diff options
Diffstat (limited to 'src/runtime/CL/functions/CLGEMM.cpp')
| -rw-r--r-- | src/runtime/CL/functions/CLGEMM.cpp | 47 |
1 files changed, 18 insertions, 29 deletions
diff --git a/src/runtime/CL/functions/CLGEMM.cpp b/src/runtime/CL/functions/CLGEMM.cpp index 492709f0d0..21a9fce233 100644 --- a/src/runtime/CL/functions/CLGEMM.cpp +++ b/src/runtime/CL/functions/CLGEMM.cpp @@ -242,10 +242,6 @@ void CLGEMM::configure_reshaped_v2(const ICLTensor *a, const ICLTensor *b, const void CLGEMM::configure_reshaped_only_rhs(const ICLTensor *a, const ICLTensor *b, const ICLTensor *c, ICLTensor *output, float alpha, float beta, const GEMMInfo &gemm_info) { - ARM_COMPUTE_ERROR_ON(c != nullptr); - ARM_COMPUTE_UNUSED(beta); - ARM_COMPUTE_UNUSED(c); - DataType data_type = a->info()->data_type(); bool reinterpret_input_as_3d = gemm_info.reinterpret_input_as_3d(); const unsigned int m = reinterpret_input_as_3d ? (a->info()->dimension(1) * a->info()->dimension(2)) : a->info()->dimension(1); @@ -254,11 +250,12 @@ void CLGEMM::configure_reshaped_only_rhs(const ICLTensor *a, const ICLTensor *b, const unsigned int batch_size = reinterpret_input_as_3d ? a->info()->dimension(3) : a->info()->dimension(2); const int depth_output_gemm3d = gemm_info.depth_output_gemm3d(); const GPUTarget gpu_target = CLScheduler::get().target(); + bool broadcast_bias = gemm_info.broadcast_bias(); // Set the target for the kernels _mm_kernel.set_target(gpu_target); - GEMMReshapeInfo reshape_info(m, n, k, 1, 1, depth_output_gemm3d, reinterpret_input_as_3d); + GEMMReshapeInfo reshape_info(m, n, k, 1, 1, depth_output_gemm3d, reinterpret_input_as_3d, broadcast_bias); // Manage intermediate buffers if(!_reshape_b_only_on_first_run) @@ -279,7 +276,7 @@ void CLGEMM::configure_reshaped_only_rhs(const ICLTensor *a, const ICLTensor *b, _reshape_rhs_kernel.configure(b, &_tmp_b, rhs_info); // Configure and tune matrix multiply kernel - _mm_reshaped_only_rhs_kernel.configure(a, &_tmp_b, output, alpha, lhs_info, rhs_info, reshape_info); + _mm_reshaped_only_rhs_kernel.configure(a, &_tmp_b, c, output, alpha, beta, lhs_info, rhs_info, reshape_info); if(!_reshape_b_only_on_first_run) { @@ -426,7 +423,6 @@ Status CLGEMM::validate_reshaped_v2(const ITensorInfo *a, const ITensorInfo *b, // Validate matrix addition kernel ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMMatrixAdditionKernel::validate(c, output, beta)); } - return Status{}; } @@ -438,17 +434,16 @@ Status CLGEMM::validate_reshaped_only_rhs(const ITensorInfo *a, const ITensorInf TensorInfo tmp_b_info{}; // Get the GPU target - const GPUTarget gpu_target = CLScheduler::get().target(); - const DataType data_type = a->data_type(); - bool reinterpret_input_as_3d = gemm_info.reinterpret_input_as_3d(); - const unsigned int m = reinterpret_input_as_3d ? (a->dimension(1) * a->dimension(2)) : a->dimension(1); - const unsigned int n = b->dimension(0); - const unsigned int k = a->dimension(0); - const unsigned int batch_size = reinterpret_input_as_3d ? a->dimension(3) : a->dimension(2); - const int depth_output_gemm3d = gemm_info.depth_output_gemm3d(); - const bool add_c = (beta != 0.f && c != nullptr); - - const GEMMReshapeInfo reshape_info = GEMMReshapeInfo(m, n, k, 1, 1, depth_output_gemm3d, reinterpret_input_as_3d); + const GPUTarget gpu_target = CLScheduler::get().target(); + const DataType data_type = a->data_type(); + bool reinterpret_input_as_3d = gemm_info.reinterpret_input_as_3d(); + const unsigned int m = reinterpret_input_as_3d ? (a->dimension(1) * a->dimension(2)) : a->dimension(1); + const unsigned int n = b->dimension(0); + const unsigned int k = a->dimension(0); + const unsigned int batch_size = reinterpret_input_as_3d ? a->dimension(3) : a->dimension(2); + const int depth_output_gemm3d = gemm_info.depth_output_gemm3d(); + const bool broadcast_bias = gemm_info.broadcast_bias(); + const GEMMReshapeInfo reshape_info = GEMMReshapeInfo(m, n, k, 1, 1, depth_output_gemm3d, reinterpret_input_as_3d, broadcast_bias); GEMMLHSMatrixInfo lhs_info; GEMMRHSMatrixInfo rhs_info; @@ -464,13 +459,7 @@ Status CLGEMM::validate_reshaped_only_rhs(const ITensorInfo *a, const ITensorInf ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMReshapeRHSMatrixKernel::validate(b, &tmp_b_info, rhs_info)); // Validate matrix multiply - ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMMatrixMultiplyReshapedOnlyRHSKernel::validate(a, &tmp_b_info, output, alpha, lhs_info, rhs_info, reshape_info)); - - if(add_c) - { - // Validate matrix addition kernel - ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMMatrixAdditionKernel::validate(c, output, beta)); - } + ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMMatrixMultiplyReshapedOnlyRHSKernel::validate(a, &tmp_b_info, c, output, alpha, beta, lhs_info, rhs_info, reshape_info)); return Status{}; } @@ -497,10 +486,10 @@ void CLGEMM::configure(const ICLTensor *a, const ICLTensor *b, const ICLTensor * // Select GEMMType _gemm_type = select_gemm_type(m, n, k, a->info()->data_type(), _reshape_b_only_on_first_run, gpu_target); - const bool is_gemm_v2 = (_gemm_type == GEMMType::RESHAPED_V2) || (_gemm_type == GEMMType::RESHAPED_ONLY_RHS); - const bool add_c = (beta != 0.f && c != nullptr); - const bool is_beta_one = std::abs(1.0f - beta) < 0.00001f; - const bool fuse_add = is_beta_one && (c != nullptr && c->info()->num_dimensions() == 1) && !is_gemm_v2; + const bool is_gemm_reshaped_only_rhs = _gemm_type == GEMMType::RESHAPED_ONLY_RHS; + const bool add_c = (beta != 0.f && c != nullptr); + const bool is_beta_one = std::abs(1.0f - beta) < 0.00001f; + const bool fuse_add = (is_beta_one && (c != nullptr && c->info()->num_dimensions() == 1)) || is_gemm_reshaped_only_rhs; switch(_gemm_type) { |