COMPMID-617: Adds CLFullyConnectionLayer validation support
Change-Id: I4d2eb9872a3165fdcaa7784596e441cbe563dbc2
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/112577
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Ioan-Cristian Szabo <ioan-cristian.szabo@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
diff --git a/src/core/CL/kernels/CLGEMMInterleave4x4Kernel.cpp b/src/core/CL/kernels/CLGEMMInterleave4x4Kernel.cpp
index 7741f12..6886f54 100644
--- a/src/core/CL/kernels/CLGEMMInterleave4x4Kernel.cpp
+++ b/src/core/CL/kernels/CLGEMMInterleave4x4Kernel.cpp
@@ -33,8 +33,55 @@
#include "arm_compute/core/Utils.h"
#include "arm_compute/core/Validate.h"
#include "arm_compute/core/Window.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
using namespace arm_compute;
+using namespace arm_compute::misc::shape_calculator;
+
+namespace
+{
+Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QASYMM8, DataType::U8, DataType::S8,
+ DataType::QS16, DataType::U16, DataType::S16, DataType::U32, DataType::S32,
+ DataType::F16, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, output);
+
+ if(output->total_size() != 0)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), compute_interleaved_shape(*input));
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, output);
+ }
+
+ return Status{};
+}
+
+std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output)
+{
+ unsigned int num_elems_processed_per_iteration_x = max_cl_vector_width / data_size_from_type(input->data_type());
+ constexpr unsigned int num_elems_processed_per_iteration_y = 4;
+ const unsigned int num_elems_written_per_iteration = num_elems_processed_per_iteration_x * num_elems_processed_per_iteration_y;
+ bool window_changed = false;
+
+ // Configure kernel window
+ Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
+ AccessWindowRectangle input_access(input, 0, 0, num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y);
+ window_changed = window_changed || update_window_and_padding(win, input_access);
+
+ // Configure window in case of configured output
+ if(output->total_size() != 0)
+ {
+ AccessWindowRectangle output_access(output, 0, 0, num_elems_written_per_iteration, 1, 4.f, 0.25f);
+ window_changed = window_changed || update_window_and_padding(win, output_access);
+ output_access.set_valid_region(win, input->valid_region());
+ }
+
+ Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
+ return std::make_pair(err, win);
+}
+} // namespace
CLGEMMInterleave4x4Kernel::CLGEMMInterleave4x4Kernel()
: _input(nullptr), _output(nullptr)
@@ -43,22 +90,13 @@
void CLGEMMInterleave4x4Kernel::configure(const ICLTensor *input, ICLTensor *output)
{
- ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::S8, DataType::QS8, DataType::QASYMM8,
- DataType::U16, DataType::S16, DataType::QS16,
- DataType::U32, DataType::S32,
- DataType::F16, DataType::F32);
- ARM_COMPUTE_ERROR_ON_NULLPTR(output);
-
- TensorShape output_shape = input->info()->tensor_shape();
- output_shape.set(0, input->info()->dimension(0) * 4);
- output_shape.set(1, std::ceil(input->info()->dimension(1) / 4.0f));
+ ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
// Output auto inizialitation if not yet initialized
- auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape));
+ auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(compute_interleaved_shape(*input->info())));
- ARM_COMPUTE_ERROR_ON_MISMATCHING_DIMENSIONS(output->info()->tensor_shape(), output_shape);
- ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
- ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input, output);
+ // Perform validate step
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info()));
_input = input;
_output = output;
@@ -68,20 +106,9 @@
_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name));
// Configure kernel window
- const unsigned int num_elems_processed_per_iteration_x = max_cl_vector_width / data_size_from_type(input->info()->data_type());
- constexpr unsigned int num_elems_processed_per_iteration_y = 4;
- const unsigned int num_elems_written_per_iteration = num_elems_processed_per_iteration_x * num_elems_processed_per_iteration_y;
-
- Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
-
- AccessWindowRectangle input_access(input->info(), 0, 0, num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y);
- AccessWindowRectangle output_access(output->info(), 0, 0, num_elems_written_per_iteration, 1, 4.f, 0.25f);
-
- update_window_and_padding(win, input_access, output_access);
-
- output_access.set_valid_region(win, input->info()->valid_region());
-
- ICLKernel::configure(win);
+ auto win_config = validate_and_configure_window(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 = "interleave4x4_";
@@ -92,6 +119,14 @@
_config_id += support::cpp11::to_string(output->info()->dimension(1));
}
+Status CLGEMMInterleave4x4Kernel::validate(const ITensorInfo *input, const ITensorInfo *output)
+{
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get()).first);
+
+ return Status{};
+}
+
void CLGEMMInterleave4x4Kernel::run(const Window &window, cl::CommandQueue &queue)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
diff --git a/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.cpp b/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.cpp
index 1d9fe4b..423592b 100644
--- a/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.cpp
@@ -46,6 +46,76 @@
class Coordinates;
} // namespace arm_compute
+namespace
+{
+using ElementsProcessed = Steps;
+
+Status validate_arguments(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, bool is_interleaved_transposed)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::QASYMM8);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::QASYMM8);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::S32);
+ if(!is_interleaved_transposed)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON(input0->dimension(0) != input1->dimension(1));
+ }
+
+ return Status{};
+}
+
+std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input0, ITensorInfo *input1, ITensorInfo *output, bool is_interleaved_transposed,
+ ElementsProcessed &num_elements_processed)
+{
+ unsigned int &num_elems_processed_per_iteration_x = num_elements_processed[0];
+ unsigned int &num_elems_processed_per_iteration_y = num_elements_processed[1];
+
+ Window win{};
+ bool window_changed = false;
+
+ // Check if the output tensor is a vector. If so,the kernel runs the vector-matrix multiplication
+ if(is_interleaved_transposed)
+ {
+ // Configure window
+ num_elems_processed_per_iteration_x = 16;
+ num_elems_processed_per_iteration_y = 4;
+ constexpr unsigned int num_elems_read_per_iteration_input0 = 4;
+ constexpr unsigned int num_elems_read_per_iteration_input1 = 16;
+
+ win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
+
+ AccessWindowRectangle input0_access(input0, 0, 0, num_elems_read_per_iteration_input0, 1);
+ AccessWindowRectangle input1_access(input1, 0, 0, num_elems_read_per_iteration_input1, 1);
+ AccessWindowRectangle output_access(output, 0, 0, num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y);
+
+ window_changed = update_window_and_padding(win, input0_access, input1_access, output_access);
+
+ output_access.set_valid_region(win, ValidRegion(Coordinates(0, 0), output->tensor_shape()));
+ }
+ else
+ {
+ // Special case for 1xN, 2xN, 3xN and 4xN input0 tensor. num_elems_processed_per_iteration_x
+ num_elems_processed_per_iteration_x = 16;
+ num_elems_processed_per_iteration_y = std::min(static_cast<int>(output->dimension(1)), 4);
+
+ // Configure window
+ win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
+
+ AccessWindowStatic input0_access(input0, 0, 0, input0->dimension(0), ceil_to_multiple(input0->dimension(1), num_elems_processed_per_iteration_y));
+ AccessWindowStatic input1_access(input1, 0, 0, ceil_to_multiple(input1->dimension(0), num_elems_processed_per_iteration_x), input1->dimension(1));
+ AccessWindowRectangle output_access(output, 0, 0, num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y);
+
+ window_changed = update_window_and_padding(win, input0_access, input1_access, output_access);
+
+ Coordinates coord;
+ coord.set_num_dimensions(output->num_dimensions());
+ output_access.set_valid_region(win, ValidRegion(coord, output->tensor_shape()));
+ }
+
+ Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
+ return std::make_pair(err, win);
+}
+} // namespace
+
CLGEMMLowpMatrixMultiplyKernel::CLGEMMLowpMatrixMultiplyKernel()
: _input0(nullptr), _input1(nullptr), _output(nullptr)
{
@@ -53,72 +123,37 @@
void CLGEMMLowpMatrixMultiplyKernel::configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, bool is_interleaved_transposed)
{
- ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::QASYMM8);
- ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::QASYMM8);
- ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::S32);
-
- if(!is_interleaved_transposed)
- {
- ARM_COMPUTE_ERROR_ON(input0->info()->dimension(0) != input1->info()->dimension(1));
- }
+ ARM_COMPUTE_ERROR_ON_NULLPTR(input0, input1, output);
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input0->info(), input1->info(), output->info(), is_interleaved_transposed));
_input0 = input0;
_input1 = input1;
_output = output;
- CLBuildOptions build_opts;
+ ElementsProcessed num_elements_processed{};
+ // Configure kernel window
+ auto win_config = validate_and_configure_window(input0->info(), input1->info(), output->info(), is_interleaved_transposed, num_elements_processed);
+ ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
+ ICLKernel::configure(win_config.second);
+
+ // Create build options
+ CLBuildOptions build_opts;
+ std::string kernel_name(" ");
if(is_interleaved_transposed)
{
- // Create kernel and set static arguments
build_opts.add_option("-DCOLS_B=" + support::cpp11::to_string(input1->info()->dimension(0)));
- _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemmlowp_mm_interleaved_transposed", build_opts.options()));
-
- // Configure window
- constexpr unsigned int num_elems_processed_per_iteration_x = 16;
- constexpr unsigned int num_elems_processed_per_iteration_y = 4;
- constexpr unsigned int num_elems_read_per_iteration_input0 = 4;
- constexpr unsigned int num_elems_read_per_iteration_input1 = 16;
-
- Window win = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
-
- AccessWindowRectangle input0_access(input0->info(), 0, 0, num_elems_read_per_iteration_input0, 1);
- AccessWindowRectangle input1_access(input1->info(), 0, 0, num_elems_read_per_iteration_input1, 1);
- AccessWindowRectangle output_access(output->info(), 0, 0, num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y);
-
- update_window_and_padding(win, input0_access, input1_access, output_access);
-
- output_access.set_valid_region(win, ValidRegion(Coordinates(0, 0), output->info()->tensor_shape()));
-
- ICLKernel::configure(win);
+ kernel_name = "gemmlowp_mm_interleaved_transposed";
}
else
{
- // Special case for 1xN, 2xN, 3xN and 4xN input0 tensor. num_elems_processed_per_iteration_x
- constexpr unsigned int num_elems_processed_per_iteration_x = 16;
- const unsigned int num_elems_processed_per_iteration_y = std::min(static_cast<int>(output->info()->dimension(1)), 4);
-
build_opts.add_option("-DCOLS_A=" + support::cpp11::to_string(input0->info()->dimension(0)));
- build_opts.add_option("-DNUM_ELEMS_PROCESSED_PER_THREAD_X=" + support::cpp11::to_string(num_elems_processed_per_iteration_x));
- build_opts.add_option("-DNUM_ELEMS_PROCESSED_PER_THREAD_Y=" + support::cpp11::to_string(num_elems_processed_per_iteration_y));
-
- _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemmlowp_mm", build_opts.options()));
-
- // Configure window
- Window win = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
-
- AccessWindowStatic input0_access(input0->info(), 0, 0, input0->info()->dimension(0), ceil_to_multiple(input0->info()->dimension(1), num_elems_processed_per_iteration_y));
- AccessWindowStatic input1_access(input1->info(), 0, 0, ceil_to_multiple(input1->info()->dimension(0), num_elems_processed_per_iteration_x), input1->info()->dimension(1));
- AccessWindowRectangle output_access(output->info(), 0, 0, num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y);
-
- update_window_and_padding(win, input0_access, input1_access, output_access);
-
- Coordinates coord;
- coord.set_num_dimensions(output->info()->num_dimensions());
- output_access.set_valid_region(win, ValidRegion(coord, output->info()->tensor_shape()));
-
- ICLKernel::configure(win);
+ build_opts.add_option("-DNUM_ELEMS_PROCESSED_PER_THREAD_X=" + support::cpp11::to_string(num_elements_processed.x()));
+ build_opts.add_option("-DNUM_ELEMS_PROCESSED_PER_THREAD_Y=" + support::cpp11::to_string(num_elements_processed.y()));
+ kernel_name = "gemmlowp_mm";
}
+ // Create kernel
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
// Set config_id for enabling LWS tuning
_config_id = "gemmlowp_";
@@ -132,6 +167,20 @@
_config_id += (is_interleaved_transposed ? support::cpp11::to_string(input1->info()->dimension(0)) : support::cpp11::to_string(input1->info()->dimension(1)));
}
+Status CLGEMMLowpMatrixMultiplyKernel::validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, bool is_interleaved_transposed)
+{
+ ElementsProcessed num_elements_processed{};
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input0, input1, output, is_interleaved_transposed));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input0->clone().get(),
+ input1->clone().get(),
+ output->clone().get(),
+ is_interleaved_transposed,
+ num_elements_processed)
+ .first);
+
+ return Status{};
+}
+
void CLGEMMLowpMatrixMultiplyKernel::run(const Window &window, cl::CommandQueue &queue)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
diff --git a/src/core/CL/kernels/CLGEMMLowpOffsetContributionKernel.cpp b/src/core/CL/kernels/CLGEMMLowpOffsetContributionKernel.cpp
index 2877a74..d05939f 100644
--- a/src/core/CL/kernels/CLGEMMLowpOffsetContributionKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMLowpOffsetContributionKernel.cpp
@@ -44,6 +44,81 @@
class Coordinates;
} // namespace arm_compute
+namespace
+{
+Status validate_arguments(const ITensorInfo *mm_result, const ITensorInfo *vector_sum_col, const ITensorInfo *vector_sum_row,
+ int32_t a_offset, int32_t b_offset)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(mm_result, 1, DataType::S32);
+
+ // If a_offset == 0, vector_sum_col can be a nullptr
+ if(a_offset != 0)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(vector_sum_col, 1, DataType::S32);
+ ARM_COMPUTE_RETURN_ERROR_ON(vector_sum_col->dimension(0) != mm_result->dimension(0));
+ }
+
+ // If b_offset == 0, vector_sum_row can be a nullptr
+ if(b_offset != 0)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(vector_sum_row, 1, DataType::S32);
+ ARM_COMPUTE_RETURN_ERROR_ON(vector_sum_row->dimension(0) != mm_result->dimension(1));
+
+ TensorShape output_shape = mm_result->tensor_shape();
+ if(output_shape.num_dimensions() > 1)
+ {
+ TensorShape vector_sum_row_shape = vector_sum_row->tensor_shape();
+ vector_sum_row_shape.collapse_from(1);
+ output_shape.collapse_from(2);
+
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(vector_sum_row_shape[1] != output_shape[2],
+ "mm_result tensor must have the same number of batches of output tensor");
+
+ if(a_offset != 0)
+ {
+ TensorShape vector_sum_col_shape = vector_sum_col->tensor_shape();
+ vector_sum_col_shape.collapse_from(1);
+
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(vector_sum_col_shape[1] != 1 && vector_sum_col_shape[1] != vector_sum_row_shape[1],
+ "vector_sum_col tensor must have the same number of batches of vector_sum_row_shape or the number of batches must be set to 1");
+ }
+ }
+ }
+
+ return Status{};
+}
+
+std::pair<Status, Window> validate_and_configure_window(ITensorInfo *mm_result, ITensorInfo *vector_sum_col, ITensorInfo *vector_sum_row,
+ int32_t a_offset, int32_t b_offset)
+{
+ constexpr unsigned int num_elems_processed_per_iteration = 16;
+ bool window_changed = false;
+
+ // Configure kernel window
+ Window win = calculate_max_window(*mm_result, Steps(num_elems_processed_per_iteration));
+
+ AccessWindowHorizontal mm_result_access(mm_result, 0, num_elems_processed_per_iteration);
+ window_changed = window_changed || update_window_and_padding(win,
+ mm_result_access);
+
+ if(a_offset != 0)
+ {
+ AccessWindowHorizontal vector_sum_col_access(vector_sum_col, 0, num_elems_processed_per_iteration);
+ window_changed = window_changed || update_window_and_padding(win,
+ vector_sum_col_access);
+ }
+ if(b_offset != 0)
+ {
+ AccessWindowStatic vector_sum_row_access(vector_sum_row, 0, 0, vector_sum_row->dimension(0), 0); // NOLINT
+ window_changed = window_changed || update_window_and_padding(win,
+ vector_sum_row_access);
+ }
+
+ Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
+ return std::make_pair(err, win);
+}
+} // namespace
+
CLGEMMLowpOffsetContributionKernel::CLGEMMLowpOffsetContributionKernel()
: _vector_sum_col(nullptr), _vector_sum_row(nullptr), _mm_result(nullptr)
{
@@ -51,7 +126,16 @@
void CLGEMMLowpOffsetContributionKernel::configure(ICLTensor *mm_result, const ICLTensor *vector_sum_col, const ICLTensor *vector_sum_row, int32_t k, int32_t a_offset, int32_t b_offset)
{
- ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(mm_result, 1, DataType::S32);
+ // Perform validate step
+ ARM_COMPUTE_ERROR_ON_NULLPTR(mm_result);
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(mm_result->info(),
+ vector_sum_col != nullptr ? vector_sum_col->info() : nullptr,
+ vector_sum_row != nullptr ? vector_sum_row->info() : nullptr,
+ a_offset, b_offset)); // NOLINT
+
+ _vector_sum_col = vector_sum_col;
+ _vector_sum_row = vector_sum_row;
+ _mm_result = mm_result;
// Set the arguments to pass at compile time
CLBuildOptions build_opts;
@@ -59,74 +143,36 @@
// If a_offset == 0, vector_sum_col can be a nullptr
if(a_offset != 0)
{
- ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(vector_sum_col, 1, DataType::S32);
- ARM_COMPUTE_ERROR_ON(vector_sum_col->info()->dimension(0) != mm_result->info()->dimension(0));
-
build_opts.add_option("-DA_OFFSET=" + support::cpp11::to_string(a_offset));
build_opts.add_option_if(vector_sum_col->info()->tensor_shape().num_dimensions() > 1, "-DSUM_COL_HAS_BATCHES");
}
-
// If b_offset == 0, vector_sum_row can be a nullptr
- if(b_offset != 0)
- {
- ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(vector_sum_row, 1, DataType::S32);
- ARM_COMPUTE_ERROR_ON(vector_sum_row->info()->dimension(0) != mm_result->info()->dimension(1));
-
- // Validate batches
- TensorShape output_shape = mm_result->info()->tensor_shape();
- if(output_shape.num_dimensions() > 1)
- {
- TensorShape vector_sum_row_shape = vector_sum_row->info()->tensor_shape();
- vector_sum_row_shape.collapse_from(1);
- output_shape.collapse_from(2);
-
- ARM_COMPUTE_ERROR_ON_MSG(vector_sum_row_shape[1] != output_shape[2], "mm_result tensor must have the same number of batches of output tensor");
-
- if(a_offset != 0)
- {
- TensorShape vector_sum_col_shape = vector_sum_col->info()->tensor_shape();
- vector_sum_col_shape.collapse_from(1);
-
- ARM_COMPUTE_ERROR_ON_MSG(vector_sum_col_shape[1] != 1
- && vector_sum_col_shape[1] != vector_sum_row_shape[1],
- "vector_sum_col tensor must have the same number of batches of vector_sum_row_shape or the number of batches must be set to 1");
- }
- }
-
- build_opts.add_option("-DB_OFFSET=" + support::cpp11::to_string(b_offset));
- }
-
+ build_opts.add_option_if(b_offset != 0, "-DB_OFFSET=" + support::cpp11::to_string(b_offset));
build_opts.add_option("-DK_OFFSET=" + support::cpp11::to_string(a_offset * b_offset * k));
// Create kernel
_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemmlowp_offset_contribution", build_opts.options()));
- _vector_sum_col = vector_sum_col;
- _vector_sum_row = vector_sum_row;
- _mm_result = mm_result;
-
- constexpr unsigned int num_elems_processed_per_iteration = 16;
-
// Configure kernel window
- Window win = calculate_max_window(*mm_result->info(), Steps(num_elems_processed_per_iteration));
+ auto win_config = validate_and_configure_window(mm_result->info(),
+ vector_sum_col != nullptr ? vector_sum_col->info() : nullptr,
+ vector_sum_row != nullptr ? vector_sum_row->info() : nullptr,
+ a_offset, b_offset); // NOLINT
+ ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
+ ICLKernel::configure(win_config.second);
+}
- AccessWindowHorizontal mm_result_access(mm_result->info(), 0, num_elems_processed_per_iteration);
+Status CLGEMMLowpOffsetContributionKernel::validate(const ITensorInfo *mm_result, const ITensorInfo *vector_sum_col, const ITensorInfo *vector_sum_row,
+ int32_t a_offset, int32_t b_offset)
+{
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(mm_result, vector_sum_col, vector_sum_row, a_offset, b_offset));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(mm_result->clone().get(),
+ vector_sum_col != nullptr ? vector_sum_col->clone().get() : nullptr,
+ vector_sum_row != nullptr ? vector_sum_row->clone().get() : nullptr,
+ a_offset, b_offset)
+ .first); // NOLINT
- update_window_and_padding(win, mm_result_access);
-
- if(a_offset != 0)
- {
- AccessWindowHorizontal vector_sum_col_access(vector_sum_col->info(), 0, num_elems_processed_per_iteration);
- update_window_and_padding(win, vector_sum_col_access);
- }
-
- if(b_offset != 0)
- {
- AccessWindowStatic vector_sum_row_access(vector_sum_row->info(), 0, 0, vector_sum_row->info()->dimension(0), 0);
- update_window_and_padding(win, vector_sum_row_access);
- }
-
- ICLKernel::configure(win);
+ return Status{};
}
void CLGEMMLowpOffsetContributionKernel::run(const Window &window, cl::CommandQueue &queue)
diff --git a/src/core/CL/kernels/CLGEMMLowpReductionKernel.cpp b/src/core/CL/kernels/CLGEMMLowpReductionKernel.cpp
index bcf04b0..6951512 100644
--- a/src/core/CL/kernels/CLGEMMLowpReductionKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMLowpReductionKernel.cpp
@@ -44,6 +44,59 @@
class Coordinates;
} // namespace arm_compute
+namespace
+{
+Status validate_arguments_matrix_a_reduction(const ITensorInfo *input, const ITensorInfo *output)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::S32);
+
+ return Status{};
+}
+std::pair<Status, Window> validate_and_configure_window_matrix_a_reduction(ITensorInfo *input, ITensorInfo *output)
+{
+ const unsigned int num_elems_processed_per_iteration = 1;
+
+ Window win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration));
+
+ AccessWindowStatic input_access(input, 0, 0, ceil_to_multiple(input->dimension(0), 16), input->dimension(1));
+ AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration);
+
+ bool window_changed = update_window_and_padding(win, input_access, output_access);
+
+ output_access.set_valid_region(win, ValidRegion(Coordinates(0, 0), output->tensor_shape()));
+
+ Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
+ return std::make_pair(err, win);
+}
+
+Status validate_arguments_matrix_b_reduction(const ITensorInfo *input, const ITensorInfo *output)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::S32);
+
+ return Status{};
+}
+
+std::pair<Status, Window> validate_and_configure_window_matrix_b_reduction(ITensorInfo *input, ITensorInfo *output)
+{
+ constexpr unsigned int num_elems_processed_per_iteration = 16;
+
+ // Configure kernel window
+ Window win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration));
+
+ AccessWindowStatic input_access(input, 0, 0, ceil_to_multiple(input->dimension(0), num_elems_processed_per_iteration), input->dimension(1));
+ AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration);
+
+ bool window_changed = update_window_and_padding(win, input_access, output_access);
+
+ output_access.set_valid_region(win, ValidRegion(Coordinates(0, 0), output->tensor_shape()));
+
+ Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
+ return std::make_pair(err, win);
+}
+} // namespace
+
ICLGEMMLowpReductionKernel::ICLGEMMLowpReductionKernel()
: _input(), _output()
{
@@ -51,8 +104,9 @@
void CLGEMMLowpMatrixAReductionKernel::configure(const ICLTensor *mtx_a, ICLTensor *vector_sum_row)
{
- ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(mtx_a, 1, DataType::QASYMM8);
- ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(vector_sum_row, 1, DataType::S32);
+ // Perform validate step
+ ARM_COMPUTE_ERROR_ON_NULLPTR(mtx_a, vector_sum_row);
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_matrix_a_reduction(mtx_a->info(), vector_sum_row->info()));
_input = mtx_a;
_output = vector_sum_row;
@@ -64,21 +118,18 @@
// Create kernel
_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemmlowp_matrix_a_reduction", build_opts.options()));
- const unsigned int num_elems_processed_per_iteration = 1;
-
// Configure kernel window
- Window win = calculate_max_window(*_output->info(), Steps(num_elems_processed_per_iteration));
+ auto win_config = validate_and_configure_window_matrix_a_reduction(_input->info(), _output->info());
+ ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
+ ICLKernel::configure(win_config.second);
+}
- AccessWindowStatic input_access(_input->info(), 0, 0, ceil_to_multiple(_input->info()->dimension(0), 16), _input->info()->dimension(1));
- AccessWindowHorizontal output_access(_output->info(), 0, num_elems_processed_per_iteration);
+Status CLGEMMLowpMatrixAReductionKernel::validate(const ITensorInfo *mtx_a, const ITensorInfo *vector_sum_row)
+{
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_matrix_a_reduction(mtx_a, vector_sum_row));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window_matrix_a_reduction(mtx_a->clone().get(), vector_sum_row->clone().get()).first);
- update_window_and_padding(win,
- input_access,
- output_access);
-
- output_access.set_valid_region(win, ValidRegion(Coordinates(0, 0), _output->info()->tensor_shape()));
-
- ICLKernel::configure(win);
+ return Status{};
}
void CLGEMMLowpMatrixAReductionKernel::run(const Window &window, cl::CommandQueue &queue)
@@ -107,8 +158,8 @@
void CLGEMMLowpMatrixBReductionKernel::configure(const ICLTensor *mtx_b, ICLTensor *vector_sum_col)
{
- ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(mtx_b, 1, DataType::QASYMM8);
- ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(vector_sum_col, 1, DataType::S32);
+ ARM_COMPUTE_ERROR_ON_NULLPTR(mtx_b, vector_sum_col);
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_matrix_b_reduction(mtx_b->info(), vector_sum_col->info()));
_input = mtx_b;
_output = vector_sum_col;
@@ -121,21 +172,18 @@
// Create kernel
_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemmlowp_matrix_b_reduction", build_opts.options()));
- constexpr unsigned int num_elems_processed_per_iteration = 16;
-
// Configure kernel window
- Window win = calculate_max_window(*vector_sum_col->info(), Steps(num_elems_processed_per_iteration));
+ auto win_config = validate_and_configure_window_matrix_b_reduction(_input->info(), _output->info());
+ ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
+ ICLKernel::configure(win_config.second);
+}
- AccessWindowStatic input_access(_input->info(), 0, 0, ceil_to_multiple(_input->info()->dimension(0), num_elems_processed_per_iteration), _input->info()->dimension(1));
- AccessWindowHorizontal output_access(_output->info(), 0, num_elems_processed_per_iteration);
+Status CLGEMMLowpMatrixBReductionKernel::validate(const ITensorInfo *mtx_b, const ITensorInfo *vector_sum_col)
+{
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_matrix_b_reduction(mtx_b, vector_sum_col));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window_matrix_b_reduction(mtx_b->clone().get(), vector_sum_col->clone().get()).first);
- update_window_and_padding(win,
- input_access,
- output_access);
-
- output_access.set_valid_region(win, ValidRegion(Coordinates(0, 0), _output->info()->tensor_shape()));
-
- ICLKernel::configure(win);
+ return Status{};
}
void CLGEMMLowpMatrixBReductionKernel::run(const Window &window, cl::CommandQueue &queue)
diff --git a/src/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.cpp
index 015b4f7..d5c93dd 100644
--- a/src/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.cpp
@@ -36,6 +36,37 @@
using namespace arm_compute;
+namespace
+{
+Status validate_arguments(const ITensorInfo *accum, const ITensorInfo *biases)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(accum, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(biases, accum);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(biases, accum);
+ ARM_COMPUTE_RETURN_ERROR_ON(biases->num_dimensions() != 1);
+
+ return Status{};
+}
+
+std::pair<Status, Window> validate_and_configure_window(ITensorInfo *accum, ITensorInfo *biases, GPUTarget gpu_target,
+ unsigned int &num_elems_processed_per_iteration)
+{
+ // Select the vector size to use (8 for Bifrost; 16 for Midgard).
+ num_elems_processed_per_iteration = (gpu_target == GPUTarget::BIFROST) ? 8 : 16;
+
+ // Configure kernel window
+ Window win = calculate_max_window(*accum, Steps(num_elems_processed_per_iteration));
+
+ AccessWindowStatic biases_access(biases, 0, 0, ceil_to_multiple(biases->dimension(0), num_elems_processed_per_iteration), biases->dimension(1));
+ AccessWindowHorizontal accum_access(accum, 0, num_elems_processed_per_iteration);
+
+ bool window_changed = update_window_and_padding(win, biases_access, accum_access);
+
+ Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
+ return std::make_pair(err, win);
+}
+} // namespace
+
CLGEMMMatrixAccumulateBiasesKernel::CLGEMMMatrixAccumulateBiasesKernel()
: _accum(nullptr), _biases(nullptr)
{
@@ -43,18 +74,21 @@
void CLGEMMMatrixAccumulateBiasesKernel::configure(ICLTensor *accum, const ICLTensor *biases)
{
- ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(accum, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32);
- ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(biases, accum);
- ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(biases, accum);
- ARM_COMPUTE_ERROR_ON(biases->info()->num_dimensions() != 1);
+ // Perform validate step
+ ARM_COMPUTE_ERROR_ON_NULLPTR(accum, biases);
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(accum->info(), biases->info()));
_biases = biases;
_accum = accum;
// Get the target architecture
- GPUTarget arch_target = get_arch_from_target(get_target());
- // Select the vector size to use (8 for Bifrost; 16 for Midgard).
- const unsigned int vector_size = (arch_target == GPUTarget::BIFROST) ? 8 : 16;
+ GPUTarget arch_target = get_arch_from_target(get_target());
+ unsigned int vector_size = 0;
+
+ // Configure kernel window
+ auto win_config = validate_and_configure_window(accum->info(), biases->info(), arch_target, vector_size);
+ ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
+ ICLKernel::configure(win_config.second);
// Add build options
CLBuildOptions build_opts;
@@ -65,18 +99,15 @@
// Create kernel
_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemm_accumulate_biases", build_opts.options()));
+}
- // Configure kernel window
- const unsigned int num_elems_processed_per_iteration = vector_size;
+Status CLGEMMMatrixAccumulateBiasesKernel::validate(const ITensorInfo *accum, const ITensorInfo *biases, GPUTarget gpu_target)
+{
+ unsigned int num_elems_processed_per_iteration = 0;
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(accum, biases));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(accum->clone().get(), biases->clone().get(), gpu_target, num_elems_processed_per_iteration).first);
- Window win = calculate_max_window(*_accum->info(), Steps(num_elems_processed_per_iteration));
-
- AccessWindowStatic biases_access(biases->info(), 0, 0, ceil_to_multiple(biases->info()->dimension(0), num_elems_processed_per_iteration), biases->info()->dimension(1));
- AccessWindowHorizontal accum_access(_accum->info(), 0, num_elems_processed_per_iteration);
-
- update_window_and_padding(win, biases_access, accum_access);
-
- ICLKernel::configure(win);
+ return Status{};
}
void CLGEMMMatrixAccumulateBiasesKernel::run(const Window &window, cl::CommandQueue &queue)
diff --git a/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp
index 16706dd..f51d0f9 100644
--- a/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp
@@ -42,6 +42,81 @@
using namespace arm_compute;
+namespace
+{
+using ElementsProcessed = Steps;
+
+inline Status validate_arguments(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, bool is_interleaved_transposed)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input1, output);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input0, input1, output);
+ if(!is_interleaved_transposed)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON(input0->dimension(0) != input1->dimension(1));
+ }
+
+ return Status{};
+}
+
+inline std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input0, ITensorInfo *input1, ITensorInfo *output,
+ bool is_interleaved_transposed, GPUTarget gpu_target,
+ ElementsProcessed &num_elements_processed)
+{
+ bool window_changed = false;
+ Window win{};
+
+ const DataType data_type = input0->data_type();
+ unsigned int &num_elems_processed_per_iteration_x = num_elements_processed[0];
+ unsigned int &num_elems_processed_per_iteration_y = num_elements_processed[1];
+
+ if(is_interleaved_transposed)
+ {
+ // Configure kernel window
+ num_elems_processed_per_iteration_x = max_cl_vector_width / data_size_from_type(data_type);
+ num_elems_processed_per_iteration_y = 4;
+
+ win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
+
+ AccessWindowRectangle input0_access(input0, 0, 0, num_elems_processed_per_iteration_y, 1, 1.f, 0.25f);
+ AccessWindowTranspose input1_access(input1, 0, 0, num_elems_processed_per_iteration_x, 1, 0.f, 0.25f);
+ AccessWindowRectangle output_access(output, 0, 0, num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y);
+
+ window_changed = update_window_and_padding(win, input0_access, input1_access, output_access);
+
+ output_access.set_valid_region(win, ValidRegion(Coordinates(0, 0), output->tensor_shape()));
+ }
+ else // The input tensors have not been reshaped
+ {
+ // Special case for 1xN, 2xN, 3xN and 4xN input0 tensor. num_elems_processed_per_iteration_x is set up for the default case.
+ num_elems_processed_per_iteration_x = max_cl_vector_width / data_size_from_type(data_type);
+ num_elems_processed_per_iteration_y = std::min(static_cast<int>(output->dimension(1)), 4);
+
+ // Create kernels according to the architecture, data type and input size.
+ if(gpu_target == GPUTarget::BIFROST && data_type == DataType::F32)
+ {
+ num_elems_processed_per_iteration_x = (input1->dimension(0) <= 1000) ? 2 : 4;
+ }
+
+ // Configure window
+ win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
+
+ AccessWindowStatic input0_access(input0, 0, 0, input0->dimension(0), ceil_to_multiple(input0->dimension(1), num_elems_processed_per_iteration_y));
+ AccessWindowStatic input1_access(input1, 0, 0, ceil_to_multiple(input1->dimension(0), num_elems_processed_per_iteration_x), input1->dimension(1));
+ AccessWindowRectangle output_access(output, 0, 0, num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y);
+
+ window_changed = update_window_and_padding(win, input0_access, input1_access, output_access);
+
+ Coordinates coord;
+ coord.set_num_dimensions(output->num_dimensions());
+ output_access.set_valid_region(win, ValidRegion(coord, output->tensor_shape()));
+ }
+
+ Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
+ return std::make_pair(err, win);
+}
+} // namespace
+
CLGEMMMatrixMultiplyKernel::CLGEMMMatrixMultiplyKernel()
: _input0(nullptr), _input1(nullptr), _output(nullptr)
{
@@ -49,13 +124,10 @@
void CLGEMMMatrixMultiplyKernel::configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, float alpha, bool is_interleaved_transposed)
{
- ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32);
- ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input1, output);
- ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input0, input1, output);
- if(!is_interleaved_transposed)
- {
- ARM_COMPUTE_ERROR_ON(input0->info()->dimension(0) != input1->info()->dimension(1));
- }
+ ARM_COMPUTE_ERROR_ON_NULLPTR(input0, input1, output);
+
+ // Perform validate step
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input0->info(), input1->info(), output->info(), is_interleaved_transposed));
_input0 = input0;
_input1 = input1;
@@ -82,14 +154,19 @@
_lws_hint = cl::NDRange(8, 8);
}
+ ElementsProcessed num_elements_processed{};
+
+ // Configure kernel window
+ auto win_config = validate_and_configure_window(input0->info(), input1->info(), output->info(), is_interleaved_transposed, arch_target, num_elements_processed);
+ ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
+ ICLKernel::configure(win_config.second);
+
// Create build options
CLBuildOptions build_opts;
build_opts.add_option_if(is_data_type_fixed_point(data_type), "-DFIXED_POINT_POSITION=" + support::cpp11::to_string(fp_pos));
- const bool multiply_alpha = std::abs(1.0f - alpha) > 0.00001f;
-
// Only define ALPHA when alpha is not 1.0f. This avoids performing unnecessary multiplications.
- if(multiply_alpha)
+ if(std::abs(1.0f - alpha) > 0.00001f)
{
build_opts.add_option_if_else(is_data_type_fixed_point(data_type),
"-DALPHA=" + support::cpp11::to_string((data_type == DataType::QS8 ? sqcvt_qs8_f32(alpha, fp_pos) : sqcvt_qs16_f32(alpha, fp_pos))),
@@ -108,49 +185,19 @@
{
kernel_name = "gemm_mm_interleaved_transposed_" + lower_string(string_from_data_type(data_type));
}
-
- // Configure kernel window
- const unsigned int num_elems_processed_per_iteration_x = max_cl_vector_width / data_size_from_type(data_type);
- constexpr unsigned int num_elems_processed_per_iteration_y = 4;
-
- Window win = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
-
- AccessWindowRectangle input0_access(input0->info(), 0, 0, num_elems_processed_per_iteration_y, 1, 1.f, 0.25f);
- AccessWindowTranspose input1_access(input1->info(), 0, 0, num_elems_processed_per_iteration_x, 1, 0.f, 0.25f);
- AccessWindowRectangle output_access(output->info(), 0, 0, num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y);
-
- update_window_and_padding(win, input0_access, input1_access, output_access);
-
- output_access.set_valid_region(win, ValidRegion(Coordinates(0, 0), output->info()->tensor_shape()));
-
- ICLKernel::configure(win);
}
else // The input tensors have not been reshaped
{
build_opts.add_option("-DCOLS_A=" + support::cpp11::to_string(input0->info()->dimension(0)));
- // Special case for 1xN, 2xN, 3xN and 4xN input0 tensor. num_elems_processed_per_iteration_x is set up for the default case.
- unsigned int num_elems_processed_per_iteration_x = max_cl_vector_width / data_size_from_type(data_type);
- const unsigned int num_elems_processed_per_iteration_y = std::min(static_cast<int>(output->info()->dimension(1)), 4);
-
// Create kernels according to the architecture, data type and input size.
if(arch_target == GPUTarget::BIFROST && data_type == DataType::F32)
{
// The first kernel is optimized for the case of 1000 or less output elements (e.g. FC8 of AlexNet and VGG-16, and
// FC1 of Inception v3). The second kernel is optimized for the case of greater than 1000 output elements (e.g.
// FC6 and FC7 of AlexNet and VGG-16).
- if(input1->info()->dimension(0) <= 1000)
- {
- // Each work-item processes 2 elements in the X dimension.
- num_elems_processed_per_iteration_x = 2;
- kernel_name = "gemm_mm_floating_point_f32_bifrost_1000";
- }
- else
- {
- // Each work-item processes 4 elements in the X dimension (as in the default case).
- num_elems_processed_per_iteration_x = 4;
- kernel_name = "gemm_mm_floating_point_f32_bifrost";
- }
+ kernel_name = (input1->info()->dimension(0) <= 1000) ? "gemm_mm_floating_point_f32_bifrost_1000" : "gemm_mm_floating_point_f32_bifrost";
+
// The work-group size equal to the Bifrost quad size has been proved to be optimal for these kernels
// via exhaustive autotuning over a range of representative layer configurations.
_lws_hint = cl::NDRange(4);
@@ -164,23 +211,8 @@
build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(data_type));
kernel_name = "gemm_mm_floating_point";
}
- build_opts.add_option("-DNUM_ELEMS_PROCESSED_PER_THREAD_Y=" + support::cpp11::to_string(num_elems_processed_per_iteration_y));
- build_opts.add_option("-DNUM_ELEMS_PROCESSED_PER_THREAD_X=" + support::cpp11::to_string(num_elems_processed_per_iteration_x));
-
- // Configure window
- Window win = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
-
- AccessWindowStatic input0_access(input0->info(), 0, 0, input0->info()->dimension(0), ceil_to_multiple(input0->info()->dimension(1), num_elems_processed_per_iteration_y));
- AccessWindowStatic input1_access(input1->info(), 0, 0, ceil_to_multiple(input1->info()->dimension(0), num_elems_processed_per_iteration_x), input1->info()->dimension(1));
- AccessWindowRectangle output_access(output->info(), 0, 0, num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y);
-
- update_window_and_padding(win, input0_access, input1_access, output_access);
-
- Coordinates coord;
- coord.set_num_dimensions(output->info()->num_dimensions());
- output_access.set_valid_region(win, ValidRegion(coord, output->info()->tensor_shape()));
-
- ICLKernel::configure(win);
+ build_opts.add_option("-DNUM_ELEMS_PROCESSED_PER_THREAD_Y=" + support::cpp11::to_string(num_elements_processed.y()));
+ build_opts.add_option("-DNUM_ELEMS_PROCESSED_PER_THREAD_X=" + support::cpp11::to_string(num_elements_processed.x()));
}
// Create kernel
@@ -198,6 +230,22 @@
_config_id += (is_interleaved_transposed ? support::cpp11::to_string(input1->info()->dimension(0)) : support::cpp11::to_string(input1->info()->dimension(1)));
}
+Status CLGEMMMatrixMultiplyKernel::validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, float alpha, bool is_interleaved_transposed, GPUTarget gpu_target)
+{
+ ElementsProcessed num_elements_processed{};
+ ARM_COMPUTE_UNUSED(alpha);
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input0, input1, output, is_interleaved_transposed));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input0->clone().get(),
+ input1->clone().get(),
+ output->clone().get(),
+ is_interleaved_transposed,
+ gpu_target,
+ num_elements_processed)
+ .first);
+
+ return Status{};
+}
+
void CLGEMMMatrixMultiplyKernel::run(const Window &window, cl::CommandQueue &queue)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
diff --git a/src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp b/src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp
index 35074f9..69a545b 100644
--- a/src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp
@@ -33,36 +33,82 @@
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Validate.h"
#include "arm_compute/core/Window.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include <cmath>
using namespace arm_compute;
+using namespace arm_compute::misc::shape_calculator;
+
+namespace
+{
+Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QASYMM8, DataType::U8, DataType::S8,
+ DataType::QS16, DataType::U16, DataType::S16, DataType::U32, DataType::S32,
+ DataType::F16, DataType::F32);
+
+ if(output->total_size() != 0)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(),
+ compute_transpose1xW_with_element_size_shape(*input));
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, output);
+ }
+
+ return Status{};
+}
+
+std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, unsigned int &num_elems_processed_per_iteration)
+{
+ num_elems_processed_per_iteration = 16 / input->element_size();
+
+ const int scale_x = num_elems_processed_per_iteration;
+ bool window_changed = false;
+
+ // Configure kernel window
+ Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration));
+
+ if((win.x().end() / scale_x) == 0)
+ {
+ return std::make_pair(ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Transposed shape would be 0 in the second dimension"), win);
+ }
+
+ AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration);
+ window_changed = window_changed || update_window_and_padding(win, input_access);
+
+ // Configure window in case of configured output
+ if(output->total_size() != 0)
+ {
+ AccessWindowTranspose output_access(output, 0, 0, num_elems_processed_per_iteration, 1, scale_x, 1.f / scale_x);
+ window_changed = window_changed || update_window_and_padding(win, output_access);
+ output_access.set_valid_region(win, ValidRegion(Coordinates(0, 0), input->tensor_shape()));
+ }
+
+ Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
+ return std::make_pair(err, win);
+}
+} // namespace
void CLGEMMTranspose1xWKernel::configure(const ICLTensor *input, ICLTensor *output)
{
- ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::S8, DataType::QS8, DataType::QASYMM8,
- DataType::U16, DataType::S16, DataType::QS16,
- DataType::U32, DataType::S32, DataType::F16, DataType::F32);
- ARM_COMPUTE_ERROR_ON_NULLPTR(output);
-
- TensorShape output_shape{ input->info()->tensor_shape() };
- const size_t transpose_w = 16 / input->info()->element_size();
- output_shape.set(0, input->info()->dimension(1) * transpose_w);
- output_shape.set(1, static_cast<size_t>(std::ceil((input->info()->dimension(0) / static_cast<float>(transpose_w)))));
+ ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
// Output tensor auto inizialitation if not yet initialized
- auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape));
+ auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(compute_transpose1xW_with_element_size_shape(*input->info())));
- ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
- ARM_COMPUTE_ERROR_ON_MISMATCHING_DIMENSIONS(output->info()->tensor_shape(), output_shape);
- ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input, output);
-
- const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size();
- const int scale_x = num_elems_processed_per_iteration;
+ // Perform validate step
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info()));
_input = input;
_output = output;
+ // Configure kernel window
+ unsigned int num_elems_processed_per_iteration = 1;
+ auto win_config = validate_and_configure_window(input->info(), output->info(), num_elems_processed_per_iteration);
+ ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
+ ICLKernel::configure(win_config.second);
+
/*
* Following an example of how the transposition1xW works when the input data type is F32
*
@@ -76,20 +122,15 @@
// Create kernel
std::string kernel_name = "gemm_transpose1x" + support::cpp11::to_string(num_elems_processed_per_iteration);
_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name));
+}
- // Configure window
- Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));
+Status CLGEMMTranspose1xWKernel::validate(const ITensorInfo *input, const ITensorInfo *output)
+{
+ unsigned int num_elems_processed_per_iteration = 1;
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), num_elems_processed_per_iteration).first);
- ARM_COMPUTE_ERROR_ON_MSG((win.x().end() / scale_x) == 0, "Transposed shape would be 0 in the second dimension");
-
- AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration);
- AccessWindowTranspose output_access(output->info(), 0, 0, num_elems_processed_per_iteration, 1, scale_x, 1.f / scale_x);
-
- update_window_and_padding(win, input_access, output_access);
-
- output_access.set_valid_region(win, ValidRegion(Coordinates(0, 0), input->info()->tensor_shape()));
-
- ICLKernel::configure(win);
+ return Status{};
}
void CLGEMMTranspose1xWKernel::run(const Window &window, cl::CommandQueue &queue)
diff --git a/src/core/CL/kernels/CLIm2ColKernel.cpp b/src/core/CL/kernels/CLIm2ColKernel.cpp
index 6514d6c..0e9f2c5 100644
--- a/src/core/CL/kernels/CLIm2ColKernel.cpp
+++ b/src/core/CL/kernels/CLIm2ColKernel.cpp
@@ -39,6 +39,24 @@
using namespace arm_compute;
+namespace
+{
+Status validate_arguments(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)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, output);
+ }
+
+ return Status{};
+}
+} // namespace
+
CLIm2ColKernel::CLIm2ColKernel()
: _input(nullptr), _output(nullptr), _convolved_dims(), _num_elems_processed_per_iteration(1), _run_func(nullptr)
{
@@ -46,9 +64,10 @@
void CLIm2ColKernel::configure(const ICLTensor *input, ICLTensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias)
{
- ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QASYMM8, DataType::QS16, DataType::F16, DataType::F32);
- ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
- ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input, output);
+ ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
+
+ // Perform validation step
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info()));
_input = input;
_output = output;
@@ -184,6 +203,15 @@
_config_id += support::cpp11::to_string(output->info()->dimension(1));
}
+Status CLIm2ColKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias)
+{
+ ARM_COMPUTE_UNUSED(kernel_dims);
+ ARM_COMPUTE_UNUSED(conv_info);
+ ARM_COMPUTE_UNUSED(has_bias);
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output));
+ return Status{};
+}
+
void CLIm2ColKernel::run(const Window &window, cl::CommandQueue &queue)
{
ARM_COMPUTE_ERROR_ON(_run_func == nullptr);