InvokeAI/invokeai/app/invocations/math.py
DekitaRPG c8b109f52e
Add 'Random Float' node <3 (#4581)
* Add 'Random Float' node <3

does what it says on the tin :)

* Add random float + random seeded float nodes

altered my random float node as requested by Millu, kept the seeded version as an alternate variant for those that would like to control the randomization seed :)

* Update math.py

* Update math.py

* feat(nodes): standardize fields to match other nodes

---------

Co-authored-by: Millun Atluri <Millu@users.noreply.github.com>
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
2023-09-26 05:57:44 +00:00

285 lines
9.9 KiB
Python

# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
from typing import Literal
import numpy as np
from pydantic import validator
from invokeai.app.invocations.primitives import FloatOutput, IntegerOutput
from .baseinvocation import BaseInvocation, FieldDescriptions, InputField, InvocationContext, invocation
@invocation("add", title="Add Integers", tags=["math", "add"], category="math", version="1.0.0")
class AddInvocation(BaseInvocation):
"""Adds two numbers"""
a: int = InputField(default=0, description=FieldDescriptions.num_1)
b: int = InputField(default=0, description=FieldDescriptions.num_2)
def invoke(self, context: InvocationContext) -> IntegerOutput:
return IntegerOutput(value=self.a + self.b)
@invocation("sub", title="Subtract Integers", tags=["math", "subtract"], category="math", version="1.0.0")
class SubtractInvocation(BaseInvocation):
"""Subtracts two numbers"""
a: int = InputField(default=0, description=FieldDescriptions.num_1)
b: int = InputField(default=0, description=FieldDescriptions.num_2)
def invoke(self, context: InvocationContext) -> IntegerOutput:
return IntegerOutput(value=self.a - self.b)
@invocation("mul", title="Multiply Integers", tags=["math", "multiply"], category="math", version="1.0.0")
class MultiplyInvocation(BaseInvocation):
"""Multiplies two numbers"""
a: int = InputField(default=0, description=FieldDescriptions.num_1)
b: int = InputField(default=0, description=FieldDescriptions.num_2)
def invoke(self, context: InvocationContext) -> IntegerOutput:
return IntegerOutput(value=self.a * self.b)
@invocation("div", title="Divide Integers", tags=["math", "divide"], category="math", version="1.0.0")
class DivideInvocation(BaseInvocation):
"""Divides two numbers"""
a: int = InputField(default=0, description=FieldDescriptions.num_1)
b: int = InputField(default=0, description=FieldDescriptions.num_2)
def invoke(self, context: InvocationContext) -> IntegerOutput:
return IntegerOutput(value=int(self.a / self.b))
@invocation(
"rand_int",
title="Random Integer",
tags=["math", "random"],
category="math",
version="1.0.0",
use_cache=False,
)
class RandomIntInvocation(BaseInvocation):
"""Outputs a single random integer."""
low: int = InputField(default=0, description=FieldDescriptions.inclusive_low)
high: int = InputField(default=np.iinfo(np.int32).max, description=FieldDescriptions.exclusive_high)
def invoke(self, context: InvocationContext) -> IntegerOutput:
return IntegerOutput(value=np.random.randint(self.low, self.high))
@invocation("rand_float", title="Random Float", tags=["math", "float", "random"], category="math", version="1.0.0")
class RandomFloatInvocation(BaseInvocation):
"""Outputs a single random float"""
low: float = InputField(default=0.0, description=FieldDescriptions.inclusive_low)
high: float = InputField(default=1.0, description=FieldDescriptions.exclusive_high)
decimals: int = InputField(default=2, description=FieldDescriptions.decimal_places)
def invoke(self, context: InvocationContext) -> FloatOutput:
random_float = np.random.uniform(self.low, self.high)
rounded_float = round(random_float, self.decimals)
return FloatOutput(value=rounded_float)
@invocation(
"float_to_int",
title="Float To Integer",
tags=["math", "round", "integer", "float", "convert"],
category="math",
version="1.0.0",
)
class FloatToIntegerInvocation(BaseInvocation):
"""Rounds a float number to (a multiple of) an integer."""
value: float = InputField(default=0, description="The value to round")
multiple: int = InputField(default=1, ge=1, title="Multiple of", description="The multiple to round to")
method: Literal["Nearest", "Floor", "Ceiling", "Truncate"] = InputField(
default="Nearest", description="The method to use for rounding"
)
def invoke(self, context: InvocationContext) -> IntegerOutput:
if self.method == "Nearest":
return IntegerOutput(value=round(self.value / self.multiple) * self.multiple)
elif self.method == "Floor":
return IntegerOutput(value=np.floor(self.value / self.multiple) * self.multiple)
elif self.method == "Ceiling":
return IntegerOutput(value=np.ceil(self.value / self.multiple) * self.multiple)
else: # self.method == "Truncate"
return IntegerOutput(value=int(self.value / self.multiple) * self.multiple)
@invocation("round_float", title="Round Float", tags=["math", "round"], category="math", version="1.0.0")
class RoundInvocation(BaseInvocation):
"""Rounds a float to a specified number of decimal places."""
value: float = InputField(default=0, description="The float value")
decimals: int = InputField(default=0, description="The number of decimal places")
def invoke(self, context: InvocationContext) -> FloatOutput:
return FloatOutput(value=round(self.value, self.decimals))
INTEGER_OPERATIONS = Literal[
"ADD",
"SUB",
"MUL",
"DIV",
"EXP",
"MOD",
"ABS",
"MIN",
"MAX",
]
INTEGER_OPERATIONS_LABELS = dict(
ADD="Add A+B",
SUB="Subtract A-B",
MUL="Multiply A*B",
DIV="Divide A/B",
EXP="Exponentiate A^B",
MOD="Modulus A%B",
ABS="Absolute Value of A",
MIN="Minimum(A,B)",
MAX="Maximum(A,B)",
)
@invocation(
"integer_math",
title="Integer Math",
tags=[
"math",
"integer",
"add",
"subtract",
"multiply",
"divide",
"modulus",
"power",
"absolute value",
"min",
"max",
],
category="math",
version="1.0.0",
)
class IntegerMathInvocation(BaseInvocation):
"""Performs integer math."""
operation: INTEGER_OPERATIONS = InputField(
default="ADD", description="The operation to perform", ui_choice_labels=INTEGER_OPERATIONS_LABELS
)
a: int = InputField(default=0, description=FieldDescriptions.num_1)
b: int = InputField(default=0, description=FieldDescriptions.num_2)
@validator("b")
def no_unrepresentable_results(cls, v, values):
if values["operation"] == "DIV" and v == 0:
raise ValueError("Cannot divide by zero")
elif values["operation"] == "MOD" and v == 0:
raise ValueError("Cannot divide by zero")
elif values["operation"] == "EXP" and v < 0:
raise ValueError("Result of exponentiation is not an integer")
return v
def invoke(self, context: InvocationContext) -> IntegerOutput:
# Python doesn't support switch statements until 3.10, but InvokeAI supports back to 3.9
if self.operation == "ADD":
return IntegerOutput(value=self.a + self.b)
elif self.operation == "SUB":
return IntegerOutput(value=self.a - self.b)
elif self.operation == "MUL":
return IntegerOutput(value=self.a * self.b)
elif self.operation == "DIV":
return IntegerOutput(value=int(self.a / self.b))
elif self.operation == "EXP":
return IntegerOutput(value=self.a**self.b)
elif self.operation == "MOD":
return IntegerOutput(value=self.a % self.b)
elif self.operation == "ABS":
return IntegerOutput(value=abs(self.a))
elif self.operation == "MIN":
return IntegerOutput(value=min(self.a, self.b))
else: # self.operation == "MAX":
return IntegerOutput(value=max(self.a, self.b))
FLOAT_OPERATIONS = Literal[
"ADD",
"SUB",
"MUL",
"DIV",
"EXP",
"ABS",
"SQRT",
"MIN",
"MAX",
]
FLOAT_OPERATIONS_LABELS = dict(
ADD="Add A+B",
SUB="Subtract A-B",
MUL="Multiply A*B",
DIV="Divide A/B",
EXP="Exponentiate A^B",
ABS="Absolute Value of A",
SQRT="Square Root of A",
MIN="Minimum(A,B)",
MAX="Maximum(A,B)",
)
@invocation(
"float_math",
title="Float Math",
tags=["math", "float", "add", "subtract", "multiply", "divide", "power", "root", "absolute value", "min", "max"],
category="math",
version="1.0.0",
)
class FloatMathInvocation(BaseInvocation):
"""Performs floating point math."""
operation: FLOAT_OPERATIONS = InputField(
default="ADD", description="The operation to perform", ui_choice_labels=FLOAT_OPERATIONS_LABELS
)
a: float = InputField(default=0, description=FieldDescriptions.num_1)
b: float = InputField(default=0, description=FieldDescriptions.num_2)
@validator("b")
def no_unrepresentable_results(cls, v, values):
if values["operation"] == "DIV" and v == 0:
raise ValueError("Cannot divide by zero")
elif values["operation"] == "EXP" and values["a"] == 0 and v < 0:
raise ValueError("Cannot raise zero to a negative power")
elif values["operation"] == "EXP" and type(values["a"] ** v) is complex:
raise ValueError("Root operation resulted in a complex number")
return v
def invoke(self, context: InvocationContext) -> FloatOutput:
# Python doesn't support switch statements until 3.10, but InvokeAI supports back to 3.9
if self.operation == "ADD":
return FloatOutput(value=self.a + self.b)
elif self.operation == "SUB":
return FloatOutput(value=self.a - self.b)
elif self.operation == "MUL":
return FloatOutput(value=self.a * self.b)
elif self.operation == "DIV":
return FloatOutput(value=self.a / self.b)
elif self.operation == "EXP":
return FloatOutput(value=self.a**self.b)
elif self.operation == "SQRT":
return FloatOutput(value=np.sqrt(self.a))
elif self.operation == "ABS":
return FloatOutput(value=abs(self.a))
elif self.operation == "MIN":
return FloatOutput(value=min(self.a, self.b))
else: # self.operation == "MAX":
return FloatOutput(value=max(self.a, self.b))