InvokeAI/invokeai/app/invocations/collections.py
2023-05-11 11:55:51 +10:00

65 lines
1.9 KiB
Python

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