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/*
* Copyright (c) 2016-2019 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 "arm_compute/core/Helpers.h"
#include "arm_compute/core/Utils.h"
#include "support/ToolchainSupport.h"
#include <algorithm>
#include <cmath>
#include <cstdint>
#include <fstream>
#include <map>
#include <string>
using namespace arm_compute;
#ifndef DOXYGEN_SKIP_THIS
std::string arm_compute::build_information()
{
static const std::string information =
#include "arm_compute_version.embed"
;
return information;
}
#endif /* DOXYGEN_SKIP_THIS */
std::string arm_compute::read_file(const std::string &filename, bool binary)
{
std::string out;
std::ifstream fs;
#ifndef ARM_COMPUTE_EXCEPTIONS_DISABLED
try
{
#endif /* ARM_COMPUTE_EXCEPTIONS_DISABLED */
fs.exceptions(std::ifstream::failbit | std::ifstream::badbit);
std::ios_base::openmode mode = std::ios::in;
if(binary)
{
mode |= std::ios::binary;
}
fs.open(filename, mode);
// Go to the end of the file
fs.seekg(0, std::ios::end);
// Reserve the memory required to store the file's content
out.reserve(fs.tellg());
// Go back to the beginning of the file
fs.seekg(0, std::ios::beg);
// Copy the content of the file
out.assign(std::istreambuf_iterator<char>(fs), std::istreambuf_iterator<char>());
#ifndef ARM_COMPUTE_EXCEPTIONS_DISABLED
}
catch(const std::ifstream::failure &e)
{
ARM_COMPUTE_ERROR("Accessing %s: %s", filename.c_str(), e.what());
}
#endif /* ARM_COMPUTE_EXCEPTIONS_DISABLED */
return out;
}
const std::string &arm_compute::string_from_format(Format format)
{
static std::map<Format, const std::string> formats_map =
{
{ Format::UNKNOWN, "UNKNOWN" },
{ Format::U8, "U8" },
{ Format::S16, "S16" },
{ Format::U16, "U16" },
{ Format::S32, "S32" },
{ Format::U32, "U32" },
{ Format::F16, "F16" },
{ Format::F32, "F32" },
{ Format::UV88, "UV88" },
{ Format::RGB888, "RGB888" },
{ Format::RGBA8888, "RGBA8888" },
{ Format::YUV444, "YUV444" },
{ Format::YUYV422, "YUYV422" },
{ Format::NV12, "NV12" },
{ Format::NV21, "NV21" },
{ Format::IYUV, "IYUV" },
{ Format::UYVY422, "UYVY422" }
};
return formats_map[format];
}
const std::string &arm_compute::string_from_channel(Channel channel)
{
static std::map<Channel, const std::string> channels_map =
{
{ Channel::UNKNOWN, "UNKNOWN" },
{ Channel::R, "R" },
{ Channel::G, "G" },
{ Channel::B, "B" },
{ Channel::A, "A" },
{ Channel::Y, "Y" },
{ Channel::U, "U" },
{ Channel::V, "V" },
{ Channel::C0, "C0" },
{ Channel::C1, "C1" },
{ Channel::C2, "C2" },
{ Channel::C3, "C3" }
};
return channels_map[channel];
}
const std::string &arm_compute::string_from_data_layout(DataLayout dl)
{
static std::map<DataLayout, const std::string> dl_map =
{
{ DataLayout::UNKNOWN, "UNKNOWN" },
{ DataLayout::NCHW, "NCHW" },
{ DataLayout::NHWC, "NHWC" },
};
return dl_map[dl];
}
const std::string &arm_compute::string_from_data_type(DataType dt)
{
static std::map<DataType, const std::string> dt_map =
{
{ DataType::UNKNOWN, "UNKNOWN" },
{ DataType::S8, "S8" },
{ DataType::U8, "U8" },
{ DataType::S16, "S16" },
{ DataType::U16, "U16" },
{ DataType::S32, "S32" },
{ DataType::U32, "U32" },
{ DataType::S64, "S64" },
{ DataType::U64, "U64" },
{ DataType::F16, "F16" },
{ DataType::F32, "F32" },
{ DataType::F64, "F64" },
{ DataType::SIZET, "SIZET" },
{ DataType::QSYMM8, "QSYMM8" },
{ DataType::QSYMM8_PER_CHANNEL, "QSYMM8_PER_CHANNEL" },
{ DataType::QASYMM8, "QASYMM8" },
{ DataType::QSYMM16, "QSYMM16" },
};
return dt_map[dt];
}
const std::string &arm_compute::string_from_activation_func(ActivationLayerInfo::ActivationFunction act)
{
static std::map<ActivationLayerInfo::ActivationFunction, const std::string> act_map =
{
{ ActivationLayerInfo::ActivationFunction::ABS, "ABS" },
{ ActivationLayerInfo::ActivationFunction::LINEAR, "LINEAR" },
{ ActivationLayerInfo::ActivationFunction::LOGISTIC, "LOGISTIC" },
{ ActivationLayerInfo::ActivationFunction::RELU, "RELU" },
{ ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, "BRELU" },
{ ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, "LU_BRELU" },
{ ActivationLayerInfo::ActivationFunction::LEAKY_RELU, "LRELU" },
{ ActivationLayerInfo::ActivationFunction::SOFT_RELU, "SRELU" },
{ ActivationLayerInfo::ActivationFunction::SQRT, "SQRT" },
{ ActivationLayerInfo::ActivationFunction::SQUARE, "SQUARE" },
{ ActivationLayerInfo::ActivationFunction::TANH, "TANH" },
{ ActivationLayerInfo::ActivationFunction::IDENTITY, "IDENTITY" },
};
return act_map[act];
}
const std::string &arm_compute::string_from_matrix_pattern(MatrixPattern pattern)
{
static std::map<MatrixPattern, const std::string> pattern_map =
{
{ MatrixPattern::BOX, "BOX" },
{ MatrixPattern::CROSS, "CROSS" },
{ MatrixPattern::DISK, "DISK" },
{ MatrixPattern::OTHER, "OTHER" },
};
return pattern_map[pattern];
}
const std::string &arm_compute::string_from_non_linear_filter_function(NonLinearFilterFunction function)
{
static std::map<NonLinearFilterFunction, const std::string> func_map =
{
{ NonLinearFilterFunction::MAX, "MAX" },
{ NonLinearFilterFunction::MEDIAN, "MEDIAN" },
{ NonLinearFilterFunction::MIN, "MIN" },
};
return func_map[function];
}
const std::string &arm_compute::string_from_interpolation_policy(InterpolationPolicy policy)
{
static std::map<InterpolationPolicy, const std::string> interpolation_policy_map =
{
{ InterpolationPolicy::AREA, "AREA" },
{ InterpolationPolicy::BILINEAR, "BILINEAR" },
{ InterpolationPolicy::NEAREST_NEIGHBOR, "NEAREST_NEIGHBOUR" },
};
return interpolation_policy_map[policy];
}
const std::string &arm_compute::string_from_border_mode(BorderMode border_mode)
{
static std::map<BorderMode, const std::string> border_mode_map =
{
{ BorderMode::UNDEFINED, "UNDEFINED" },
{ BorderMode::CONSTANT, "CONSTANT" },
{ BorderMode::REPLICATE, "REPLICATE" },
};
return border_mode_map[border_mode];
}
const std::string &arm_compute::string_from_norm_type(NormType type)
{
static std::map<NormType, const std::string> norm_type_map =
{
{ NormType::IN_MAP_1D, "IN_MAP_1D" },
{ NormType::IN_MAP_2D, "IN_MAP_2D" },
{ NormType::CROSS_MAP, "CROSS_MAP" },
};
return norm_type_map[type];
}
const std::string &arm_compute::string_from_pooling_type(PoolingType type)
{
static std::map<PoolingType, const std::string> pool_type_map =
{
{ PoolingType::MAX, "MAX" },
{ PoolingType::AVG, "AVG" },
{ PoolingType::L2, "L2" },
};
return pool_type_map[type];
}
const std::string &arm_compute::string_from_gemmlowp_output_stage(GEMMLowpOutputStageType output_stage)
{
static std::map<GEMMLowpOutputStageType, const std::string> output_stage_map =
{
{ GEMMLowpOutputStageType::NONE, "" },
{ GEMMLowpOutputStageType::QUANTIZE_DOWN, "quantize_down" },
{ GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, "quantize_down_fixedpoint" },
{ GEMMLowpOutputStageType::QUANTIZE_DOWN_FLOAT, "quantize_down_float" }
};
return output_stage_map[output_stage];
}
std::string arm_compute::string_from_pixel_value(const PixelValue &value, const DataType data_type)
{
std::stringstream ss;
std::string converted_string;
switch(data_type)
{
case DataType::U8:
case DataType::QASYMM8:
// Needs conversion to 32 bit, otherwise interpreted as ASCII values
ss << uint32_t(value.get<uint8_t>());
converted_string = ss.str();
break;
case DataType::S8:
// Needs conversion to 32 bit, otherwise interpreted as ASCII values
ss << int32_t(value.get<int8_t>());
converted_string = ss.str();
break;
case DataType::U16:
ss << value.get<uint16_t>();
converted_string = ss.str();
break;
case DataType::S16:
case DataType::QSYMM16:
ss << value.get<int16_t>();
converted_string = ss.str();
break;
case DataType::U32:
ss << value.get<uint32_t>();
converted_string = ss.str();
break;
case DataType::S32:
ss << value.get<int32_t>();
converted_string = ss.str();
break;
case DataType::F32:
converted_string = float_to_string_with_full_precision(value.get<float>());
break;
case DataType::F16:
static_assert(sizeof(half) == 2, "Half must be 16 bit");
ss << value.get<half>();
converted_string = ss.str();
break;
default:
ARM_COMPUTE_ERROR("Not handled");
}
return converted_string;
}
std::string arm_compute::lower_string(const std::string &val)
{
std::string res = val;
std::transform(res.begin(), res.end(), res.begin(), ::tolower);
return res;
}
PadStrideInfo arm_compute::calculate_same_pad(TensorShape input_shape, TensorShape weights_shape, PadStrideInfo conv_info, DataLayout data_layout, const Size2D &dilation,
const DimensionRoundingType &rounding_type)
{
const unsigned int width_idx = arm_compute::get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
const unsigned int height_idx = arm_compute::get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
const unsigned int in_width = input_shape[width_idx];
const unsigned int in_height = input_shape[height_idx];
const unsigned int kernel_width = weights_shape[width_idx];
const unsigned int kernel_height = weights_shape[height_idx];
const auto &strides = conv_info.stride();
// Calculate output dimensions
const auto is_ceil = static_cast<unsigned int>(rounding_type == DimensionRoundingType::CEIL);
const unsigned int out_width = ((in_width - is_ceil) + strides.first - 1) / strides.first + is_ceil;
const unsigned int out_height = ((in_height - is_ceil) + strides.second - 1) / strides.second + is_ceil;
// Calculate effective weights sizes
const int real_weight_width = (kernel_width - 1) * dilation.x() + 1;
const int real_weight_height = (kernel_height - 1) * dilation.y() + 1;
// Calculate total pad
const int pad_width = std::max(0, static_cast<int>((out_width - 1) * strides.first + real_weight_width - in_width));
const int pad_height = std::max(0, static_cast<int>((out_height - 1) * strides.second + real_weight_height - in_height));
// Calculate individual paddings
const unsigned int pad_left = pad_width / 2;
const unsigned int pad_top = pad_height / 2;
const unsigned int pad_right = pad_width - pad_left;
const unsigned int pad_bottom = pad_height - pad_top;
PadStrideInfo same_info(strides.first, strides.second, pad_left, pad_right, pad_top, pad_bottom, rounding_type);
// Check for correctness of predicted output shape against the one calculated using the generated info
const auto out_dims = scaled_dimensions(in_width, in_height, kernel_width, kernel_height, same_info, dilation);
ARM_COMPUTE_ERROR_ON(out_dims.first != out_width || out_dims.second != out_height);
ARM_COMPUTE_UNUSED(out_dims);
return same_info;
}
std::pair<unsigned int, unsigned int> arm_compute::deconvolution_output_dimensions(
unsigned int in_width, unsigned int in_height, unsigned int kernel_width, unsigned int kernel_height, unsigned int padx, unsigned int pady,
unsigned int stride_x, unsigned int stride_y)
{
ARM_COMPUTE_ERROR_ON(in_width < 1 || in_height < 1);
ARM_COMPUTE_ERROR_ON(((in_width - 1) * stride_x + kernel_width) < 2 * padx);
ARM_COMPUTE_ERROR_ON(((in_height - 1) * stride_y + kernel_height) < 2 * pady);
const int w = stride_x * (in_width - 1) + kernel_width - 2 * padx;
const int h = stride_y * (in_height - 1) + kernel_height - 2 * pady;
return std::make_pair<unsigned int, unsigned int>(w, h);
}
std::pair<unsigned int, unsigned int> arm_compute::scaled_dimensions(unsigned int width, unsigned int height,
unsigned int kernel_width, unsigned int kernel_height,
const PadStrideInfo &pad_stride_info,
const Size2D &dilation)
{
const unsigned int pad_left = pad_stride_info.pad_left();
const unsigned int pad_top = pad_stride_info.pad_top();
const unsigned int pad_right = pad_stride_info.pad_right();
const unsigned int pad_bottom = pad_stride_info.pad_bottom();
const unsigned int stride_x = pad_stride_info.stride().first;
const unsigned int stride_y = pad_stride_info.stride().second;
unsigned int w = 0;
unsigned int h = 0;
switch(pad_stride_info.round())
{
case DimensionRoundingType::FLOOR:
w = static_cast<unsigned int>(std::floor((static_cast<float>(width + pad_left + pad_right - (dilation.x() * (kernel_width - 1) + 1)) / stride_x) + 1));
h = static_cast<unsigned int>(std::floor((static_cast<float>(height + pad_top + pad_bottom - (dilation.y() * (kernel_height - 1) + 1)) / stride_y) + 1));
break;
case DimensionRoundingType::CEIL:
w = static_cast<unsigned int>(std::ceil((static_cast<float>(width + pad_left + pad_right - (dilation.x() * (kernel_width - 1) + 1)) / stride_x) + 1));
h = static_cast<unsigned int>(std::ceil((static_cast<float>(height + pad_top + pad_bottom - (dilation.y() * (kernel_height - 1) + 1)) / stride_y) + 1));
break;
default:
ARM_COMPUTE_ERROR("Unsupported rounding type");
}
return std::make_pair(w, h);
}
#ifdef ARM_COMPUTE_ASSERTS_ENABLED
void arm_compute::print_consecutive_elements(std::ostream &s, DataType dt, const uint8_t *ptr, unsigned int n, int stream_width, const std::string &element_delim)
{
switch(dt)
{
case DataType::QASYMM8:
case DataType::U8:
print_consecutive_elements_impl<uint8_t>(s, ptr, n, stream_width, element_delim);
break;
case DataType::S8:
print_consecutive_elements_impl<int8_t>(s, reinterpret_cast<const int8_t *>(ptr), n, stream_width, element_delim);
break;
case DataType::U16:
print_consecutive_elements_impl<uint16_t>(s, reinterpret_cast<const uint16_t *>(ptr), n, stream_width, element_delim);
break;
case DataType::S16:
case DataType::QSYMM16:
print_consecutive_elements_impl<int16_t>(s, reinterpret_cast<const int16_t *>(ptr), n, stream_width, element_delim);
break;
case DataType::U32:
print_consecutive_elements_impl<uint32_t>(s, reinterpret_cast<const uint32_t *>(ptr), n, stream_width, element_delim);
break;
case DataType::S32:
print_consecutive_elements_impl<int32_t>(s, reinterpret_cast<const int32_t *>(ptr), n, stream_width, element_delim);
break;
case DataType::F32:
print_consecutive_elements_impl<float>(s, reinterpret_cast<const float *>(ptr), n, stream_width, element_delim);
break;
case DataType::F16:
print_consecutive_elements_impl<half>(s, reinterpret_cast<const half *>(ptr), n, stream_width, element_delim);
break;
default:
ARM_COMPUTE_ERROR("Undefined element size for given data type");
}
}
int arm_compute::max_consecutive_elements_display_width(std::ostream &s, DataType dt, const uint8_t *ptr, unsigned int n)
{
switch(dt)
{
case DataType::QASYMM8:
case DataType::U8:
return max_consecutive_elements_display_width_impl<uint8_t>(s, ptr, n);
case DataType::S8:
return max_consecutive_elements_display_width_impl<int8_t>(s, reinterpret_cast<const int8_t *>(ptr), n);
case DataType::U16:
return max_consecutive_elements_display_width_impl<uint16_t>(s, reinterpret_cast<const uint16_t *>(ptr), n);
case DataType::S16:
case DataType::QSYMM16:
return max_consecutive_elements_display_width_impl<int16_t>(s, reinterpret_cast<const int16_t *>(ptr), n);
case DataType::U32:
return max_consecutive_elements_display_width_impl<uint32_t>(s, reinterpret_cast<const uint32_t *>(ptr), n);
case DataType::S32:
return max_consecutive_elements_display_width_impl<int32_t>(s, reinterpret_cast<const int32_t *>(ptr), n);
case DataType::F32:
return max_consecutive_elements_display_width_impl<float>(s, reinterpret_cast<const float *>(ptr), n);
case DataType::F16:
return max_consecutive_elements_display_width_impl<half>(s, reinterpret_cast<const half *>(ptr), n);
default:
ARM_COMPUTE_ERROR("Undefined element size for given data type");
}
return 0;
}
#endif /* ARM_COMPUTE_ASSERTS_ENABLED */