diff options
| -rw-r--r-- | src/core/CL/kernels/CLPoolingLayerKernel.cpp | 2 | ||||
| -rw-r--r-- | src/core/CL/kernels/CLSoftmaxLayerKernel.cpp | 418 | ||||
| -rw-r--r-- | tests/validation/CL/SoftmaxLayer.cpp | 16 |
3 files changed, 264 insertions, 172 deletions
diff --git a/src/core/CL/kernels/CLPoolingLayerKernel.cpp b/src/core/CL/kernels/CLPoolingLayerKernel.cpp index 7fd2689c43..b0942e55b1 100644 --- a/src/core/CL/kernels/CLPoolingLayerKernel.cpp +++ b/src/core/CL/kernels/CLPoolingLayerKernel.cpp @@ -52,7 +52,7 @@ void auto_init(const ITensorInfo *input, ITensorInfo *output, unsigned int poole output_shape.set(0, pooled_w); output_shape.set(1, pooled_h); - auto_init_if_empty(*output, output_shape, 1, input->data_type(), input->fixed_point_position(), input->quantization_info()); + auto_init_if_empty(*output, input->clone()->set_tensor_shape(output_shape)); } Error validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const PoolingLayerInfo &pool_info) diff --git a/src/core/CL/kernels/CLSoftmaxLayerKernel.cpp b/src/core/CL/kernels/CLSoftmaxLayerKernel.cpp index 5d71424189..71f375f007 100644 --- a/src/core/CL/kernels/CLSoftmaxLayerKernel.cpp +++ b/src/core/CL/kernels/CLSoftmaxLayerKernel.cpp @@ -78,33 +78,250 @@ CLBuildOptions prepare_quantized_softmax_build_options(float input_scale, float return build_opts; } + +// Arguments Validation + +Error validate_arguments_1DMax(const ITensorInfo *input, const ITensorInfo *output) +{ + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QASYMM8, DataType::QS16, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output); + + // Checks performed when output is configured + if(output->total_size() != 0) + { + // Softmax across the x dimension + TensorShape output_shape{ input->tensor_shape() }; + output_shape.set(0, 1); + + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(input, output); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape); + } + + return Error{}; +} + +Error validate_arguments_1DShiftExpSum(const ITensorInfo *input, const ITensorInfo *max, const ITensorInfo *output, const ITensorInfo *sum) +{ + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QASYMM8, DataType::QS16, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(max, sum, output); + + const bool is_quantized_asymmetric = is_data_type_quantized_asymmetric(input->data_type()); + + // Checks performed when output is configured + if(output->total_size() != 0) + { + if(is_quantized_asymmetric) + { + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::S32); + } + else + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); + } + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(input, output); + } + + // Checks performed when sum is configured + if(sum->total_size() != 0) + { + if(is_quantized_asymmetric) + { + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(sum, 1, DataType::S32); + } + else + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(max, sum); + } + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(max, sum); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(max, sum); + } + + return Error{}; +} + +Error validate_arguments_1DMaxShiftExpSum(const ITensorInfo *input, const ITensorInfo *max, const ITensorInfo *output, const ITensorInfo *sum) +{ + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(max, sum, output); + + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, max); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(input, max); + + // Checks performed when output is configured + if(output->total_size() != 0) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(input, output); + } + + // Checks performed when sum is configured + if(sum->total_size() != 0) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(max, sum); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(max, sum); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(max, sum); + } + + return Error{}; +} + +Error validate_arguments_1DNorm(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output) +{ + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QS16, DataType::S32, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(sum, output); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, sum); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(input, sum); + + // Note: output should always have a scale of 1/256 and offset 0 + const QuantizationInfo allowed_quantization_info = QuantizationInfo(1.f / 256, 0); + const bool is_quantized_asymmetric = (input->data_type() == DataType::S32); + + // Checks performed when output is configured + if(output->total_size() != 0) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(input, output); + if(!is_quantized_asymmetric) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); + } + else + { + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::QASYMM8); + ARM_COMPUTE_RETURN_ERROR_ON(output->quantization_info() != allowed_quantization_info); + } + } + + return Error{}; +} + +// Window validation + +std::pair<Error, Window> validate_and_configure_window_1DMax(ITensorInfo *input, ITensorInfo *output) +{ + TensorShape output_shape{ input->tensor_shape() }; + output_shape.set(0, 1); + + // Output auto initialization if not yet initialized + auto_init_if_empty(*output, input->clone()->set_tensor_shape(output_shape)); + + // The kernel loops over all elements in steps of 16 + const unsigned int num_elems_processed_per_iteration = ceil_to_multiple(input->dimension(0), 16); + constexpr unsigned int num_elems_written_per_iteration = 1; + + Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration)); + AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration); + AccessWindowHorizontal output_access(output, 0, num_elems_written_per_iteration); + + bool window_changed = update_window_and_padding(win, input_access, output_access); + + output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape())); + + Error err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Error{}; + return std::make_pair(err, win); +} + +std::pair<Error, Window> validate_and_configure_window_1DShiftExpSum(ITensorInfo *input, ITensorInfo *max, ITensorInfo *output, ITensorInfo *sum) +{ + const bool is_quantized_asymmetric = is_data_type_quantized_asymmetric(input->data_type()); + const DataType tmp_data_type = is_quantized_asymmetric ? DataType::S32 : input->data_type(); + + // Output auto initialization if not yet initialized + auto_init_if_empty(*sum, max->clone()->set_data_type(tmp_data_type).set_fixed_point_position(input->fixed_point_position())); + auto_init_if_empty(*output, input->clone()->set_data_type(tmp_data_type)); + + // The kernel loops over all elements in steps of 16 + const unsigned int num_elems_processed_per_iteration = ceil_to_multiple(input->dimension(0), 16); + + Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration)); + + AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration); + AccessWindowHorizontal max_access(max, 0, 1); + AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration); + AccessWindowHorizontal sum_access(sum, 0, 1); + + bool window_changed = update_window_and_padding(win, input_access, max_access, output_access, sum_access); + + output_access.set_valid_region(win, input->valid_region()); + sum_access.set_valid_region(win, ValidRegion(Coordinates(), sum->tensor_shape())); + + Error err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Error{}; + return std::make_pair(err, win); +} + +std::pair<Error, Window> validate_and_configure_window_1DMaxShiftExpSum(ITensorInfo *input, ITensorInfo *max, ITensorInfo *output, ITensorInfo *sum) +{ + // Output auto initialization if not yet initialized + auto_init_if_empty(*sum, input->clone()->set_tensor_shape(max->tensor_shape())); + auto_init_if_empty(*output, *input->clone()); + + CLLogits1DMaxShiftExpSumKernel::ParallelReductionInfo parallel_reduction_info = CLLogits1DMaxShiftExpSumKernel::is_parallel_reduction(input->dimension(0)); + unsigned int vector_size = std::get<1>(parallel_reduction_info); + const unsigned int num_elems_x = ceil_to_multiple(input->tensor_shape().x(), vector_size); + Window win = calculate_max_window(*input, Steps(num_elems_x)); + + AccessWindowHorizontal input_access(input, 0, num_elems_x); + AccessWindowHorizontal max_access(max, 0, 1); + AccessWindowHorizontal output_access(output, 0, num_elems_x); + AccessWindowHorizontal sum_access(sum, 0, 1); + + bool window_changed = update_window_and_padding(win, input_access, max_access, output_access, sum_access); + + output_access.set_valid_region(win, input->valid_region()); + sum_access.set_valid_region(win, ValidRegion(Coordinates(), sum->tensor_shape())); + + Error err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Error{}; + return std::make_pair(err, win); +} + +std::pair<Error, Window> validate_and_configure_window_1DNorm(ITensorInfo *input, ITensorInfo *output, ITensorInfo *sum) +{ + const QuantizationInfo allowed_quantization_info = QuantizationInfo(1.f / 256, 0); + const bool is_quantized_asymmetric = (input->data_type() == DataType::S32); + const DataType output_data_type = is_quantized_asymmetric ? DataType::QASYMM8 : input->data_type(); + + // Output auto initialization if not yet initialized + auto_init_if_empty(*output, + input->clone()->set_data_type(output_data_type).set_quantization_info(allowed_quantization_info)); + + constexpr unsigned int num_elems_processed_per_iteration = 16; + + Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration)); + + AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration); + AccessWindowStatic sum_access(sum, 0, 0, 1, sum->dimension(1)); + AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration); + + bool window_changed = update_window_and_padding(win, input_access, sum_access, output_access); + + output_access.set_valid_region(win, input->valid_region()); + + Error err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Error{}; + return std::make_pair(err, win); +} + } // namespace void CLLogits1DMaxKernel::configure(const ICLTensor *input, ICLTensor *output) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); - // Softmax across the x dimension TensorShape output_shape{ input->info()->tensor_shape() }; output_shape.set(0, 1); // Output auto initialization if not yet initialized - auto_init_if_empty(*output->info(), - output_shape, - 1, - input->info()->data_type(), - input->info()->fixed_point_position(), - input->info()->quantization_info()); + auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape)); // Perform validation step - ARM_COMPUTE_ERROR_THROW_ON(CLLogits1DMaxKernel::validate(input->info(), output->info())); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_1DMax(input->info(), output->info())); _input = input; _output = output; const DataType data_type = input->info()->data_type(); - // The kernel loops over all elements in steps of 16 - const unsigned int num_elems_processed_per_iteration = ceil_to_multiple(input->info()->dimension(0), 16); // Set build options CLBuildOptions build_opts; @@ -124,17 +341,9 @@ void CLLogits1DMaxKernel::configure(const ICLTensor *input, ICLTensor *output) _kernel.setArg<cl_uint>(idx++, input->info()->dimension(0)); // Configure kernel window - constexpr unsigned int num_elems_written_per_iteration = 1; - - Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration)); - AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration); - AccessWindowHorizontal output_access(output->info(), 0, num_elems_written_per_iteration); - - update_window_and_padding(win, input_access, output_access); - - output_access.set_valid_region(win, ValidRegion(Coordinates(), output->info()->tensor_shape())); - - ICLKernel::configure(win); + auto win_config = validate_and_configure_window_1DMax(input->info(), output->info()); + ARM_COMPUTE_ERROR_THROW_ON(win_config.first); + ICLKernel::configure(win_config.second); // Set config_id for enabling LWS tuning _config_id = "softmax_layer_"; @@ -147,20 +356,8 @@ void CLLogits1DMaxKernel::configure(const ICLTensor *input, ICLTensor *output) Error CLLogits1DMaxKernel::validate(const ITensorInfo *input, const ITensorInfo *output) { - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QASYMM8, DataType::QS16, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output); - - // Checks performed when output is configured - if(output->total_size() != 0) - { - // Softmax across the x dimension - TensorShape output_shape{ input->tensor_shape() }; - output_shape.set(0, 1); - - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(input, output); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape); - } + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_1DMax(input, output)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window_1DMax(input->clone().get(), output->clone().get()).first); return Error{}; } @@ -178,11 +375,11 @@ void CLLogits1DShiftExpSumKernel::configure(const ICLTensor *input, const ICLTen const DataType tmp_data_type = is_quantized_asymmetric ? DataType::S32 : input->info()->data_type(); // Output auto initialization if not yet initialized - auto_init_if_empty(*sum->info(), max->info()->tensor_shape(), 1, tmp_data_type, input->info()->fixed_point_position()); - auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, tmp_data_type, input->info()->fixed_point_position()); + auto_init_if_empty(*sum->info(), max->info()->clone()->set_data_type(tmp_data_type).set_fixed_point_position(input->info()->fixed_point_position())); + auto_init_if_empty(*output->info(), input->info()->clone()->set_data_type(tmp_data_type)); // Perform validation step - ARM_COMPUTE_ERROR_THROW_ON(CLLogits1DShiftExpSumKernel::validate(input->info(), max->info(), output->info(), sum->info())); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_1DShiftExpSum(input->info(), max->info(), output->info(), sum->info())); _input = input; _max = max; @@ -192,9 +389,6 @@ void CLLogits1DShiftExpSumKernel::configure(const ICLTensor *input, const ICLTen const DataType dt = input->info()->data_type(); auto beta_int = static_cast<int>(lround(beta * (1 << input->info()->fixed_point_position()))); - // The kernel loops over all elements in steps of 16 - const unsigned int num_elems_processed_per_iteration = ceil_to_multiple(input->info()->dimension(0), 16); - // Set build options CLBuildOptions build_opts; build_opts.add_option(std::string("-DDATA_TYPE=" + get_cl_type_from_data_type(dt))); @@ -217,57 +411,15 @@ void CLLogits1DShiftExpSumKernel::configure(const ICLTensor *input, const ICLTen _kernel.setArg<cl_uint>(idx++, input->info()->dimension(0)); // Configure window - Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration)); - - AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration); - AccessWindowHorizontal max_access(max->info(), 0, 1); - AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration); - AccessWindowHorizontal sum_access(sum->info(), 0, 1); - - update_window_and_padding(win, input_access, max_access, output_access, sum_access); - - output_access.set_valid_region(win, input->info()->valid_region()); - sum_access.set_valid_region(win, ValidRegion(Coordinates(), sum->info()->tensor_shape())); - - ICLKernel::configure(win); + auto win_config = validate_and_configure_window_1DShiftExpSum(input->info(), max->info(), output->info(), sum->info()); + ARM_COMPUTE_ERROR_THROW_ON(win_config.first); + ICLKernel::configure(win_config.second); } Error CLLogits1DShiftExpSumKernel::validate(const ITensorInfo *input, const ITensorInfo *max, const ITensorInfo *output, const ITensorInfo *sum) { - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QASYMM8, DataType::QS16, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(max, sum, output); - - const bool is_quantized_asymmetric = is_data_type_quantized_asymmetric(input->data_type()); - - // Checks performed when output is configured - if(output->total_size() != 0) - { - if(is_quantized_asymmetric) - { - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::S32); - } - else - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); - } - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(input, output); - } - - // Checks performed when sum is configured - if(sum->total_size() != 0) - { - if(is_quantized_asymmetric) - { - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(sum, 1, DataType::S32); - } - else - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(max, sum); - } - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(max, sum); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(max, sum); - } + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_1DShiftExpSum(input, max, output, sum)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window_1DShiftExpSum(input->clone().get(), max->clone().get(), output->clone().get(), sum->clone().get()).first); return Error{}; } @@ -310,11 +462,11 @@ void CLLogits1DMaxShiftExpSumKernel::configure(const ICLTensor *input, ICLTensor ARM_COMPUTE_ERROR_ON_NULLPTR(input, max, sum, output); // Output auto initialization if not yet initialized - auto_init_if_empty(*sum->info(), max->info()->tensor_shape(), 1, input->info()->data_type(), input->info()->fixed_point_position()); - auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, input->info()->data_type(), input->info()->fixed_point_position()); + auto_init_if_empty(*sum->info(), input->info()->clone()->set_tensor_shape(max->info()->tensor_shape())); + auto_init_if_empty(*output->info(), *input->info()->clone()); // Perform validation step - ARM_COMPUTE_ERROR_THROW_ON(CLLogits1DMaxShiftExpSumKernel::validate(input->info(), max->info(), output->info(), sum->info())); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_1DMaxShiftExpSum(input->info(), max->info(), output->info(), sum->info())); _input = input; _max = max; @@ -366,45 +518,15 @@ void CLLogits1DMaxShiftExpSumKernel::configure(const ICLTensor *input, ICLTensor _kernel.setArg<cl_uint>(idx++, reduction_dim_size); // Configure window - const unsigned int num_elems_x = ceil_to_multiple(input->info()->tensor_shape().x(), vector_size); - Window win = calculate_max_window(*input->info(), Steps(num_elems_x)); - - AccessWindowHorizontal input_access(input->info(), 0, num_elems_x); - AccessWindowHorizontal max_access(max->info(), 0, 1); - AccessWindowHorizontal output_access(output->info(), 0, num_elems_x); - AccessWindowHorizontal sum_access(sum->info(), 0, 1); - - update_window_and_padding(win, input_access, max_access, output_access, sum_access); - - output_access.set_valid_region(win, input->info()->valid_region()); - sum_access.set_valid_region(win, ValidRegion(Coordinates(), sum->info()->tensor_shape())); - - ICLKernel::configure(win); + auto win_config = validate_and_configure_window_1DMaxShiftExpSum(input->info(), max->info(), output->info(), sum->info()); + ARM_COMPUTE_ERROR_THROW_ON(win_config.first); + ICLKernel::configure(win_config.second); } Error CLLogits1DMaxShiftExpSumKernel::validate(const ITensorInfo *input, const ITensorInfo *max, const ITensorInfo *output, const ITensorInfo *sum) { - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(max, sum, output); - - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, max); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(input, max); - - // Checks performed when output is configured - if(output->total_size() != 0) - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(input, output); - } - - // Checks performed when sum is configured - if(sum->total_size() != 0) - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(max, sum); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(max, sum); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(max, sum); - } + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_1DMaxShiftExpSum(input, max, output, sum)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window_1DMaxShiftExpSum(input->clone().get(), max->clone().get(), output->clone().get(), sum->clone().get()).first); return Error{}; } @@ -467,7 +589,7 @@ void CLLogits1DNormKernel::configure(const ICLTensor *input, const ICLTensor *su input->info()->clone()->set_data_type(output_data_type).set_quantization_info(allowed_quantization_info)); // Perform validation step - ARM_COMPUTE_ERROR_THROW_ON(CLLogits1DNormKernel::validate(input->info(), sum->info(), output->info())); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_1DNorm(input->info(), sum->info(), output->info())); _input = input; _sum = sum; @@ -486,47 +608,15 @@ void CLLogits1DNormKernel::configure(const ICLTensor *input, const ICLTensor *su _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options())); // Configure window - constexpr unsigned int num_elems_processed_per_iteration = 16; - - Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration)); - - AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration); - AccessWindowStatic sum_access(sum->info(), 0, 0, 1, sum->info()->dimension(1)); - AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration); - - update_window_and_padding(win, input_access, sum_access, output_access); - - output_access.set_valid_region(win, input->info()->valid_region()); - - ICLKernel::configure(win); + auto win_config = validate_and_configure_window_1DNorm(input->info(), output->info(), sum->info()); + ARM_COMPUTE_ERROR_THROW_ON(win_config.first); + ICLKernel::configure(win_config.second); } Error CLLogits1DNormKernel::validate(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output) { - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QS16, DataType::S32, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(sum, output); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, sum); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(input, sum); - - // Note: output should always have a scale of 1/256 and offset 0 - const QuantizationInfo allowed_quantization_info = QuantizationInfo(1.f / 256, 0); - const bool is_quantized_asymmetric = (input->data_type() == DataType::S32); - - // Checks performed when output is configured - if(output->total_size() != 0) - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(input, output); - if(!is_quantized_asymmetric) - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); - } - else - { - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::QASYMM8); - ARM_COMPUTE_RETURN_ERROR_ON(output->quantization_info() != allowed_quantization_info); - } - } + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_1DNorm(input, sum, output)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window_1DNorm(input->clone().get(), output->clone().get(), sum->clone().get()).first); return Error{}; } diff --git a/tests/validation/CL/SoftmaxLayer.cpp b/tests/validation/CL/SoftmaxLayer.cpp index b935ef55a0..f43e680c9b 100644 --- a/tests/validation/CL/SoftmaxLayer.cpp +++ b/tests/validation/CL/SoftmaxLayer.cpp @@ -118,9 +118,10 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip( TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 2), // Mismatching fixed point TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8, // Invalid output quantization info QuantizationInfo(1.f/256, 12)), - TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), - TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 3), - TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8, + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Window shrink + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 3), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QASYMM8, QuantizationInfo(1.f/256, 12)), }), framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F16), @@ -129,14 +130,15 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip( TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8, QuantizationInfo(1.f/256, 12)), TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), - TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 3), - TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8, + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 3), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QASYMM8, QuantizationInfo(1.f/256, 0)), })), - framework::dataset::make("Expected", { true, true, true, true, false, false, false })), + framework::dataset::make("Expected", { true, true, true, true, true, false, false, false })), input_info, output_info, expected) { - ARM_COMPUTE_EXPECT(bool(CLSoftmaxLayer::validate(&input_info, &output_info)) == expected, framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(bool(CLSoftmaxLayer::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false))) == expected, framework::LogLevel::ERRORS); } // clang-format on // *INDENT-ON* |