from __future__ import annotations

import torch

try:
    import triton
    import triton.language as tl
except ImportError:  # pragma: no cover - depends on local environment
    triton = None
    tl = None


TRITON_AVAILABLE = triton is not None


if TRITON_AVAILABLE:

    @triton.jit
    def row_softmax_kernel(
        x_ptr,
        out_ptr,
        num_cols,
        stride_x_row,
        stride_out_row,
        block_size: tl.constexpr,
    ):
        row_idx = tl.program_id(axis=0)
        col_offsets = tl.arange(0, block_size)
        # TODO(student): convert row_idx and col_offsets into pointers for this row.
        # TODO(student): load a row with masking.
        # TODO(student): subtract the row max for stability.
        # TODO(student): exponentiate, sum, and normalize.
        # TODO(student): store the normalized row.
        pass


def triton_row_softmax(x: torch.Tensor, block_size: int = 128) -> torch.Tensor:
    if not TRITON_AVAILABLE:
        raise RuntimeError("Triton is not installed in this environment.")
    if x.ndim != 2:
        raise ValueError(f"expected 2D input, got {tuple(x.shape)}")
    if not x.is_cuda:
        raise ValueError("Triton kernels in this lab expect CUDA tensors.")
    raise NotImplementedError("TODO(student): implement row-wise softmax launch logic.")