[nference] remove wint float32 (PaddlePaddle#72545)

Author: zhoutianzi666

paddle/phi/kernels/fusion/cutlass/cutlass_kernels/fpA_intB_gemm/fpA_intB_gemm.h

@@ -123,42 +123,4 @@ class CutlassFpAIntBGemmRunner {
   int multi_processor_count_;
 };
 
-// This allocation is present to help with compiling with other structures in
-// FT. It will throw an error in all functions because this runner assumes the
-// weight type and the activation type are different. We allow empty classes to
-// be created, but any calls to gemm or gemm_bias_act will throw an error.
-template <typename WeightType>
-class CutlassFpAIntBGemmRunner<float, WeightType> {
- public:
-  CutlassFpAIntBGemmRunner() = default;
-  ~CutlassFpAIntBGemmRunner() = default;
-
-  void gemm(const float* A,
-            const WeightType* B,
-            const float* weight_scales,
-            float* C,
-            int m,
-            int n,
-            int k,
-            int group_size,
-            char* workspace_ptr,
-            const size_t workspace_bytes,
-            cudaStream_t stream);
-
-  void gemm_bias_act(const float* A,
-                     const WeightType* B,
-                     const float* weight_scales,
-                     const float* biases,
-                     float* C,
-                     int m,
-                     int n,
-                     int k,
-                     int group_size,
-                     std::string activation_type,
-                     char* workspace_ptr,
-                     const size_t workspace_bytes,
-                     cudaStream_t stream);
-
-  int getWorkspaceSize(const int m, const int n, const int k);
-};
 }  // namespace phi

paddle/phi/kernels/fusion/cutlass/cutlass_kernels/fpA_intB_gemm/fpA_intB_gemm_template.cu

@@ -823,58 +823,10 @@ int CutlassFpAIntBGemmRunner<T, WeightType>::getWorkspaceSize(const int m,
   return max_grid_m * max_grid_n * split_k_limit * 4;
 }
 
-// =============================== Specialization T == WeightType
-// =======================================
-template <typename WeightType>
-void CutlassFpAIntBGemmRunner<float, WeightType>::gemm_bias_act(
-    const float* A,
-    const WeightType* B,
-    const float* weight_scales,
-    const float* biases,
-    float* C,
-    int m,
-    int n,
-    int k,
-    int group_size,
-    std::string activation_type,
-    char* workspace_ptr,
-    const size_t workspace_bytes,
-    cudaStream_t stream) {
-  throw std::runtime_error(
-      ("Attempting to run mixed gemm bias act when the types are the same is "
-       "an error."));
-}
-
-template <typename WeightType>
-void CutlassFpAIntBGemmRunner<float, WeightType>::gemm(
-    const float* A,
-    const WeightType* B,
-    const float* weight_scales,
-    float* C,
-    int m,
-    int n,
-    int k,
-    int group_size,
-    char* workspace_ptr,
-    const size_t workspace_bytes,
-    cudaStream_t stream) {
-  throw std::runtime_error((
-      "Attempting to run mixed gemm when the types are the same is an error."));
-}
-
-template <typename WeightType>
-int CutlassFpAIntBGemmRunner<float, WeightType>::getWorkspaceSize(const int m,
-                                                                  const int n,
-                                                                  const int k) {
-  return 0;
-}
-
-template class CutlassFpAIntBGemmRunner<float, uint8_t>;
 template class CutlassFpAIntBGemmRunner<half, uint8_t>;
 #ifdef PADDLE_CUDA_BF16
 template class CutlassFpAIntBGemmRunner<__nv_bfloat16, uint8_t>;
 #endif
-template class CutlassFpAIntBGemmRunner<float, cutlass::uint4b_t>;
 template class CutlassFpAIntBGemmRunner<half, cutlass::uint4b_t>;
 #ifdef PADDLE_CUDA_BF16
 template class CutlassFpAIntBGemmRunner<__nv_bfloat16, cutlass::uint4b_t>;