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151 lines
4.8 KiB
151 lines
4.8 KiB
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the
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import base64
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import math
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from paddlespeech.cli.log import logger
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def wav2base64(wav_file: str):
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"""
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read wave file and covert to base64 string
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"""
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with open(wav_file, 'rb') as f:
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base64_bytes = base64.b64encode(f.read())
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base64_string = base64_bytes.decode('utf-8')
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return base64_string
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def base64towav(base64_string: str):
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pass
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def self_check():
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""" self check resource
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"""
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return True
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def denorm(data, mean, std):
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"""stream am model need to denorm
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"""
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return data * std + mean
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def get_chunks(data, block_size, pad_size, step):
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"""Divide data into multiple chunks
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Args:
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data (tensor): data
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block_size (int): [description]
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pad_size (int): [description]
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step (str): set "am" or "voc", generate chunk for step am or vocoder(voc)
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Returns:
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list: chunks list
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"""
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if block_size == -1:
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return [data]
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if step == "am":
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data_len = data.shape[1]
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elif step == "voc":
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data_len = data.shape[0]
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else:
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logger.error("Please set correct type to get chunks, am or voc")
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chunks = []
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n = math.ceil(data_len / block_size)
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for i in range(n):
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start = max(0, i * block_size - pad_size)
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end = min((i + 1) * block_size + pad_size, data_len)
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if step == "am":
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chunks.append(data[:, start:end, :])
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elif step == "voc":
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chunks.append(data[start:end, :])
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else:
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logger.error("Please set correct type to get chunks, am or voc")
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return chunks
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def compute_delay(receive_time_list, chunk_duration_list):
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"""compute delay
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Args:
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receive_time_list (list): Time to receive each packet
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chunk_duration_list (list): The audio duration corresponding to each packet
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Returns:
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[list]: Delay time list
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"""
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assert (len(receive_time_list) == len(chunk_duration_list))
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delay_time_list = []
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play_time = receive_time_list[0] + chunk_duration_list[0]
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for i in range(1, len(receive_time_list)):
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receive_time = receive_time_list[i]
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delay_time = receive_time - play_time
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# 有延迟
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if delay_time > 0:
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play_time = play_time + delay_time + chunk_duration_list[i]
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delay_time_list.append(delay_time)
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# 没有延迟
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else:
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play_time = play_time + chunk_duration_list[i]
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return delay_time_list
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def count_engine(logfile: str="./nohup.out"):
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"""For inference on the statistical engine side
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Args:
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logfile (str, optional): server log. Defaults to "./nohup.out".
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"""
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first_response_list = []
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final_response_list = []
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duration_list = []
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with open(logfile, "r") as f:
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for line in f.readlines():
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if "- first response time:" in line:
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first_response = float(line.splie(" ")[-2])
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first_response_list.append(first_response)
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elif "- final response time:" in line:
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final_response = float(line.splie(" ")[-2])
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final_response_list.append(final_response)
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elif "- The durations of audio is:" in line:
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duration = float(line.splie(" ")[-2])
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duration_list.append(duration)
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assert (len(first_response_list) == len(final_response_list) and
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len(final_response_list) == len(duration_list))
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avg_first_response = sum(first_response_list) / len(first_response_list)
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avg_final_response = sum(final_response_list) / len(final_response_list)
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avg_duration = sum(duration_list) / len(duration_list)
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RTF = sum(final_response_list) / sum(duration_list)
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print(
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"************************* engine result ***************************************"
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)
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print(
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f"test num: {len(duration_list)}, avg first response: {avg_first_response} s, avg final response: {avg_final_response} s, avg duration: {avg_duration}, RTF: {RTF}"
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)
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print(
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f"min duration: {min(duration_list)} s, max duration: {max(duration_list)} s"
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)
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print(
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f"max first response: {max(first_response_list)} s, min first response: {min(first_response_list)} s"
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)
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print(
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f"max final response: {max(final_response_list)} s, min final response: {min(final_response_list)} s"
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)
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