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author | Georgios Pinitas <georgios.pinitas@arm.com> | 2017-11-29 10:17:56 +0000 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:41:36 +0000 |
commit | b6f182d3e5b69cc193d7e5ec397c4d61083572d5 (patch) | |
tree | bb55a14c3783d3024b77d7a2bc0e1a001d956d94 /tests | |
parent | 2fdc40956a4d521ec811bf33aafd0b1e756d6d54 (diff) | |
download | ComputeLibrary-b6f182d3e5b69cc193d7e5ec397c4d61083572d5.tar.gz |
COMPMID-556: Fix CLDepthwiseConvolution3x3 Kernel.
Kernel was not sliding the input window.
Change-Id: Ia5903ceaed1243e86bee773a84102d8a1132dfa5
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/111055
Tested-by: BSG Visual Compute Jenkins server to access repositories on http://mpd-gerrit.cambridge.arm.com <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Diffstat (limited to 'tests')
-rw-r--r-- | tests/datasets/DepthwiseConvolutionDataset.h | 10 | ||||
-rw-r--r-- | tests/validation/CPP/DepthwiseConvolution.cpp | 52 |
2 files changed, 33 insertions, 29 deletions
diff --git a/tests/datasets/DepthwiseConvolutionDataset.h b/tests/datasets/DepthwiseConvolutionDataset.h index 430d2c9aca..2c8347fc8c 100644 --- a/tests/datasets/DepthwiseConvolutionDataset.h +++ b/tests/datasets/DepthwiseConvolutionDataset.h @@ -161,10 +161,10 @@ class SmallDepthwiseConvolutionDataset3x3 final : public DepthwiseConvolutionDat public: SmallDepthwiseConvolutionDataset3x3() { - add_config(TensorShape(7U, 7U, 3U), TensorShape(3U, 3U, 3U), TensorShape(3U), TensorShape(5U, 5U, 3U), PadStrideInfo(1, 1, 0, 0)); + add_config(TensorShape(7U, 7U, 3U, 2U), TensorShape(3U, 3U, 3U), TensorShape(3U), TensorShape(5U, 5U, 3U, 2U), PadStrideInfo(1, 1, 0, 0)); add_config(TensorShape(33U, 27U, 11U), TensorShape(3U, 3U, 11U), TensorShape(11U), TensorShape(11U, 14U, 11U), PadStrideInfo(3, 2, 1, 1)); - add_config(TensorShape(21U, 31U, 9U), TensorShape(3U, 3U, 9U), TensorShape(9U), TensorShape(21U, 15U, 9U), PadStrideInfo(1, 2, 1, 0)); - add_config(TensorShape(33U, 27U, 11U), TensorShape(3U, 3U, 11U), TensorShape(11U), TensorShape(31U, 14U, 11U), PadStrideInfo(1, 2, 0, 1)); + add_config(TensorShape(21U, 31U, 9U, 4U), TensorShape(3U, 3U, 9U), TensorShape(9U), TensorShape(21U, 15U, 9U, 4U), PadStrideInfo(1, 2, 1, 0)); + add_config(TensorShape(33U, 27U, 11U, 3U), TensorShape(3U, 3U, 11U), TensorShape(11U), TensorShape(31U, 14U, 11U, 3U), PadStrideInfo(1, 2, 0, 1)); } }; @@ -173,11 +173,11 @@ class LargeDepthwiseConvolutionDataset3x3 final : public DepthwiseConvolutionDat public: LargeDepthwiseConvolutionDataset3x3() { - add_config(TensorShape(233U, 277U, 55U), TensorShape(3U, 3U, 55U), TensorShape(55U), TensorShape(116U, 275U, 55U), PadStrideInfo(2, 1, 0, 0)); + add_config(TensorShape(233U, 277U, 55U, 3U), TensorShape(3U, 3U, 55U), TensorShape(55U), TensorShape(116U, 275U, 55U, 3U), PadStrideInfo(2, 1, 0, 0)); add_config(TensorShape(333U, 277U, 77U), TensorShape(3U, 3U, 77U), TensorShape(77U), TensorShape(111U, 138U, 77U), PadStrideInfo(3, 2, 1, 0)); add_config(TensorShape(177U, 311U, 22U), TensorShape(3U, 3U, 22U), TensorShape(22U), TensorShape(177U, 156U, 22U), PadStrideInfo(1, 2, 1, 1)); add_config(TensorShape(233U, 277U, 55U), TensorShape(3U, 3U, 55U), TensorShape(55U), TensorShape(231U, 138U, 55U), PadStrideInfo(1, 2, 0, 0)); - add_config(TensorShape(333U, 277U, 77U), TensorShape(3U, 3U, 77U), TensorShape(77U), TensorShape(166U, 93U, 77U), PadStrideInfo(2, 3, 0, 1)); + add_config(TensorShape(333U, 277U, 77U, 5U), TensorShape(3U, 3U, 77U), TensorShape(77U), TensorShape(166U, 93U, 77U, 5U), PadStrideInfo(2, 3, 0, 1)); add_config(TensorShape(177U, 311U, 22U), TensorShape(3U, 3U, 22U), TensorShape(22U), TensorShape(89U, 311U, 22U), PadStrideInfo(2, 1, 1, 1)); } }; diff --git a/tests/validation/CPP/DepthwiseConvolution.cpp b/tests/validation/CPP/DepthwiseConvolution.cpp index ad0653846b..229e044783 100644 --- a/tests/validation/CPP/DepthwiseConvolution.cpp +++ b/tests/validation/CPP/DepthwiseConvolution.cpp @@ -137,6 +137,7 @@ SimpleTensor<uint8_t> depthwise_convolution(const SimpleTensor<uint8_t> &src, co const int input_width = src.shape().x(); const int input_height = src.shape().y(); const int input_depth = src.shape().z(); + const int num_batches = src.shape().total_size() / (input_width * input_height * input_depth); const int filter_half_size = filter_width / 2; const int pad_x = std::min(filter_half_size, static_cast<int>(conv_info.pad().first)); @@ -145,37 +146,40 @@ SimpleTensor<uint8_t> depthwise_convolution(const SimpleTensor<uint8_t> &src, co const int minimum_y = -pad_y + filter_half_size; int out_pos = 0; - for(int z = 0; z < input_depth; ++z) + for(int r = 0; r < num_batches; ++r) { - int32_t bias_val = *static_cast<const int32_t *>(biases(Coordinates(z))); - for(int y = minimum_y; y < input_height + pad_y - filter_half_size; y += conv_info.stride().second) + for(int z = 0; z < input_depth; ++z) { - for(int x = minimum_x; x < input_width + pad_x - filter_half_size; x += conv_info.stride().first) + int32_t bias_val = *static_cast<const int32_t *>(biases(Coordinates(z))); + for(int y = minimum_y; y < input_height + pad_y - filter_half_size; y += conv_info.stride().second) { - Coordinates coords(x, y, z); - int filter_offset = filter_plane * z; - - uint32_t val = 0; - for(int j = y - filter_half_size; j <= (y + filter_half_size); ++j) + for(int x = minimum_x; x < input_width + pad_x - filter_half_size; x += conv_info.stride().first) { - for(int i = x - filter_half_size; i <= (x + filter_half_size); ++i) + Coordinates coords(x, y, z); + int filter_offset = filter_plane * z; + + uint32_t val = 0; + for(int j = y - filter_half_size; j <= (y + filter_half_size); ++j) { - coords.set(0, i); - coords.set(1, j); - auto in_val = tensor_elem_at<uint8_t>(src, coords, BorderMode::CONSTANT, 0); - uint8_t w_val = *(weights.data() + filter_offset); - val += (in_val + input_offset) * (w_val + weights_offset); - ++filter_offset; + for(int i = x - filter_half_size; i <= (x + filter_half_size); ++i) + { + coords.set(0, i); + coords.set(1, j); + auto in_val = tensor_elem_at<uint8_t>(src, coords, BorderMode::CONSTANT, 0); + uint8_t w_val = *(weights.data() + filter_offset); + val += (in_val + input_offset) * (w_val + weights_offset); + ++filter_offset; + } } + val += bias_val; + val = asymm_rounding_divide_by_pow2(asymm_int_mult(val, output_multiplier), output_shift); + val += output_offset; + val = std::max<int32_t>(val, 0); + val = std::min<int32_t>(val, 255); + + // Store the result + dst[out_pos++] = val; } - val += bias_val; - val = asymm_rounding_divide_by_pow2(asymm_int_mult(val, output_multiplier), output_shift); - val += output_offset; - val = std::max<int32_t>(val, 0); - val = std::min<int32_t>(val, 255); - - // Store the result - dst[out_pos++] = val; } } } |