COMPMID-661: directconv-uint8 (#20)
Change-Id: I84f7a1ce3658be0d3c91e65096467258af48f0b6
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/94341
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp
index f9142f4..3219952 100644
--- a/src/core/CL/CLKernelLibrary.cpp
+++ b/src/core/CL/CLKernelLibrary.cpp
@@ -58,7 +58,7 @@
(cond) ? add_option(std::move(option_true)) : add_option(std::move(option_false));
}
-CLBuildOptions::StringSet CLBuildOptions::options() const
+const CLBuildOptions::StringSet &CLBuildOptions::options() const
{
return _build_opts;
}
@@ -186,6 +186,7 @@
{ "direct_convolution3x3_f32_bifrost", "direct_convolution3x3.cl" },
{ "direct_convolution5x5", "direct_convolution5x5.cl" },
{ "direct_convolution5x5_f32_bifrost", "direct_convolution5x5.cl" },
+ { "direct_convolution_1x1_3x3_5x5_quantized", "direct_convolution_1x1_3x3_5x5_quantized.cl" },
{ "erode", "erode.cl" },
{ "fast_corners", "fast_corners.cl" },
{ "fill_image_borders_constant", "fill_border.cl" },
@@ -423,6 +424,10 @@
#include "./cl_kernels/direct_convolution5x5.clembed"
},
{
+ "direct_convolution_1x1_3x3_5x5_quantized.cl",
+#include "./cl_kernels/direct_convolution_1x1_3x3_5x5_quantized.clembed"
+ },
+ {
"erode.cl",
#include "./cl_kernels/erode.clembed"
},
@@ -463,6 +468,10 @@
#include "./cl_kernels/helpers.hembed"
},
{
+ "helpers_asymm.h",
+#include "./cl_kernels/helpers_asymm.hembed"
+ },
+ {
"histogram.cl",
#include "./cl_kernels/histogram.clembed"
},
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
new file mode 100644
index 0000000..7a860f2
--- /dev/null
+++ b/src/core/CL/cl_kernels/direct_convolution_1x1_3x3_5x5_quantized.cl
@@ -0,0 +1,252 @@
+/*
+ * Copyright (c) 2017 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[out] 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. Same as @p src_ptr
+ * @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 uchar *bias_addr = ((__global uchar *)(vector_offset(&biases, kernel_index)));
+ uchar8 bias_data = *bias_addr;
+ pixels0 += convert_int8(bias_data);
+#endif /* defined(HAS_BIAS) */
+
+ pixels0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(pixels0, output_multiplier, output_shift, 8);
+ pixels0 = pixels0 + output_offset;
+ pixels0 = max(pixels0, 0);
+ pixels0 = min(pixels0, 255);
+
+ vstore8(convert_uchar8(pixels0), 0, (__global uchar *)dst.ptr);
+}
+#endif // defined(DATA_TYPE) && defined(STRIDE_X) && defined(WEIGHTS_DEPTH)
diff --git a/src/core/CL/cl_kernels/helpers_asymm.h b/src/core/CL/cl_kernels/helpers_asymm.h
new file mode 100644
index 0000000..3c1d58b
--- /dev/null
+++ b/src/core/CL/cl_kernels/helpers_asymm.h
@@ -0,0 +1,91 @@
+/*
+ * Copyright (c) 2017 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.
+ */
+#ifndef ARM_COMPUTE_HELPERS_ASYMM_H
+#define ARM_COMPUTE_HELPERS_ASYMM_H
+
+#include "helpers.h"
+
+/** Correctly-rounded-to-nearest division by a power-of-two.
+ *
+ * @param[in] size Size of vector.
+ *
+ * @return Correctly-rounded-to-nearest division by a power-of-two.
+ */
+#define ASYMM_ROUNDING_DIVIDE_BY_POW2_IMPL(size) \
+ inline VEC_DATA_TYPE(int, size) asymm_rounding_divide_by_POW2_##size(VEC_DATA_TYPE(int, size) x, int exponent) \
+ { \
+ VEC_DATA_TYPE(int, size) \
+ mask = (1 << exponent) - 1; \
+ const VEC_DATA_TYPE(int, size) zero = 0; \
+ const VEC_DATA_TYPE(int, size) one = 1; \
+ VEC_DATA_TYPE(int, size) \
+ threshold = (mask >> 1) + select(zero, one, x < 0); \
+ return (x >> exponent) + select(zero, one, (x & mask) > threshold); \
+ }
+
+ASYMM_ROUNDING_DIVIDE_BY_POW2_IMPL(8)
+ASYMM_ROUNDING_DIVIDE_BY_POW2_IMPL(16)
+
+#define ASYMM_ROUNDING_DIVIDE_BY_POW2(x, exponent, size) asymm_rounding_divide_by_POW2_##size(x, exponent)
+
+/** Product of two numbers, interpreting them as fixed-point values in the interval [-1, 1),
+ * rounding to the nearest value, and saturating -1 * -1 to the maximum value.
+ *
+ * @param[in] size Size of vector.
+ *
+ * @return Product of two fixed-point numbers.
+ */
+#define ASYMM_MULT_IMP(size) \
+ inline VEC_DATA_TYPE(int, size) asymm_mult##size(VEC_DATA_TYPE(int, size) a, VEC_DATA_TYPE(int, size) b) \
+ { \
+ VEC_DATA_TYPE(int, size) \
+ overflow = a == b && a == INT_MIN; \
+ VEC_DATA_TYPE(long, size) \
+ a_64 = convert_long##size(a); \
+ VEC_DATA_TYPE(long, size) \
+ b_64 = convert_long##size(b); \
+ VEC_DATA_TYPE(long, size) \
+ ab_64 = a_64 * b_64; \
+ VEC_DATA_TYPE(long, size) \
+ mask1 = 1 << 30; \
+ VEC_DATA_TYPE(long, size) \
+ mask2 = 1 - (1 << 30); \
+ VEC_DATA_TYPE(long, size) \
+ nudge = select(mask2, mask1, ab_64 >= 0); \
+ VEC_DATA_TYPE(long, size) \
+ mask = 1ll << 31; \
+ VEC_DATA_TYPE(int, size) \
+ ab_x2_high32 = convert_int##size((ab_64 + nudge) / mask); \
+ return select(ab_x2_high32, INT_MAX, overflow); \
+ }
+
+ASYMM_MULT_IMP(8)
+ASYMM_MULT_IMP(16)
+
+#define ASYMM_MULT(a, b, size) asymm_mult##size(a, b)
+
+#define ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(x, quantized_multiplier, right_shift, size) \
+ ASYMM_ROUNDING_DIVIDE_BY_POW2(ASYMM_MULT(x, quantized_multiplier, size), right_shift, size)
+
+#endif // ARM_COMPUTE_HELPERS_ASYMM_H
diff --git a/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp b/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp
index 4224d9b..53e4639 100644
--- a/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp
+++ b/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp
@@ -34,6 +34,7 @@
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Utils.h"
#include "arm_compute/core/Validate.h"
+#include "arm_compute/core/utils/quantization/AsymmHelpers.h"
#include "support/ToolchainSupport.h"
using namespace arm_compute;
@@ -50,7 +51,7 @@
void CLDirectConvolutionLayerKernel::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info)
{
- ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32);
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32);
ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights);
ARM_COMPUTE_ERROR_ON_MSG(weights->info()->dimension(0) != weights->info()->dimension(1),
"Weights should have same width as length");
@@ -70,6 +71,7 @@
}
const unsigned int kernel_size = weights->info()->dimension(0);
+ const DataType data_type = input->info()->data_type();
// Get convolved dimensions
unsigned int output_width = 0;
@@ -99,21 +101,20 @@
_biases = biases;
_border_size = BorderSize(_conv_pad_y, _conv_pad_x);
- std::set<std::string> options;
-
const GPUTarget gpu_target = get_arch_from_target(get_target());
- if(_biases != nullptr)
- {
- options.emplace("-DHAS_BIAS");
- }
+ std::stringstream kernel_name;
+ kernel_name << "direct_convolution" << kernel_size << "x" << kernel_size;
- if((gpu_target == GPUTarget::BIFROST) && (kernel_size <= 5) && (_conv_stride_x == 1) && (_conv_stride_y == 1) && (input->info()->data_type() == DataType::F32))
- {
- options.emplace("-DWEIGHTS_DEPTH=" + support::cpp11::to_string(_weights->info()->dimension(2)));
+ CLBuildOptions build_options;
+ build_options.add_option_if(_biases != nullptr, std::string("-DHAS_BIAS"));
- std::string kernel_name = "direct_convolution" + support::cpp11::to_string(kernel_size) + "x" + support::cpp11::to_string(kernel_size) + "_f32_bifrost";
- _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, options));
+ if((gpu_target == GPUTarget::BIFROST) && (kernel_size <= 5) && (_conv_stride_x == 1) && (_conv_stride_y == 1) && (data_type == DataType::F32))
+ {
+ build_options.add_option(std::string("-DWEIGHTS_DEPTH=" + support::cpp11::to_string(_weights->info()->dimension(2))));
+
+ kernel_name << "_f32_bifrost";
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name.str(), build_options.options()));
// Configure kernel window
Window win = calculate_max_window(*output->info());
@@ -174,35 +175,22 @@
}
else
{
- std::stringstream kernel_name;
- kernel_name << "direct_convolution" << kernel_size << "x" << kernel_size;
- DataType promoted_type = input->info()->data_type();
+ bool is_quantized_fixed_point = is_data_type_fixed_point(data_type);
+ bool is_quantized_asymm = is_data_type_quantized_assymetric(data_type);
+ DataType promoted_type = (is_quantized_fixed_point) ? get_promoted_data_type(data_type) : data_type;
- options.emplace("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
- options.emplace("-DDATA_SIZE=" + get_data_size_from_data_type(input->info()->data_type()));
- options.emplace("-DWEIGHTS_DEPTH=" + support::cpp11::to_string(_weights->info()->dimension(2)));
- options.emplace("-DSTRIDE_X=" + support::cpp11::to_string(_conv_stride_x));
+ build_options.add_option_if(is_quantized_asymm, std::string("-DKERNEL_SIZE=" + support::cpp11::to_string(kernel_size)));
+ build_options.add_option(std::string("-DDATA_TYPE=" + get_cl_type_from_data_type(data_type)));
+ build_options.add_option(std::string("-DDATA_SIZE=" + get_data_size_from_data_type(data_type)));
+ build_options.add_option(std::string("-DWEIGHTS_DEPTH=" + support::cpp11::to_string(_weights->info()->dimension(2))));
+ build_options.add_option(std::string("-DSTRIDE_X=" + support::cpp11::to_string(_conv_stride_x)));
+ build_options.add_option_if(is_quantized_fixed_point,
+ std::string("-DFIXED_POINT_POSITION=" + support::cpp11::to_string(input->info()->fixed_point_position())));
+ build_options.add_option(std::string("-DDATA_TYPE_PROMOTED=" + get_cl_type_from_data_type(promoted_type)));
- if(is_data_type_fixed_point(input->info()->data_type()))
- {
- options.emplace("-DFIXED_POINT_POSITION=" + support::cpp11::to_string(input->info()->fixed_point_position()));
-
- switch(input->info()->data_type())
- {
- case DataType::QS8:
- promoted_type = DataType::QS16;
- break;
- case DataType::QS16:
- promoted_type = DataType::QS32;
- break;
- default:
- ARM_COMPUTE_ERROR("Datatype not supported");
- }
- }
-
- options.emplace("-DDATA_TYPE_PROMOTED=" + get_cl_type_from_data_type(promoted_type));
-
- _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name.str(), options));
+ // Create kernel
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(is_quantized_asymm ? "direct_convolution_1x1_3x3_5x5_quantized" : kernel_name.str(),
+ build_options.options()));
// Configure kernel window
@@ -231,9 +219,26 @@
ICLKernel::configure(win);
}
+ // Set static kernel arguments
+ if(is_data_type_quantized_assymetric(data_type))
+ {
+ int output_multiplier = 0;
+ int output_shift = 0;
+
+ float multiplier = _input->info()->quantization_info().scale * _weights->info()->quantization_info().scale / _output->info()->quantization_info().scale;
+ ARM_COMPUTE_THROW_ON_ERROR(quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift));
+
+ unsigned int idx = 3 * num_arguments_per_3D_tensor() + ((_biases != nullptr) ? num_arguments_per_1D_tensor() : 0) + 1;
+ _kernel.setArg(idx++, -_input->info()->quantization_info().offset);
+ _kernel.setArg(idx++, -_weights->info()->quantization_info().offset);
+ _kernel.setArg(idx++, _output->info()->quantization_info().offset);
+ _kernel.setArg(idx++, output_multiplier);
+ _kernel.setArg(idx++, output_shift);
+ }
+
// Set config_id for enabling LWS tuning
_config_id = "direct_convolution_";
- _config_id += lower_string(string_from_data_type(input->info()->data_type()));
+ _config_id += lower_string(string_from_data_type(data_type));
_config_id += "_";
_config_id += support::cpp11::to_string(kernel_size);
_config_id += "_";
diff --git a/src/core/CL/kernels/CLFillBorderKernel.cpp b/src/core/CL/kernels/CLFillBorderKernel.cpp
index 2e066c7..66504e6 100644
--- a/src/core/CL/kernels/CLFillBorderKernel.cpp
+++ b/src/core/CL/kernels/CLFillBorderKernel.cpp
@@ -122,6 +122,7 @@
switch(dt)
{
case DataType::U8:
+ case DataType::QASYMM8:
set_constant_border<uint8_t>(idx, constant_border_value);
break;
case DataType::QS8:
diff --git a/src/core/utils/quantization/AsymmHelpers.cpp b/src/core/utils/quantization/AsymmHelpers.cpp
new file mode 100644
index 0000000..4ba5f44
--- /dev/null
+++ b/src/core/utils/quantization/AsymmHelpers.cpp
@@ -0,0 +1,60 @@
+/*
+ * Copyright (c) 2017 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 "arm_compute/core/utils/quantization/AsymmHelpers.h"
+
+#include <cmath>
+#include <limits>
+#include <numeric>
+
+using namespace arm_compute::quantization;
+
+arm_compute::Error arm_compute::quantization::calculate_quantized_multiplier_less_than_one(double multiplier,
+ int *quant_multiplier,
+ int *right_shift)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON(quant_multiplier == nullptr);
+ ARM_COMPUTE_RETURN_ERROR_ON(right_shift == nullptr);
+ ARM_COMPUTE_RETURN_ERROR_ON(multiplier < 0);
+ ARM_COMPUTE_RETURN_ERROR_ON(multiplier >= 1);
+ if(multiplier == 0)
+ {
+ *quant_multiplier = 0;
+ *right_shift = 0;
+ return arm_compute::Error{};
+ }
+ const double q = std::frexp(multiplier, right_shift);
+ *right_shift *= -1;
+ auto q_fixed = static_cast<int64_t>(round(q * (1ll << 31)));
+ ARM_COMPUTE_RETURN_ERROR_ON(q_fixed > (1ll << 31));
+ if(q_fixed == (1ll << 31))
+ {
+ q_fixed /= 2;
+ --*right_shift;
+ }
+ ARM_COMPUTE_RETURN_ERROR_ON(*right_shift < 0);
+ ARM_COMPUTE_RETURN_ERROR_ON(q_fixed > std::numeric_limits<int32_t>::max());
+ *quant_multiplier = static_cast<int>(q_fixed);
+
+ return arm_compute::Error{};
+}
\ No newline at end of file