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Weight gradient kernels for dense and MoE models (#95)

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* Init weight gradient kernels.

* Support unaligned n,k and gmem stride

* Update docs

* Several cleanups

* Remove restrictions on N

* Add stride(0) assertions

---------

Co-authored-by: Chenggang Zhao <chenggangz@deepseek.com>
This commit is contained in:
Zhean Xu
2025-05-14 14:47:58 +08:00
committed by GitHub
parent d75b218b7b
commit 04278f6dee
12 changed files with 911 additions and 72 deletions
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4
deep_gemm/jit_kernels/__init__.py
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@@ -3,6 +3,10 @@ from .m_grouped_gemm import (
m_grouped_gemm_fp8_fp8_bf16_nt_contiguous,
m_grouped_gemm_fp8_fp8_bf16_nt_masked
)
from .wgrad_gemm import (
wgrad_gemm_fp8_fp8_fp32_nt,
k_grouped_wgrad_gemm_fp8_fp8_fp32_nt
)
from .utils import (
ceil_div, set_num_sms, get_num_sms,
get_col_major_tma_aligned_tensor,