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HowToSD-ComfyUI-Data-Analysis/modules/pytorch_wrapper/pt_mm.py
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1.2 KiB
Python

from typing import Any, Dict
import torch
class PtMm:
"""
Performs 2D matrix multiplication on two PyTorch tensors.
category: PyTorch wrapper - Matrix operations
"""
@classmethod
def INPUT_TYPES(cls) -> Dict[str, Any]:
"""
Defines the required input types.
Returns:
Dict[str, Any]: A dictionary of required input types.
"""
return {
"required": {
"tens_a": ("TENSOR", {}),
"tens_b": ("TENSOR", {})
}
}
RETURN_TYPES: tuple = ("TENSOR",)
FUNCTION: str = "f"
CATEGORY: str = "Data Analysis"
def f(self, tens_a: torch.Tensor, tens_b: torch.Tensor) -> tuple:
"""
Performs 2D matrix multiplication on two PyTorch tensors.
Args:
tens_a (torch.Tensor): A 2D PyTorch tensor.
tens_b (torch.Tensor): A 2D PyTorch tensor that supports matrix multiplication with `tens_a`.
Returns:
tuple: A tuple containing the resultant tensor.
"""
if tens_a.dim() != 2 or tens_b.dim() != 2:
raise ValueError("torch.mm() only supports 2D tensors.")
return (torch.mm(tens_a, tens_b),)