# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654) and the InvokeAI Team import numpy as np from pydantic import ValidationInfo, field_validator from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation from invokeai.app.invocations.fields import InputField from invokeai.app.invocations.primitives import IntegerCollectionOutput from invokeai.app.services.shared.invocation_context import InvocationContext from invokeai.app.util.misc import SEED_MAX @invocation( "range", title="Integer Range", tags=["collection", "integer", "range"], category="collections", version="1.0.0" ) 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") @field_validator("stop") def stop_gt_start(cls, v: int, info: ValidationInfo): if "start" in info.data and v <= info.data["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", version="1.0.0", ) class RangeOfSizeInvocation(BaseInvocation): """Creates a range from start to start + (size * step) incremented by step""" start: int = InputField(default=0, description="The start of the range") size: int = InputField(default=1, gt=0, 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.step * self.size), self.step)) ) @invocation( "random_range", title="Random Range", tags=["range", "integer", "random", "collection"], category="collections", version="1.0.1", use_cache=False, ) 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( default=0, ge=0, le=SEED_MAX, description="The seed for the RNG (omit for random)", ) 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)))