Fix for inclusion of "arm_gemm" from src into "Types.h" from core
- Added arm_compute::WeightFormat and converted to/from arm_gemm::WeightFormat
when needed through two map function.
- Moved to_string(WeightFormat) to TypePrinter.h
Resolves: COMPMID-5415
Signed-off-by: Ramy Elgammal <ramy.elgammal@arm.com>
Change-Id: I65f7942100bcd4dbf2c5cf6c07f26c8e1e3bf86e
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/c/VisualCompute/ComputeLibrary/+/438511
Tested-by: bsgcomp <bsgcomp@arm.com>
Reviewed-by: Pablo Tello <pablo.tello@arm.com>
Reviewed-by: Sicong Li <sicong.li@arm.com>
Comments-Addressed: bsgcomp <bsgcomp@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7985
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
diff --git a/tests/validation/fixtures/ConvolutionLayerFixture.h b/tests/validation/fixtures/ConvolutionLayerFixture.h
index d3804ee..c58a0a2 100644
--- a/tests/validation/fixtures/ConvolutionLayerFixture.h
+++ b/tests/validation/fixtures/ConvolutionLayerFixture.h
@@ -122,14 +122,14 @@
{
case DataType::QASYMM8:
{
- std::pair<int, int> bounds = get_quantized_bounds(tensor.quantization_info(), -1.0f, 1.0f);
+ std::pair<int, int> bounds = get_quantized_bounds(tensor.quantization_info(), -1.0f, 1.0f);
std::uniform_int_distribution<uint32_t> distribution(bounds.first, bounds.second);
library->fill(tensor, distribution, i);
break;
}
case DataType::QASYMM8_SIGNED:
{
- std::pair<int, int> bounds = get_quantized_qasymm8_signed_bounds(tensor.quantization_info(), -1.0f, 1.0f);
+ std::pair<int, int> bounds = get_quantized_qasymm8_signed_bounds(tensor.quantization_info(), -1.0f, 1.0f);
std::uniform_int_distribution<int32_t> distribution(bounds.first, bounds.second);
library->fill(tensor, distribution, i);
break;
@@ -400,7 +400,7 @@
};
#ifdef ARM_COMPUTE_ENABLE_FIXED_FORMAT_KERNELS
-inline TensorInfo prepare_weights(const TensorInfo tensor_info, const arm_gemm::WeightFormat weight_format)
+inline TensorInfo prepare_weights(const TensorInfo tensor_info, const arm_compute::WeightFormat weight_format)
{
const DataLayout data_layout = tensor_info.data_layout();
ARM_COMPUTE_EXPECT(data_layout == DataLayout::NHWC, framework::LogLevel::ERRORS);
@@ -411,8 +411,8 @@
const int W = tensor_shape[get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH)];
const int C = tensor_shape[get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL)]; // C=I
- const int interleave_by = arm_gemm::interleave_by(weight_format);
- const int block_by = arm_gemm::block_by(weight_format);
+ const int interleave_by = arm_compute::interleave_by(weight_format);
+ const int block_by = arm_compute::block_by(weight_format);
const int Ip = arm_gemm::roundup<unsigned int>(C, block_by); // C'=I'
const int Op = arm_gemm::roundup<unsigned int>(N, interleave_by); // O'=N'
@@ -421,12 +421,12 @@
}
template <typename ScalarType, typename AccessorType>
-inline void rearrange_data(const AccessorType src, AccessorType dst, const arm_gemm::WeightFormat weight_format)
+inline void rearrange_data(const AccessorType src, AccessorType dst, const arm_compute::WeightFormat weight_format)
{
- ARM_COMPUTE_EXPECT(arm_gemm::is_fixed_format(weight_format), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(arm_compute::is_fixed_format(weight_format), framework::LogLevel::ERRORS);
// Data Layout: OHWIo<interleave_by>i<block_by>
- const int interleave_by = arm_gemm::interleave_by(weight_format);
- const int block_by = arm_gemm::block_by(weight_format);
+ const int interleave_by = arm_compute::interleave_by(weight_format);
+ const int block_by = arm_compute::block_by(weight_format);
const TensorShape src_tensor_shape = src.shape();
const DataLayout data_layout = src.data_layout();
ARM_COMPUTE_EXPECT(data_layout == DataLayout::NHWC, framework::LogLevel::ERRORS);
@@ -545,12 +545,12 @@
const int kernel_width = weights_shape[get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH)];
const int num_kernels = weights_shape[get_data_layout_dimension_index(_data_layout, DataLayoutDimension::BATCHES)];
- const WeightsInfo query_weights_info(/*reshape_weights*/ false, kernel_width, kernel_height, num_kernels, false, arm_gemm::WeightFormat::ANY);
+ const WeightsInfo query_weights_info(/*reshape_weights*/ false, kernel_width, kernel_height, num_kernels, false, arm_compute::WeightFormat::ANY);
const bool kernel_found = bool(ConvolutionFunction::has_opt_impl(_computed_weight_format, &src_tensor_info, &weight_tensor_info,
&bias_tensor_info, &dst_tensor_info, conv_info, query_weights_info));
// Make surethat the setup founds a fixed-format kernel as requested by the test case.
ARM_COMPUTE_EXPECT(kernel_found, framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(arm_gemm::is_fixed_format(_computed_weight_format), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(arm_compute::is_fixed_format(_computed_weight_format), framework::LogLevel::ERRORS);
const WeightsInfo weights_info(/*reshape_weights*/ false, kernel_width, kernel_height, num_kernels, false, _computed_weight_format);
configure_and_execute_kernel(src_tensor_info, weight_tensor_info, bias_tensor_info, dst_tensor_info, weights_info, conv_info,
@@ -576,7 +576,7 @@
protected:
std::unique_ptr<ConvolutionFunction> conv{};
- arm_gemm::WeightFormat _computed_weight_format{ arm_gemm::WeightFormat::UNSPECIFIED };
+ arm_compute::WeightFormat _computed_weight_format{ arm_compute::WeightFormat::UNSPECIFIED };
TensorClass _target{};
SimpleTensor<ScalarType> _reference{};
};
@@ -669,7 +669,7 @@
{
public:
template <typename...>
- void setup(DataType data_type, arm_gemm::WeightFormat query_weight_format)
+ void setup(DataType data_type, arm_compute::WeightFormat query_weight_format)
{
auto conv = std::make_unique<ConvolutionClass>();
const auto src_info = TensorInfo(TensorShape(1U, 5U, 2U), 1, data_type, DataLayout::NHWC);
@@ -683,8 +683,8 @@
}
protected:
- bool _kernel_found{ false };
- arm_gemm::WeightFormat _computed_weight_format{ arm_gemm::WeightFormat::UNSPECIFIED };
+ bool _kernel_found{ false };
+ arm_compute::WeightFormat _computed_weight_format{ arm_compute::WeightFormat::UNSPECIFIED };
};
#endif // ARM_COMPUTE_ENABLE_FIXED_FORMAT_KERNELS