[kernel slimming] Move fast_hadamard_transform to jit_kernel (#18475)

sgl-kernel/CMakeLists.txt

@@ -106,15 +106,6 @@ FetchContent_Declare(
 )
 FetchContent_Populate(repo-mscclpp)
 
-# fast-hadamard-transform
-FetchContent_Declare(
-    repo-fast-hadamard-transform
-    GIT_REPOSITORY https://github.com/sgl-project/fast-hadamard-transform.git
-    GIT_TAG 48f3c13764dc2ec662ade842a4696a90a137f1bc
-    GIT_SHALLOW OFF
-)
-FetchContent_Populate(repo-fast-hadamard-transform)
-
 # ccache option
 option(ENABLE_CCACHE "Whether to use ccache" ON)
 find_program(CCACHE_FOUND ccache)
@@ -343,9 +334,6 @@ set(SOURCES
     "${repo-flashinfer_SOURCE_DIR}/csrc/renorm.cu"
     "${repo-flashinfer_SOURCE_DIR}/csrc/sampling.cu"
 
-    "${repo-fast-hadamard-transform_SOURCE_DIR}/csrc/fast_hadamard_transform_cuda.cu"
-    "${repo-fast-hadamard-transform_SOURCE_DIR}/csrc/fast_hadamard_transform.cpp"
-
     "${repo-flash-attention_SOURCE_DIR}/csrc/flash_attn/src/flash_fwd_sparse_hdim128_bf16_causal_sm80.cu"
     "${repo-flash-attention_SOURCE_DIR}/csrc/flash_attn/src/flash_fwd_sparse_hdim128_bf16_sm80.cu"
     "${repo-flash-attention_SOURCE_DIR}/csrc/flash_attn/src/flash_fwd_sparse_hdim128_fp16_causal_sm80.cu"

sgl-kernel/csrc/common_extension.cc

@@ -591,24 +591,6 @@ TORCH_LIBRARY_FRAGMENT(sgl_kernel, m) {
       "es_sm100_mxfp8_blockscaled_grouped_quant(Tensor input, Tensor problem_sizes, Tensor expert_offsets, Tensor "
       "blockscale_offsets, Tensor quant_output, Tensor scale_factor) -> () ");
   m.impl("es_sm100_mxfp8_blockscaled_grouped_quant", &es_sm100_mxfp8_blockscaled_grouped_quant);
-
-  /*
-   * From fast-hadamard-transform
-   */
-  m.def("fast_hadamard_transform(Tensor x, float scale) -> Tensor");
-  m.impl("fast_hadamard_transform", torch::kCUDA, &fast_hadamard_transform);
-
-  m.def("fast_hadamard_transform_12N(Tensor x, float scale) -> Tensor");
-  m.impl("fast_hadamard_transform_12N", torch::kCUDA, &fast_hadamard_transform_12N);
-
-  m.def("fast_hadamard_transform_20N(Tensor x, float scale) -> Tensor");
-  m.impl("fast_hadamard_transform_20N", torch::kCUDA, &fast_hadamard_transform_20N);
-
-  m.def("fast_hadamard_transform_28N(Tensor x, float scale) -> Tensor");
-  m.impl("fast_hadamard_transform_28N", torch::kCUDA, &fast_hadamard_transform_28N);
-
-  m.def("fast_hadamard_transform_40N(Tensor x, float scale) -> Tensor");
-  m.impl("fast_hadamard_transform_40N", torch::kCUDA, &fast_hadamard_transform_40N);
 }
 
 REGISTER_EXTENSION(common_ops)

sgl-kernel/include/sgl_kernel_ops.h

@@ -936,15 +936,6 @@ void es_sm100_mxfp8_blockscaled_grouped_quant(
     torch::Tensor& quant_output,
     torch::Tensor& scale_factor);
 
-/*
- * From fast-hadamard-transform
- */
-torch::Tensor fast_hadamard_transform(torch::Tensor& x, double scale);
-torch::Tensor fast_hadamard_transform_12N(torch::Tensor& x, double scale);
-torch::Tensor fast_hadamard_transform_20N(torch::Tensor& x, double scale);
-torch::Tensor fast_hadamard_transform_28N(torch::Tensor& x, double scale);
-torch::Tensor fast_hadamard_transform_40N(torch::Tensor& x, double scale);
-
 /*
  * From flashmla
  */

sgl-kernel/python/sgl_kernel/__init__.py

@@ -65,13 +65,6 @@ from sgl_kernel.gemm import (
     silu_and_mul_scaled_fp4_grouped_quant,
 )
 from sgl_kernel.grammar import apply_token_bitmask_inplace_cuda
-from sgl_kernel.hadamard import (
-    hadamard_transform,
-    hadamard_transform_12n,
-    hadamard_transform_20n,
-    hadamard_transform_28n,
-    hadamard_transform_40n,
-)
 from sgl_kernel.kvcacheio import (
     transfer_kv_all_layer,
     transfer_kv_all_layer_mla,

sgl-kernel/python/sgl_kernel/hadamard.py

@@ -1,21 +0,0 @@
-import torch
-
-
-def hadamard_transform(x: torch.Tensor, scale: float = 1.0) -> torch.Tensor:
-    return torch.ops.sgl_kernel.fast_hadamard_transform.default(x, scale)
-
-
-def hadamard_transform_12n(x: torch.Tensor, scale: float = 1.0) -> torch.Tensor:
-    return torch.ops.sgl_kernel.fast_hadamard_transform_12N.default(x, scale)
-
-
-def hadamard_transform_20n(x: torch.Tensor, scale: float = 1.0) -> torch.Tensor:
-    return torch.ops.sgl_kernel.fast_hadamard_transform_20N.default(x, scale)
-
-
-def hadamard_transform_28n(x: torch.Tensor, scale: float = 1.0) -> torch.Tensor:
-    return torch.ops.sgl_kernel.fast_hadamard_transform_28N.default(x, scale)
-
-
-def hadamard_transform_40n(x: torch.Tensor, scale: float = 1.0) -> torch.Tensor:
-    return torch.ops.sgl_kernel.fast_hadamard_transform_40N.default(x, scale)

sgl-kernel/tests/test_hadamard.py

@@ -5,7 +5,14 @@ import torch
 import torch.nn.functional as F
 from einops import rearrange, repeat
 from scipy.linalg import hadamard
-from sgl_kernel import hadamard_transform
+
+try:
+    from sgl_kernel import hadamard_transform
+except Exception:
+    pytest.skip(
+        "sgl-kernel hadamard interface was removed (migrated to jit_kernel)",
+        allow_module_level=True,
+    )
 
 
 def hadamard_transform_ref(x, scale=1.0):