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authorAdnan AlSinan <adnan.alsinan@arm.com>2021-07-05 13:12:52 +0100
committerGeorgios Pinitas <georgios.pinitas@arm.com>2021-07-25 13:04:23 +0000
commit7075fe2c5ee6f7cfe7cfd9454d905235e70b9ac4 (patch)
treeb65671bdf37eb1ef8cc30ef64ab572da795546fa /src/core/CL/cl_kernels/nhwc/space_to_batch.cl
parent22f5ed51f1b01f7cf6993a556a0b763e437926fc (diff)
downloadComputeLibrary-7075fe2c5ee6f7cfe7cfd9454d905235e70b9ac4.tar.gz
Reorganize the kernels into nhwc, nchw and common folders
The Following kernels have been split into nchw/nhwc kernels files: - batchnormalization_layer - batch_to_space - channel_shuffle - depth_to_space - dequantization_layer - im2col - normalization_layer - normalize_planar_yuv_layer - normalize_planar_yuv_layer_quantized - pooling_layer - pooling_layer_quantized - remap - reorg_layer - scale - scale_quantized - space_to_batch - space_to_depth - upsample_layer - winograd_filter_transform - winograd_input_transform - winograd_output_transform The following kernels have been moved to nchw folder: - direct_convolution1x1 - direct_convolution3x3 - direct_convolution5x5 - direct_convolution_quantized - prior_box_layer The following kernels have been moved to nhwc folder: - direct_convolution - dwc_native_fp_nhwc - dwc_native_quantized_nhwc The following kernels have been removed: - sobel_filter While the rest kerenls have been moved to the common folder. Partially resolves COMPMID-4453 Signed-off-by: Adnan AlSinan <adnan.alsinan@arm.com> Change-Id: Ic327ac935687ec351c610c65a3c6357f364a5a58 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5919 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/core/CL/cl_kernels/nhwc/space_to_batch.cl')
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diff --git a/src/core/CL/cl_kernels/nhwc/space_to_batch.cl b/src/core/CL/cl_kernels/nhwc/space_to_batch.cl
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+/*
+ * Copyright (c) 2018-2021 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 "helpers.h"
+
+#if defined(BATCH_SIZE) && defined(DATA_TYPE) && defined(WIDTH_IN) && defined(HEIGHT_IN)
+/** Calculate the space to batch conversion. (NHWC)
+ *
+ * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=float
+ * @note The block shape tensor rank must be passed at compile time using -DBLOCK_SHAPE_DIM. e.g. -DBLOCK_SHAPE_DIM=2
+ *
+ * @param[in] input_ptr Pointer to the source tensor. Supported data types: All
+ * @param[in] input_stride_x Stride of the source tensor in X dimension (in bytes)
+ * @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] input_stride_y Stride of the source image in Y dimension (in bytes)
+ * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] input_stride_z Stride of the source tensor in Z dimension (in bytes)
+ * @param[in] input_step_z input_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in] input_offset_first_element_in_bytes The offset of the first element in the first source image
+ * @param[in] paddings_ptr Pointer to the second source image. Supported data types: S32
+ * @param[in] paddings_stride_x Stride of the paddinds tensor in X dimension (in bytes)
+ * @param[in] paddings_step_x paddings_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] paddings_stride_y Stride of the paddinds tensor in Y dimension (in bytes)
+ * @param[in] paddings_step_y paddings_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] paddingse_offset_first_element_in_bytes The offset of the first element in the second source image
+ * @param[in] block_shape_ptr Pointer to the block shape tensor. Supported data types: S32
+ * @param[in] block_shape_stride_x Stride of the block shape tensor in X dimension (in bytes)
+ * @param[in] block_shape_step_x block_shape_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] block_shape_offset_first_element_in_bytes The offset of the first element in the block shapetensor
+ * @param[in] batch_id The output tensor batch id
+ * @param[out] output_ptr Pointer to the destination tensor. Supported data types: same as @p input_ptr
+ * @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes)
+ * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes)
+ * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] output_stride_z Stride of the destination tensor in Z dimension (in bytes)
+ * @param[in] output_step_z output_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination image
+ */
+__kernel void space_to_batch_nhwc(
+ TENSOR4D_DECLARATION(input),
+ IMAGE_DECLARATION(paddings),
+ VECTOR_DECLARATION(block_shape),
+ const int batch_id,
+ TENSOR3D_DECLARATION(output))
+{
+ Tensor4D in = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(input, 0);
+ Image pad = CONVERT_TO_IMAGE_STRUCT_NO_STEP(paddings);
+ Vector block = CONVERT_TO_VECTOR_STRUCT_NO_STEP(block_shape);
+ Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output);
+
+ const int pad_left_x = *((__global int *)offset(&pad, 0, 0));
+ const int pad_right_x = *((__global int *)offset(&pad, 1, 0));
+ const int pad_left_y = *((__global int *)offset(&pad, 0, 1));
+ const int pad_right_y = *((__global int *)offset(&pad, 1, 1));
+
+ int block_x = *((__global int *)vector_offset(&block, 0));
+ int block_y = *((__global int *)vector_offset(&block, 1));
+
+ const int out_x = get_global_id(1);
+ const int out_y = get_global_id(2);
+ const int z = get_global_id(0);
+
+ const int pos_x = out_x * block_x + ((batch_id / BATCH_IN) % block_x);
+ const int pos_y = out_y * block_y + ((batch_id / BATCH_IN) / block_x);
+
+ if(((pos_y >= pad_left_y) && (pos_y < pad_left_y + HEIGHT_IN) && (pos_x >= pad_left_x) && (pos_x < pad_left_x + WIDTH_IN)))
+ {
+ const int w = batch_id % BATCH_IN;
+ const int in_x = pos_x - pad_left_x;
+ const int in_y = pos_y - pad_left_y;
+
+ *((__global DATA_TYPE *)out.ptr) = *((__global DATA_TYPE *)tensor4D_offset(&in, z, in_x, in_y, w));
+ }
+}
+#endif // defined(BATCH_SIZE) && defined(DATA_TYPE) && defined(WIDTH_IN) && defined(HEIGHT_IN)
+
+#if defined(BATCH_SIZE) && defined(DATA_TYPE) && defined(BLOCK_SHAPE_X) && defined(BLOCK_SHAPE_Y) && defined(PAD_LEFT_X) && defined(PAD_RIGHT_X) && defined(PAD_LEFT_Y) && defined(PAD_RIGHT_Y) && defined(WIDTH_IN) && defined(HEIGHT_IN)
+/** Calculate the space to batch conversion. (NHWC)
+ *
+ * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=float
+ * @note The input tensor batch size must be passed at compile time using -DBATCH_SIZE. e.g. -DBATCH_SIZE=2
+ * @note The block shape x must be passed at compile time using -DBLOCK_SHAPE_X. e.g. -DBLOCK_SHAPE_X=2
+ * @note The block shape y must be passed at compile time using -DBLOCK_SHAPE_Y. e.g. -DBLOCK_SHAPE_Y=2
+ * @note The starting pad value of x must be passed at compile time using -DPAD_LEFT_X. e.g. -DPAD_LEFT_X=2
+ * @note The ending pad value of x must be passed at compile time using -DPAD_RIGHT_X. e.g. -DPAD_RIGHT_X=2
+ * @note The starting pad value of y must be passed at compile time using -DPAD_LEFT_Y. e.g. -DPAD_LEFT_Y=2
+ * @note The ending pad value of y must be passed at compile time using -DPAD_RIGHT_Y. e.g. -DPAD_RIGHT_X=2
+ *
+ * @param[in] input_ptr Pointer to the source tensor. Supported data types: All
+ * @param[in] input_stride_x Stride of the source tensor in X dimension (in bytes)
+ * @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] input_stride_y Stride of the source image in Y dimension (in bytes)
+ * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] input_stride_z Stride of the source tensor in Z dimension (in bytes)
+ * @param[in] input_step_z input_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in] input_offset_first_element_in_bytes The offset of the first element in the first source image
+ * @param[in] batch_id The output tensor batch id
+ * @param[out] output_ptr Pointer to the destination tensor. Supported data types: same as @p input_ptr
+ * @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes)
+ * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes)
+ * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] output_stride_z Stride of the source tensor in Z dimension (in bytes)
+ * @param[in] output_step_z output_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination image
+ */
+__kernel void space_to_batch_static_nhwc(
+ TENSOR4D_DECLARATION(input),
+ const int batch_id,
+ TENSOR3D_DECLARATION(output))
+{
+ Tensor4D in = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(input, 0);
+ Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output);
+
+ int block_x = BLOCK_SHAPE_X;
+ int block_y = BLOCK_SHAPE_Y;
+
+ const int out_x = get_global_id(1);
+ const int out_y = get_global_id(2);
+ const int z = get_global_id(0);
+
+ const int pos_x = out_x * block_x + ((batch_id / BATCH_IN) % block_x);
+ const int pos_y = out_y * block_y + ((batch_id / BATCH_IN) / block_x);
+
+ if(pos_y >= PAD_LEFT_Y && pos_y < PAD_LEFT_Y + HEIGHT_IN && pos_x >= PAD_LEFT_X && pos_x < PAD_LEFT_X + WIDTH_IN)
+ {
+ const int w = batch_id % BATCH_IN;
+ const int in_x = pos_x - PAD_LEFT_X;
+ const int in_y = pos_y - PAD_LEFT_Y;
+
+ *((__global DATA_TYPE *)out.ptr) = *((__global DATA_TYPE *)tensor4D_offset(&in, z, in_x, in_y, w));
+ }
+}
+#endif // defined(BATCH_SIZE) && defined(DATA_TYPE) && defined(BLOCK_SHAPE_X) && defined(BLOCK_SHAPE_Y) && defined(PAD_LEFT_X) && defined(PAD_RIGHT_X) && defined(PAD_LEFT_Y) && defined(PAD_RIGHT_Y) && defined(WIDTH_IN) && defined(HEIGHT_IN) \ No newline at end of file