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- # Copyright 2020 Huawei Technologies Co., Ltd
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- # ============================================================================
- """
- The parser for AI CPU preprocess data.
- """
- import os
-
- from tabulate import tabulate
-
- from mindinsight.profiler.common._utils import fwrite_format, get_file_join_name
- from mindinsight.profiler.common.log import logger
-
- _source_file_target = 'DATA_PREPROCESS.dev.AICPU'
- _dst_file_title = 'title:DATA_PREPROCESS AICPU'
- _dst_file_column_title = ['serial_number', 'node_name', 'total_time(us)', 'dispatch_time(us)',
- 'RunV2_start', 'compute_start', 'memcpy_start', 'memcpy_end', 'RunV2_end']
-
-
- class DataPreProcessParser:
- """
- The Parser for AI CPU preprocess data.
-
- Args:
- input_path(str): The profiling job path.
- output_filename(str): The output data path and name.
-
- """
-
- def __init__(self, input_path, output_filename):
- self._input_path = input_path
- self._output_filename = output_filename
- self._source_file_name = self._get_source_file()
-
- def _get_source_file(self):
- """Get log file name, which was created by ada service."""
-
- return get_file_join_name(self._input_path, _source_file_target)
-
- def execute(self):
- """Execute the parser, get result data, and write it to the output file."""
-
- if not os.path.exists(self._source_file_name):
- logger.info("Did not find the aicpu profiling source file")
- return
-
- with open(self._source_file_name, 'rb') as ai_cpu_data:
- ai_cpu_str = str(ai_cpu_data.read().replace(b'\n\x00', b' ___ ')
- .replace(b'\x00', b' ___ '))[2:-1]
- ai_cpu_lines = ai_cpu_str.split(" ___ ")
-
- node_list = list()
- ai_cpu_total_time_summary = 0
- # node serial number
- serial_number = 1
- for i in range(len(ai_cpu_lines)-1):
- node_line = ai_cpu_lines[i]
- thread_line = ai_cpu_lines[i+1]
- if "Node" in node_line and "Thread" in thread_line:
- # get the node data from node_line
- node_name = node_line.split(',')[0].split(':')[-1]
- run_v2_start = node_line.split(',')[1].split(':')[-1]
- compute_start = node_line.split(',')[2].split(':')[-1]
- mercy_start = node_line.split(',')[3].split(':')[-1]
- mercy_end = node_line.split(',')[4].split(':')[-1]
- run_v2_end = node_line.split(',')[5].split(':')[-1]
- # get total_time and dispatch_time from thread line
- total_time = thread_line.split(',')[-1].split('=')[-1].split()[0]
- dispatch_time = thread_line.split(',')[-2].split('=')[-1].split()[0]
-
- node_data = [serial_number, node_name, total_time, dispatch_time, run_v2_start, compute_start,
- mercy_start, mercy_end, run_v2_end]
-
- node_list.append(node_data)
- # calculate the total time
- ai_cpu_total_time_summary += int(total_time)
- # increase node serial number
- serial_number += 1
- elif "Node" in node_line and "Thread" not in thread_line:
- node_name = node_line.split(',')[0].split(':')[-1]
- logger.warning("The node:%s cannot find thread data", node_name)
-
- node_list.append(["AI CPU Total Time(us):", ai_cpu_total_time_summary])
-
- if node_list:
- fwrite_format(self._output_filename, data_source=_dst_file_title, is_print=True,
- is_start=True)
- fwrite_format(self._output_filename,
- data_source=tabulate(node_list, _dst_file_column_title,
- tablefmt='simple'),
- is_start=True, is_print=True)
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