diff options
| -rw-r--r-- | arm_compute/core/Utils.h | 8 | ||||
| -rw-r--r-- | src/core/CL/CLKernelLibrary.cpp | 3 | ||||
| -rw-r--r-- | src/core/CL/cl_kernels/batchnormalization_layer.cl | 125 | ||||
| -rw-r--r-- | src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp | 7 | ||||
| -rw-r--r-- | src/core/Utils.cpp | 12 | ||||
| -rw-r--r-- | tests/benchmark/CL/BatchNormalizationLayer.cpp | 12 | ||||
| -rw-r--r-- | tests/validation/CL/BatchNormalizationLayer.cpp | 6 |
7 files changed, 152 insertions, 21 deletions
diff --git a/arm_compute/core/Utils.h b/arm_compute/core/Utils.h index 23668e0169..060d5904d4 100644 --- a/arm_compute/core/Utils.h +++ b/arm_compute/core/Utils.h @@ -917,7 +917,13 @@ const std::string &string_from_format(Format format); * @return The string describing the channel. */ const std::string &string_from_channel(Channel channel); - +/** Convert a data layout identity into a string. + * + * @param[in] dl @ref DataLayout to be translated to string. + * + * @return The string describing the data layout. + */ +const std::string &string_from_data_layout(DataLayout dl); /** Convert a data type identity into a string. * * @param[in] dt @ref DataType to be translated to string. diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp index db0e51bb48..1c773bc42f 100644 --- a/src/core/CL/CLKernelLibrary.cpp +++ b/src/core/CL/CLKernelLibrary.cpp @@ -151,7 +151,8 @@ const std::map<std::string, std::string> CLKernelLibrary::_kernel_program_map = { "activation_layer_qa8", "activation_layer_qa8.cl" }, { "arithmetic_add", "arithmetic_op.cl" }, { "arithmetic_sub", "arithmetic_op.cl" }, - { "batchnormalization_layer", "batchnormalization_layer.cl" }, + { "batchnormalization_layer_nchw", "batchnormalization_layer.cl" }, + { "batchnormalization_layer_nhwc", "batchnormalization_layer.cl" }, { "bitwise_or", "bitwise_op.cl" }, { "bitwise_and", "bitwise_op.cl" }, { "bitwise_xor", "bitwise_op.cl" }, diff --git a/src/core/CL/cl_kernels/batchnormalization_layer.cl b/src/core/CL/cl_kernels/batchnormalization_layer.cl index 29b62d3d92..9c980da62a 100644 --- a/src/core/CL/cl_kernels/batchnormalization_layer.cl +++ b/src/core/CL/cl_kernels/batchnormalization_layer.cl @@ -87,19 +87,19 @@ * @param[in] gamma_offset_first_element_in_bytes The offset of the first element in the gamma source tensor * @param[in] epsilon Epsilon parameter in the batch normalization equation */ -__kernel void batchnormalization_layer(TENSOR3D_DECLARATION(input), +__kernel void batchnormalization_layer_nchw(TENSOR3D_DECLARATION(input), #ifndef IN_PLACE - TENSOR3D_DECLARATION(output), + TENSOR3D_DECLARATION(output), #endif /* not IN_PLACE */ - VECTOR_DECLARATION(mean), - VECTOR_DECLARATION(var), + VECTOR_DECLARATION(mean), + VECTOR_DECLARATION(var), #ifndef USE_DEFAULT_BETA - VECTOR_DECLARATION(beta), + VECTOR_DECLARATION(beta), #endif /* USE_DEFAULT_BETA */ #ifndef USE_DEFAULT_GAMMA - VECTOR_DECLARATION(gamma), + VECTOR_DECLARATION(gamma), #endif /* USE_DEFAULT_GAMMA */ - float epsilon) + float epsilon) { Tensor3D in = CONVERT_TO_TENSOR3D_STRUCT(input); #ifdef IN_PLACE @@ -145,7 +145,7 @@ __kernel void batchnormalization_layer(TENSOR3D_DECLARATION(input), res = MUL_OP(gamma_vec, x_bar); #else /* USE_DEFAULT_GAMMA */ // gamma is equal to 1, no need to perform multiplications - res = x_bar; + res = x_bar; #endif /* USE_DEFAULT_GAMMA */ #ifndef USE_DEFAULT_BETA @@ -161,4 +161,113 @@ __kernel void batchnormalization_layer(TENSOR3D_DECLARATION(input), (res, 0, (__global DATA_TYPE *)out.ptr); } +/** Apply batch normalization on tensors with NHWC format. + * + * @param[in] input_ptr Pointer to the first source tensor. Supported data types: QS8/QS16/F16/F32 + * @param[in] input_stride_x Stride of the first 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 first 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 first 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 first 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] mean_ptr Pointer to the mean source tensor. Supported data types: same as @p input_ptr + * @param[in] mean_stride_x Stride of the mean source tensor in X dimension (in bytes) + * @param[in] mean_step_x mean_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] mean_offset_first_element_in_bytes The offset of the first element in the mean source tensor + * @param[in] var_ptr Pointer to the var tensor. Supported data types: same as @p input_ptr + * @param[in] var_stride_x Stride of the var tensor in X dimension (in bytes) + * @param[in] var_step_x var_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] var_offset_first_element_in_bytes The offset of the first element in the var source tensor + * @param[in] beta_ptr Pointer to the beta source tensor. Supported data types: same as @p input_ptr + * @param[in] beta_stride_x Stride of the beta source tensor in X dimension (in bytes) + * @param[in] beta_step_x beta_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] beta_offset_first_element_in_bytes The offset of the first element in the beta source tensor + * @param[in] gamma_ptr Pointer to the gamma source tensor. Supported data types: same as @p input_ptr + * @param[in] gamma_stride_x Stride of the gamma source tensor in X dimension (in bytes) + * @param[in] gamma_step_x gamma_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] gamma_offset_first_element_in_bytes The offset of the first element in the gamma source tensor + * @param[in] epsilon Epsilon parameter in the batch normalization equation + */ +__kernel void batchnormalization_layer_nhwc(TENSOR3D_DECLARATION(input), +#ifndef IN_PLACE + TENSOR3D_DECLARATION(output), +#endif /* not IN_PLACE */ + VECTOR_DECLARATION(mean), + VECTOR_DECLARATION(var), +#ifndef USE_DEFAULT_BETA + VECTOR_DECLARATION(beta), +#endif /* USE_DEFAULT_BETA */ +#ifndef USE_DEFAULT_GAMMA + VECTOR_DECLARATION(gamma), +#endif /* USE_DEFAULT_GAMMA */ + float epsilon) +{ + Tensor3D in = CONVERT_TO_TENSOR3D_STRUCT(input); +#ifdef IN_PLACE + Tensor3D out = in; +#else /* IN_PLACE */ + Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output); +#endif /* IN_PLACE */ + Vector mean = CONVERT_TO_VECTOR_STRUCT(mean); + Vector var = CONVERT_TO_VECTOR_STRUCT(var); +#ifndef USE_DEFAULT_BETA + Vector beta = CONVERT_TO_VECTOR_STRUCT(beta); +#endif /* USE_DEFAULT_BETA */ +#ifndef USE_DEFAULT_GAMMA + Vector gamma = CONVERT_TO_VECTOR_STRUCT(gamma); +#endif /* USE_DEFAULT_GAMMA */ + + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + data = 0; + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + denominator = 0; + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + numerator = 0; + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + x_bar = 0; + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + res = 0; + + const int current_slice = get_global_id(0); + + data = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)in.ptr); + denominator = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(var.ptr + current_slice * VEC_SIZE * var.stride_x)); + denominator = INVSQRT_OP(ADD_OP(denominator, ((VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(epsilon)))); + + // Calculate x bar and store results + numerator = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(mean.ptr + current_slice * VEC_SIZE * mean.stride_x)); + numerator = SUB_OP(data, numerator); + x_bar = MUL_OP(numerator, denominator); + +#ifndef USE_DEFAULT_GAMMA + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + gamma_vec = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(gamma.ptr + current_slice * VEC_SIZE * gamma.stride_x)); + + res = MUL_OP(gamma_vec, x_bar); +#else /* USE_DEFAULT_GAMMA */ + // gamma is equal to 1, no need to perform multiplications + res = x_bar; +#endif /* USE_DEFAULT_GAMMA */ + +#ifndef USE_DEFAULT_BETA + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + beta_vec = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(beta.ptr + current_slice * VEC_SIZE * beta.stride_x)); + // beta is not zero, hence we need to perform the addition + res = ADD_OP(res, beta_vec); +#endif /* USE_DEFAULT_BETA */ + + res = ACTIVATION_FUNC(res); + + VSTORE(VEC_SIZE) + (res, 0, (__global DATA_TYPE *)out.ptr); +} #endif /* defined(VEC_SIZE) && defined(DATA_TYPE) */ diff --git a/src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp b/src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp index 62f21eed96..3a2211c522 100644 --- a/src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp +++ b/src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp @@ -49,6 +49,7 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mean, var); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, mean, var); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, mean, var); + ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::CHANNEL)) != mean->dimension(0)); if(beta != nullptr) { ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mean, beta); @@ -62,7 +63,6 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, gamma); } - ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(2) != mean->dimension(0)); if(act_info.enabled()) { ActivationLayerInfo::ActivationFunction act = act_info.activation(); @@ -75,6 +75,7 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, if(output != nullptr && output->total_size() != 0) { ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, output); } @@ -152,7 +153,7 @@ void CLBatchNormalizationLayerKernel::configure(ICLTensor *input, ICLTensor *out build_opts.add_option_if(gamma == nullptr, "-DUSE_DEFAULT_GAMMA"); // Create kernel - _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("batchnormalization_layer", build_opts.options())); + _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("batchnormalization_layer_" + lower_string(string_from_data_layout(input->info()->data_layout())), build_opts.options())); // Set kernel static arguments unsigned int include_output = (!_run_in_place) ? 1 : 0; @@ -173,6 +174,8 @@ void CLBatchNormalizationLayerKernel::configure(ICLTensor *input, ICLTensor *out ICLKernel::configure(win_config.second); _config_id = "batch_normalization_layer_"; + _config_id += string_from_data_layout(input->info()->data_layout()); + _config_id += "_"; _config_id += string_from_data_type(input->info()->data_type()); _config_id += "_"; _config_id += support::cpp11::to_string(input->info()->dimension(0)); diff --git a/src/core/Utils.cpp b/src/core/Utils.cpp index 4a237f9daa..b5663e63e4 100644 --- a/src/core/Utils.cpp +++ b/src/core/Utils.cpp @@ -126,6 +126,18 @@ const std::string &arm_compute::string_from_channel(Channel channel) return channels_map[channel]; } +const std::string &arm_compute::string_from_data_layout(DataLayout dl) +{ + static std::map<DataLayout, const std::string> dl_map = + { + { DataLayout::UNKNOWN, "UNKNOWN" }, + { DataLayout::NCHW, "NCHW" }, + { DataLayout::NHWC, "NHWC" }, + }; + + return dl_map[dl]; +} + const std::string &arm_compute::string_from_data_type(DataType dt) { static std::map<DataType, const std::string> dt_map = diff --git a/tests/benchmark/CL/BatchNormalizationLayer.cpp b/tests/benchmark/CL/BatchNormalizationLayer.cpp index 3d11aea1e7..9ae80a8854 100644 --- a/tests/benchmark/CL/BatchNormalizationLayer.cpp +++ b/tests/benchmark/CL/BatchNormalizationLayer.cpp @@ -56,7 +56,7 @@ REGISTER_FIXTURE_DATA_TEST_CASE(MobileNetBatchNormalizationLayer, CLBatchNormali framework::dataset::make("UseBeta", { false, true }))), framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f))), data_types), - framework::dataset::make("DataLayout", { DataLayout::NCHW })), + framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), framework::dataset::make("Batches", 1))); REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2BatchNormalizationLayer, CLBatchNormalizationLayerFixture, framework::DatasetMode::ALL, @@ -65,7 +65,7 @@ REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2BatchNormalizationLayer, CLBatchNormalizat framework::dataset::make("UseBeta", { false, true }))), framework::dataset::make("ActivationInfo", ActivationLayerInfo())), data_types), - framework::dataset::make("DataLayout", { DataLayout::NCHW })), + framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), framework::dataset::make("Batches", 1))); REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4BatchNormalizationLayer, CLBatchNormalizationLayerFixture, framework::DatasetMode::ALL, @@ -74,7 +74,7 @@ REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4BatchNormalizationLayer, CLB framework::dataset::make("UseBeta", { false, true }))), framework::dataset::make("ActivationInfo", ActivationLayerInfo())), data_types), - framework::dataset::make("DataLayout", { DataLayout::NCHW })), + framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), framework::dataset::make("Batches", 1))); TEST_SUITE(NIGHTLY) @@ -85,7 +85,7 @@ REGISTER_FIXTURE_DATA_TEST_CASE(MobileNetBatchNormalizationLayer, CLBatchNormali framework::dataset::make("UseBeta", { false, true }))), framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f))), data_types), - framework::dataset::make("DataLayout", { DataLayout::NCHW })), + framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), framework::dataset::make("Batches", { 4, 8 }))); REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2BatchNormalizationLayer, CLBatchNormalizationLayerFixture, framework::DatasetMode::NIGHTLY, @@ -94,7 +94,7 @@ REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2BatchNormalizationLayer, CLBatchNormalizat framework::dataset::make("UseBeta", { false, true }))), framework::dataset::make("ActivationInfo", ActivationLayerInfo())), data_types), - framework::dataset::make("DataLayout", { DataLayout::NCHW })), + framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), framework::dataset::make("Batches", { 4, 8 }))); REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4BatchNormalizationLayer, CLBatchNormalizationLayerFixture, framework::DatasetMode::NIGHTLY, @@ -103,7 +103,7 @@ REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4BatchNormalizationLayer, CLB framework::dataset::make("UseBeta", { false, true }))), framework::dataset::make("ActivationInfo", ActivationLayerInfo())), data_types), - framework::dataset::make("DataLayout", { DataLayout::NCHW })), + framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), framework::dataset::make("Batches", { 4, 8 }))); TEST_SUITE_END() TEST_SUITE_END() diff --git a/tests/validation/CL/BatchNormalizationLayer.cpp b/tests/validation/CL/BatchNormalizationLayer.cpp index 6190e67dba..f6dc6b377c 100644 --- a/tests/validation/CL/BatchNormalizationLayer.cpp +++ b/tests/validation/CL/BatchNormalizationLayer.cpp @@ -66,7 +66,7 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(combi combine(framework::dataset::make("UseBeta", { false, true }), framework::dataset::make("UseGamma", { false, true }))), framework::dataset::make("DataType", { DataType::QS8, DataType::QS16, DataType::F16, DataType::F32 })), - framework::dataset::make("DataLayout", { DataLayout::NCHW })), + framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), shape0, shape1, epsilon, use_gamma, use_beta, dt, data_layout) { // Set fixed point position data type allowed @@ -168,7 +168,7 @@ FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixture<float>, framewor framework::dataset::make("UseGamma", { false, true }))), act_infos), framework::dataset::make("DataType", DataType::F32)), - framework::dataset::make("DataLayout", { DataLayout::NCHW }))) + framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f32, 0); @@ -181,7 +181,7 @@ FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixture<half>, framework framework::dataset::make("UseGamma", { false, true }))), framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f))), framework::dataset::make("DataType", DataType::F16)), - framework::dataset::make("DataLayout", { DataLayout::NCHW }))) + framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f16, 0); |