ComfyUI/comfy/graph.py

import nodes

from comfy.graph_utils import is_link

class DependencyCycleError(Exception):
    pass

class NodeInputError(Exception):
    pass

class NodeNotFoundError(Exception):
    pass

class DynamicPrompt:
    def __init__(self, original_prompt):
        # The original prompt provided by the user
        self.original_prompt = original_prompt
        # Any extra pieces of the graph created during execution
        self.ephemeral_prompt = {}
        self.ephemeral_parents = {}
        self.ephemeral_display = {}

    def get_node(self, node_id):
        if node_id in self.ephemeral_prompt:
            return self.ephemeral_prompt[node_id]
        if node_id in self.original_prompt:
            return self.original_prompt[node_id]
        raise NodeNotFoundError(f"Node {node_id} not found")

    def has_node(self, node_id):
        return node_id in self.original_prompt or node_id in self.ephemeral_prompt

    def add_ephemeral_node(self, node_id, node_info, parent_id, display_id):
        self.ephemeral_prompt[node_id] = node_info
        self.ephemeral_parents[node_id] = parent_id
        self.ephemeral_display[node_id] = display_id

    def get_real_node_id(self, node_id):
        while node_id in self.ephemeral_parents:
            node_id = self.ephemeral_parents[node_id]
        return node_id

    def get_parent_node_id(self, node_id):
        return self.ephemeral_parents.get(node_id, None)

    def get_display_node_id(self, node_id):
        while node_id in self.ephemeral_display:
            node_id = self.ephemeral_display[node_id]
        return node_id

    def all_node_ids(self):
        return set(self.original_prompt.keys()).union(set(self.ephemeral_prompt.keys()))

    def get_original_prompt(self):
        return self.original_prompt

def get_input_info(class_def, input_name):
    valid_inputs = class_def.INPUT_TYPES()
    input_info = None
    input_category = None
    if "required" in valid_inputs and input_name in valid_inputs["required"]:
        input_category = "required"
        input_info = valid_inputs["required"][input_name]
    elif "optional" in valid_inputs and input_name in valid_inputs["optional"]:
        input_category = "optional"
        input_info = valid_inputs["optional"][input_name]
    elif "hidden" in valid_inputs and input_name in valid_inputs["hidden"]:
        input_category = "hidden"
        input_info = valid_inputs["hidden"][input_name]
    if input_info is None:
        return None, None, None
    input_type = input_info[0]
    if len(input_info) > 1:
        extra_info = input_info[1]
    else:
        extra_info = {}
    return input_type, input_category, extra_info

class TopologicalSort:
    def __init__(self, dynprompt):
        self.dynprompt = dynprompt
        self.pendingNodes = {}
        self.blockCount = {} # Number of nodes this node is directly blocked by
        self.blocking = {} # Which nodes are blocked by this node

    def get_input_info(self, unique_id, input_name):
        class_type = self.dynprompt.get_node(unique_id)["class_type"]
        class_def = nodes.NODE_CLASS_MAPPINGS[class_type]
        return get_input_info(class_def, input_name)

    def make_input_strong_link(self, to_node_id, to_input):
        inputs = self.dynprompt.get_node(to_node_id)["inputs"]
        if to_input not in inputs:
            raise NodeInputError(f"Node {to_node_id} says it needs input {to_input}, but there is no input to that node at all")
        value = inputs[to_input]
        if not is_link(value):
            raise NodeInputError(f"Node {to_node_id} says it needs input {to_input}, but that value is a constant")
        from_node_id, from_socket = value
        self.add_strong_link(from_node_id, from_socket, to_node_id)

    def add_strong_link(self, from_node_id, from_socket, to_node_id):
        self.add_node(from_node_id)
        if to_node_id not in self.blocking[from_node_id]:
            self.blocking[from_node_id][to_node_id] = {}
            self.blockCount[to_node_id] += 1
        self.blocking[from_node_id][to_node_id][from_socket] = True

    def add_node(self, unique_id, include_lazy=False, subgraph_nodes=None):
        if unique_id in self.pendingNodes:
            return
        self.pendingNodes[unique_id] = True
        self.blockCount[unique_id] = 0
        self.blocking[unique_id] = {}

        inputs = self.dynprompt.get_node(unique_id)["inputs"]
        for input_name in inputs:
            value = inputs[input_name]
            if is_link(value):
                from_node_id, from_socket = value
                if subgraph_nodes is not None and from_node_id not in subgraph_nodes:
                    continue
                input_type, input_category, input_info = self.get_input_info(unique_id, input_name)
                is_lazy = input_info is not None and "lazy" in input_info and input_info["lazy"]
                if include_lazy or not is_lazy:
                    self.add_strong_link(from_node_id, from_socket, unique_id)

    def get_ready_nodes(self):
        return [node_id for node_id in self.pendingNodes if self.blockCount[node_id] == 0]

    def pop_node(self, unique_id):
        del self.pendingNodes[unique_id]
        for blocked_node_id in self.blocking[unique_id]:
            self.blockCount[blocked_node_id] -= 1
        del self.blocking[unique_id]

    def is_empty(self):
        return len(self.pendingNodes) == 0

# ExecutionList implements a topological dissolve of the graph. After a node is staged for execution,
# it can still be returned to the graph after having further dependencies added.
class ExecutionList(TopologicalSort):
    def __init__(self, dynprompt, output_cache):
        super().__init__(dynprompt)
        self.output_cache = output_cache
        self.staged_node_id = None

    def add_strong_link(self, from_node_id, from_socket, to_node_id):
        if self.output_cache.get(from_node_id) is not None:
            # Nothing to do
            return
        super().add_strong_link(from_node_id, from_socket, to_node_id)

    def stage_node_execution(self):
        assert self.staged_node_id is None
        if self.is_empty():
            return None, None, None
        available = self.get_ready_nodes()
        if len(available) == 0:
            cycled_nodes = self.get_nodes_in_cycle()
            # Because cycles composed entirely of static nodes are caught during initial validation,
            # we will 'blame' the first node in the cycle that is not a static node.
            blamed_node = cycled_nodes[0]
            for node_id in cycled_nodes:
                display_node_id = self.dynprompt.get_display_node_id(node_id)
                if display_node_id != node_id:
                    blamed_node = display_node_id
                    break
            ex = DependencyCycleError("Dependency cycle detected")
            error_details = {
                "node_id": blamed_node,
                "exception_message": str(ex),
                "exception_type": "graph.DependencyCycleError",
                "traceback": [],
                "current_inputs": []
            }
            return None, error_details, ex
        next_node = available[0]
        # If an output node is available, do that first.
        # Technically this has no effect on the overall length of execution, but it feels better as a user
        # for a PreviewImage to display a result as soon as it can
        # Some other heuristics could probably be used here to improve the UX further.
        for node_id in available:
            class_type = self.dynprompt.get_node(node_id)["class_type"]
            class_def = nodes.NODE_CLASS_MAPPINGS[class_type]
            if hasattr(class_def, 'OUTPUT_NODE') and class_def.OUTPUT_NODE == True:
                next_node = node_id
                break
        self.staged_node_id = next_node
        return self.staged_node_id, None, None

    def unstage_node_execution(self):
        assert self.staged_node_id is not None
        self.staged_node_id = None

    def complete_node_execution(self):
        node_id = self.staged_node_id
        self.pop_node(node_id)
        self.staged_node_id = None

    def get_nodes_in_cycle(self):
        # We'll dissolve the graph in reverse topological order to leave only the nodes in the cycle.
        # We're skipping some of the performance optimizations from the original TopologicalSort to keep
        # the code simple (and because having a cycle in the first place is a catastrophic error)
        blocked_by = { node_id: {} for node_id in self.pendingNodes }
        for from_node_id in self.blocking:
            for to_node_id in self.blocking[from_node_id]:
                if True in self.blocking[from_node_id][to_node_id].values():
                    blocked_by[to_node_id][from_node_id] = True
        to_remove = [node_id for node_id in blocked_by if len(blocked_by[node_id]) == 0]
        while len(to_remove) > 0:
            for node_id in to_remove:
                for to_node_id in blocked_by:
                    if node_id in blocked_by[to_node_id]:
                        del blocked_by[to_node_id][node_id]
                del blocked_by[node_id]
            to_remove = [node_id for node_id in blocked_by if len(blocked_by[node_id]) == 0]
        return list(blocked_by.keys())

# Return this from a node and any users will be blocked with the given error message.
# If the message is None, execution will be blocked silently instead.
# Generally, you should avoid using this functionality unless absolutley necessary. Whenever it's
# possible, a lazy input will be more efficient and have a better user experience.
# This functionality is useful in two cases:
# 1. You want to conditionally prevent an output node from executing. (Particularly a built-in node
#    like SaveImage. For your own output nodes, I would recommend just adding a BOOL input and using
#    lazy evaluation to let it conditionally disable itself.)
# 2. You have a node with multiple possible outputs, some of which are invalid and should not be used.
#    (I would recommend not making nodes like this in the future -- instead, make multiple nodes with
#    different outputs. Unfortunately, there are several popular existing nodes using this pattern.)
class ExecutionBlocker:
    def __init__(self, message):
        self.message = message