# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654) and the InvokeAI Team import numpy as np from pydantic import validator from invokeai.app.invocations.primitives import IntegerCollectionOutput from invokeai.app.util.misc import SEED_MAX, get_random_seed from .baseinvocation import BaseInvocation, InputField, InvocationContext, invocation @invocation("range", title="Integer Range", tags=["collection", "integer", "range"], category="collections") class RangeInvocation(BaseInvocation): """Creates a range of numbers from start to stop with step""" start: int = InputField(default=0, description="The start of the range") stop: int = InputField(default=10, description="The stop of the range") step: int = InputField(default=1, description="The step of the range") @validator("stop") def stop_gt_start(cls, v, values): if "start" in values and v <= values["start"]: raise ValueError("stop must be greater than start") return v def invoke(self, context: InvocationContext) -> IntegerCollectionOutput: return IntegerCollectionOutput(collection=list(range(self.start, self.stop, self.step))) @invocation( "range_of_size", title="Integer Range of Size", tags=["collection", "integer", "size", "range"], category="collections", ) class RangeOfSizeInvocation(BaseInvocation): """Creates a range from start to start + size with step""" start: int = InputField(default=0, description="The start of the range") size: int = InputField(default=1, description="The number of values") step: int = InputField(default=1, description="The step of the range") def invoke(self, context: InvocationContext) -> IntegerCollectionOutput: return IntegerCollectionOutput(collection=list(range(self.start, self.start + self.size, self.step))) @invocation( "random_range", title="Random Range", tags=["range", "integer", "random", "collection"], category="collections", ) class RandomRangeInvocation(BaseInvocation): """Creates a collection of random numbers""" low: int = InputField(default=0, description="The inclusive low value") high: int = InputField(default=np.iinfo(np.int32).max, description="The exclusive high value") size: int = InputField(default=1, description="The number of values to generate") seed: int = InputField( ge=0, le=SEED_MAX, description="The seed for the RNG (omit for random)", default_factory=get_random_seed, ) def invoke(self, context: InvocationContext) -> IntegerCollectionOutput: rng = np.random.default_rng(self.seed) return IntegerCollectionOutput(collection=list(rng.integers(low=self.low, high=self.high, size=self.size)))