Implementation of ClPooling3d

 - For NDHWC layout
 - For F16 and F32 data types
 - Mixed Precision stil not supported

Resolves: COMPMID-4670
Signed-off-by: ramy.elgammal@arm.com
Change-Id: I0e14a13e4625569e8e5ee67e6033bd1efe0da469
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7262
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: SiCong Li <sicong.li@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 0 insertions, 221 deletions

diff --git a/tests/validation/reference/Pool3D.cpp b/tests/validation/reference/Pool3D.cpp
deleted file mode 100644
index 85a594e262..0000000000
--- a/tests/validation/reference/Pool3D.cpp
+++ /dev/null
@@ -1,221 +0,0 @@
-/*
- * Copyright (c) 2022 Arm Limited.
- *
- * SPDX-License-Identifier: MIT
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to
- * deal in the Software without restriction, including without limitation the
- * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
- * sell copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-
-#include "Pool3D.h"
-#include "arm_compute/core/utils/misc/ShapeCalculator.h"
-#include "tests/validation/Helpers.h"
-
-namespace arm_compute
-{
-namespace test
-{
-namespace validation
-{
-namespace reference
-{
-using namespace arm_compute::misc::shape_calculator;
-
-template <typename T>
-SimpleTensor<T> pool3d_internal(const SimpleTensor<T> &src, const Pool3DInfo &pool3d_info, SimpleTensor<uint32_t> *indices)
-{
-    TensorShape     pooled_shape = compute_pool3d_shape(src.shape(), pool3d_info);
-    SimpleTensor<T> dst{ pooled_shape, src.data_type(), 1 };
-
-    if(indices != nullptr)
-    {
-        *indices = SimpleTensor<uint32_t> { pooled_shape, DataType::U32, 1 };
-    }
-
-    const int idx_channel = 0;
-    const int idx_width   = 1;
-    const int idx_height  = 2;
-    const int idx_depth   = 3;
-    const int idx_batch   = 4;
-
-    const int pool_size_width  = pool3d_info.is_global_pooling ? src.shape()[idx_width] : pool3d_info.pool_size.width;
-    const int pool_size_height = pool3d_info.is_global_pooling ? src.shape()[idx_height] : pool3d_info.pool_size.height;
-    const int pool_size_depth  = pool3d_info.is_global_pooling ? src.shape()[idx_depth] : pool3d_info.pool_size.depth;
-
-    const int pool_stride_width  = static_cast<int>(pool3d_info.strides.width);
-    const int pool_stride_height = static_cast<int>(pool3d_info.strides.height);
-    const int pool_stride_depth  = static_cast<int>(pool3d_info.strides.depth);
-
-    const int pad_left  = static_cast<int>(pool3d_info.padding.left);
-    const int pad_top   = static_cast<int>(pool3d_info.padding.top);
-    const int pad_front = static_cast<int>(pool3d_info.padding.front);
-
-    const int pad_right  = static_cast<int>(pool3d_info.padding.right);
-    const int pad_bottom = static_cast<int>(pool3d_info.padding.bottom);
-    const int pad_back   = static_cast<int>(pool3d_info.padding.back);
-
-    const int num_channels = static_cast<int>(src.shape()[idx_channel]);
-    const int num_batches  = static_cast<int>(src.shape()[idx_batch]);
-
-    ARM_COMPUTE_ERROR_ON(num_channels != static_cast<int>(dst.shape()[idx_channel]));
-    ARM_COMPUTE_ERROR_ON(num_batches != static_cast<int>(dst.shape()[idx_batch]));
-
-    const int w_src = static_cast<int>(src.shape()[idx_width]);
-    const int h_src = static_cast<int>(src.shape()[idx_height]);
-    const int d_src = static_cast<int>(src.shape()[idx_depth]);
-    const int w_dst = static_cast<int>(dst.shape()[idx_width]);
-    const int h_dst = static_cast<int>(dst.shape()[idx_height]);
-    const int d_dst = static_cast<int>(dst.shape()[idx_depth]);
-
-    const bool exclude_padding = pool3d_info.exclude_padding;
-
-    const int height_stride_src = num_channels * w_src;
-    const int depth_stride_src  = height_stride_src * h_src;
-    const int batch_stride_src  = depth_stride_src * d_src;
-    const int height_stride_dst = num_channels * w_dst;
-    const int depth_stride_dst  = height_stride_dst * h_dst;
-    const int batch_stride_dst  = depth_stride_dst * d_dst;
-
-    for(int b = 0; b < num_batches; ++b)
-    {
-        const int batch_offset_dst = b * batch_stride_dst;
-        const int batch_offset_src = b * batch_stride_src;
-        for(int c = 0; c < num_channels; ++c)
-        {
-            for(int d = 0; d < d_dst; ++d)
-            {
-                const int depth_offset_dst = d * depth_stride_dst;
-                for(int h = 0; h < h_dst; ++h)
-                {
-                    const int height_offset_dst = h * height_stride_dst;
-                    for(int w = 0; w < w_dst; ++w)
-                    {
-                        int wstart = w * pool_stride_width - pad_left;
-                        int hstart = h * pool_stride_height - pad_top;
-                        int dstart = d * pool_stride_depth - pad_front;
-                        int wend   = std::min(wstart + pool_size_width, w_src + pad_right);
-                        int hend   = std::min(hstart + pool_size_height, h_src + pad_bottom);
-                        int dend   = std::min(dstart + pool_size_depth, d_src + pad_back);
-
-                        // this may not be equal to pool_w * pool_h * pool_d because of
-                        // DimensionRoundingType choice (CEIL)
-                        int pool_size = (dend - dstart) * (hend - hstart) * (wend - wstart);
-
-                        // limit [start, end) to [0, w_src)
-                        wstart = std::max(wstart, 0);
-                        hstart = std::max(hstart, 0);
-                        dstart = std::max(dstart, 0);
-                        wend   = std::min(wend, w_src);
-                        hend   = std::min(hend, h_src);
-                        dend   = std::min(dend, d_src);
-
-                        auto max_val = -std::numeric_limits<T>::infinity();
-                        int  max_index{ 0 };
-                        T    avg_val = static_cast<T>(0.f);
-                        T    l2_val  = static_cast<T>(0.f);
-
-                        if(exclude_padding)
-                        {
-                            pool_size = (dend - dstart) * (hend - hstart) * (wend - wstart);
-                        }
-
-                        for(int z = dstart; z < dend; ++z)
-                        {
-                            const int depth_offset_src = z * depth_stride_src;
-                            for(int y = hstart; y < hend; ++y)
-                            {
-                                const int height_offset_src = y * height_stride_src;
-                                for(int x = wstart; x < wend; ++x)
-                                {
-                                    const auto val = static_cast<T>(
-                                                         src[batch_offset_src + depth_offset_src + height_offset_src + x * num_channels + c]);
-
-                                    if(val > max_val)
-                                    {
-                                        max_val   = val;
-                                        max_index = coord2index(src.shape(), Coordinates(c, x, y, z, 0));
-                                    }
-
-                                    avg_val += val;
-                                    l2_val += val * val;
-                                }
-                            }
-                        }
-
-                        avg_val /= pool_size;
-                        l2_val = static_cast<T>(std::sqrt(l2_val / pool_size));
-
-                        int dst_index = batch_offset_dst + depth_offset_dst + height_offset_dst + w * num_channels + c;
-                        switch(pool3d_info.pool_type)
-                        {
-                            case PoolingType::MAX:
-                                dst[dst_index] = static_cast<T>(max_val);
-                                break;
-                            case PoolingType::AVG:
-                                dst[dst_index] = static_cast<T>(avg_val);
-                                break;
-                            case PoolingType::L2:
-                                dst[dst_index] = static_cast<T>(l2_val);
-                                break;
-                            default:
-                                ARM_COMPUTE_ERROR("Pooling Type should be either MAX, AVG or L2");
-                        }
-
-                        if(indices != nullptr)
-                        {
-                            (*indices)[dst_index] = max_index;
-                        }
-                    }
-                }
-            }
-        }
-    }
-
-    return dst;
-}
-
-template SimpleTensor<float> pool3d(const SimpleTensor<float> &src, const Pool3DInfo &pool3d_info, const QuantizationInfo &output_qinfo, SimpleTensor<uint32_t> *indices);
-template SimpleTensor<half> pool3d(const SimpleTensor<half> &src, const Pool3DInfo &pool3d_info, const QuantizationInfo &output_qinfo, SimpleTensor<uint32_t> *indices);
-
-template <typename T>
-SimpleTensor<T> pool3d(const SimpleTensor<T> &src, const Pool3DInfo &pool3d_info, const QuantizationInfo &output_qinfo, SimpleTensor<uint32_t> *indices)
-{
-    ARM_COMPUTE_UNUSED(output_qinfo);
-    return pool3d_internal<T>(src, pool3d_info, indices);
-}
-
-template <>
-SimpleTensor<int8_t> pool3d<int8_t>(const SimpleTensor<int8_t> &src, const Pool3DInfo &pool3d_info, const QuantizationInfo &output_qinfo, SimpleTensor<uint32_t> *indices)
-{
-    SimpleTensor<float> src_tmp = convert_from_asymmetric(src);
-    SimpleTensor<float> dst_tmp = pool3d_internal<float>(src_tmp, pool3d_info, indices);
-    return convert_to_asymmetric<int8_t>(dst_tmp, output_qinfo);
-}
-
-template <>
-SimpleTensor<uint8_t> pool3d<uint8_t>(const SimpleTensor<uint8_t> &src, const Pool3DInfo &pool3d_info, const QuantizationInfo &output_qinfo, SimpleTensor<uint32_t> *indices)
-{
-    SimpleTensor<float> src_tmp = convert_from_asymmetric(src);
-    SimpleTensor<float> dst_tmp = pool3d_internal<float>(src_tmp, pool3d_info, indices);
-    return convert_to_asymmetric<uint8_t>(dst_tmp, output_qinfo);
-}
-
-} // namespace reference
-} // namespace validation
-} // namespace test
-} // namespace arm_compute
\ No newline at end of file