0.0, the second image
input doesn't even need to be evaluated (and visa-versa if the mix
factor is 1.0).
2. Dynamic expansion of nodes. This allows for the creation of dynamic
"node groups". Specifically, custom nodes can return subgraphs that
replace the original node in the graph. This is an incredibly
powerful concept. Using this functionality, it was easy to
implement:
a. Components (a.k.a. node groups)
b. Flow control (i.e. while loops) via tail recursion
c. All-in-one nodes that replicate the WebUI functionality
d. and more
All of those were able to be implemented entirely via custom nodes,
so those features are *not* a part of this PR. (There are some
front-end changes that should occur before that functionality is
made widely available, particularly around variant sockets.)
The custom nodes associated with this PR can be found at:
https://github.com/BadCafeCode/execution-inversion-demo-comfyui
Note that some of them require that variant socket types ("*") be
enabled.
* Allow `input_info` to be of type `None`
* Handle errors (like OOM) more gracefully
* Add a command-line argument to enable variants
This allows the use of nodes that have sockets of type '*' without
applying a patch to the code.
* Fix an overly aggressive assertion.
This could happen when attempting to evaluate `IS_CHANGED` for a node
during the creation of the cache (in order to create the cache key).
* Fix Pyright warnings
* Add execution model unit tests
* Fix issue with unused literals
Behavior should now match the master branch with regard to undeclared
inputs. Undeclared inputs that are socket connections will be used while
undeclared inputs that are literals will be ignored.
* Make custom VALIDATE_INPUTS skip normal validation
Additionally, if `VALIDATE_INPUTS` takes an argument named `input_types`,
that variable will be a dictionary of the socket type of all incoming
connections. If that argument exists, normal socket type validation will
not occur. This removes the last hurdle for enabling variant types
entirely from custom nodes, so I've removed that command-line option.
I've added appropriate unit tests for these changes.
* Fix example in unit test
This wouldn't have caused any issues in the unit test, but it would have
bugged the UI if someone copy+pasted it into their own node pack.
* Use fstrings instead of '%' formatting syntax
* Use custom exception types.
* Display an error for dependency cycles
Previously, dependency cycles that were created during node expansion
would cause the application to quit (due to an uncaught exception). Now,
we'll throw a proper error to the UI. We also make an attempt to 'blame'
the most relevant node in the UI.
* Add docs on when ExecutionBlocker should be used
* Remove unused functionality
* Rename ExecutionResult.SLEEPING to PENDING
* Remove superfluous function parameter
* Pass None for uneval inputs instead of default
This applies to `VALIDATE_INPUTS`, `check_lazy_status`, and lazy values
in evaluation functions.
* Add a test for mixed node expansion
This test ensures that a node that returns a combination of expanded
subgraphs and literal values functions correctly.
* Raise exception for bad get_node calls.
* Minor refactor of IsChangedCache.get
* Refactor `map_node_over_list` function
* Fix ui output for duplicated nodes
* Add documentation on `check_lazy_status`
* Add file for execution model unit tests
* Clean up Javascript code as per review
* Improve documentation
Converted some comments to docstrings as per review
* Add a new unit test for mixed lazy results
This test validates that when an output list is fed to a lazy node, the
node will properly evaluate previous nodes that are needed by any inputs
to the lazy node.
No code in the execution model has been changed. The test already
passes.
* Allow kwargs in VALIDATE_INPUTS functions
When kwargs are used, validation is skipped for all inputs as if they
had been mentioned explicitly.
* List cached nodes in `execution_cached` message
This was previously just bugged in this PR.
2024-08-15 15:21:11 +00:00
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|
result = client.run(g)
|
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images1 = result.get_images(output1)
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images2 = result.get_images(output2)
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assert len(images1) == 1, "Should have 1 image"
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assert len(images2) == 1, "Should have 1 image"
|
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|
2024-08-22 03:38:46 +00:00
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|
# This tests that only constant outputs are used in the call to `IS_CHANGED`
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def test_is_changed_with_outputs(self, client: ComfyClient, builder: GraphBuilder):
|
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|
g = builder
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input1 = g.node("StubConstantImage", value=0.5, height=512, width=512, batch_size=1)
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|
test_node = g.node("TestIsChangedWithConstants", image=input1.out(0), value=0.5)
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|
|
output = g.node("PreviewImage", images=test_node.out(0))
|
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|
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|
|
result = client.run(g)
|
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|
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"
|
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|
assert not result.did_run(test_node), "The execution should have been cached"
|
2024-09-08 13:48:47 +00:00
|
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|
# This tests that nodes with OUTPUT_IS_LIST function correctly when they receive an ExecutionBlocker
|
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|
# as input. We also test that when that list (containing an ExecutionBlocker) is passed to a node,
|
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# only that one entry in the list is blocked.
|
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|
|
def test_execution_block_list_output(self, client: ComfyClient, builder: GraphBuilder):
|
|
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|
g = builder
|
|
|
|
image1 = g.node("StubImage", content="BLACK", height=512, width=512, batch_size=1)
|
|
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|
image2 = g.node("StubImage", content="WHITE", height=512, width=512, batch_size=1)
|
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|
|
image3 = g.node("StubImage", content="BLACK", height=512, width=512, batch_size=1)
|
|
|
|
image_list = g.node("TestMakeListNode", value1=image1.out(0), value2=image2.out(0), value3=image3.out(0))
|
|
|
|
int1 = g.node("StubInt", value=1)
|
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|
|
int2 = g.node("StubInt", value=2)
|
|
|
|
int3 = g.node("StubInt", value=3)
|
|
|
|
int_list = g.node("TestMakeListNode", value1=int1.out(0), value2=int2.out(0), value3=int3.out(0))
|
|
|
|
compare = g.node("TestIntConditions", a=int_list.out(0), b=2, operation="==")
|
|
|
|
blocker = g.node("TestExecutionBlocker", input=image_list.out(0), block=compare.out(0), verbose=False)
|
|
|
|
|
|
|
|
list_output = g.node("TestMakeListNode", value1=blocker.out(0))
|
|
|
|
output = g.node("PreviewImage", images=list_output.out(0))
|
|
|
|
|
|
|
|
result = client.run(g)
|
|
|
|
assert result.did_run(output), "The execution should have run"
|
|
|
|
images = result.get_images(output)
|
|
|
|
assert len(images) == 2, "Should have 2 images"
|
|
|
|
assert numpy.array(images[0]).min() == 0 and numpy.array(images[0]).max() == 0, "First image should be black"
|
|
|
|
assert numpy.array(images[1]).min() == 0 and numpy.array(images[1]).max() == 0, "Second image should also be black"
|