InvokeAI/tests/test_graph_execution_state.py
2024-03-26 09:18:46 +11:00

225 lines
7.9 KiB
Python

from typing import Optional
from unittest.mock import Mock
import pytest
# This import must happen before other invoke imports or test in other files(!!) break
from .test_nodes import ( # isort: split
PromptCollectionTestInvocation,
PromptTestInvocation,
TextToImageTestInvocation,
)
from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, InvocationContext
from invokeai.app.invocations.collections import RangeInvocation
from invokeai.app.invocations.math import AddInvocation, MultiplyInvocation
from invokeai.app.services.shared.graph import (
CollectInvocation,
Graph,
GraphExecutionState,
IterateInvocation,
)
from .test_nodes import create_edge
@pytest.fixture
def simple_graph() -> Graph:
g = Graph()
g.add_node(PromptTestInvocation(id="1", prompt="Banana sushi"))
g.add_node(TextToImageTestInvocation(id="2"))
g.add_edge(create_edge("1", "prompt", "2", "prompt"))
return g
def invoke_next(g: GraphExecutionState) -> tuple[Optional[BaseInvocation], Optional[BaseInvocationOutput]]:
n = g.next()
if n is None:
return (None, None)
print(f"invoking {n.id}: {type(n)}")
o = n.invoke(Mock(InvocationContext))
g.complete(n.id, o)
return (n, o)
def test_graph_state_executes_in_order(simple_graph: Graph):
g = GraphExecutionState(graph=simple_graph)
n1 = invoke_next(g)
n2 = invoke_next(g)
n3 = g.next()
assert g.prepared_source_mapping[n1[0].id] == "1"
assert g.prepared_source_mapping[n2[0].id] == "2"
assert n3 is None
assert g.results[n1[0].id].prompt == n1[0].prompt
assert n2[0].prompt == n1[0].prompt
def test_graph_is_complete(simple_graph: Graph):
g = GraphExecutionState(graph=simple_graph)
_ = invoke_next(g)
_ = invoke_next(g)
_ = g.next()
assert g.is_complete()
def test_graph_is_not_complete(simple_graph: Graph):
g = GraphExecutionState(graph=simple_graph)
_ = invoke_next(g)
_ = g.next()
assert not g.is_complete()
# TODO: test completion with iterators/subgraphs
def test_graph_state_expands_iterator():
graph = Graph()
graph.add_node(RangeInvocation(id="0", start=0, stop=3, step=1))
graph.add_node(IterateInvocation(id="1"))
graph.add_node(MultiplyInvocation(id="2", b=10))
graph.add_node(AddInvocation(id="3", b=1))
graph.add_edge(create_edge("0", "collection", "1", "collection"))
graph.add_edge(create_edge("1", "item", "2", "a"))
graph.add_edge(create_edge("2", "value", "3", "a"))
g = GraphExecutionState(graph=graph)
while not g.is_complete():
invoke_next(g)
prepared_add_nodes = g.source_prepared_mapping["3"]
results = {g.results[n].value for n in prepared_add_nodes}
expected = {1, 11, 21}
assert results == expected
def test_graph_state_collects():
graph = Graph()
test_prompts = ["Banana sushi", "Cat sushi"]
graph.add_node(PromptCollectionTestInvocation(id="1", collection=list(test_prompts)))
graph.add_node(IterateInvocation(id="2"))
graph.add_node(PromptTestInvocation(id="3"))
graph.add_node(CollectInvocation(id="4"))
graph.add_edge(create_edge("1", "collection", "2", "collection"))
graph.add_edge(create_edge("2", "item", "3", "prompt"))
graph.add_edge(create_edge("3", "prompt", "4", "item"))
g = GraphExecutionState(graph=graph)
_ = invoke_next(g)
_ = invoke_next(g)
_ = invoke_next(g)
_ = invoke_next(g)
_ = invoke_next(g)
n6 = invoke_next(g)
assert isinstance(n6[0], CollectInvocation)
assert sorted(g.results[n6[0].id].collection) == sorted(test_prompts)
def test_graph_state_prepares_eagerly():
"""Tests that all prepareable nodes are prepared"""
graph = Graph()
test_prompts = ["Banana sushi", "Cat sushi"]
graph.add_node(PromptCollectionTestInvocation(id="prompt_collection", collection=list(test_prompts)))
graph.add_node(IterateInvocation(id="iterate"))
graph.add_node(PromptTestInvocation(id="prompt_iterated"))
graph.add_edge(create_edge("prompt_collection", "collection", "iterate", "collection"))
graph.add_edge(create_edge("iterate", "item", "prompt_iterated", "prompt"))
# separated, fully-preparable chain of nodes
graph.add_node(PromptTestInvocation(id="prompt_chain_1", prompt="Dinosaur sushi"))
graph.add_node(PromptTestInvocation(id="prompt_chain_2"))
graph.add_node(PromptTestInvocation(id="prompt_chain_3"))
graph.add_edge(create_edge("prompt_chain_1", "prompt", "prompt_chain_2", "prompt"))
graph.add_edge(create_edge("prompt_chain_2", "prompt", "prompt_chain_3", "prompt"))
g = GraphExecutionState(graph=graph)
g.next()
assert "prompt_collection" in g.source_prepared_mapping
assert "prompt_chain_1" in g.source_prepared_mapping
assert "prompt_chain_2" in g.source_prepared_mapping
assert "prompt_chain_3" in g.source_prepared_mapping
assert "iterate" not in g.source_prepared_mapping
assert "prompt_iterated" not in g.source_prepared_mapping
def test_graph_executes_depth_first():
"""Tests that the graph executes depth-first, executing a branch as far as possible before moving to the next branch"""
graph = Graph()
test_prompts = ["Banana sushi", "Cat sushi"]
graph.add_node(PromptCollectionTestInvocation(id="prompt_collection", collection=list(test_prompts)))
graph.add_node(IterateInvocation(id="iterate"))
graph.add_node(PromptTestInvocation(id="prompt_iterated"))
graph.add_node(PromptTestInvocation(id="prompt_successor"))
graph.add_edge(create_edge("prompt_collection", "collection", "iterate", "collection"))
graph.add_edge(create_edge("iterate", "item", "prompt_iterated", "prompt"))
graph.add_edge(create_edge("prompt_iterated", "prompt", "prompt_successor", "prompt"))
g = GraphExecutionState(graph=graph)
_ = invoke_next(g)
_ = invoke_next(g)
_ = invoke_next(g)
_ = invoke_next(g)
# Because ordering is not guaranteed, we cannot compare results directly.
# Instead, we must count the number of results.
def get_completed_count(g: GraphExecutionState, id: str):
ids = list(g.source_prepared_mapping[id])
completed_ids = [i for i in g.executed if i in ids]
return len(completed_ids)
# Check at each step that the number of executed nodes matches the expectation for depth-first execution
assert get_completed_count(g, "prompt_iterated") == 1
assert get_completed_count(g, "prompt_successor") == 0
_ = invoke_next(g)
assert get_completed_count(g, "prompt_iterated") == 1
assert get_completed_count(g, "prompt_successor") == 1
_ = invoke_next(g)
assert get_completed_count(g, "prompt_iterated") == 2
assert get_completed_count(g, "prompt_successor") == 1
_ = invoke_next(g)
assert get_completed_count(g, "prompt_iterated") == 2
assert get_completed_count(g, "prompt_successor") == 2
# Because this tests deterministic ordering, we run it multiple times
@pytest.mark.parametrize("execution_number", range(5))
def test_graph_iterate_execution_order(execution_number: int):
"""Tests that iterate nodes execution is ordered by the order of the collection"""
graph = Graph()
test_prompts = ["Banana sushi", "Cat sushi", "Strawberry Sushi", "Dinosaur Sushi"]
graph.add_node(PromptCollectionTestInvocation(id="prompt_collection", collection=list(test_prompts)))
graph.add_node(IterateInvocation(id="iterate"))
graph.add_node(PromptTestInvocation(id="prompt_iterated"))
graph.add_edge(create_edge("prompt_collection", "collection", "iterate", "collection"))
graph.add_edge(create_edge("iterate", "item", "prompt_iterated", "prompt"))
g = GraphExecutionState(graph=graph)
_ = invoke_next(g)
_ = invoke_next(g)
assert _[1].item == "Banana sushi"
_ = invoke_next(g)
assert _[1].item == "Cat sushi"
_ = invoke_next(g)
assert _[1].item == "Strawberry Sushi"
_ = invoke_next(g)
assert _[1].item == "Dinosaur Sushi"
_ = invoke_next(g)