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-rw-r--r--src/cpu/kernels/CpuQuantizeKernel.cpp461
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diff --git a/src/cpu/kernels/CpuQuantizeKernel.cpp b/src/cpu/kernels/CpuQuantizeKernel.cpp
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+/*
+ * Copyright (c) 2017-2022, 2024 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 "src/cpu/kernels/CpuQuantizeKernel.h"
+
+#include "arm_compute/core/Error.h"
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/Utils.h"
+#include "arm_compute/core/Validate.h"
+#include "arm_compute/core/Window.h"
+
+#include "src/core/CPP/Validate.h"
+#include "src/core/helpers/AutoConfiguration.h"
+#include "src/core/helpers/WindowHelpers.h"
+#include "src/core/NEON/NEAsymm.h"
+#include "src/core/NEON/NEMath.h"
+#include "src/core/NEON/wrapper/wrapper.h"
+
+#include <arm_neon.h>
+#include <map>
+
+namespace arm_compute
+{
+namespace cpu
+{
+namespace kernels
+{
+namespace
+{
+constexpr auto window_step = 16;
+
+Status validate_arguments(const ITensorInfo *src, const ITensorInfo *dst)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, dst);
+ ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(src);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED,
+ DataType::F16, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON(dst->tensor_shape().total_size() == 0);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(dst, 1, DataType::QSYMM8, DataType::QASYMM8,
+ DataType::QASYMM8_SIGNED, DataType::QASYMM16);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(src, dst);
+
+ return Status{};
+}
+
+template <typename T>
+inline float32x4x4_t load_value(const T *input_ptr)
+{
+ using Tx16_t = typename wrapper::traits::neon_vector<T, 16>::type;
+ return arm_compute::convert_to_float32x4x4<Tx16_t>(wrapper::vloadq(input_ptr));
+}
+
+template <>
+inline float32x4x4_t load_value(const float *input_ptr)
+{
+ return {wrapper::vloadq(input_ptr), wrapper::vloadq(input_ptr + 4), wrapper::vloadq(input_ptr + 8),
+ wrapper::vloadq(input_ptr + 12)};
+}
+#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+template <>
+inline float32x4x4_t load_value(const float16_t *input_ptr)
+{
+ return {vcvt_f32_f16(wrapper::vload(input_ptr)), vcvt_f32_f16(wrapper::vload(input_ptr + 4)),
+ vcvt_f32_f16(wrapper::vload(input_ptr + 8)), vcvt_f32_f16(wrapper::vload(input_ptr + 12))};
+}
+
+#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+
+template <typename element_type>
+using vector_type = wrapper::traits::neon_vector_t<element_type, window_step>;
+
+template <typename quantized_type>
+vector_type<quantized_type> vquantize_qasymm8(const float32x4x4_t &qv, const UniformQuantizationInfo &qi);
+
+template <>
+vector_type<uint8_t> vquantize_qasymm8<uint8_t>(const float32x4x4_t &qv, const UniformQuantizationInfo &qi)
+{
+ return vquantize(qv, qi);
+}
+
+template <>
+vector_type<int8_t> vquantize_qasymm8<int8_t>(const float32x4x4_t &qv, const UniformQuantizationInfo &qi)
+{
+ return vquantize_signed(qv, qi);
+}
+
+template <typename TOut, typename = typename std::enable_if<std::is_signed<TOut>::value, bool>::type>
+inline int8x16_t recombine_8_16(int16x8_t lower, int16x8_t upper)
+{
+ return wrapper::vcombine(wrapper::vqmovn(lower), wrapper::vqmovn(upper));
+}
+
+template <typename TOut, typename = typename std::enable_if<std::is_unsigned<TOut>::value, bool>::type>
+inline uint8x16_t recombine_8_16(int16x8_t lower, int16x8_t upper)
+{
+ return wrapper::vcombine(wrapper::vqmovun(lower), wrapper::vqmovun(upper));
+}
+
+} // namespace
+
+void CpuQuantizeKernel::configure(const ITensorInfo *src, ITensorInfo *dst)
+{
+ ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst);
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, dst));
+
+ static const std::map<std::string, QuantizeFunctionExecutorPtr> quant_map = {
+ {"op_QASYMM8_QASYMM8", &CpuQuantizeKernel::run_quantize_qasymm8<uint8_t, uint8_t>},
+ {"op_QASYMM8_QASYMM8_SIGNED", &CpuQuantizeKernel::run_quantize_qasymm8<uint8_t, int8_t>},
+ {"op_QASYMM8_QASYMM16", &CpuQuantizeKernel::run_quantize_qasymm16<uint8_t>},
+
+ {"op_QASYMM8_SIGNED_QASYMM8", &CpuQuantizeKernel::run_quantize_qasymm8<int8_t, uint8_t>},
+ {"op_QASYMM8_SIGNED_QASYMM8_SIGNED", &CpuQuantizeKernel::run_quantize_qasymm8<int8_t, int8_t>},
+ {"op_QASYMM8_SIGNED_QASYMM16", &CpuQuantizeKernel::run_quantize_qasymm16<int8_t>},
+
+ // Functions for offset only requantization
+ {"op_OFFSET_ONLY_QASYMM8_QASYMM8", &CpuQuantizeKernel::run_requantize_offset_only<uint8_t, uint8_t>},
+ {"op_OFFSET_ONLY_QASYMM8_QASYMM8_SIGNED", &CpuQuantizeKernel::run_requantize_offset_only<uint8_t, int8_t>},
+ {"op_OFFSET_ONLY_QASYMM8_SIGNED_QASYMM8", &CpuQuantizeKernel::run_requantize_offset_only<int8_t, uint8_t>},
+ {"op_OFFSET_ONLY_QASYMM8_SIGNED_QASYMM8_SIGNED",
+ &CpuQuantizeKernel::run_requantize_offset_only<int8_t, int8_t>},
+
+ // Functions for offset uint8 to int8 and vice versa quantization (no scale changes)
+ {"op_OFFSET_ONLY_CONVERT_QASYMM8_SIGNED_QASYMM8",
+ &CpuQuantizeKernel::run_requantize_offset_only_convert<int8_t, uint8_t>},
+ {"op_OFFSET_ONLY_CONVERT_QASYMM8_QASYMM8_SIGNED",
+ &CpuQuantizeKernel::run_requantize_offset_only_convert<uint8_t, int8_t>},
+
+ {"op_F32_QSYMM8", &CpuQuantizeKernel::run_quantize_qsymm8<float, int8_t>},
+
+ {"op_F32_QASYMM8", &CpuQuantizeKernel::run_quantize_qasymm8<float, uint8_t>},
+ {"op_F32_QASYMM8_SIGNED", &CpuQuantizeKernel::run_quantize_qasymm8<float, int8_t>},
+ {"op_F32_QASYMM16", &CpuQuantizeKernel::run_quantize_qasymm16<float>},
+
+#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+ {"op_F16_QASYMM8", &CpuQuantizeKernel::run_quantize_qasymm8<float16_t, uint8_t>},
+ {"op_F16_QASYMM8_SIGNED", &CpuQuantizeKernel::run_quantize_qasymm8<float16_t, int8_t>},
+ {"op_F16_QASYMM16", &CpuQuantizeKernel::run_quantize_qasymm16<float16_t>},
+#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC*/
+ };
+
+ std::string function_to_call("op_");
+
+ // For offset only functions - must be 8-bit and have identical scale values.
+ if (src->quantization_info().scale() == dst->quantization_info().scale() &&
+ (is_data_type_quantized_asymmetric_char(src->data_type()) &&
+ is_data_type_quantized_asymmetric_char(dst->data_type())))
+ {
+ function_to_call += "OFFSET_ONLY_";
+ // For optimized datatype conversion 8-bit re-quantization offset only functions.
+ // These must have an offset of exactly 128 to match requirements - has specific circumstances to match use case.
+ auto uqinfo =
+ compute_requantization_scale_offset(src->quantization_info().uniform(), dst->quantization_info().uniform());
+ const auto src_dt = src->data_type();
+ if (src->data_type() != dst->data_type() && ((src_dt == DataType::QASYMM8_SIGNED && uqinfo.offset == 128) ||
+ (src_dt == DataType::QASYMM8 && uqinfo.offset == -128)))
+ {
+ function_to_call += "CONVERT_";
+ }
+ }
+
+ // Specify datatype for function
+ function_to_call += string_from_data_type(src->data_type()) + "_";
+ function_to_call += string_from_data_type(dst->data_type());
+
+ auto it = quant_map.find(function_to_call);
+
+ if (it == quant_map.end())
+ {
+ ARM_COMPUTE_ERROR("Unsupported combination of input and output data types");
+ }
+ _func = it->second;
+
+ // Calculate window. Squash if possible.
+ Window win;
+ std::tie(win, _split_dimension) = calculate_squashed_or_max_window(*src);
+
+ ICpuKernel::configure(win);
+}
+
+Status CpuQuantizeKernel::validate(const ITensorInfo *src, const ITensorInfo *dst)
+{
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src, dst));
+ return Status{};
+}
+
+template <typename TIn, typename TOut>
+void CpuQuantizeKernel::run_quantize_qsymm8(const ITensor *src, ITensor *dst, const Window &window)
+{
+ const auto window_start_x = static_cast<int>(window.x().start());
+ const auto window_end_x = static_cast<int>(window.x().end());
+
+ const UniformQuantizationInfo uqinfo_in = src->info()->quantization_info().uniform();
+ UniformQuantizationInfo uqinfo = dst->info()->quantization_info().uniform();
+ uqinfo = compute_requantization_scale_offset(uqinfo_in, uqinfo);
+
+ // Collapse window and reset first dimension to handle tail calculations manually
+ Window win_collapsed = window.collapse_if_possible(window, Window::DimZ);
+ win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1));
+
+ Iterator input(src, win_collapsed);
+ Iterator output(dst, win_collapsed);
+ execute_window_loop(
+ win_collapsed,
+ [&](const Coordinates &)
+ {
+ auto input_ptr = reinterpret_cast<const TIn *>(input.ptr());
+ auto output_ptr = reinterpret_cast<TOut *>(output.ptr());
+ int x = window_start_x;
+ for (; x <= (window_end_x - window_step); x += window_step)
+ {
+ wrapper::vstore(&output_ptr[x], vquantize_qasymm8<TOut>(load_value(&input_ptr[x]), uqinfo));
+ }
+ // Compute left-over elements
+ for (; x < window_end_x; ++x)
+ {
+ output_ptr[x] = quantize_qsymm8(input_ptr[x], dst->info()->quantization_info());
+ }
+ },
+ input, output);
+}
+
+template <typename TIn, typename TOut>
+void CpuQuantizeKernel::run_requantize_offset_only_convert(const ITensor *src, ITensor *dst, const Window &window)
+{
+ const auto window_start_x = static_cast<int>(window.x().start());
+ const auto window_end_x = static_cast<int>(window.x().end());
+
+ // Calculate output offset difference.
+ const UniformQuantizationInfo uqinfo_in = src->info()->quantization_info().uniform();
+ UniformQuantizationInfo uqinfo = dst->info()->quantization_info().uniform();
+ uqinfo = compute_requantization_scale_offset(uqinfo_in, uqinfo);
+
+ // Collapse window and reset first dimension to handle tail calculations manually
+ Window win_collapsed = window.collapse_if_possible(window, Window::DimZ);
+
+ win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1));
+
+ // Duplicate offset in signed vector format
+ const int8x16_t offset = wrapper::vdup_n(static_cast<int8_t>(uqinfo.offset), wrapper::traits::vector_128_tag{});
+
+ Iterator input(src, win_collapsed);
+ Iterator output(dst, win_collapsed);
+ execute_window_loop(
+ win_collapsed,
+ [&](const Coordinates &)
+ {
+ auto input_ptr = reinterpret_cast<const TIn *>(input.ptr());
+ auto output_ptr = reinterpret_cast<TOut *>(output.ptr());
+ int x = window_start_x;
+ for (; x <= (window_end_x - window_step); x += window_step)
+ {
+ const wrapper::traits::neon_vector_t<TIn, window_step> qv =
+ wrapper::vloadq(input_ptr + x); // load 128 bit vector of 8 bit datatype
+
+ // Signed addition.
+ auto res = vaddq_s8(reinterpret_cast<int8x16_t>(qv), offset);
+
+ // Output is dependent on datatype.
+ wrapper::vstore(&output_ptr[x],
+ reinterpret_cast<wrapper::traits::neon_vector_t<TOut, window_step>>(res));
+ }
+ // Compute left-over elements
+ for (; x < window_end_x; ++x)
+ {
+ auto result = uqinfo.offset + static_cast<int32_t>(input_ptr[x]);
+ output_ptr[x] = static_cast<TOut>(result);
+ }
+ },
+ input, output);
+}
+
+template <typename TIn, typename TOut>
+void CpuQuantizeKernel::run_requantize_offset_only(const ITensor *src, ITensor *dst, const Window &window)
+{
+ const auto window_start_x = static_cast<int>(window.x().start());
+ const auto window_end_x = static_cast<int>(window.x().end());
+
+ const UniformQuantizationInfo uqinfo_in = src->info()->quantization_info().uniform();
+ UniformQuantizationInfo uqinfo = dst->info()->quantization_info().uniform();
+ uqinfo = compute_requantization_scale_offset(uqinfo_in, uqinfo);
+
+ // Collapse window and reset first dimension to handle tail calculations manually
+ Window win_collapsed = window.collapse_if_possible(window, Window::DimZ);
+ win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1));
+
+ // Duplicate offset in signed vector format
+ const int16x8_t offset = wrapper::vdup_n(static_cast<int16_t>(uqinfo.offset), wrapper::traits::vector_128_tag{});
+
+ const int32_t low_bound = (dst->info()->data_type() == DataType::QASYMM8) ? 0 : -128;
+ const int32_t upper_bound = (dst->info()->data_type() == DataType::QASYMM8) ? 255 : 127;
+
+ Iterator input(src, win_collapsed);
+ Iterator output(dst, win_collapsed);
+ execute_window_loop(
+ win_collapsed,
+ [&](const Coordinates &)
+ {
+ auto input_ptr = reinterpret_cast<const TIn *>(input.ptr());
+ TOut *output_ptr = reinterpret_cast<TOut *>(output.ptr());
+
+ int x = window_start_x;
+ for (; x <= (window_end_x - window_step); x += window_step)
+ {
+ const auto qv = wrapper::vloadq(input_ptr + x); // load 128 bit vector of 8 bit datatype
+ int16x8_t lower = reinterpret_cast<int16x8_t>(wrapper::vmovl(wrapper::vgetlow(qv)));
+ int16x8_t upper = reinterpret_cast<int16x8_t>(wrapper::vmovl(wrapper::vgethigh(qv)));
+
+ // Signed addition.
+ lower = wrapper::vqadd(lower, offset);
+ upper = wrapper::vqadd(upper, offset);
+
+ // Output is dependent on datatype.
+ auto res = recombine_8_16<TOut>(lower, upper);
+ wrapper::vstore(&output_ptr[x], res);
+ }
+ // Compute left-over elements
+ for (; x < window_end_x; ++x)
+ {
+ // Add offset and clamp result to within the range of the output datatype.
+ int32_t result = uqinfo.offset + static_cast<int32_t>(input_ptr[x]);
+ result = utility::clamp<int32_t>(result, low_bound, upper_bound);
+
+ // Cast result to output datatype.
+ output_ptr[x] = static_cast<TOut>(result);
+ }
+ },
+ input, output);
+}
+
+template <typename TIn, typename TOut>
+void CpuQuantizeKernel::run_quantize_qasymm8(const ITensor *src, ITensor *dst, const Window &window)
+{
+ const auto window_start_x = static_cast<int>(window.x().start());
+ const auto window_end_x = static_cast<int>(window.x().end());
+
+ const UniformQuantizationInfo uqinfo_in = src->info()->quantization_info().uniform();
+ UniformQuantizationInfo uqinfo = dst->info()->quantization_info().uniform();
+ if (is_data_type_quantized_asymmetric(src->info()->data_type()))
+ {
+ uqinfo = compute_requantization_scale_offset(uqinfo_in, uqinfo);
+ }
+#ifdef __aarch64__
+ constexpr RoundingPolicy rounding_policy = RoundingPolicy::TO_NEAREST_EVEN;
+#else //__aarch64__
+ constexpr RoundingPolicy rounding_policy = RoundingPolicy::TO_ZERO;
+#endif //__aarch64__
+
+ // Collapse window and reset first dimension to handle tail calculations manually
+ Window win_collapsed = window.collapse_if_possible(window, Window::DimZ);
+ win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1));
+
+ Iterator input(src, win_collapsed);
+ Iterator output(dst, win_collapsed);
+ execute_window_loop(
+ win_collapsed,
+ [&](const Coordinates &)
+ {
+ auto input_ptr = reinterpret_cast<const TIn *>(input.ptr());
+ auto output_ptr = reinterpret_cast<TOut *>(output.ptr());
+
+ int x = window_start_x;
+ for (; x <= (window_end_x - window_step); x += window_step)
+ {
+ wrapper::vstore(&output_ptr[x], vquantize_qasymm8<TOut>(load_value(&input_ptr[x]), uqinfo));
+ }
+ // Compute left-over elements
+ for (; x < window_end_x; ++x)
+ {
+ output_ptr[x] = Qasymm8QuantizationHelper<TOut>::quantize(input_ptr[x], uqinfo, rounding_policy);
+ }
+ },
+ input, output);
+}
+
+template <typename T>
+void CpuQuantizeKernel::run_quantize_qasymm16(const ITensor *src, ITensor *dst, const Window &window)
+{
+ const auto window_start_x = static_cast<int>(window.x().start());
+ const auto window_end_x = static_cast<int>(window.x().end());
+
+ const UniformQuantizationInfo uqinfo_in = src->info()->quantization_info().uniform();
+ UniformQuantizationInfo uqinfo = dst->info()->quantization_info().uniform();
+ if (is_data_type_quantized_asymmetric(src->info()->data_type()))
+ {
+ uqinfo = compute_requantization_scale_offset(uqinfo_in, uqinfo);
+ }
+#ifdef __aarch64__
+ constexpr RoundingPolicy rounding_policy = RoundingPolicy::TO_NEAREST_EVEN;
+#else //__aarch64__
+ constexpr RoundingPolicy rounding_policy = RoundingPolicy::TO_ZERO;
+#endif //__aarch64__
+
+ // Collapse window and reset first dimension to handle tail calculations manually
+ Window win_collapsed = window.collapse_if_possible(window, Window::DimZ);
+ win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1));
+
+ Iterator input(src, win_collapsed);
+ Iterator output(dst, win_collapsed);
+ execute_window_loop(
+ win_collapsed,
+ [&](const Coordinates &)
+ {
+ auto input_ptr = reinterpret_cast<const T *>(input.ptr());
+ auto output_ptr = reinterpret_cast<uint16_t *>(output.ptr());
+
+ int x = window_start_x;
+ for (; x <= (window_end_x - window_step); x += window_step)
+ {
+ uint16x8x2_t tmp = vquantize_qasymm16(load_value(&input_ptr[x]), uqinfo);
+ vst1q_u16(&output_ptr[x], tmp.val[0]);
+ vst1q_u16(&output_ptr[x + 8], tmp.val[1]);
+ }
+ // Compute left-over elements
+ for (; x < window_end_x; ++x)
+ {
+ output_ptr[x] = quantize_qasymm16(input_ptr[x], uqinfo, rounding_policy);
+ }
+ },
+ input, output);
+}
+
+void CpuQuantizeKernel::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info)
+{
+ ARM_COMPUTE_UNUSED(info);
+ ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICpuKernel::window(), window);
+ ARM_COMPUTE_ERROR_ON(_func == nullptr);
+
+ const auto src = tensors.get_const_tensor(TensorType::ACL_SRC);
+ auto dst = tensors.get_tensor(TensorType::ACL_DST);
+ (this->*_func)(src, dst, window);
+}
+
+const char *CpuQuantizeKernel::name() const
+{
+ return "CpuQuantizeKernel";
+}
+
+} // namespace kernels
+} // namespace cpu
+} // namespace arm_compute
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-03 17:46:21 +0000