ComfyUI/comfy/graph_utils.py
guill 5cfe38f41c
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 11:21:11 -04:00

140 lines
4.4 KiB
Python

def is_link(obj):
if not isinstance(obj, list):
return False
if len(obj) != 2:
return False
if not isinstance(obj[0], str):
return False
if not isinstance(obj[1], int) and not isinstance(obj[1], float):
return False
return True
# The GraphBuilder is just a utility class that outputs graphs in the form expected by the ComfyUI back-end
class GraphBuilder:
_default_prefix_root = ""
_default_prefix_call_index = 0
_default_prefix_graph_index = 0
def __init__(self, prefix = None):
if prefix is None:
self.prefix = GraphBuilder.alloc_prefix()
else:
self.prefix = prefix
self.nodes = {}
self.id_gen = 1
@classmethod
def set_default_prefix(cls, prefix_root, call_index, graph_index = 0):
cls._default_prefix_root = prefix_root
cls._default_prefix_call_index = call_index
cls._default_prefix_graph_index = graph_index
@classmethod
def alloc_prefix(cls, root=None, call_index=None, graph_index=None):
if root is None:
root = GraphBuilder._default_prefix_root
if call_index is None:
call_index = GraphBuilder._default_prefix_call_index
if graph_index is None:
graph_index = GraphBuilder._default_prefix_graph_index
result = f"{root}.{call_index}.{graph_index}."
GraphBuilder._default_prefix_graph_index += 1
return result
def node(self, class_type, id=None, **kwargs):
if id is None:
id = str(self.id_gen)
self.id_gen += 1
id = self.prefix + id
if id in self.nodes:
return self.nodes[id]
node = Node(id, class_type, kwargs)
self.nodes[id] = node
return node
def lookup_node(self, id):
id = self.prefix + id
return self.nodes.get(id)
def finalize(self):
output = {}
for node_id, node in self.nodes.items():
output[node_id] = node.serialize()
return output
def replace_node_output(self, node_id, index, new_value):
node_id = self.prefix + node_id
to_remove = []
for node in self.nodes.values():
for key, value in node.inputs.items():
if is_link(value) and value[0] == node_id and value[1] == index:
if new_value is None:
to_remove.append((node, key))
else:
node.inputs[key] = new_value
for node, key in to_remove:
del node.inputs[key]
def remove_node(self, id):
id = self.prefix + id
del self.nodes[id]
class Node:
def __init__(self, id, class_type, inputs):
self.id = id
self.class_type = class_type
self.inputs = inputs
self.override_display_id = None
def out(self, index):
return [self.id, index]
def set_input(self, key, value):
if value is None:
if key in self.inputs:
del self.inputs[key]
else:
self.inputs[key] = value
def get_input(self, key):
return self.inputs.get(key)
def set_override_display_id(self, override_display_id):
self.override_display_id = override_display_id
def serialize(self):
serialized = {
"class_type": self.class_type,
"inputs": self.inputs
}
if self.override_display_id is not None:
serialized["override_display_id"] = self.override_display_id
return serialized
def add_graph_prefix(graph, outputs, prefix):
# Change the node IDs and any internal links
new_graph = {}
for node_id, node_info in graph.items():
# Make sure the added nodes have unique IDs
new_node_id = prefix + node_id
new_node = { "class_type": node_info["class_type"], "inputs": {} }
for input_name, input_value in node_info.get("inputs", {}).items():
if is_link(input_value):
new_node["inputs"][input_name] = [prefix + input_value[0], input_value[1]]
else:
new_node["inputs"][input_name] = input_value
new_graph[new_node_id] = new_node
# Change the node IDs in the outputs
new_outputs = []
for n in range(len(outputs)):
output = outputs[n]
if is_link(output):
new_outputs.append([prefix + output[0], output[1]])
else:
new_outputs.append(output)
return new_graph, tuple(new_outputs)