mirror of
https://github.com/invoke-ai/InvokeAI
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71 lines
2.1 KiB
Python
71 lines
2.1 KiB
Python
# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
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from typing import Literal, Optional
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import numpy as np
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from pydantic import Field, validator
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from invokeai.app.util.misc import SEED_MAX, get_random_seed
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from .baseinvocation import (
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BaseInvocation,
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InvocationContext,
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BaseInvocationOutput,
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)
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class IntCollectionOutput(BaseInvocationOutput):
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"""A collection of integers"""
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type: Literal["int_collection"] = "int_collection"
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# Outputs
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collection: list[int] = Field(default=[], description="The int collection")
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class RangeInvocation(BaseInvocation):
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"""Creates a range"""
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type: Literal["range"] = "range"
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# Inputs
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start: int = Field(default=0, description="The start of the range")
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stop: int = Field(default=10, description="The stop of the range")
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step: int = Field(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) -> IntCollectionOutput:
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return IntCollectionOutput(
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collection=list(range(self.start, self.stop, self.step))
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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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type: Literal["random_range"] = "random_range"
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# Inputs
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low: int = Field(default=0, description="The inclusive low value")
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high: int = Field(
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default=np.iinfo(np.int32).max, description="The exclusive high value"
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)
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size: int = Field(default=1, description="The number of values to generate")
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seed: int = Field(
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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) -> IntCollectionOutput:
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rng = np.random.default_rng(self.seed)
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return IntCollectionOutput(
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collection=list(rng.integers(low=self.low, high=self.high, size=self.size))
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)
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