From e5bf4c55eff186a8871206fbc1b02391fd8d75b2 Mon Sep 17 00:00:00 2001 From: Michele Di Giorgio Date: Thu, 14 Feb 2019 17:47:33 +0000 Subject: COMPMID-1710: Fix CL logistic activation for QASYMM8 Logistic activation in QASYMM8 is performed in floating point and then converting back to QASYMM8. However, if input and output have different quantization information, a double conversion is done leading to loss in accuracy. This patch creates a special case kernel for logistic activation. Change-Id: Ia18ee0b2f84701674f88785bcd13753b50d64a08 Signed-off-by: Michele Di Giorgio Reviewed-on: https://review.mlplatform.org/696 Reviewed-by: Gian Marco Iodice Tested-by: Arm Jenkins --- src/core/CL/CLKernelLibrary.cpp | 1 + src/core/CL/cl_kernels/activation_layer_qa8.cl | 94 ++++++++++++++++++++----- src/core/CL/kernels/CLActivationLayerKernel.cpp | 41 ++++++----- 3 files changed, 99 insertions(+), 37 deletions(-) diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp index ce846d1dc5..a7d371dabc 100644 --- a/src/core/CL/CLKernelLibrary.cpp +++ b/src/core/CL/CLKernelLibrary.cpp @@ -149,6 +149,7 @@ const std::map CLKernelLibrary::_kernel_program_map = { "accumulate_weighted", "accumulate.cl" }, { "activation_layer", "activation_layer.cl" }, { "activation_layer_qa8", "activation_layer_qa8.cl" }, + { "activation_layer_logistic_qa8", "activation_layer_qa8.cl" }, { "batch_to_space_nchw", "batch_to_space.cl" }, { "batch_to_space_static_nchw", "batch_to_space.cl" }, { "batch_to_space_nhwc", "batch_to_space.cl" }, diff --git a/src/core/CL/cl_kernels/activation_layer_qa8.cl b/src/core/CL/cl_kernels/activation_layer_qa8.cl index 8f6a807613..cfb61376ca 100644 --- a/src/core/CL/cl_kernels/activation_layer_qa8.cl +++ b/src/core/CL/cl_kernels/activation_layer_qa8.cl @@ -1,5 +1,5 @@ /* - * Copyright (c) 2016-2018 ARM Limited. + * Copyright (c) 2016-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -26,16 +26,6 @@ #define TYPE VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) #define VEC_FLOAT VEC_DATA_TYPE(float, VEC_SIZE) -// Logistic Activation -inline TYPE logistic_op(TYPE x) -{ - VEC_FLOAT x_flt = CONVERT(x, VEC_FLOAT); - x_flt = round(x_flt - (float)O1_VAL) * ((float)S1_VAL); - x_flt = 1.f / (1.f + exp(-x_flt)); - - const TYPE x_u8 = CONVERT_SAT(round(x_flt / ((float)S1_VAL)) + (float)O1_VAL, TYPE); - return x_u8; -} // RELU Activation inline TYPE relu_op(TYPE x) { @@ -95,14 +85,14 @@ inline TYPE lu_brelu_op(TYPE x) * @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 image - * @param[out] output_ptr Pointer to the destination image. Supported data types: same as @p input_ptr - * @param[in] output_stride_x Stride of the destination image 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 image 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 source 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 image + * @param[out] output_ptr (Optional) Pointer to the destination image. Supported data types: same as @p input_ptr + * @param[in] output_stride_x (Optional) Stride of the destination image in X dimension (in bytes) + * @param[in] output_step_x (Optional) output_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] output_stride_y (Optional) Stride of the destination image in Y dimension (in bytes) + * @param[in] output_step_y (Optional) output_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] output_stride_z (Optional) Stride of the source tensor in Z dimension (in bytes) + * @param[in] output_step_z (Optional) output_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] output_offset_first_element_in_bytes (Optional) The offset of the first element in the destination image */ __kernel void activation_layer_qa8( TENSOR3D_DECLARATION(input) @@ -131,3 +121,69 @@ __kernel void activation_layer_qa8( } #endif /* defined(ACT) */ + +#if defined(O2_VAL) && defined(S2_VAL) +#define OFFSET_OUT O2_VAL +#define SCALE_OUT S2_VAL +#else // defined(O2_VAL) && defined(S2_VAL) +#define OFFSET_OUT O1_VAL +#define SCALE_OUT S1_VAL +#endif // defined(O2_VAL) && defined(S2_VAL) + +/** This performs a Logistic activation function on QASYMM8 inputs. + * + * @note In order to perform the activation function "in-place", the pre-processor -DIN_PLACE must be passed at compile time + * + * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short + * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16 + * @note A, B variables required by some activation functions are set using -DA_VAL= and -DB_VAL= respectively. + * @note Quantization scales of the input/output tensors are passed in with -DS1_VAL= and -DS2_VAL= respectively. + * @note Quantization offsets of the input/output tensors are passed in with -DO1_VAL= and -DO2_VAL= respectively. + * @note Quantized value of constant zero should be given as a preprocessor argument using -DCONST_0=value. e.g. -DCONST_0=128. + * + * @param[in] input_ptr Pointer to the source image. Supported data types: QASYMM8 + * @param[in] input_stride_x Stride of the source image 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 image 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 image + * @param[out] output_ptr (Optional) Pointer to the destination image. Supported data types: same as @p input_ptr + * @param[in] output_stride_x (Optional) Stride of the destination image in X dimension (in bytes) + * @param[in] output_step_x (Optional) output_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] output_stride_y (Optional) Stride of the destination image in Y dimension (in bytes) + * @param[in] output_step_y (Optional) output_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] output_stride_z (Optional) Stride of the source tensor in Z dimension (in bytes) + * @param[in] output_step_z (Optional) output_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] output_offset_first_element_in_bytes (Optional) The offset of the first element in the destination image + */ +__kernel void activation_layer_logistic_qa8( + TENSOR3D_DECLARATION(input) +#ifndef IN_PLACE + , + TENSOR3D_DECLARATION(output) +#endif /* not IN_PLACE */ +) +{ + // Get pixels pointer + Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input); +#ifdef IN_PLACE + Tensor3D output = input; +#else /* IN_PLACE */ + Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output); +#endif /* IN_PLACE */ + + // Load data + TYPE data = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)input.ptr); + + VEC_FLOAT data_flt = CONVERT(data, VEC_FLOAT); + data_flt = round(data_flt - (float)O1_VAL) * ((float)S1_VAL); + data_flt = 1.f / (1.f + exp(-data_flt)); + + data = CONVERT_SAT(round(data_flt / ((float)SCALE_OUT)) + (float)OFFSET_OUT, TYPE); + + // Store result + VSTORE(VEC_SIZE) + (data, 0, (__global DATA_TYPE *)output.ptr); +} diff --git a/src/core/CL/kernels/CLActivationLayerKernel.cpp b/src/core/CL/kernels/CLActivationLayerKernel.cpp index 73a4d7d2c6..100184d2f3 100644 --- a/src/core/CL/kernels/CLActivationLayerKernel.cpp +++ b/src/core/CL/kernels/CLActivationLayerKernel.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2016-2018 ARM Limited. + * Copyright (c) 2016-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -129,24 +129,25 @@ void CLActivationLayerKernel::configure(ICLTensor *input, ICLTensor *output, Act b_const_int = input->info()->quantization_info().quantize(b_const, RoundingPolicy::TO_NEAREST_UP); } + const bool is_logistic_activation_quantized = is_data_type_quantized_asymmetric(dt) && act_info.activation() == ActivationLayerInfo::ActivationFunction::LOGISTIC; // Set build options - std::set build_opts; - build_opts.emplace(("-DACT=" + lower_string(string_from_activation_func(act_info.activation())))); - build_opts.emplace(("-DDATA_TYPE=" + get_cl_type_from_data_type(dt))); - build_opts.emplace(("-DSELECT_DATA_TYPE=" + get_cl_select_type_from_data_type(dt))); - build_opts.emplace(("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration))); + CLBuildOptions build_opts; + build_opts.add_option_if(!is_logistic_activation_quantized, "-DACT=" + lower_string(string_from_activation_func(act_info.activation()))); + build_opts.add_option(("-DDATA_TYPE=" + get_cl_type_from_data_type(dt))); + build_opts.add_option(("-DSELECT_DATA_TYPE=" + get_cl_select_type_from_data_type(dt))); + build_opts.add_option(("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration))); if(is_data_type_quantized(dt)) { - build_opts.emplace(("-DA_VAL=" + support::cpp11::to_string(a_const_int))); - build_opts.emplace(("-DB_VAL=" + support::cpp11::to_string(b_const_int))); + build_opts.add_option(("-DA_VAL=" + support::cpp11::to_string(a_const_int))); + build_opts.add_option(("-DB_VAL=" + support::cpp11::to_string(b_const_int))); const int o1 = input->info()->quantization_info().offset; const float s1 = input->info()->quantization_info().scale; // Quantized value of 0 corresponds to the offset o1 - build_opts.emplace(("-DCONST_0=" + support::cpp11::to_string(o1))); - build_opts.emplace(("-DS1_VAL=" + float_to_string_with_full_precision(s1))); - build_opts.emplace(("-DO1_VAL=" + support::cpp11::to_string(o1))); + build_opts.add_option(("-DCONST_0=" + support::cpp11::to_string(o1))); + build_opts.add_option(("-DS1_VAL=" + float_to_string_with_full_precision(s1))); + build_opts.add_option(("-DO1_VAL=" + support::cpp11::to_string(o1))); // Set scale and offset of the input and output if they have different quantization info if(is_data_type_quantized_asymmetric(dt) && output != nullptr) @@ -156,22 +157,26 @@ void CLActivationLayerKernel::configure(ICLTensor *input, ICLTensor *output, Act if(o1 != o2 || s1 != s2) { - build_opts.emplace(("-DS2_VAL=" + float_to_string_with_full_precision(s2))); - build_opts.emplace(("-DO2_VAL=" + support::cpp11::to_string(o2))); + build_opts.add_option(("-DS2_VAL=" + float_to_string_with_full_precision(s2))); + build_opts.add_option(("-DO2_VAL=" + support::cpp11::to_string(o2))); } } } else { - build_opts.emplace(("-DA_VAL=" + float_to_string_with_full_precision(a_const))); - build_opts.emplace(("-DB_VAL=" + float_to_string_with_full_precision(b_const))); + build_opts.add_option(("-DA_VAL=" + float_to_string_with_full_precision(a_const))); + build_opts.add_option(("-DB_VAL=" + float_to_string_with_full_precision(b_const))); } - build_opts.emplace((_run_in_place) ? "-DIN_PLACE" : ""); + build_opts.add_option_if(_run_in_place, "-DIN_PLACE"); // Create kernel - std::string kernel_name = is_data_type_quantized_asymmetric(dt) ? std::string("activation_layer_qa8") : std::string("activation_layer"); - _kernel = static_cast(CLKernelLibrary::get().create_kernel(kernel_name, build_opts)); + std::string kernel_name = std::string("activation_layer"); + if(is_data_type_quantized_asymmetric(dt)) + { + kernel_name += is_logistic_activation_quantized ? std::string("_logistic_qa8") : std::string("_qa8"); + } + _kernel = static_cast(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options())); // Make sure _kernel is initialized before calling the parent's configure _input = input; -- cgit v1.2.1