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[onert] Apply structured binding in ARMComputeEx #14664

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Feb 19, 2025
Merged

[onert] Apply structured binding in ARMComputeEx #14664

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8 changes: 4 additions & 4 deletions runtime/compute/ARMComputeEx/arm_compute/core/utils/misc/ShapeCalculatorEx.h
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Expand Up @@ -77,8 +77,7 @@ inline TensorShape compute_transposeconv_upsampled_shape(
unsigned int invalid_bottom, unsigned int &pad_left, unsigned int &pad_right,
unsigned int &pad_top, unsigned int &pad_bottom)
{
unsigned int sx = info.stride().first;
unsigned int sy = info.stride().second;
auto [sx, sy] = info.stride();
const DataLayout data_layout = input.data_layout();
const size_t idx_w = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
const size_t idx_h = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
Expand Down Expand Up @@ -139,8 +138,9 @@ compute_transposeconv_output_shape(const std::pair<unsigned int, unsigned int> &
const int batch_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES);

TensorShape out_shape{input_shape};
out_shape.set(width_idx, out_dims.first);
out_shape.set(height_idx, out_dims.second);
auto [width, height] = out_dims;
out_shape.set(width_idx, width);
out_shape.set(height_idx, height);
out_shape.set(channel_idx, weights_shape[batch_idx]);
return out_shape;
}
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6 changes: 3 additions & 3 deletions runtime/compute/ARMComputeEx/src/core/CL/kernels/CLEmbeddingLookupKernel.cpp
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Expand Up @@ -115,9 +115,9 @@ void CLEmbeddingLookupKernel::configure(const ICLTensor *input, ICLTensor *outpu
static_cast<cl::Kernel>(CLKernelLibraryEx::get().create_kernel(kernel_name.str(), build_opts));

// Configure kernel window
auto win_config = validate_and_configure_window(input->info(), output->info());
ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
ICLKernel::configure_internal(win_config.second);
auto [error, window] = validate_and_configure_window(input->info(), output->info());
ARM_COMPUTE_ERROR_THROW_ON(error);
ICLKernel::configure_internal(window);
}

void CLEmbeddingLookupKernel::run(const Window &window, cl::CommandQueue &queue)
Expand Down
6 changes: 3 additions & 3 deletions runtime/compute/ARMComputeEx/src/core/CL/kernels/CLHashtableLookupKernel.cpp
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Expand Up @@ -132,9 +132,9 @@ void CLHashtableLookupKernel::configure(const ICLTensor *lookups, const ICLTenso
static_cast<cl::Kernel>(CLKernelLibraryEx::get().create_kernel(kernel_name.str(), build_opts));

// Configure kernel window
auto win_config = validate_and_configure_window(input->info(), output->info());
ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
ICLKernel::configure_internal(win_config.second);
auto [error, window] = validate_and_configure_window(input->info(), output->info());
ARM_COMPUTE_ERROR_THROW_ON(error);
ICLKernel::configure_internal(window);
}

void CLHashtableLookupKernel::run(const Window &window, cl::CommandQueue &queue)
Expand Down
6 changes: 3 additions & 3 deletions runtime/compute/ARMComputeEx/src/core/CL/kernels/CLInstanceNormalizationLayerKernelEx.cpp
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Expand Up @@ -139,9 +139,9 @@ void CLInstanceNormalizationLayerKernelEx::configure(ICLTensor *input, ICLTensor
CLKernelLibraryEx::get().create_kernel("instance_normalization_ex", build_opts.options()));

// Configure kernel window
auto win_config = validate_and_configure_window(_input->info(), _output->info());
ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config));
ICLKernel::configure_internal(std::get<1>(win_config));
auto [error, window] = validate_and_configure_window(_input->info(), _output->info());
ARM_COMPUTE_ERROR_THROW_ON(error);
ICLKernel::configure_internal(window);
}

Status CLInstanceNormalizationLayerKernelEx::validate(const ITensorInfo *input,
Expand Down
8 changes: 4 additions & 4 deletions runtime/compute/ARMComputeEx/src/core/CL/kernels/CLOneHotKernel.cpp
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Expand Up @@ -120,13 +120,13 @@ void CLOneHotKernel::configure_common(const ICLTensor *indices, const ICLTensor
ARM_COMPUTE_ERROR_THROW_ON(
validate_arguments(indices->info(), on_value->info(), output->info(), depth, axis));
// Configure kernel window
auto win_config =
auto [error, window] =
validate_and_configure_window(indices->info(), on_value->info(), output->info(), depth, axis);
ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
ARM_COMPUTE_ERROR_THROW_ON(error);
if (_is_off_value_memset)
{
// Replace window with calculated by infices info
win_config.second = calculate_max_window(*indices->info(), Steps());
window = calculate_max_window(*indices->info(), Steps());
}
_indices = indices;
_on_value = on_value;
Expand All @@ -144,7 +144,7 @@ void CLOneHotKernel::configure_common(const ICLTensor *indices, const ICLTensor
const std::string kernel_name = _is_off_value_memset ? "one_hot_only_on_value" : "one_hot";
_kernel = static_cast<cl::Kernel>(
CLKernelLibraryEx::get().create_kernel(kernel_name, build_opts.options()));
ICLKernel::configure_internal(win_config.second);
ICLKernel::configure_internal(window);
}
Status CLOneHotKernel::validate(const ITensorInfo *indices, const ITensorInfo *on_value,
const ITensorInfo *off_value, const ITensorInfo *output, int depth,
Expand Down
13 changes: 7 additions & 6 deletions runtime/compute/ARMComputeEx/src/core/CL/kernels/CLPadLayerKernelEx.cpp
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Expand Up @@ -65,8 +65,9 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output,
const auto is_reflect = static_cast<unsigned int>(mode == PaddingMode::REFLECT);
for (size_t i = 0; i < padding.size(); ++i)
{
ARM_COMPUTE_RETURN_ERROR_ON(padding.at(i).first > (input->dimension(i) - is_reflect));
ARM_COMPUTE_RETURN_ERROR_ON(padding.at(i).second > (input->dimension(i) - is_reflect));
auto [pad_before, pad_after] = padding.at(i);
ARM_COMPUTE_RETURN_ERROR_ON(pad_before > (input->dimension(i) - is_reflect));
ARM_COMPUTE_RETURN_ERROR_ON(pad_after > (input->dimension(i) - is_reflect));
}
}

Expand Down Expand Up @@ -152,10 +153,10 @@ void CLPadLayerKernelEx::configure(const CLCompileContext &compile_context, cons

// Configure window
unsigned int vec_size;
auto win_config = validate_and_configure_window(input->info(), output->info(), padding,
constant_value, mode, vec_size);
ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
ICLKernel::configure_internal(win_config.second);
auto [error, window] = validate_and_configure_window(input->info(), output->info(), padding,
constant_value, mode, vec_size);
ARM_COMPUTE_ERROR_THROW_ON(error);
ICLKernel::configure_internal(window);

// Set build options
std::string kernel_name = "pad_layer_";
Expand Down
6 changes: 3 additions & 3 deletions runtime/compute/ARMComputeEx/src/core/CL/kernels/CLQuantizationSymmetricKernel.cpp
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Expand Up @@ -125,9 +125,9 @@ void CLQuantizationSymmetricKernel::configure(const ICLTensor *input, const ICLT
const bool multi_access_x = (input_width_x / vec_size_x > 0);

// Configure kernel window
auto win_config = validate_and_configure_window(input->info(), output->info());
ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
ICLKernel::configure_internal(win_config.second);
auto [error, window] = validate_and_configure_window(input->info(), output->info());
ARM_COMPUTE_ERROR_THROW_ON(error);
ICLKernel::configure_internal(window);

// Create kernel
CLBuildOptions build_opts;
Expand Down
6 changes: 3 additions & 3 deletions runtime/compute/ARMComputeEx/src/core/CL/kernels/CLScaleFactorSymm8Kernel.cpp
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Expand Up @@ -121,11 +121,11 @@ void CLScaleFactorSymm8Kernel::configure(const ICLTensor *input, ICLTensor *outp
_kernel = static_cast<cl::Kernel>(
CLKernelLibraryEx::get().create_kernel("scale_factor_symm8", build_opts));

auto win_config = validate_and_configure_window(input->info(), output->info());
auto [error, window] = validate_and_configure_window(input->info(), output->info());

ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config));
ARM_COMPUTE_ERROR_THROW_ON(error);

ICLKernel::configure_internal(std::get<1>(win_config));
ICLKernel::configure_internal(window);
}

Status CLScaleFactorSymm8Kernel::validate(const ITensorInfo *input, const ITensorInfo *output)
Expand Down
6 changes: 3 additions & 3 deletions runtime/compute/ARMComputeEx/src/core/NEON/kernels/NEGEMMMatrixAccumulateBiasesKernel.cpp
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Expand Up @@ -117,9 +117,9 @@ void NEGEMMMatrixAccumulateBiasesKernel::configure(ITensor *accum, const ITensor
_accum = accum;

// Configure kernel window
auto win_config = validate_and_configure_window(accum->info(), biases->info());
ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
INEKernel::configure(win_config.second);
auto [error, window] = validate_and_configure_window(accum->info(), biases->info());
ARM_COMPUTE_ERROR_THROW_ON(error);
INEKernel::configure(window);
}

Status NEGEMMMatrixAccumulateBiasesKernel::validate(const ITensorInfo *accum,
Expand Down
7 changes: 3 additions & 4 deletions runtime/compute/ARMComputeEx/src/core/NEON/kernels/NEInstanceNormalizationLayerKernelEx.cpp
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Expand Up @@ -274,10 +274,9 @@ void NEInstanceNormalizationLayerKernelEx::configure(ITensor *input, ITensor *ou
}

// Configure kernel window
auto win_config = validate_and_configure_window(_input->info(), _output->info());
ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config));

INEKernel::configure(std::get<1>(win_config));
auto [error, window] = validate_and_configure_window(_input->info(), _output->info());
ARM_COMPUTE_ERROR_THROW_ON(error);
INEKernel::configure(window);
}

Status NEInstanceNormalizationLayerKernelEx::validate(const ITensorInfo *input,
Expand Down
3 changes: 2 additions & 1 deletion runtime/compute/ARMComputeEx/src/core/NEON/kernels/NEQuantizationSymmetricKernel.cpp
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Expand Up @@ -186,7 +186,8 @@ template <typename T> void NEQuantizationSymmetricKernel::quantize(const Window
const auto start = reinterpret_cast<const T *>(input.ptr());
const auto min_max = std::minmax_element(start, start + dim_x);
const auto int8_scale = 127;
auto range = std::max(std::abs(*min_max.first), std::abs(*min_max.second));
auto [min_val_ptr, max_val_ptr] = min_max;
auto range = std::max(std::abs(*min_val_ptr), std::abs(*max_val_ptr));
if (range == 0)
{
*reinterpret_cast<T *>(_scale_factor->ptr_to_element({id.y()})) = 1;
Expand Down
3 changes: 1 addition & 2 deletions runtime/compute/ARMComputeEx/src/core/UtilsEx.cpp
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Expand Up @@ -49,8 +49,7 @@ arm_compute::transposeconv_output_dimensions(unsigned int in_width, unsigned int
const PadStrideInfo &info, unsigned int invalid_right,
unsigned int invalid_bottom)
{
const unsigned int stride_x = info.stride().first;
const unsigned int stride_y = info.stride().second;
const auto [stride_x, stride_y] = info.stride();
const unsigned int padx = info.pad_left() + info.pad_right();
const unsigned int pady = info.pad_top() + info.pad_bottom();

Expand Down
3 changes: 1 addition & 2 deletions runtime/compute/ARMComputeEx/src/runtime/CL/functions/CLDirectTransposeConvLayer.cpp
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Expand Up @@ -154,8 +154,7 @@ void CLDirectTransposeConvLayer::configure(const CLCompileContext &compile_conte
unsigned int pad_right = 0;
unsigned int pad_top = 0;
unsigned int pad_bottom = 0;
const unsigned int stride_x = info.stride().first;
const unsigned int stride_y = info.stride().second;
const auto [stride_x, stride_y] = info.stride();

const DataLayout data_layout = input->info()->data_layout();

Expand Down
6 changes: 3 additions & 3 deletions runtime/compute/ARMComputeEx/src/runtime/CL/functions/CLGEMMMatrixAccumulateBiasesKernel.cpp
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Expand Up @@ -120,10 +120,10 @@ void CLGEMMMatrixAccumulateBiasesKernel::configure(const CLCompileContext &compi
unsigned int vector_size = 0;

// Configure kernel window
auto win_config =
auto [error, window] =
validate_and_configure_window(accum->info(), biases->info(), gpu_target, vector_size);
ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
ICLKernel::configure_internal(win_config.second);
ARM_COMPUTE_ERROR_THROW_ON(error);
ICLKernel::configure_internal(window);

// Add build options
CLBuildOptions build_opts;
Expand Down
6 changes: 3 additions & 3 deletions runtime/compute/ARMComputeEx/src/runtime/CL/functions/CLTransposeConvLayer.cpp
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Expand Up @@ -142,9 +142,9 @@ DeconvolutionMethod CLTransposeConvLayer::get_deconvolution_method(
const size_t idx_w = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
const size_t idx_h = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);

if (weights->dimension(idx_w) != deconv_info.stride().first ||
weights->dimension(idx_h) != deconv_info.stride().second || invalid_right != 0 ||
invalid_bottom != 0)
auto [stride_w, stride_h] = deconv_info.stride();
if (weights->dimension(idx_w) != stride_w || weights->dimension(idx_h) != stride_h ||
invalid_right != 0 || invalid_bottom != 0)
{
return DeconvolutionMethod::DIRECT;
}
Expand Down
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