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