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path: root/src/core/NEON/kernels/NEQuantizationLayerKernel.cpp
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Diffstat (limited to 'src/core/NEON/kernels/NEQuantizationLayerKernel.cpp')
-rw-r--r--src/core/NEON/kernels/NEQuantizationLayerKernel.cpp78
1 files changed, 51 insertions, 27 deletions
diff --git a/src/core/NEON/kernels/NEQuantizationLayerKernel.cpp b/src/core/NEON/kernels/NEQuantizationLayerKernel.cpp
index 2beb730448..113abad6b6 100644
--- a/src/core/NEON/kernels/NEQuantizationLayerKernel.cpp
+++ b/src/core/NEON/kernels/NEQuantizationLayerKernel.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -26,6 +26,7 @@
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/NEON/NEAsymm.h"
+#include "arm_compute/core/NEON/NEMath.h"
#include "arm_compute/core/NEON/wrapper/wrapper.h"
#include "arm_compute/core/Utils.h"
#include "arm_compute/core/Validate.h"
@@ -46,7 +47,7 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::F16, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape().total_size() == 0);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::QASYMM16);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
@@ -54,6 +55,14 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output)
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),
@@ -62,7 +71,8 @@ inline float32x4x4_t load_value(const float *input_ptr)
wrapper::vloadq(input_ptr + 12) };
}
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
-inline const float32x4x4_t load_value(const float16_t *input_ptr)
+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)),
@@ -105,34 +115,38 @@ void NEQuantizationLayerKernel::configure(const ITensor *input, ITensor *output)
_input = input;
_output = output;
- static std::map<DataType, QuantizationFunctionExecutorPtr> quant_map_f32 =
+ static const std::map<std::string, QuantizationFunctionExecutorPtr> quant_map =
{
- { DataType::QASYMM8, &NEQuantizationLayerKernel::run_quantize_qasymm8<float, uint8_t> },
- { DataType::QASYMM8_SIGNED, &NEQuantizationLayerKernel::run_quantize_qasymm8<float, int8_t> },
- { DataType::QASYMM16, &NEQuantizationLayerKernel::run_quantize_qasymm16<float> },
- };
+ { "op_QASYMM8_QASYMM8", &NEQuantizationLayerKernel::run_quantize_qasymm8<uint8_t, uint8_t> },
+ { "op_QASYMM8_QASYMM8_SIGNED", &NEQuantizationLayerKernel::run_quantize_qasymm8<uint8_t, int8_t> },
+ { "op_QASYMM8_QASYMM16", &NEQuantizationLayerKernel::run_quantize_qasymm16<uint8_t> },
+
+ { "op_QASYMM8_SIGNED_QASYMM8", &NEQuantizationLayerKernel::run_quantize_qasymm8<int8_t, uint8_t> },
+ { "op_QASYMM8_SIGNED_QASYMM8_SIGNED", &NEQuantizationLayerKernel::run_quantize_qasymm8<int8_t, int8_t> },
+ { "op_QASYMM8_SIGNED_QASYMM16", &NEQuantizationLayerKernel::run_quantize_qasymm16<int8_t> },
+
+ { "op_F32_QASYMM8", &NEQuantizationLayerKernel::run_quantize_qasymm8<float, uint8_t> },
+ { "op_F32_QASYMM8_SIGNED", &NEQuantizationLayerKernel::run_quantize_qasymm8<float, int8_t> },
+ { "op_F32_QASYMM16", &NEQuantizationLayerKernel::run_quantize_qasymm16<float> },
+
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
- static std::map<DataType, QuantizationFunctionExecutorPtr> quant_map_f16 =
- {
- { DataType::QASYMM8, &NEQuantizationLayerKernel::run_quantize_qasymm8<float16_t, uint8_t> },
- { DataType::QASYMM8_SIGNED, &NEQuantizationLayerKernel::run_quantize_qasymm8<float16_t, int8_t> },
- { DataType::QASYMM16, &NEQuantizationLayerKernel::run_quantize_qasymm16<float16_t> },
- };
+ { "op_F16_QASYMM8", &NEQuantizationLayerKernel::run_quantize_qasymm8<float16_t, uint8_t> },
+ { "op_F16_QASYMM8_SIGNED", &NEQuantizationLayerKernel::run_quantize_qasymm8<float16_t, int8_t> },
+ { "op_F16_QASYMM16", &NEQuantizationLayerKernel::run_quantize_qasymm16<float16_t> },
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC*/
+ };
+
+ std::string function_to_call("op_");
+ function_to_call += string_from_data_type(_input->info()->data_type()) + "_";
+ function_to_call += string_from_data_type(_output->info()->data_type());
+
+ auto it = quant_map.find(function_to_call);
- switch(input->info()->data_type())
+ if(it == quant_map.end())
{
- case DataType::F32:
- _func = quant_map_f32[output->info()->data_type()];
- break;
-#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
- case DataType::F16:
- _func = quant_map_f16[output->info()->data_type()];
- break;
-#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
- default:
- ARM_COMPUTE_ERROR("Unsupported input data type.");
+ ARM_COMPUTE_ERROR("Unsupported combination of input and output data types");
}
+ _func = it->second;
// Configure kernel window
Window win_config = calculate_max_window(*input->info(), Steps());
@@ -156,7 +170,12 @@ void NEQuantizationLayerKernel::run_quantize_qasymm8(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 = _output->info()->quantization_info().uniform();
+ const UniformQuantizationInfo uqinfo_in = _input->info()->quantization_info().uniform();
+ UniformQuantizationInfo uqinfo = _output->info()->quantization_info().uniform();
+ if(is_data_type_quantized_asymmetric(_input->info()->data_type()))
+ {
+ uqinfo = compute_requantization_scale_offset(uqinfo_in, uqinfo);
+ }
#ifdef __aarch64__
constexpr RoundingPolicy rounding_policy = RoundingPolicy::TO_NEAREST_EVEN;
#else //__aarch64__
@@ -194,7 +213,12 @@ void NEQuantizationLayerKernel::run_quantize_qasymm16(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 = _output->info()->quantization_info().uniform();
+ const UniformQuantizationInfo uqinfo_in = _input->info()->quantization_info().uniform();
+ UniformQuantizationInfo uqinfo = _output->info()->quantization_info().uniform();
+ if(is_data_type_quantized_asymmetric(_input->info()->data_type()))
+ {
+ uqinfo = compute_requantization_scale_offset(uqinfo_in, uqinfo);
+ }
#ifdef __aarch64__
constexpr RoundingPolicy rounding_policy = RoundingPolicy::TO_NEAREST_EVEN;
#else //__aarch64__
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-06 17:54:56 +0000