From 9f89baebb81e6a01ec06fe916564da45eb204f34 Mon Sep 17 00:00:00 2001 From: Gian Marco Iodice Date: Thu, 22 Jun 2017 12:09:49 +0100 Subject: COMPMID-411 - Ported CLGEMMInterleave4x4Kernel and CLGEMMTranspose1xWKernel to support 8 bit fixed point Change-Id: If236c9047ed536e808a0ed26e97e1799ca938e03 Reviewed-on: http://mpd-gerrit.cambridge.arm.com/78529 Tested-by: Kaizen Reviewed-by: Moritz Pflanzer Reviewed-by: Georgios Pinitas --- src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp | 13 ++++++------- 1 file changed, 6 insertions(+), 7 deletions(-) (limited to 'src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp') diff --git a/src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp b/src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp index 4067280bf0..0ef02f8a46 100644 --- a/src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp +++ b/src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp @@ -40,8 +40,8 @@ using namespace arm_compute; void CLGEMMTranspose1xWKernel::configure(const ICLTensor *input, ICLTensor *output) { - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::F16, DataType::F32); - ARM_COMPUTE_ERROR_ON(output == nullptr); + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::S8, DataType::QS8, DataType::U16, DataType::S16, DataType::U32, DataType::S32, DataType::F16, DataType::F32); + ARM_COMPUTE_ERROR_ON_NULLPTR(output); TensorShape output_shape{ input->info()->tensor_shape() }; const size_t transpose_w = 16 / input->info()->element_size(); @@ -53,6 +53,7 @@ void CLGEMMTranspose1xWKernel::configure(const ICLTensor *input, ICLTensor *outp ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); ARM_COMPUTE_ERROR_ON_MISMATCHING_DIMENSIONS(output->info()->tensor_shape(), output_shape); + ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input, output); const unsigned int num_elems_processed_per_iteration = max_cl_vector_width / data_size_from_type(input->info()->data_type()); const float scale_x = num_elems_processed_per_iteration; @@ -69,13 +70,11 @@ void CLGEMMTranspose1xWKernel::configure(const ICLTensor *input, ICLTensor *outp * |a20 a21 a22 a23| = | a00 a01 a02 a03 || a10 a11 a12 a13 || a20 a21 a22 a23 || a30 a31 a32 a33 | * |a30 a31 a32 a33| * - * If the input data type is F32, the output matrix will have the following shape: [ height * 4, width / 4 ] - * If the input data type is F16, the output matrix will have the following shape: [ height * 8, width / 8 ] + * The output matrix will have the following shape: [ height * W, ceil(width / W) ], where W = (16 / element size of the tensor) */ // Create kernel - std::string data_type_name = lower_string(string_from_data_type(input->info()->data_type())); - std::string kernel_name = "gemm_transpose1x" + val_to_string(num_elems_processed_per_iteration) + "_" + data_type_name; - _kernel = static_cast(CLKernelLibrary::get().create_kernel(kernel_name)); + std::string kernel_name = "gemm_transpose1x" + val_to_string(num_elems_processed_per_iteration); + _kernel = static_cast(CLKernelLibrary::get().create_kernel(kernel_name)); // Configure window Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration)); -- cgit v1.2.1