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path: root/src/cpu/operators/CpuGemmConv2d.cpp
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Diffstat (limited to 'src/cpu/operators/CpuGemmConv2d.cpp')
-rw-r--r--src/cpu/operators/CpuGemmConv2d.cpp64
1 files changed, 32 insertions, 32 deletions
diff --git a/src/cpu/operators/CpuGemmConv2d.cpp b/src/cpu/operators/CpuGemmConv2d.cpp
index 0174d0eed3..f3a16f104f 100644
--- a/src/cpu/operators/CpuGemmConv2d.cpp
+++ b/src/cpu/operators/CpuGemmConv2d.cpp
@@ -62,13 +62,13 @@ CpuGemmConv2d::SkipInfo CpuGemmConv2d::skip_im_col_info(const ITensorInfo *src,
const unsigned int kernel_height = weights->dimension(idx_height);
unsigned int conv_w = 0;
unsigned int conv_h = 0;
- std::tie(conv_w, conv_h) = scaled_dimensions(src->dimension(idx_width),
- src->dimension(idx_height),
- kernel_width,
- kernel_height,
- conv_info,
- dilation);
- const bool skip_im2col = (data_layout == DataLayout::NHWC && kernel_width == 1 && kernel_height == 1 && conv_info.stride().first == 1 && conv_info.stride().second == 1);
+ std::tie(conv_w, conv_h) = scaled_dimensions(src->dimension(idx_width),
+ src->dimension(idx_height),
+ kernel_width,
+ kernel_height,
+ conv_info,
+ dilation);
+ const bool skip_im2col = (data_layout == DataLayout::NHWC && kernel_width == 1 && kernel_height == 1 && conv_info.stride().first == 1 && conv_info.stride().second == 1);
if(skip_im2col)
{
@@ -99,7 +99,7 @@ CpuGemmConv2d::CpuGemmConv2d()
CpuGemmConv2d::~CpuGemmConv2d() = default;
void CpuGemmConv2d::configure_mm(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, ITensorInfo *dst, const ActivationLayerInfo &act_info,
- bool enable_fast_math, int gemm_3d_depth, bool fixed_format, arm_gemm::WeightFormat weight_format)
+ bool enable_fast_math, int gemm_3d_depth, bool fixed_format, arm_compute::WeightFormat weight_format)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(src, weights);
ARM_COMPUTE_ERROR_THROW_ON(validate_mm(src, weights, biases, dst, act_info, enable_fast_math, gemm_3d_depth, _skip_im2col, fixed_format, weight_format));
@@ -139,8 +139,8 @@ void CpuGemmConv2d::configure_mm(const ITensorInfo *src, const ITensorInfo *weig
PixelValue type_min{};
PixelValue type_max{};
std::tie(type_min, type_max) = get_min_max(data_type);
- int32_t min_activation = type_min.get<int32_t>();
- int32_t max_activation = type_max.get<int32_t>();
+ int32_t min_activation = type_min.get<int32_t>();
+ int32_t max_activation = type_max.get<int32_t>();
if(supported_acts.count(act_info.activation()) != 0)
{
@@ -179,7 +179,7 @@ void CpuGemmConv2d::configure_mm(const ITensorInfo *src, const ITensorInfo *weig
}
Status CpuGemmConv2d::validate_mm(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *dst,
- const ActivationLayerInfo &act_info, bool enable_fast_math, int gemm_3d_depth, bool skip_im2col, bool fixed_format, arm_gemm::WeightFormat weight_format)
+ const ActivationLayerInfo &act_info, bool enable_fast_math, int gemm_3d_depth, bool skip_im2col, bool fixed_format, arm_compute::WeightFormat weight_format)
{
const DataType data_type = src->data_type();
const bool is_quantized = is_data_type_quantized_asymmetric(data_type);
@@ -203,8 +203,8 @@ Status CpuGemmConv2d::validate_mm(const ITensorInfo *src, const ITensorInfo *wei
PixelValue type_min{};
PixelValue type_max{};
std::tie(type_min, type_max) = get_min_max(data_type);
- int32_t min_activation = type_min.get<int32_t>();
- int32_t max_activation = type_max.get<int32_t>();
+ int32_t min_activation = type_min.get<int32_t>();
+ int32_t max_activation = type_max.get<int32_t>();
const std::set<ActivationLayerInfo::ActivationFunction> supported_acts = { ActivationLayerInfo::ActivationFunction::RELU,
ActivationLayerInfo::ActivationFunction::BOUNDED_RELU,
@@ -288,8 +288,8 @@ void CpuGemmConv2d::configure(const ITensorInfo *src, const ITensorInfo *weights
ITensorInfo *gemm_output_to_use = dst;
// Get convolved dimensions
- unsigned int conv_w = 0;
- unsigned int conv_h = 0;
+ unsigned int conv_w = 0;
+ unsigned int conv_h = 0;
std::tie(conv_w, conv_h) = scaled_dimensions(src->dimension(idx_width),
src->dimension(idx_height),
kernel_width,
@@ -306,8 +306,8 @@ void CpuGemmConv2d::configure(const ITensorInfo *src, const ITensorInfo *weights
_skip_col2im = skip_info.skip_col2im;
// Get parameters from conv_info
- unsigned int stride_x = 0;
- unsigned int stride_y = 0;
+ unsigned int stride_x = 0;
+ unsigned int stride_y = 0;
std::tie(stride_x, stride_y) = conv_info.stride();
unsigned int mat_weights_cols = weights->dimension(idx_kernels);
@@ -360,7 +360,7 @@ void CpuGemmConv2d::configure(const ITensorInfo *src, const ITensorInfo *weights
// Configure GEMM
// In case we need to skip col2im, GEMM3D (gemm_3d_depth != 0) must be called in order to avoid reshaping the output matrix
const unsigned int gemm_3d_depth = _skip_col2im ? conv_h : 0;
- const bool fixed_format = weights_info.weight_format() != arm_gemm::WeightFormat::UNSPECIFIED;
+ const bool fixed_format = weights_info.weight_format() != arm_compute::WeightFormat::UNSPECIFIED;
configure_mm(gemm_input_to_use, &_weights_reshaped, biases, gemm_output_to_use, act_info, enable_fast_math, gemm_3d_depth, fixed_format, weights_info.weight_format());
if(!_skip_col2im && _data_layout == DataLayout::NCHW)
@@ -388,7 +388,7 @@ void CpuGemmConv2d::configure(const ITensorInfo *src, const ITensorInfo *weights
_aux_mem[GemmOutput] = MemoryInfo(offset_int_vec(GemmOutput), MemoryLifetime::Temporary, _gemm_output.total_size());
}
-Status CpuGemmConv2d::has_opt_impl(arm_gemm::WeightFormat &expected_weight_format, const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *dst,
+Status CpuGemmConv2d::has_opt_impl(arm_compute::WeightFormat &expected_weight_format, const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *dst,
const PadStrideInfo &conv_info,
const WeightsInfo &weights_info, const Size2D &dilation, const ActivationLayerInfo &act_info, const bool enable_fast_math)
{
@@ -399,12 +399,12 @@ Status CpuGemmConv2d::has_opt_impl(arm_gemm::WeightFormat &expected_weight_forma
const unsigned int kernel_height = weights->dimension(idx_height);
unsigned int conv_w = 0;
unsigned int conv_h = 0;
- std::tie(conv_w, conv_h) = scaled_dimensions(src->dimension(idx_width),
- src->dimension(idx_height),
- kernel_width,
- kernel_height,
- conv_info,
- dilation);
+ std::tie(conv_w, conv_h) = scaled_dimensions(src->dimension(idx_width),
+ src->dimension(idx_height),
+ kernel_width,
+ kernel_height,
+ conv_info,
+ dilation);
const CpuGemmConv2d::SkipInfo skip_info = CpuGemmConv2d::skip_im_col_info(src, weights, conv_info,
dilation, act_info);
@@ -412,7 +412,7 @@ Status CpuGemmConv2d::has_opt_impl(arm_gemm::WeightFormat &expected_weight_forma
const bool skip_im2col = skip_info.skip_im2col;
const bool skip_col2im = skip_info.skip_col2im;
const unsigned int gemm_3d_depth = skip_col2im ? conv_h : 0;
- const bool fixed_format = weights_info.weight_format() != arm_gemm::WeightFormat::UNSPECIFIED;
+ const bool fixed_format = weights_info.weight_format() != arm_compute::WeightFormat::UNSPECIFIED;
const GEMMInfo gemm_info = GEMMInfo(false, false, true /* Reshape weights only for the first run */,
gemm_3d_depth, skip_im2col /* Reinterpret the input as 3D if im2col is skipped */,
false, GEMMLowpOutputStageInfo(), false, enable_fast_math, false, act_info, experimental::PostOpList<ITensorInfo *>(), fixed_format, weights_info.weight_format());
@@ -464,9 +464,9 @@ Status CpuGemmConv2d::validate(const ITensorInfo *src, const ITensorInfo *weight
dilation);
// Check if GEMM3D is supported
- const CpuGemmConv2d::SkipInfo skip_info = CpuGemmConv2d::skip_im_col_info(src, weights, conv_info,
- dilation, act_info);
- const bool skip_im2col = skip_info.skip_im2col, skip_col2im = skip_info.skip_col2im;
+ const CpuGemmConv2d::SkipInfo skip_info = CpuGemmConv2d::skip_im_col_info(src, weights, conv_info,
+ dilation, act_info);
+ const bool skip_im2col = skip_info.skip_im2col, skip_col2im = skip_info.skip_col2im;
ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_channel) != src->dimension(idx_channel));
ARM_COMPUTE_RETURN_ERROR_ON(weights->num_dimensions() > 4);
@@ -527,7 +527,7 @@ Status CpuGemmConv2d::validate(const ITensorInfo *src, const ITensorInfo *weight
}
info_gemm.set_quantization_info(dst->quantization_info()).set_data_layout(src->data_layout());
gemm_output_to_use = &info_gemm;
- const bool fixed_format = weights_info.weight_format() != arm_gemm::WeightFormat::UNSPECIFIED;
+ const bool fixed_format = weights_info.weight_format() != arm_compute::WeightFormat::UNSPECIFIED;
ARM_COMPUTE_RETURN_ON_ERROR(validate_mm(gemm_input_to_use, weights_to_use, biases, gemm_output_to_use, act_info, enable_fast_math, skip_col2im ? conv_h : 0, skip_im2col, fixed_format,
weights_info.weight_format()));
@@ -558,7 +558,7 @@ void CpuGemmConv2d::run(ITensorPack &tensors)
{
// Run input reshaping
unsigned int y_dim = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT);
- ITensorPack pack =
+ ITensorPack pack =
{
{ TensorType::ACL_SRC, src },
{ TensorType::ACL_DST, im2col_output.get() }
@@ -652,7 +652,7 @@ void CpuGemmConv2d::prepare(ITensorPack &tensors)
// Run weights reshaping and mark original weights tensor as unused
CpuAuxTensorHandler weights_reshaped(offset_int_vec(WeightsReshaped), _weights_reshaped, tensors);
auto weights = tensors.get_const_tensor(TensorType::ACL_SRC_1);
- ITensorPack pack =
+ ITensorPack pack =
{
{ TensorType::ACL_SRC, weights },
{ TensorType::ACL_DST, weights_reshaped.get() }
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-25 11:03:47 +0000