COMPMID-2744 [CL] add support for 9x9 quantized direct convolution

Change-Id: I858ce5b9a530f8568e154f5d724d267e142ef9b2
Signed-off-by: Sang-Hoon Park <sang-hoon.park@arm.com>
Reviewed-on: https://review.mlplatform.org/c/2091
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-by: Giuseppe Rossini <giuseppe.rossini@arm.com>

1 files changed, 0 insertions, 249 deletions

diff --git a/src/core/CL/cl_kernels/direct_convolution_1x1_3x3_5x5_quantized.cl b/src/core/CL/cl_kernels/direct_convolution_1x1_3x3_5x5_quantized.cl
deleted file mode 100644
index 5ad9afb23c..0000000000
--- a/src/core/CL/cl_kernels/direct_convolution_1x1_3x3_5x5_quantized.cl
+++ /dev/null
@@ -1,249 +0,0 @@
-/*
- * Copyright (c) 2017-2019 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_asymm.h"
-
-#undef CONVERT_SAT
-
-#if defined(DATA_TYPE) && defined(STRIDE_X) && defined(WEIGHTS_DEPTH)
-
-#if KERNEL_SIZE == 5
-
-#if STRIDE_X == 1
-#define CONVOLUTION1x5(acc, src_row_ptr, weights_row_ptr) CONVOLUTION1x5_STRIDE1(acc, src_row_ptr, weights_row_ptr)
-#elif STRIDE_X == 2
-#define CONVOLUTION1x5(acc, src_row_ptr, weights_row_ptr) CONVOLUTION1x5_STRIDE2(acc, src_row_ptr, weights_row_ptr)
-#else /* STRIDE_X not equals 1 or 2 */
-#error "STRIDE_X larger than 2 is not supported"
-#endif /* STRIDE_X */
-
-#define CONVOLUTION1x5_STRIDE1(acc, src_row_ptr, weights_row_ptr)                                                    \
-    ({                                                                                                               \
-        int4 weights_values0 = convert_int4(vload4(0, weights_row_ptr));                                             \
-        int  weights_value1  = convert_int(*(weights_row_ptr + 4));                                                  \
-        int8 src0            = convert_int8(vload8(0, src_row_ptr));                                                 \
-        int4 src1            = convert_int4(vload4(0, src_row_ptr + 8));                                             \
-        acc += (src0 + input_offset) * ((int8)weights_values0.s0 + weight_offset);                                   \
-        acc += ((int8)(src0.s1234, src0.s567, src1.s0) + input_offset) * ((int8)weights_values0.s1 + weight_offset); \
-        acc += ((int8)(src0.s234, src0.s567, src1.s01) + input_offset) * ((int8)weights_values0.s2 + weight_offset); \
-        acc += ((int8)(src0.s345, src0.s67, src1.s012) + input_offset) * ((int8)weights_values0.s3 + weight_offset); \
-        acc += ((int8)(src0.s45, src0.s67, src1.s0123) + input_offset) * ((int8)weights_value1 + weight_offset);     \
-    })
-
-#define CONVOLUTION1x5_STRIDE2(acc, src_row_ptr, weights_row_ptr)                                                    \
-    ({                                                                                                               \
-        int4  weights_values0 = convert_int4(vload4(0, weights_row_ptr));                                            \
-        int   weights_value1  = convert_int(*(weights_row_ptr + 4));                                                 \
-        int16 src0            = convert_int16(vload16(0, src_row_ptr));                                              \
-        int4  src1            = convert_int4(vload4(0, src_row_ptr + 16));                                           \
-        acc += (src0.even + input_offset) * ((int8)weights_values0.s0 + weight_offset);                              \
-        acc += ((int8)(src0.s1357, src0.s9BDF) + input_offset) * ((int8)weights_values0.s1 + weight_offset);         \
-        acc += ((int8)(src0.s2468, src0.sACE, src1.s0) + input_offset) * ((int8)weights_values0.s2 + weight_offset); \
-        acc += ((int8)(src0.s3579, src0.sBDF, src1.s1) + input_offset) * ((int8)weights_values0.s3 + weight_offset); \
-        acc += ((int8)(src0.s468a, src0.sCE, src1.s02) + input_offset) * ((int8)weights_value1 + weight_offset);     \
-    })
-
-#elif KERNEL_SIZE == 3
-
-#if STRIDE_X == 1
-#define CONVOLUTION1x3(acc, src_row_ptr, weights_row_ptr) CONVOLUTION1x3_STRIDE1(acc, src_row_ptr, weights_row_ptr)
-#elif STRIDE_X == 2
-#define CONVOLUTION1x3(acc, src_row_ptr, weights_row_ptr) CONVOLUTION1x3_STRIDE2(acc, src_row_ptr, weights_row_ptr)
-#else /* STRIDE_X not equals 1 or 2 */
-#error "STRIDE_X larger than 2 is not supported"
-#endif /* STRIDE_X */
-
-#define CONVOLUTION1x3_STRIDE1(acc, src_row_ptr, weights_row_ptr)                                                    \
-    ({                                                                                                               \
-        int3 weights_values0 = convert_int3(vload3(0, weights_row_ptr));                                             \
-        int8 src0            = convert_int8(vload8(0, src_row_ptr));                                                 \
-        int2 src1            = convert_int2(vload2(0, src_row_ptr + 8));                                             \
-        acc += (src0 + input_offset) * ((int8)weights_values0.s0 + weight_offset);                                   \
-        acc += ((int8)(src0.s1234, src0.s567, src1.s0) + input_offset) * ((int8)weights_values0.s1 + weight_offset); \
-        acc += ((int8)(src0.s234, src0.s567, src1.s01) + input_offset) * ((int8)weights_values0.s2 + weight_offset); \
-    })
-
-#define CONVOLUTION1x3_STRIDE2(acc, src_row_ptr, weights_row_ptr)                                                 \
-    ({                                                                                                            \
-        int3  weights_values0 = convert_int3(vload3(0, weights_row_ptr));                                         \
-        int16 src0            = convert_int16(vload16(0, src_row_ptr));                                           \
-        int   src1            = convert_int(*(src_row_ptr + 16));                                                 \
-        acc += (src0.even + input_offset) * ((int8)weights_values0.s0 + weight_offset);                           \
-        acc += ((int8)(src0.s1357, src0.s9BDF) + input_offset) * ((int8)weights_values0.s1 + weight_offset);      \
-        acc += ((int8)(src0.s2468, src0.sACE, src1) + input_offset) * ((int8)weights_values0.s2 + weight_offset); \
-    })
-
-#elif KERNEL_SIZE == 1
-
-#if STRIDE_X == 3
-#define INPUT_PIXEL extract_input_stride3
-#elif STRIDE_X == 2
-#define INPUT_PIXEL extract_input_stride2
-#elif STRIDE_X == 1
-#define INPUT_PIXEL extract_input_stride1
-
-#else /* STRIDE_X not equals 1, 2 or 3 */
-#error "Only support strides 1, 2 and 3"
-#endif /* STRIDE_X */
-
-/** Extracts a 1D horizontal vector from the input tensor with stride as 1.
- *
- * @param[in] input_pixel Pointer to the first pixel.
- *
- * @return extracted input pixels.
- */
-inline uchar8 extract_input_stride1(__global const uchar *input_pixel)
-{
-    return vload8(0, input_pixel);
-}
-
-/** Extracts a 1D horizontal vector from the input tensor with stride as 2.
- *
- * @param[in] input_pixel Pointer to the first pixel.
- *
- * @return extracted input pixels.
- */
-inline uchar8 extract_input_stride2(__global const uchar *input_pixel)
-{
-    uchar16 temp = vload16(0, input_pixel);
-    return temp.s02468ace;
-}
-
-/** Extracts a 1D horizontal vector from the input tensor with stride as 3 and 8-bit data size.
- *
- * @param[in] input_pixel Pointer to the first pixel.
- *
- * @return extracted input pixels.
- */
-inline uchar8 extract_input_stride3(__global const uchar *input_pixel)
-{
-    uchar16 temp1 = vload16(0, input_pixel);
-    uchar16 temp2 = vload16(0, input_pixel + 12);
-    return (uchar8)(temp1.s0369, temp2.s0369);
-}
-
-#else /* KERNEL_SIZE not equals 1, 3 or 5 */
-#error "Only kernel sizes 1, 3 and 5 are supported"
-#endif /* KERNEL_SIZE */
-
-/** This kernel performs a direct convolution to convolve the low three dimensions.
- *
- * @note The convolution stride x must be passed at compile time using -DSTRIDE_X e.g. -DSTRIDE_X=1
- * @note The third dimensions of the weights tensors must be passed at compile time using -DWEIGHTS_DEPTH
- * @note If biases are used then -DHAS_BIAS has to be passed at compile time
- *
- * @param[in]  src_ptr                               Pointer to the source tensor. Supported data types: QASYMM8
- * @param[in]  src_stride_x                          Stride of the source tensor in X dimension (in bytes)
- * @param[in]  src_step_x                            src_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in]  src_stride_y                          Stride of the source tensor in Y dimension (in bytes)
- * @param[in]  src_step_y                            src_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in]  src_stride_z                          Stride of the source tensor in Z dimension (in bytes)
- * @param[in]  src_step_z                            src_stride_z * number of elements along Z processed per workitem(in bytes)
- * @param[in]  src_offset_first_element_in_bytes     The offset of the first element in the source tensor
- * @param[out] dst_ptr                               Pointer to the destination tensor. Supported data types: same as @p src_ptr
- * @param[in]  dst_stride_x                          Stride of the destination tensor in X dimension (in bytes)
- * @param[in]  dst_step_x                            dst_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in]  dst_stride_y                          Stride of the destination tensor in Y dimension (in bytes)
- * @param[in]  dst_step_y                            dst_stride_y * number of elements along Z processed per workitem(in bytes)
- * @param[in]  dst_stride_z                          Stride of the destination tensor in Z dimension (in bytes)
- * @param[in]  dst_step_z                            dst_stride_z * number of elements along Z processed per workitem(in bytes)
- * @param[in]  dst_offset_first_element_in_bytes     The offset of the first element in the destination tensor
- * @param[in]  weights_ptr                           Pointer to the weights tensor. Supported data types: same as @p weights_ptr
- * @param[in]  weights_stride_x                      Stride of the weights tensor in X dimension (in bytes)
- * @param[in]  weights_step_x                        weights_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in]  weights_stride_y                      Stride of the weights tensor in Y dimension (in bytes)
- * @param[in]  weights_step_y                        weights_stride_y * number of elements along y processed per workitem(in bytes)
- * @param[in]  weights_stride_z                      Stride of the weights tensor in Z dimension (in bytes)
- * @param[in]  weights_step_z                        weights_stride_z * number of elements along Z processed per workitem(in bytes)
- * @param[in]  weights_offset_first_element_in_bytes The offset of the first element in the weights tensor
- * @param[in]  biases_ptr                            Pointer to the biases tensor. Supported data types: S32
- * @param[in]  biases_stride_x                       Stride of the biases tensor in X dimension (in bytes)
- * @param[in]  biases_step_x                         biases_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in]  biases_offset_first_element_in_bytes  The offset of the first element in the biases tensor
- * @param[in]  weights_stride_w                      Stride of the weights tensor in the 4th dimension
- * @param[in]  input_offset                          Input offset quantization parameter
- * @param[in]  weight_offset                         Weights offset quantization parameter
- * @param[in]  output_offset                         Output offset quantization parameter
- * @param[in]  output_multiplier                     Output integer multiplier quantization parameter
- * @param[in]  output_shift                          Output integer shift quantization parameter
- */
-__kernel void direct_convolution_1x1_3x3_5x5_quantized(
-    TENSOR3D_DECLARATION(src),
-    TENSOR3D_DECLARATION(dst),
-    TENSOR3D_DECLARATION(weights),
-#ifdef HAS_BIAS
-    VECTOR_DECLARATION(biases),
-#endif /* defined(HAS_BIAS) */
-    unsigned int weights_stride_w,
-    int          input_offset,
-    int          weight_offset,
-    int          output_offset,
-    int          output_multiplier,
-    int          output_shift)
-{
-    Image    src     = CONVERT_TO_IMAGE_STRUCT(src);
-    Tensor3D weights = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(weights);
-    Tensor3D dst     = CONVERT_TO_TENSOR3D_STRUCT(dst);
-
-    int8 pixels0 = 0;
-
-    __global uchar *weights_addr = (__global uchar *)tensor3D_offset(&weights, 0, 0, 0);
-    __global uchar *src_addr     = (__global uchar *)offset(&src, 0, 0);
-
-    const int kernel_index = get_global_id(2);
-    weights_addr += kernel_index * weights_stride_w;
-
-    for(volatile int d = 0; d < WEIGHTS_DEPTH; ++d)
-    {
-#if KERNEL_SIZE == 5
-        CONVOLUTION1x5(pixels0, (__global uchar *)src_addr, (__global uchar *)weights_addr);
-        CONVOLUTION1x5(pixels0, (__global uchar *)(src_addr + 1 * src_stride_y), (__global uchar *)(weights_addr + 1 * weights_stride_y));
-        CONVOLUTION1x5(pixels0, (__global uchar *)(src_addr + 2 * src_stride_y), (__global uchar *)(weights_addr + 2 * weights_stride_y));
-        CONVOLUTION1x5(pixels0, (__global uchar *)(src_addr + 3 * src_stride_y), (__global uchar *)(weights_addr + 3 * weights_stride_y));
-        CONVOLUTION1x5(pixels0, (__global uchar *)(src_addr + 4 * src_stride_y), (__global uchar *)(weights_addr + 4 * weights_stride_y));
-#elif KERNEL_SIZE == 3
-        CONVOLUTION1x3(pixels0, (__global uchar *)(src_addr + 0 * src_stride_y), (__global uchar *)(weights_addr + 0 * weights_stride_y));
-        CONVOLUTION1x3(pixels0, (__global uchar *)(src_addr + 1 * src_stride_y), (__global uchar *)(weights_addr + 1 * weights_stride_y));
-        CONVOLUTION1x3(pixels0, (__global uchar *)(src_addr + 2 * src_stride_y), (__global uchar *)(weights_addr + 2 * weights_stride_y));
-#elif KERNEL_SIZE == 1
-        int weight       = convert_int(*(__global uchar *)weights_addr);
-        int8 input_pixel = convert_int8(INPUT_PIXEL((__global uchar *)src_addr));
-        pixels0 += (input_pixel + input_offset) * ((int8)weight + weight_offset);
-#endif /* (KERNEL_SIZE == 1) || (KERNEL_SIZE == 3) || (KERNEL_SIZE == 5) */
-
-        src_addr += src_stride_z;
-        weights_addr += weights_stride_z;
-    }
-
-#ifdef HAS_BIAS
-    Vector        biases    = CONVERT_TO_VECTOR_STRUCT_NO_STEP(biases);
-    __global int *bias_addr = ((__global int *)(vector_offset(&biases, kernel_index)));
-    pixels0 += (int8)(*bias_addr);
-#endif /* defined(HAS_BIAS) */
-
-    pixels0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(pixels0, output_multiplier, output_shift, 8);
-    pixels0 = pixels0 + output_offset;
-
-    vstore8(convert_uchar8_sat(pixels0), 0, (__global uchar *)dst.ptr);
-}
-#endif // defined(DATA_TYPE) && defined(STRIDE_X) && defined(WEIGHTS_DEPTH)