3daacb5e09
* POT enabling for GNA * POT enabling for GNA * POT enabling for GNA - accuracy improvements
204 lines
9.9 KiB
C++
204 lines
9.9 KiB
C++
// Copyright (C) 2018-2020 Intel Corporation
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// SPDX-License-Identifier: Apache-2.0
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//
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#pragma once
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#include <string>
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#include <vector>
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#include <gflags/gflags.h>
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#include <iostream>
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/// @brief message for help argument
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static const char help_message[] = "Print a usage message.";
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/// @brief message for images argument
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static const char input_message[] = "Required. Paths to an .ark files. Example of usage: <file1.ark,file2.ark> or <file.ark>.";
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/// @brief message for model argument
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static const char model_message[] = "Required. Path to an .xml file with a trained model (required if -rg is missing).";
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/// @brief message for plugin argument
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static const char plugin_message[] = "Plugin name. For example MKLDNNPlugin. If this parameter is pointed, " \
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"the sample will look for this plugin only";
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/// @brief message for assigning cnn calculation to device
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static const char target_device_message[] = "Specify a target device to infer on. CPU, GPU, GNA_AUTO, GNA_HW, GNA_SW, "
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"GNA_SW_EXACT and HETERO with combination of GNA as the primary device and CPU"
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" as a secondary (e.g. HETERO:GNA,CPU) are supported. The list of available devices is shown below. "
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"The sample will look for a suitable plugin for device specified.";
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/// @brief message for performance counters
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static const char performance_counter_message[] = "Enables per-layer performance report";
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/// @brief message for user library argument
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static const char custom_cpu_library_message[] = "Required for MKLDNN (CPU)-targeted custom layers." \
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"Absolute path to a shared library with the kernels impl.";
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/// @brief message for score output argument
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static const char output_message[] = "Output file name (default name is scores.ark).";
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/// @brief message for reference score file argument
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static const char reference_score_message[] = "Read reference score .ark file and compare scores.";
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/// @brief message for read GNA model argument
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static const char read_gna_model_message[] = "Read GNA model from file using path/filename provided (required if -m is missing).";
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/// @brief message for write GNA model argument
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static const char write_gna_model_message[] = "Write GNA model to file using path/filename provided.";
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/// @brief message for write GNA embedded model argument
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static const char write_embedded_model_message[] = "Write GNA embedded model to file using path/filename provided.";
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/// @brief message for write GNA embedded model generation argument
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static const char write_embedded_model_generation_message[] = "Optional. GNA generation configuration string for embedded export."
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"Can be GNA1 (default) or GNA3.";
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/// @brief message for quantization argument
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static const char quantization_message[] = "Input quantization mode: static (default), dynamic, or user (use with -sf).";
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/// @brief message for quantization bits argument
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static const char quantization_bits_message[] = "Weight bits for quantization: 8 or 16 (default)";
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/// @brief message for scale factor argument
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static const char scale_factor_message[] = "Optional user-specified input scale factor for quantization (use with -q user). "
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"If the network contains multiple inputs, provide scale factors by separating them with commas.";
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/// @brief message for batch size argument
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static const char batch_size_message[] = "Batch size 1-8 (default 1)";
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/// @brief message for #threads for CPU inference
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static const char infer_num_threads_message[] = "Optional. Number of threads to use for concurrent async" \
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" inference requests on the GNA.";
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/// @brief message for left context window argument
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static const char context_window_message_l[] = "Optional. Number of frames for left context windows (default is 0). " \
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"Works only with context window networks."
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" If you use the cw_l or cw_r flag, then batch size and nthreads arguments are ignored.";
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/// @brief message for right context window argument
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static const char context_window_message_r[] = "Optional. Number of frames for right context windows (default is 0). " \
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"Works only with context window networks."
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" If you use the cw_r or cw_l flag, then batch size and nthreads arguments are ignored.";
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/// @brief message for output layer names
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static const char output_layer_names_message[] = "Optional. Layer names for output blobs. " \
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"The names are separated with \",\" " \
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"Example: Output1:port,Output2:port ";
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/// @brief message for inputs layer names
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static const char input_layer_names_message[] = "Optional. Layer names for input blobs. " \
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"The names are separated with \",\" " \
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"Example: Input1,Input2 ";
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/// @brief message for PWL max error percent
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static const char pwl_max_error_percent_message[] = "Optional. The maximum percent of error for PWL function." \
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"The value must be in <0, 100> range. The default value is 1.0.";
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/// \brief Define flag for showing help message <br>
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DEFINE_bool(h, false, help_message);
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/// \brief Define parameter for set image file <br>
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/// It is a required parameter
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DEFINE_string(i, "", input_message);
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/// \brief Define parameter for set model file <br>
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/// It is a required parameter
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DEFINE_string(m, "", model_message);
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/// \brief Define parameter for set plugin name <br>
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/// It is a required parameter
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DEFINE_string(p, "", plugin_message);
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/// \brief device the target device to infer on <br>
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DEFINE_string(d, "CPU", target_device_message);
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/// \brief Enable per-layer performance report
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DEFINE_bool(pc, false, performance_counter_message);
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/// @brief Absolute path to CPU library with user layers <br>
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/// It is a optional parameter
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DEFINE_string(l, "", custom_cpu_library_message);
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/// @brief Write model to file (model.bin)
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DEFINE_string(o, "", output_message);
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/// @brief Read reference score file
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DEFINE_string(r, "", reference_score_message);
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/// @brief Read GNA model from file (model.bin)
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DEFINE_string(rg, "", read_gna_model_message);
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/// @brief Write GNA model to file (model.bin)
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DEFINE_string(wg, "", write_gna_model_message);
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/// @brief Write GNA embedded model to file (model.bin)
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DEFINE_string(we, "", write_embedded_model_message);
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/// @brief Optional GNA embedded device generation (default GNA1 aka Sue Creek)
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DEFINE_string(we_gen, "GNA1", write_embedded_model_generation_message);
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/// @brief Input quantization mode (default static)
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DEFINE_string(q, "static", quantization_message);
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/// @brief Input quantization bits (default 16)
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DEFINE_int32(qb, 16, quantization_bits_message);
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/// @brief Scale factor for quantization (default 1.0)
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DEFINE_string(sf, "", scale_factor_message);
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/// @brief Batch size (default 1)
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DEFINE_int32(bs, 1, batch_size_message);
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/// @brief Number of threads to use for inference on the CPU (also affects Hetero cases)
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DEFINE_int32(nthreads, 1, infer_num_threads_message);
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/// @brief Right context window size (default 0)
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DEFINE_int32(cw_r, 0, context_window_message_r);
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/// @brief Left context window size (default 0)
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DEFINE_int32(cw_l, 0, context_window_message_l);
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/// @brief Output layer name
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DEFINE_string(oname, "", output_layer_names_message);
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/// @brief Input layer name
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DEFINE_string(iname, "", input_layer_names_message);
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/// @brief PWL max error percent
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DEFINE_double(pwl_me, 1.0, pwl_max_error_percent_message);
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/**
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* \brief This function show a help message
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*/
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static void showUsage() {
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std::cout << std::endl;
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std::cout << "speech_sample [OPTION]" << std::endl;
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std::cout << "Options:" << std::endl;
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std::cout << std::endl;
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std::cout << " -h " << help_message << std::endl;
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std::cout << " -i \"<path>\" " << input_message << std::endl;
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std::cout << " -m \"<path>\" " << model_message << std::endl;
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std::cout << " -o \"<path>\" " << output_message << std::endl;
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std::cout << " -l \"<absolute_path>\" " << custom_cpu_library_message << std::endl;
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std::cout << " -d \"<device>\" " << target_device_message << std::endl;
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std::cout << " -p " << plugin_message << std::endl;
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std::cout << " -pc " << performance_counter_message << std::endl;
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std::cout << " -q \"<mode>\" " << quantization_message << std::endl;
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std::cout << " -qb \"<integer>\" " << quantization_bits_message << std::endl;
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std::cout << " -sf \"<double>\" " << scale_factor_message << std::endl;
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std::cout << " -bs \"<integer>\" " << batch_size_message << std::endl;
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std::cout << " -r \"<path>\" " << reference_score_message << std::endl;
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std::cout << " -rg \"<path>\" " << read_gna_model_message << std::endl;
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std::cout << " -wg \"<path>\" " << write_gna_model_message << std::endl;
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std::cout << " -we \"<path>\" " << write_embedded_model_message << std::endl;
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std::cout << " -we_gen \"<generation>\" " << write_embedded_model_generation_message << std::endl;
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std::cout << " -nthreads \"<integer>\" " << infer_num_threads_message << std::endl;
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std::cout << " -cw_l \"<integer>\" " << context_window_message_l << std::endl;
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std::cout << " -cw_r \"<integer>\" " << context_window_message_r << std::endl;
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std::cout << " -oname \"<string>\" " << output_layer_names_message << std::endl;
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std::cout << " -iname \"<string>\" " << input_layer_names_message << std::endl;
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std::cout << " -pwl_me \"<double>\" " << pwl_max_error_percent_message << std::endl;
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}
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