799be77e33
* [Python API] Move samples and docs to the new directory * move samples to the new directory * try to fix build and pychecks * fix links * fix pychecks * fix cmake * fix cpack installation * Update inference-engine/ie_bridges/python/CMakeLists.txt Co-authored-by: Sergey Lyubimtsev <sergey.lyubimtsev@intel.com> Co-authored-by: Sergey Lyubimtsev <sergey.lyubimtsev@intel.com>
104 lines
3.3 KiB
Python
104 lines
3.3 KiB
Python
# -*- coding: utf-8 -*-
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# Copyright (C) 2018-2021 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import logging as log
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import sys
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from typing import IO, Any
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import numpy as np
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def read_ark_file(file_name: str) -> dict:
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"""Read utterance matrices from a .ark file"""
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def read_key(input_file: IO[Any]) -> str:
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"""Read a identifier of utterance matrix"""
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key = ''
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char = input_file.read(1).decode()
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while char not in ('', ' '):
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key += char
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char = input_file.read(1).decode()
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return key
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def read_matrix(input_file: IO[Any]) -> np.ndarray:
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"""Read a utterance matrix"""
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header = input_file.read(5).decode()
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if 'FM' in header:
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num_of_bytes = 4
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dtype = 'float32'
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elif 'DM' in header:
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num_of_bytes = 8
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dtype = 'float64'
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else:
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log.error(f'The utterance header "{header}" does not contain information about a type of elements.')
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sys.exit(-7)
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_, rows, _, cols = np.frombuffer(input_file.read(10), 'int8, int32, int8, int32')[0]
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buffer = input_file.read(rows * cols * num_of_bytes)
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vector = np.frombuffer(buffer, dtype)
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matrix = np.reshape(vector, (rows, cols))
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return matrix
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utterances = {}
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with open(file_name, 'rb') as input_file:
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key = read_key(input_file)
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while key:
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utterances[key] = read_matrix(input_file)
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key = read_key(input_file)
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return utterances
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def write_ark_file(file_name: str, utterances: dict):
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"""Write utterance matrices to a .ark file"""
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with open(file_name, 'wb') as output_file:
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for key, matrix in sorted(utterances.items()):
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# write a matrix key
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output_file.write(key.encode())
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output_file.write(' '.encode())
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output_file.write('\0B'.encode())
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# write a matrix precision
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if matrix.dtype == 'float32':
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output_file.write('FM '.encode())
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elif matrix.dtype == 'float64':
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output_file.write('DM '.encode())
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# write a matrix shape
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output_file.write('\04'.encode())
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output_file.write(matrix.shape[0].to_bytes(4, byteorder='little', signed=False))
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output_file.write('\04'.encode())
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output_file.write(matrix.shape[1].to_bytes(4, byteorder='little', signed=False))
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# write a matrix data
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output_file.write(matrix.tobytes())
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def read_utterance_file(file_name: str) -> dict:
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"""Read utterance matrices from a file"""
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file_extension = file_name.split('.')[-1]
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if file_extension == 'ark':
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return read_ark_file(file_name)
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elif file_extension == 'npz':
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return dict(np.load(file_name))
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else:
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log.error(f'The file {file_name} cannot be read. The sample supports only .ark and .npz files.')
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sys.exit(-1)
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def write_utterance_file(file_name: str, utterances: dict):
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"""Write utterance matrices to a file"""
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file_extension = file_name.split('.')[-1]
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if file_extension == 'ark':
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write_ark_file(file_name, utterances)
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elif file_extension == 'npz':
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np.savez(file_name, **utterances)
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else:
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log.error(f'The file {file_name} cannot be written. The sample supports only .ark and .npz files.')
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sys.exit(-2)
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