43 lines
1.2 KiB
Python
43 lines
1.2 KiB
Python
from typing import Any, Dict
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import torch
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class PtStack:
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"""
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Creates a new axis and stacks two PyTorch tensors along the new axis.
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category: PyTorch wrapper - Transform
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"""
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@classmethod
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def INPUT_TYPES(cls) -> Dict[str, Any]:
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"""
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Defines the required input types.
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Returns:
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Dict[str, Any]: A dictionary of required input types.
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"""
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return {
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"required": {
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"tens_a": ("TENSOR", {}),
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"tens_b": ("TENSOR", {}),
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"dim": ("INT", {"default":1, "min":-10, "max":10})
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}
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}
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RETURN_TYPES: tuple = ("TENSOR",)
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FUNCTION: str = "f"
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CATEGORY: str = "Data Analysis"
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def f(self, tens_a: torch.Tensor, tens_b: torch.Tensor, dim: int) -> tuple:
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"""
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Stacks two PyTorch tensors and create a new axis.
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Args:
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tens_a (torch.Tensor): A PyTorch tensor of any shape.
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tens_b (torch.Tensor): A PyTorch tensor of shape that supports concatenation with `tens_a`.
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dim (int): An axis to stack on.
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Returns:
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tuple: A tuple containing the resultant tensor.
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"""
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return (torch.stack([tens_a, tens_b], dim=dim),)
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