COMPMID-617 Add validation window to CLSoftmaxLayer
Change-Id: Iaa99b8950c148e39333fa663db5f862a982f3765
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/111130
Tested-by: BSG Visual Compute Jenkins server to access repositories on http://mpd-gerrit.cambridge.arm.com <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
diff --git a/src/core/CL/kernels/CLPoolingLayerKernel.cpp b/src/core/CL/kernels/CLPoolingLayerKernel.cpp
index 7fd2689..b0942e5 100644
--- a/src/core/CL/kernels/CLPoolingLayerKernel.cpp
+++ b/src/core/CL/kernels/CLPoolingLayerKernel.cpp
@@ -52,7 +52,7 @@
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 5d71424..71f375f 100644
--- a/src/core/CL/kernels/CLSoftmaxLayerKernel.cpp
+++ b/src/core/CL/kernels/CLSoftmaxLayerKernel.cpp
@@ -78,74 +78,10 @@
return build_opts;
}
-} // namespace
-void CLLogits1DMaxKernel::configure(const ICLTensor *input, ICLTensor *output)
-{
- ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
+// Arguments Validation
- // 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());
-
- // Perform validation step
- ARM_COMPUTE_ERROR_THROW_ON(CLLogits1DMaxKernel::validate(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;
- build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(data_type));
- build_opts.add_option_if(is_data_type_fixed_point(data_type),
- "-DFIXED_POINT_POSITION=" + support::cpp11::to_string(input->info()->fixed_point_position()));
- build_opts.add_option_if(data_type == DataType::F16, "-DUSE_F16");
- // Tell the kernel that the width is not a multiple of 16
- build_opts.add_option_if((input->info()->dimension(0) % max_cl_vector_width) != 0, "-DNON_MULTIPLE_OF_16");
-
- // Create kernel
- std::string kernel_name = is_data_type_quantized_asymmetric(data_type) ? "softmax_layer_max_quantized" : "softmax_layer_max";
- _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
-
- // Set fixed arguments
- unsigned int idx = 2 * num_arguments_per_3D_tensor(); //Skip the input and output parameters
- _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);
-
- // Set config_id for enabling LWS tuning
- _config_id = "softmax_layer_";
- _config_id += lower_string(string_from_data_type(data_type));
- _config_id += "_";
- _config_id += support::cpp11::to_string(input->info()->dimension(0));
- _config_id += "_";
- _config_id += support::cpp11::to_string(input->info()->dimension(1));
-}
-
-Error CLLogits1DMaxKernel::validate(const ITensorInfo *input, const ITensorInfo *output)
+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);
@@ -165,74 +101,7 @@
return Error{};
}
-CLLogits1DShiftExpSumKernel::CLLogits1DShiftExpSumKernel()
- : _input(nullptr), _max(nullptr), _output(nullptr), _sum(nullptr)
-{
-}
-
-void CLLogits1DShiftExpSumKernel::configure(const ICLTensor *input, const ICLTensor *max, ICLTensor *output, ICLTensor *sum, float beta)
-{
- ARM_COMPUTE_ERROR_ON_NULLPTR(input, max, sum, output);
-
- const bool is_quantized_asymmetric = is_data_type_quantized_asymmetric(input->info()->data_type());
- 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());
-
- // Perform validation step
- ARM_COMPUTE_ERROR_THROW_ON(CLLogits1DShiftExpSumKernel::validate(input->info(), max->info(), output->info(), sum->info()));
-
- _input = input;
- _max = max;
- _output = output;
- _sum = sum;
-
- 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)));
- build_opts.add_option_if(is_data_type_fixed_point(dt),
- std::string("-DFIXED_POINT_POSITION=" + support::cpp11::to_string(input->info()->fixed_point_position())));
- build_opts.add_option_if(dt == DataType::F16, std::string("-DUSE_F16"));
- // Tell the kernel that the width is not a multiple of 16
- build_opts.add_option_if((input->info()->dimension(0) % max_cl_vector_width) != 0, std::string("-DNON_MULTIPLE_OF_16"));
- build_opts.add_option_if(is_data_type_fixed_point(dt) && (beta != 1.0f), std::string("-DBETA=" + support::cpp11::to_string(beta_int)));
- build_opts.add_option_if(is_data_type_float(dt) && (beta != 1.0f), std::string("-DBETA=" + float_to_string_with_full_precision(beta)));
- build_opts.add_options_if(is_quantized_asymmetric,
- prepare_quantized_softmax_build_options(input->info()->quantization_info().scale, beta).options());
-
- // Create kernel
- std::string kernel_name = is_quantized_asymmetric ? "softmax_layer_shift_exp_sum_quantized" : "softmax_layer_shift_exp_sum";
- _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
-
- // Set fixed arguments
- unsigned int idx = 4 * num_arguments_per_3D_tensor(); //Skip the input and output parameters
- _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);
-}
-
-Error CLLogits1DShiftExpSumKernel::validate(const ITensorInfo *input, const ITensorInfo *max, const ITensorInfo *output, const ITensorInfo *sum)
+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);
@@ -272,6 +141,289 @@
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);
+
+ 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(), input->info()->clone()->set_tensor_shape(output_shape));
+
+ // Perform validation step
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_1DMax(input->info(), output->info()));
+
+ _input = input;
+ _output = output;
+
+ const DataType data_type = input->info()->data_type();
+
+ // Set build options
+ CLBuildOptions build_opts;
+ build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(data_type));
+ build_opts.add_option_if(is_data_type_fixed_point(data_type),
+ "-DFIXED_POINT_POSITION=" + support::cpp11::to_string(input->info()->fixed_point_position()));
+ build_opts.add_option_if(data_type == DataType::F16, "-DUSE_F16");
+ // Tell the kernel that the width is not a multiple of 16
+ build_opts.add_option_if((input->info()->dimension(0) % max_cl_vector_width) != 0, "-DNON_MULTIPLE_OF_16");
+
+ // Create kernel
+ std::string kernel_name = is_data_type_quantized_asymmetric(data_type) ? "softmax_layer_max_quantized" : "softmax_layer_max";
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+
+ // Set fixed arguments
+ unsigned int idx = 2 * num_arguments_per_3D_tensor(); //Skip the input and output parameters
+ _kernel.setArg<cl_uint>(idx++, input->info()->dimension(0));
+
+ // Configure kernel window
+ 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_";
+ _config_id += lower_string(string_from_data_type(data_type));
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(input->info()->dimension(0));
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(input->info()->dimension(1));
+}
+
+Error CLLogits1DMaxKernel::validate(const ITensorInfo *input, const ITensorInfo *output)
+{
+ 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{};
+}
+
+CLLogits1DShiftExpSumKernel::CLLogits1DShiftExpSumKernel()
+ : _input(nullptr), _max(nullptr), _output(nullptr), _sum(nullptr)
+{
+}
+
+void CLLogits1DShiftExpSumKernel::configure(const ICLTensor *input, const ICLTensor *max, ICLTensor *output, ICLTensor *sum, float beta)
+{
+ ARM_COMPUTE_ERROR_ON_NULLPTR(input, max, sum, output);
+
+ const bool is_quantized_asymmetric = is_data_type_quantized_asymmetric(input->info()->data_type());
+ 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()->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(validate_arguments_1DShiftExpSum(input->info(), max->info(), output->info(), sum->info()));
+
+ _input = input;
+ _max = max;
+ _output = output;
+ _sum = sum;
+
+ const DataType dt = input->info()->data_type();
+ auto beta_int = static_cast<int>(lround(beta * (1 << input->info()->fixed_point_position())));
+
+ // Set build options
+ CLBuildOptions build_opts;
+ build_opts.add_option(std::string("-DDATA_TYPE=" + get_cl_type_from_data_type(dt)));
+ build_opts.add_option_if(is_data_type_fixed_point(dt),
+ std::string("-DFIXED_POINT_POSITION=" + support::cpp11::to_string(input->info()->fixed_point_position())));
+ build_opts.add_option_if(dt == DataType::F16, std::string("-DUSE_F16"));
+ // Tell the kernel that the width is not a multiple of 16
+ build_opts.add_option_if((input->info()->dimension(0) % max_cl_vector_width) != 0, std::string("-DNON_MULTIPLE_OF_16"));
+ build_opts.add_option_if(is_data_type_fixed_point(dt) && (beta != 1.0f), std::string("-DBETA=" + support::cpp11::to_string(beta_int)));
+ build_opts.add_option_if(is_data_type_float(dt) && (beta != 1.0f), std::string("-DBETA=" + float_to_string_with_full_precision(beta)));
+ build_opts.add_options_if(is_quantized_asymmetric,
+ prepare_quantized_softmax_build_options(input->info()->quantization_info().scale, beta).options());
+
+ // Create kernel
+ std::string kernel_name = is_quantized_asymmetric ? "softmax_layer_shift_exp_sum_quantized" : "softmax_layer_shift_exp_sum";
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+
+ // Set fixed arguments
+ unsigned int idx = 4 * num_arguments_per_3D_tensor(); //Skip the input and output parameters
+ _kernel.setArg<cl_uint>(idx++, input->info()->dimension(0));
+
+ // Configure window
+ 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_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{};
+}
+
void CLLogits1DShiftExpSumKernel::run(const Window &window, cl::CommandQueue &queue)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
@@ -310,11 +462,11 @@
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 @@
_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 @@
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 @@
_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{};
}