diff options
Diffstat (limited to 'tests/validation/reference/SoftmaxLayer.cpp')
-rw-r--r-- | tests/validation/reference/SoftmaxLayer.cpp | 89 |
1 files changed, 48 insertions, 41 deletions
diff --git a/tests/validation/reference/SoftmaxLayer.cpp b/tests/validation/reference/SoftmaxLayer.cpp index 00206766f8..3fbac32a9b 100644 --- a/tests/validation/reference/SoftmaxLayer.cpp +++ b/tests/validation/reference/SoftmaxLayer.cpp @@ -25,6 +25,7 @@ #include "arm_compute/core/Helpers.h" #include "arm_compute/core/Types.h" +#include "utils/TypePrinter.h" namespace arm_compute { @@ -35,39 +36,43 @@ namespace validation namespace reference { template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type> -SimpleTensor<T> softmax_layer_generic(const SimpleTensor<T> &src, float beta, int32_t reduce_end_axis, bool is_log) +SimpleTensor<T> softmax_layer_generic(const SimpleTensor<T> &src, float beta, int32_t axis, bool is_log) { // Create reference SimpleTensor<T> dst{ src.shape(), src.data_type(), 1 }; - // Convert reduce-before axis (inclusive) to first n axes to reduce - const size_t first_n_reduce_axes = dim_index_2_num_dims(reduce_end_axis, static_cast<int32_t>(src.shape().num_dimensions())); + const int32_t n_dims = static_cast<int32_t>(src.shape().num_dimensions()); + ARM_COMPUTE_ERROR_ON(axis < -n_dims || axis >= n_dims); - // Compute reference. Lower dims are the collapsing of the first axis - // dimensions (i.e., the flattened dimension of each batch). The upper dims are - // instead the batches we want to normalize + const unsigned int actual_axis = static_cast<unsigned int>(wrap_around(axis, n_dims)); + Window window; + window.use_tensor_dimensions(src.shape()); + const unsigned int axis_dimension = src.shape()[actual_axis]; + window.set(actual_axis, Window::Dimension(0, 1, 1)); - const int lower_dims = src.shape().total_size_lower(first_n_reduce_axes); - - const int upper_dims = src.shape().total_size_upper(first_n_reduce_axes); - -#if defined(_OPENMP) - #pragma omp parallel for -#endif /* _OPENMP */ - for(int r = 0; r < upper_dims; ++r) + execute_window_loop(window, [&](const Coordinates & id) { - const T *src_row_ptr = src.data() + r * lower_dims; - T *dst_row_ptr = dst.data() + r * lower_dims; - - // Find max - const T max = *std::max_element(src_row_ptr, src_row_ptr + lower_dims); + // Find max along axis + Coordinates offset(id); + offset.set(actual_axis, 0); + T max = *reinterpret_cast<const T *>(src(offset)); + for(unsigned int axis_id = 1; axis_id < axis_dimension; ++axis_id) + { + offset.set(actual_axis, axis_id); + const T val = *reinterpret_cast<const T *>(src(offset)); + if(val > max) + { + max = val; + } + } // Regularize T sum(0.f); - std::transform(src_row_ptr, src_row_ptr + lower_dims, dst_row_ptr, [&sum, max, beta, is_log](T val) + for(unsigned int axis_id = 0; axis_id < axis_dimension; ++axis_id) { - T res{ (val - max) *beta }; - + offset.set(actual_axis, axis_id); + const T val = *reinterpret_cast<const T *>(src(offset)); + T res{ (val - max) *beta }; if(is_log) { sum += std::exp(res); @@ -77,50 +82,52 @@ SimpleTensor<T> softmax_layer_generic(const SimpleTensor<T> &src, float beta, in res = std::exp(res); sum += res; } - return res; - }); + *reinterpret_cast<T *>(dst(offset)) = res; + } // Normalize - std::transform(dst_row_ptr, dst_row_ptr + lower_dims, dst_row_ptr, [sum, is_log](T val) + for(unsigned int axis_id = 0; axis_id < axis_dimension; ++axis_id) { + offset.set(actual_axis, axis_id); + const T val = *reinterpret_cast<const T *>(dst(offset)); if(is_log) { - return val - static_cast<T>(std::log(sum)); + *reinterpret_cast<T *>(dst(offset)) = val - static_cast<T>(std::log(sum)); } else { - return val / sum; + *reinterpret_cast<T *>(dst(offset)) = val / sum; } - }); - } - + } + }); return dst; } -template SimpleTensor<float> softmax_layer_generic(const SimpleTensor<float> &src, float beta, int32_t reduce_end_axis, bool is_log); -template SimpleTensor<half> softmax_layer_generic(const SimpleTensor<half> &src, float beta, int32_t reduce_end_axis, bool is_log); +template SimpleTensor<float> softmax_layer_generic(const SimpleTensor<float> &src, float beta, int32_t axis, bool is_log); +template SimpleTensor<half> softmax_layer_generic(const SimpleTensor<half> &src, float beta, int32_t axis, bool is_log); template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type> -SimpleTensor<T> softmax_layer(const SimpleTensor<T> &src, float beta, int32_t reduce_end_axis) +SimpleTensor<T> softmax_layer(const SimpleTensor<T> &src, float beta, int32_t axis, bool is_log) { - return softmax_layer_generic<T>(src, beta, reduce_end_axis, false); + return softmax_layer_generic<T>(src, beta, axis, is_log); } template < typename T, typename std::enable_if < std::is_same<T, uint8_t>::value || std::is_same<T, int8_t>::value, int >::type > -SimpleTensor<T> softmax_layer(const SimpleTensor<T> &src, float beta, int32_t reduce_end_axis) +SimpleTensor<T> softmax_layer(const SimpleTensor<T> &src, float beta, int32_t axis, bool is_log) { - const QuantizationInfo output_quantization_info = arm_compute::get_softmax_output_quantization_info(src.data_type(), false); + const QuantizationInfo output_quantization_info = arm_compute::get_softmax_output_quantization_info(src.data_type(), is_log); SimpleTensor<float> src_tmp = convert_from_asymmetric(src); - SimpleTensor<float> dst_tmp = softmax_layer<float>(src_tmp, beta, reduce_end_axis); + SimpleTensor<float> dst_tmp = softmax_layer<float>(src_tmp, beta, axis, is_log); SimpleTensor<T> dst = convert_to_asymmetric<T>(dst_tmp, output_quantization_info); return dst; } -template SimpleTensor<float> softmax_layer(const SimpleTensor<float> &src, float beta, int32_t reduce_end_axis); -template SimpleTensor<half> softmax_layer(const SimpleTensor<half> &src, float beta, int32_t reduce_end_axis); -template SimpleTensor<uint8_t> softmax_layer(const SimpleTensor<uint8_t> &src, float beta, int32_t reduce_end_axis); -template SimpleTensor<int8_t> softmax_layer(const SimpleTensor<int8_t> &src, float beta, int32_t reduce_end_axis); +template SimpleTensor<float> softmax_layer(const SimpleTensor<float> &src, float beta, int32_t axis, bool is_log); +template SimpleTensor<half> softmax_layer(const SimpleTensor<half> &src, float beta, int32_t axis, bool is_log); +template SimpleTensor<uint8_t> softmax_layer(const SimpleTensor<uint8_t> &src, float beta, int32_t axis, bool is_log); +template SimpleTensor<int8_t> softmax_layer(const SimpleTensor<int8_t> &src, float beta, int32_t axis, bool is_log); + } // namespace reference } // namespace validation } // namespace test |