# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0


from typing import List

import torch


def left_pad_and_stack_1d(tensors: List[torch.Tensor]) -> torch.Tensor:
    """Left-pad variable-length 1D tensors with NaN and stack them into a batch."""
    if not tensors:
        raise ValueError("At least one tensor is required.")

    max_len = max(len(c) for c in tensors)
    padded = []
    for index, c in enumerate(tensors):
        if not isinstance(c, torch.Tensor):
            raise TypeError(f"Item {index} is not a torch.Tensor.")
        if c.ndim != 1:
            raise ValueError(f"Item {index} must be 1D; got shape {tuple(c.shape)}.")
        padding = torch.full(
            size=(max_len - len(c),),
            fill_value=torch.nan,
            dtype=c.dtype,
            device=c.device,
        )
        padded.append(torch.concat((padding, c), dim=-1))
    return torch.stack(padded)


left_pad_and_stack_1D = left_pad_and_stack_1d