diff options
Diffstat (limited to 'src/core/CL/kernels')
-rw-r--r-- | src/core/CL/kernels/CLGEMMInterleave4x4Kernel.cpp | 16 | ||||
-rw-r--r-- | src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp | 13 |
2 files changed, 18 insertions, 11 deletions
diff --git a/src/core/CL/kernels/CLGEMMInterleave4x4Kernel.cpp b/src/core/CL/kernels/CLGEMMInterleave4x4Kernel.cpp index 71d42c5606..7312cc25cb 100644 --- a/src/core/CL/kernels/CLGEMMInterleave4x4Kernel.cpp +++ b/src/core/CL/kernels/CLGEMMInterleave4x4Kernel.cpp @@ -43,11 +43,19 @@ CLGEMMInterleave4x4Kernel::CLGEMMInterleave4x4Kernel() void CLGEMMInterleave4x4Kernel::configure(const ICLTensor *input, ICLTensor *output) { - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::S8, DataType::U16, DataType::S16, DataType::U32, DataType::S32, DataType::F16, DataType::F32); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8, DataType::S8, DataType::U16, DataType::S16, DataType::U32, DataType::S32, DataType::F16, DataType::F32); + 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(); + output_shape.set(0, input->info()->dimension(0) * 4); + output_shape.set(1, std::ceil(input->info()->dimension(1) / 4.0f)); + + // Output auto inizialitation if not yet initialized + auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), input->info()->fixed_point_position()); + + ARM_COMPUTE_ERROR_ON_MISMATCHING_DIMENSIONS(output->info()->tensor_shape(), output_shape); ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); - ARM_COMPUTE_ERROR_ON(output->info()->dimension(0) != input->info()->dimension(0) * 4); - ARM_COMPUTE_ERROR_ON(output->info()->dimension(1) != std::ceil(static_cast<float>(input->info()->dimension(1)) / 4.0f)); + ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input, output); _input = input; _output = output; 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<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name)); + std::string kernel_name = "gemm_transpose1x" + val_to_string(num_elems_processed_per_iteration); + _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name)); // Configure window Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration)); |