From 7a452fe8630b3ce0a58f63869178d06aaba325fc Mon Sep 17 00:00:00 2001 From: Manuel Bottini Date: Wed, 31 Mar 2021 18:22:59 +0100 Subject: Remove OpenCL padding: CLL2NormalizeLayerKernel Resolves: COMPMID-3909 Change-Id: I00a1705ed202002e2a6053702272181805fa6869 Signed-off-by: Manuel Bottini Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5360 Reviewed-by: Georgios Pinitas Comments-Addressed: Arm Jenkins Tested-by: Arm Jenkins --- src/core/CL/cl_kernels/l2_normalize.cl | 229 +++++++++++++---------- src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp | 51 ++--- 2 files changed, 147 insertions(+), 133 deletions(-) diff --git a/src/core/CL/cl_kernels/l2_normalize.cl b/src/core/CL/cl_kernels/l2_normalize.cl index 14b37e3257..fbe3406239 100644 --- a/src/core/CL/cl_kernels/l2_normalize.cl +++ b/src/core/CL/cl_kernels/l2_normalize.cl @@ -1,5 +1,5 @@ /* - * Copyright (c) 2016-2019 Arm Limited. + * Copyright (c) 2016-2021 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -23,142 +23,167 @@ */ #include "helpers.h" +#if defined(VEC_SIZE_X) && defined(VEC_SIZE_LEFTOVER_X) /** This kernel performs l2 normalization on x-axis * * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float - * @note The data size must be passed at compile time using -DDATA_SIZE e.g. -DDATA_SIZE=32 + * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE_X=size. e.g. -DVEC_SIZE_X=16 + * @note The leftover size in the X dimension shoud be given as preprocessor argument using -DVEC_SIZE_LEFTOVER_X is; x_dimension % VEC_SIZE_X. e.g. -DVEC_SIZE_LEFTOVER_X=1 * - * @param[in] src_ptr Pointer to the source tensor. Supported data types: F16/F32 - * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes) - * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes) - * @param[in] src_step_y src_stride_y * number of elements along X processed per workitem(in bytes) - * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor - * @param[in] sum_ptr Pointer to the source tensor. Supported data types: F16/F32 - * @param[in] sum_stride_x Stride of the source tensor in X dimension (in bytes) - * @param[in] sum_step_x sum_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] sum_stride_y Stride of the source tensor in Y dimension (in bytes) - * @param[in] sum_step_y sum_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] sum_offset_first_element_in_bytes The offset of the first element in the source tensor - * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr - * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) - * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) - * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor - * @param[in] epsilon Epsilon value + * @param[in] input_ptr Pointer to the source tensor. Supported data types: F16/F32 + * @param[in] input_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] input_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] input_step_y input_stride_y * number of elements along X processed per workitem(in bytes) + * @param[in] input_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[in] sum_ptr Pointer to the source tensor. Supported data types: F16/F32 + * @param[in] sum_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] sum_step_x sum_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] sum_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] sum_step_y sum_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] sum_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[out] output_ptr Pointer to the destination tensor. Supported data types: same as @p input_ptr + * @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes) + * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination tensor + * @param[in] epsilon Epsilon value */ __kernel void l2_normalize_x( - IMAGE_DECLARATION(src), + IMAGE_DECLARATION(input), IMAGE_DECLARATION(sum), - IMAGE_DECLARATION(dst), + IMAGE_DECLARATION(output), DATA_TYPE epsilon) { - Image src = CONVERT_TO_IMAGE_STRUCT(src); - Image sum = CONVERT_TO_IMAGE_STRUCT(sum); - Image dst = CONVERT_TO_IMAGE_STRUCT(dst); + // Offset computation + const uint x_offs = max((int)(get_global_id(0) * VEC_SIZE_X - (VEC_SIZE_X - VEC_SIZE_LEFTOVER_X) % VEC_SIZE_X), 0); - VEC_DATA_TYPE(DATA_TYPE, 16) - in = vload16(0, (__global DATA_TYPE *)src.ptr); - VEC_DATA_TYPE(DATA_TYPE, 16) - normalize_value = (VEC_DATA_TYPE(DATA_TYPE, 16))rsqrt(fmax(((__global DATA_TYPE *)sum.ptr)[0], epsilon)); + // Address computation + __global uchar *input_addr = input_ptr + input_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE) + get_global_id(1) * input_stride_y; + __global uchar *sum_addr = sum_ptr + sum_offset_first_element_in_bytes + get_global_id(1) * sum_stride_y; + __global uchar *output_addr = output_ptr + output_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE) + get_global_id(1) * output_stride_y; - vstore16(in * normalize_value, 0, (__global DATA_TYPE *)dst.ptr); + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X) + in = VLOAD(VEC_SIZE_X)(0, (__global DATA_TYPE *)input_addr); + + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X) + normalize_value = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X))rsqrt(fmax(*((__global DATA_TYPE *)sum_addr), epsilon)); + + const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X) + data0 = in * normalize_value; + + STORE_VECTOR_SELECT(data, DATA_TYPE, output_addr, VEC_SIZE_X, VEC_SIZE_LEFTOVER_X, VEC_SIZE_LEFTOVER_X != 0 && get_global_id(0) == 0); } /** This kernel performs l2 normalization on y-axis. * * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float - * @note The data size must be passed at compile time using -DDATA_SIZE e.g. -DDATA_SIZE=32 + * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE_X=size. e.g. -DVEC_SIZE_X=16 + * @note The leftover size in the X dimension shoud be given as preprocessor argument using -DVEC_SIZE_LEFTOVER_X is; x_dimension % VEC_SIZE_X. e.g. -DVEC_SIZE_LEFTOVER_X=1 * - * @param[in] src_ptr Pointer to the source tensor. Supported data types: F16/F32 - * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes) - * @param[in] src_step_x src_stride_x * number of elements along Y processed per workitem(in bytes) - * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes) - * @param[in] src_step_y src_stride_y * number of elements along X processed per workitem(in bytes) - * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor - * @param[in] sum_ptr Pointer to the source tensor. Supported data types: F16/F32 - * @param[in] sum_stride_x Stride of the source tensor in X dimension (in bytes) - * @param[in] sum_step_x sum_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] sum_stride_y Stride of the source tensor in Y dimension (in bytes) - * @param[in] sum_step_y sum_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] sum_offset_first_element_in_bytes The offset of the first element in the source tensor - * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr - * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) - * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) - * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor - * @param[in] epsilon Epsilon value + * @param[in] input_ptr Pointer to the source tensor. Supported data types: F16/F32 + * @param[in] input_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] input_step_x input_stride_x * number of elements along Y processed per workitem(in bytes) + * @param[in] input_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] input_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[in] sum_ptr Pointer to the source tensor. Supported data types: F16/F32 + * @param[in] sum_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] sum_step_x sum_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] sum_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] sum_step_y sum_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] sum_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[out] output_ptr Pointer to the destination tensor. Supported data types: same as @p input_ptr + * @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes) + * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination tensor + * @param[in] epsilon Epsilon value */ __kernel void l2_normalize_y( - IMAGE_DECLARATION(src), + IMAGE_DECLARATION(input), IMAGE_DECLARATION(sum), - IMAGE_DECLARATION(dst), + IMAGE_DECLARATION(output), DATA_TYPE epsilon) { - Image src = CONVERT_TO_IMAGE_STRUCT(src); - Image sum = CONVERT_TO_IMAGE_STRUCT(sum); - Image dst = CONVERT_TO_IMAGE_STRUCT(dst); + // Offset computation + const uint x_offs = max((int)(get_global_id(0) * VEC_SIZE_X - (VEC_SIZE_X - VEC_SIZE_LEFTOVER_X) % VEC_SIZE_X), 0); + + // Address computation + __global uchar *input_addr = input_ptr + input_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE) + get_global_id(1) * input_stride_y; + __global uchar *sum_addr = sum_ptr + sum_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE); + __global uchar *output_addr = output_ptr + output_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE) + get_global_id(1) * output_stride_y; - VEC_DATA_TYPE(DATA_TYPE, 16) - in = vload16(0, (__global DATA_TYPE *)src.ptr); - VEC_DATA_TYPE(DATA_TYPE, 16) - sums = vload16(0, (__global DATA_TYPE *)sum.ptr); + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X) + in = VLOAD(VEC_SIZE_X)(0, (__global DATA_TYPE *)input_addr); + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X) + sums = VLOAD(VEC_SIZE_X)(0, (__global DATA_TYPE *)sum_addr); - VEC_DATA_TYPE(DATA_TYPE, 16) - normalize_value = (VEC_DATA_TYPE(DATA_TYPE, 16))rsqrt(fmax(sums, epsilon)); + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X) + normalize_value = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X))rsqrt(fmax(sums, epsilon)); - vstore16(in * normalize_value, 0, (__global DATA_TYPE *)dst.ptr); + const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X) + data0 = in * normalize_value; + + STORE_VECTOR_SELECT(data, DATA_TYPE, output_addr, VEC_SIZE_X, VEC_SIZE_LEFTOVER_X, VEC_SIZE_LEFTOVER_X != 0 && get_global_id(0) == 0); } + /** This kernel performs l2 normalization on z-axis. * * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float - * @note The data size must be passed at compile time using -DDATA_SIZE e.g. -DDATA_SIZE=32 + * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE_X=size. e.g. -DVEC_SIZE_X=16 + * @note The leftover size in the X dimension shoud be given as preprocessor argument using -DVEC_SIZE_LEFTOVER_X is; x_dimension % VEC_SIZE_X. e.g. -DVEC_SIZE_LEFTOVER_X=1 * - * @param[in] src_ptr Pointer to the source tensor. Supported data types: F16/F32 - * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes) - * @param[in] src_step_x src_stride_x * number of elements along Y processed per workitem(in bytes) - * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes) - * @param[in] src_step_y src_stride_y * number of elements along X processed per workitem(in bytes) - * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes) - * @param[in] src_step_z src_stride_z * number of elements along Z processed per workitem(in bytes) - * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor - * @param[in] sum_ptr Pointer to the source tensor. Supported data types: F16/F32 - * @param[in] sum_stride_x Stride of the source tensor in X dimension (in bytes) - * @param[in] sum_step_x sum_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] sum_stride_y Stride of the source tensor in Y dimension (in bytes) - * @param[in] sum_step_y sum_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] sum_stride_z Stride of the source tensor in Z dimension (in bytes) - * @param[in] sum_step_z sum_stride_z * number of elements along Z processed per workitem(in bytes) - * @param[in] sum_offset_first_element_in_bytes The offset of the first element in the source tensor - * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr - * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) - * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) - * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) - * @param[in] dst_step_z dst_stride_z * number of elements along Y processed per workitem(in bytes) - * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor - * @param[in] epsilon Epsilon value + * @param[in] input_ptr Pointer to the source tensor. Supported data types: F16/F32 + * @param[in] input_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] input_step_x input_stride_x * number of elements along Y processed per workitem(in bytes) + * @param[in] input_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] input_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] input_step_z input_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] input_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[in] sum_ptr Pointer to the source tensor. Supported data types: F16/F32 + * @param[in] sum_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] sum_step_x sum_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] sum_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] sum_step_y sum_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] sum_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] sum_step_z sum_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] sum_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[out] output_ptr Pointer to the destination tensor. Supported data types: same as @p input_ptr + * @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes) + * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] output_stride_z Stride of the destination tensor in Z dimension (in bytes) + * @param[in] output_step_z output_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination tensor + * @param[in] epsilon Epsilon value */ __kernel void l2_normalize_z( - TENSOR3D_DECLARATION(src), + TENSOR3D_DECLARATION(input), TENSOR3D_DECLARATION(sum), - TENSOR3D_DECLARATION(dst), + TENSOR3D_DECLARATION(output), DATA_TYPE epsilon) { - Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src); - Tensor3D sum = CONVERT_TO_TENSOR3D_STRUCT(sum); - Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst); + // Offset computation + const uint x_offs = max((int)(get_global_id(0) * VEC_SIZE_X - (VEC_SIZE_X - VEC_SIZE_LEFTOVER_X) % VEC_SIZE_X), 0); - VEC_DATA_TYPE(DATA_TYPE, 16) - in = vload16(0, (__global DATA_TYPE *)src.ptr); - VEC_DATA_TYPE(DATA_TYPE, 16) - sums = vload16(0, (__global DATA_TYPE *)sum.ptr); + // Address computation + __global uchar *input_addr = input_ptr + input_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE) + get_global_id(1) * input_stride_y + get_global_id(2) * input_stride_z; + __global uchar *sum_addr = sum_ptr + sum_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE) + get_global_id(1) * sum_stride_y; + __global uchar *output_addr = output_ptr + output_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE) + get_global_id(1) * output_stride_y + get_global_id(2) * output_stride_z; - VEC_DATA_TYPE(DATA_TYPE, 16) - normalize_value = (VEC_DATA_TYPE(DATA_TYPE, 16))rsqrt(fmax(sums, epsilon)); + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X) + in = VLOAD(VEC_SIZE_X)(0, (__global DATA_TYPE *)input_addr); + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X) + sums = VLOAD(VEC_SIZE_X)(0, (__global DATA_TYPE *)sum_addr); - vstore16(in * normalize_value, 0, (__global DATA_TYPE *)dst.ptr); -} \ No newline at end of file + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X) + data0 = in * ((VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X))(rsqrt(fmax(sums, epsilon)))); + + STORE_VECTOR_SELECT(data, DATA_TYPE, output_addr, VEC_SIZE_X, VEC_SIZE_LEFTOVER_X, VEC_SIZE_LEFTOVER_X != 0 && get_global_id(0) == 0); +} +#endif // defined(VEC_SIZE_X) && defined(VEC_SIZE_LEFTOVER_X) \ No newline at end of file diff --git a/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp b/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp index 213770591f..d9f293ba73 100644 --- a/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp +++ b/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp @@ -36,14 +36,14 @@ #include "support/StringSupport.h" +#include "utils/TypePrinter.h" + namespace arm_compute { namespace { constexpr int max_input_tensor_dim = 3; -constexpr unsigned int num_elems_processed_per_iteration = 16; - Status validate_arguments(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, int axis, float epsilon) { ARM_COMPUTE_UNUSED(epsilon); @@ -71,23 +71,6 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *sum, cons return Status{}; } - -std::tuple validate_and_configure_window(ITensorInfo *input, ITensorInfo *output) -{ - Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration)); - - // Output tensor auto initialization if not yet initialized - auto_init_if_empty(*output, input->tensor_shape(), 1, input->data_type()); - - AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration); - AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration); - - bool window_changed = update_window_and_padding(win, input_access, output_access); - - Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; - - return std::make_tuple(err, win); -} } // namespace CLL2NormalizeLayerKernel::CLL2NormalizeLayerKernel() @@ -104,6 +87,7 @@ void CLL2NormalizeLayerKernel::configure(const CLCompileContext &compile_context { ARM_COMPUTE_ERROR_ON_NULLPTR(input, sum, output); ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), sum->info(), output->info(), axis, epsilon)); + auto padding_info = get_padding_info({ input, sum, output }); _input = input; _sum = sum; @@ -111,10 +95,14 @@ void CLL2NormalizeLayerKernel::configure(const CLCompileContext &compile_context _actual_axis = wrap_around(axis, max_input_tensor_dim); _epsilon = epsilon; + const unsigned int vec_size_x = adjust_vec_size(max_cl_vector_width / input->info()->element_size(), input->info()->dimension(0)); + const int vec_size_x_leftovers = input->info()->dimension(0) % vec_size_x; + // Set build options - std::set build_opts; - build_opts.emplace(("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()))); - build_opts.emplace(("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration))); + CLBuildOptions build_opts; + build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())); + build_opts.add_option("-DVEC_SIZE_X=" + support::cpp11::to_string(vec_size_x)); + build_opts.add_option("-DVEC_SIZE_LEFTOVER_X=" + support::cpp11::to_string(vec_size_x_leftovers)); // Create kernel std::string kernel_name; @@ -122,21 +110,21 @@ void CLL2NormalizeLayerKernel::configure(const CLCompileContext &compile_context switch(_actual_axis) { case 0: - kernel_name = "x"; + kernel_name = "l2_normalize_x"; idx = num_arguments_per_2D_tensor() * 3; break; case 1: - kernel_name = "y"; + kernel_name = "l2_normalize_y"; idx = num_arguments_per_2D_tensor() * 3; break; case 2: - kernel_name = "z"; + kernel_name = "l2_normalize_z"; idx = num_arguments_per_3D_tensor() * 3; break; default: ARM_COMPUTE_ERROR("Axis not supported"); } - _kernel = create_kernel(compile_context, "l2_normalize_" + kernel_name, build_opts); + _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); // Set epsilon argument if(input->info()->data_type() == DataType::F32) @@ -149,17 +137,18 @@ void CLL2NormalizeLayerKernel::configure(const CLCompileContext &compile_context } // Configure kernel window - auto win_config = validate_and_configure_window(_input->info(), _output->info()); - ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config)); + Window win = calculate_max_window(*input->info(), Steps(vec_size_x)); - ICLKernel::configure_internal(std::get<1>(win_config)); + // Output tensor auto initialization if not yet initialized + auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, input->info()->data_type()); + + ICLKernel::configure_internal(win); + ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info)); } Status CLL2NormalizeLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, int axis, float epsilon) { ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, sum, output, axis, epsilon)); - ARM_COMPUTE_RETURN_ON_ERROR(std::get<0>(validate_and_configure_window(input->clone().get(), output->clone().get()))); - return Status{}; } -- cgit v1.2.1