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The `@invocation` decorator is extended with an optional `version` arg. On execution of the decorator, the version string is parsed using the `semver` package (this was an indirect dependency and has been added to `pyproject.toml`). All built-in nodes are set with `version="1.0.0"`. The version is added to the OpenAPI Schema for consumption by the client.
74 lines
2.8 KiB
Python
74 lines
2.8 KiB
Python
# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654) and the InvokeAI Team
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import numpy as np
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from pydantic import validator
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from invokeai.app.invocations.primitives import IntegerCollectionOutput
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from invokeai.app.util.misc import SEED_MAX, get_random_seed
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from .baseinvocation import BaseInvocation, InputField, InvocationContext, invocation
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@invocation(
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"range", title="Integer Range", tags=["collection", "integer", "range"], category="collections", version="1.0.0"
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)
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class RangeInvocation(BaseInvocation):
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"""Creates a range of numbers from start to stop with step"""
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start: int = InputField(default=0, description="The start of the range")
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stop: int = InputField(default=10, description="The stop of the range")
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step: int = InputField(default=1, description="The step of the range")
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@validator("stop")
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def stop_gt_start(cls, v, values):
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if "start" in values and v <= values["start"]:
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raise ValueError("stop must be greater than start")
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return v
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def invoke(self, context: InvocationContext) -> IntegerCollectionOutput:
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return IntegerCollectionOutput(collection=list(range(self.start, self.stop, self.step)))
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@invocation(
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"range_of_size",
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title="Integer Range of Size",
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tags=["collection", "integer", "size", "range"],
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category="collections",
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version="1.0.0",
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)
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class RangeOfSizeInvocation(BaseInvocation):
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"""Creates a range from start to start + size with step"""
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start: int = InputField(default=0, description="The start of the range")
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size: int = InputField(default=1, description="The number of values")
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step: int = InputField(default=1, description="The step of the range")
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def invoke(self, context: InvocationContext) -> IntegerCollectionOutput:
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return IntegerCollectionOutput(collection=list(range(self.start, self.start + self.size, self.step)))
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@invocation(
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"random_range",
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title="Random Range",
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tags=["range", "integer", "random", "collection"],
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category="collections",
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version="1.0.0",
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)
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class RandomRangeInvocation(BaseInvocation):
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"""Creates a collection of random numbers"""
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low: int = InputField(default=0, description="The inclusive low value")
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high: int = InputField(default=np.iinfo(np.int32).max, description="The exclusive high value")
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size: int = InputField(default=1, description="The number of values to generate")
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seed: int = InputField(
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ge=0,
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le=SEED_MAX,
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description="The seed for the RNG (omit for random)",
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default_factory=get_random_seed,
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)
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def invoke(self, context: InvocationContext) -> IntegerCollectionOutput:
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rng = np.random.default_rng(self.seed)
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return IntegerCollectionOutput(collection=list(rng.integers(low=self.low, high=self.high, size=self.size)))
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