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author | Giuseppe Rossini <giuseppe.rossini@arm.com> | 2018-08-24 10:24:12 +0100 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:54:54 +0000 |
commit | 87e896a46a9403813654cadd609960c3b2af87be (patch) | |
tree | e2083418cc808e9acb5078265f1186008d724971 /tests/validation/reference/SoftmaxLayer.cpp | |
parent | e3d24cee3688b2ddffd5858aba4904bf51398f08 (diff) | |
download | ComputeLibrary-87e896a46a9403813654cadd609960c3b2af87be.tar.gz |
[COMPMID-1353] Add support for 4D Softmax layer on OpenCL
Change-Id: I4342d4240fe5b1aab234c015684a1216c3990a5f
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/145631
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Diffstat (limited to 'tests/validation/reference/SoftmaxLayer.cpp')
-rw-r--r-- | tests/validation/reference/SoftmaxLayer.cpp | 20 |
1 files changed, 12 insertions, 8 deletions
diff --git a/tests/validation/reference/SoftmaxLayer.cpp b/tests/validation/reference/SoftmaxLayer.cpp index aa640ad5e6..7f2c36ecef 100644 --- a/tests/validation/reference/SoftmaxLayer.cpp +++ b/tests/validation/reference/SoftmaxLayer.cpp @@ -39,21 +39,25 @@ SimpleTensor<T> softmax_layer(const SimpleTensor<T> &src, float beta) // Create reference SimpleTensor<T> dst{ src.shape(), src.data_type(), 1 }; - // Compute reference - const int cols = src.shape()[0]; - const int upper_dims = src.num_elements() / cols; + const bool is_4D_input = (src.shape().num_dimensions() > 2); + + // Compute reference. Lower dims are + // - the number of columns for the 2D case + // - the collapsing of the first three dimensions (i.e., the flattened dimension of each batch) in the 4D case + const int lower_dims = (is_4D_input ? src.shape()[2] * src.shape()[1] * src.shape()[0] : src.shape()[0]); + const int upper_dims = src.num_elements() / lower_dims; for(int r = 0; r < upper_dims; ++r) { - const T *src_row_ptr = src.data() + r * cols; - T *dst_row_ptr = dst.data() + r * cols; + 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 + cols); + const T max = *std::max_element(src_row_ptr, src_row_ptr + lower_dims); // Regularize T sum(0.f); - std::transform(src_row_ptr, src_row_ptr + cols, dst_row_ptr, [&sum, max, beta](T val) + std::transform(src_row_ptr, src_row_ptr + lower_dims, dst_row_ptr, [&sum, max, beta](T val) { const T res(std::exp((val - max) * beta)); sum += res; @@ -61,7 +65,7 @@ SimpleTensor<T> softmax_layer(const SimpleTensor<T> &src, float beta) }); // Normalize - std::transform(dst_row_ptr, dst_row_ptr + cols, dst_row_ptr, [sum](T val) + std::transform(dst_row_ptr, dst_row_ptr + lower_dims, dst_row_ptr, [sum](T val) { return val / sum; }); |