import torch
import helion
import helion.language as hl

@helion.kernel
def invalid_broadcast_kernel(x: torch.Tensor) -> torch.Tensor:
    M, N = x.shape
    out = torch.zeros_like(x)
    for row_tile, col_tile in hl.tile([M, N]):
        row_idx = row_tile.index  # shape [tile0]
        col_idx = col_tile.index  # shape [tile1]
        # Create 2D grid of differences
        diff = row_idx[:, None] - col_idx  # shape [tile0, tile1]
        # BUG: row_idx has shape [tile0], diff has shape [tile0, tile1]
        # PyTorch right-aligns: [tile0] -> [1, tile0]
        # Then broadcasts [1, tile0] with [tile0, tile1], which incorrectly
        # aligns tile0 dimension with tile1 dimension
        result = (row_idx > 0) & (diff >= 0)
        out[row_tile, col_tile] = result.float()
    return out

x = torch.randn(64, 64, device="cuda")
invalid_broadcast_kernel(x)