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Merge pull request #63 from fzyzcjy/patch-2

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Super tiny fix typo
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Liang 2025-03-14 10:27:48 +08:00 committed by GitHub
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deep_gemm/jit_kernels/m_grouped_gemm.py
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@ -51,7 +51,7 @@ def m_grouped_gemm_fp8_fp8_bf16_nt_contiguous(lhs: Tuple[torch.Tensor, torch.Ten
the second element is an FP32 128x128 scaling tensor for RHS of shape `[num_groups, ⌈n / 128⌉, ⌈k / 128⌉]`. the second element is an FP32 128x128 scaling tensor for RHS of shape `[num_groups, ⌈n / 128⌉, ⌈k / 128⌉]`.
out: the BF16 output tensor of shape `[m_sum, n]`, representing the result. out: the BF16 output tensor of shape `[m_sum, n]`, representing the result.
m_indices: a tensor of shape `[m_sum]` with type `torch.int`. m_indices: a tensor of shape `[m_sum]` with type `torch.int`.
`m_indices[i]` records the group which the j-th row of the LHS belong to, `m_indices[i]` records the group which the i-th row of the LHS belong to,
which means that the i-th row of the LHS matrix will be multiplied with `rhs[m_indices[i]]`. which means that the i-th row of the LHS matrix will be multiplied with `rhs[m_indices[i]]`.
Values of `m_indices` in every-m-alignment-block must also be the same. Values of `m_indices` in every-m-alignment-block must also be the same.
""" """