add aicpu pareser

mindinsight/profiler/parser/aicpu_data_parser.py

+# 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.
+# ============================================================================
+"""
+Parser for AI CPU preprocess data.
+"""
+
+from mindinsight.profiler.common._utils import fwrite_format, get_file_join_name
+from tabulate import tabulate
+
+_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 hwts 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"""
+        ai_cpu_lines = list()
+        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(" ___ ")
+        create_session_cnt = 0
+        for line in ai_cpu_lines:
+            if "Create session start" in line:
+                create_session_cnt += 1
+        start_idx = create_session_cnt * 2
+        ai_cpu_lines = ai_cpu_lines[start_idx:-3]
+        node_list = list()
+        ai_cpu_total_time_summary = 0
+
+        if start_idx > 0:
+            serial_number = 1
+            for line in ai_cpu_lines:
+                if "Node" in line:
+                    node_name = line.split(',')[0].split(':')[-1]
+                    run_v2_start = line.split(',')[1].split(':')[-1]
+                    compute_start = line.split(',')[2].split(':')[-1]
+                    mercy_start = line.split(',')[3].split(':')[-1]
+                    mercy_end = line.split(',')[4].split(':')[-1]
+                    run_v2_end = line.split(',')[5].split(':')[-1]
+                    node_data = [serial_number, node_name, run_v2_start, compute_start,
+                                 mercy_start, mercy_end, run_v2_end]
+                    node_list.append(node_data)
+                    serial_number += 1
+                elif "Thread" in line:
+                    # total_time and dispatch_time joins node list
+                    total_time = line.split(',')[-1].split('=')[-1].split()[0]
+                    dispatch_time = line.split(',')[-2].split('=')[-1].split()[0]
+                    if node_list:
+                        node_list[-1][2:2] = [total_time, dispatch_time]
+                        ai_cpu_total_time_summary += int(total_time)
+            node_list.append(["AI CPU Total Time:", 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)