add me daily monitor files
This commit is contained in:
huangbingjian
parent
2e9a52fc5c
commit
7e3afac1c0
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# Copyright 2021 Huawei Technologies Co., Ltd
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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 specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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import sys
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import re
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import json
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import os
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import time
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import openpyxl as opx
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def parse_arguments():
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print(sys.argv)
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me_report_path = sys.argv[1]
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log_path = sys.argv[2]
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n_iter = sys.argv[3]
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out = sys.argv[4]
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assert n_iter.isdigit()
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return me_report_path, log_path, int(n_iter), out
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def extract_by_keyword(doc, keyword, pattern):
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rst = []
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for i, s in enumerate(doc):
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if keyword in s:
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p = re.findall(pattern, s)
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print("L%d: extracted %s from '%s'" % (i, p, s.strip()))
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rst.extend(p)
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return rst
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def process_log(fname, log_path, n_iter, keyword, pattern):
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rnt = {}
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for i in range(1, 1+n_iter):
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fname_path = os.path.join(log_path, fname % i)
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with open(fname_path) as f:
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print("\nLoading %s" % fname_path)
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rst = extract_by_keyword(f, keyword, pattern)
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rnt[fname % i] = rst
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return rnt
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def summarize(func):
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def wrapper(*args, **kwargs):
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log = func(*args, **kwargs)
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times = list(log.items())
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times.sort(key=lambda x: x[1])
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min_file, min_time = times[0]
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avg = sum(map(lambda x: x[1], times)) / len(times)
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log["min_time"] = min_time
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log["min_file"] = min_file
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log["avg_time"] = avg
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return log
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return wrapper
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@summarize
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def process_bert_log(log_path, n_iter):
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fname = "bert%d.log"
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total = process_log(fname, log_path, n_iter, "TotalTime", r"\d+.\d+")
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task = process_log(fname, log_path, n_iter, "task_emit", r"\d+.\d+")
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log = {}
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for fname in total:
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log[fname] = float(total[fname][0]) - float(task[fname][0])
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return log
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@summarize
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def process_resnet_log(log_path, n_iter):
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fname = "resnet%d.log"
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total = process_log(fname, log_path, n_iter, "TotalTime", r"\d+.\d+")
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task = process_log(fname, log_path, n_iter, "task_emit", r"\d+.\d+")
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log = {}
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for fname in total:
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log[fname] = float(total[fname][0]) - float(task[fname][0])
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return log
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@summarize
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def process_gpt_log(log_path, n_iter):
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fname = "gpt%d.log"
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total = process_log(fname, log_path, n_iter, "TotalTime", r"\d+.\d+")
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task = process_log(fname, log_path, n_iter, "task_emit", r"\d+.\d+")
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log = {}
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for fname in total:
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log[fname] = float(total[fname][0]) - float(task[fname][0])
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return log
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@summarize
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def process_reid_log(log_path, n_iter):
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log = {}
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for i in range(8):
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fname = "reid_%d_"+str(i)+".log"
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total = process_log(fname, log_path, n_iter, "TotalTime", r"\d+.\d+")
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task = process_log(fname, log_path, n_iter, "task_emit", r"\d+.\d+")
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for fname in total:
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log[fname] = float(total[fname][0]) - float(task[fname][0])
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return log
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def write_to_me_report(log, me_report_path):
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wb = opx.load_workbook(me_report_path)
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sheet = wb["Sheet"]
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idx = sheet.max_row + 1
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date = time.strftime('%m%d', time.localtime())
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sheet['A%d' % idx] = date
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sheet['B%d' % idx] = round(log["reid"]["min_time"], 2)
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sheet['C%d' % idx] = round(log["bert"]["min_time"], 2)
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sheet['D%d' % idx] = round(log['resnet']["min_time"], 2)
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sheet['E%d' % idx] = round(log['gpt']["min_time"], 2)
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wb.save(me_report_path)
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def generate_report():
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me_report_path, log_path, n_iter, out = parse_arguments()
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log_data = {}
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bert_log = process_bert_log(log_path, n_iter)
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resnet_log = process_resnet_log(log_path, n_iter)
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gpt_log = process_gpt_log(log_path, n_iter)
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reid_log = process_reid_log(log_path, n_iter)
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log_data["bert"] = bert_log
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log_data["resnet"] = resnet_log
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log_data["gpt"] = gpt_log
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log_data["reid"] = reid_log
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with open(out, "w") as f:
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json.dump(log_data, f, indent=2)
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write_to_me_report(log_data, me_report_path)
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if __name__ == "__main__":
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generate_report()
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@ -0,0 +1,104 @@
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# Copyright 2021 Huawei Technologies Co., Ltd
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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 specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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import os
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import sys
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import json
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import openpyxl as opx
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import matplotlib.ticker as ticker
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import matplotlib.pyplot as plt
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def parse_arguments():
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log_path = sys.argv[1]
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log_data = sys.argv[2]
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me_report = sys.argv[3]
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n_days = sys.argv[4]
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assert n_days.isdigit()
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return log_path, log_data, me_report, int(n_days)
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def read_data(log_data, me_report_path, n_days):
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with open(log_data) as f:
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log = json.load(f)
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wb = opx.load_workbook(me_report_path)
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sheet = wb["Sheet"]
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n_row = sheet.max_row
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date = [cell[0].value for cell in sheet["A2":"A%d" % n_row]]
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reid_data = [float(cell[0].value) for cell in sheet["B2":"B%d" % n_row]]
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bert_data = [float(cell[0].value) for cell in sheet["C2":"C%d" % n_row]]
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resnet_data = [float(cell[0].value) for cell in sheet["D2":"D%d" % n_row]]
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gpt_data = [float(cell[0].value) for cell in sheet["E43":"E%d" % n_row]]
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if n_days > 0:
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date = date[-n_days:]
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reid_data = reid_data[-n_days:]
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bert_data = bert_data[-n_days:]
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resnet_data = resnet_data[-n_days:]
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gpt_data = gpt_data[-n_days:]
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return log, date, reid_data, bert_data, resnet_data, gpt_data
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def draw_figure(x_data, y_data, labels, title, out, height=24, width=8, tick_space=2):
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print("Generating figure to: %s" % out)
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plt.figure(figsize=(height, width))
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for y, label in zip(y_data, labels):
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x = x_data[-len(y):]
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n_data = len(x)
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assert len(x) == len(
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y), "assume len(x) == len(y), while %d != %d" % (len(x), len(y))
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plt.plot(x, y, linewidth=2, marker='o', markersize=5, label=label)
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ax = plt.gca()
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ax.xaxis.set_major_locator(ticker.MultipleLocator(tick_space))
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for i in range(n_data):
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if i % 2 == 0:
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plt.text(x[i], y[i], y[i], ha='center',
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va='bottom', fontsize=8)
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plt.title(title)
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plt.xlabel("Date")
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plt.ylabel("Time(s)")
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plt.grid()
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plt.legend()
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plt.savefig(out)
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def generate_report(log, labels, log_path):
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for label in labels:
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fname = log[label]["min_file"]
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fname_path = os.path.join(log_path, fname)
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out_path = os.path.join(log_path, "reports", label+"_me.log")
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print("Generating report to: %s" % out_path)
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os.system("grep -A 230 'TotalTime = ' %s > %s" %
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(fname_path, out_path))
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def process_data():
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log_path, log_data, me_report, n_days = parse_arguments()
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log, date, reid_data, bert_data, resnet_data, gpt_data = read_data(
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log_data, me_report, n_days)
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draw_figure(date,
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[reid_data, bert_data, gpt_data],
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["ReID", "BERT", "GPT"],
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"ReID&BERT&GPT",
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os.path.join(log_path, "reports", "reid_bert_gpt.png")
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)
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draw_figure(date, [resnet_data], ["ResNet"], "ResNet",
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os.path.join(log_path, "reports", "resnet.png"))
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generate_report(log, list(log.keys()), log_path)
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if __name__ == "__main__":
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process_data()
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#!/bin/bash
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# Copyright 2021 Huawei Technologies Co., Ltd
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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 specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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stage=0
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days=7
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iter=5
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device_id=0
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n_worker=128
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work_dir="/opt/npu/me_monitor"
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me_report_path=$work_dir/logs/ME_report_daily.xlsx
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log_dir=logs_$(date "+%m%d-%H%M")
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log_path=$work_dir/logs/$log_dir
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ms_master="https://gitee.com/mindspore/mindspore.git"
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log_data="data.json"
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ci_mode=true
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set -e
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set -o pipefail
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# parse arguments from command line
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while getopts "s:d:i:l:" args
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do
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case $args in
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s)
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stage=$OPTARG
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;;
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d)
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days=$OPTARG
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;;
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i)
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iter=$OPTARG
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;;
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l)
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log_dir=$OPTARG
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log_path=$work_dir/logs/$log_dir
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;;
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?)
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echo "unknown argument"
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exit 1
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;;
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esac
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done
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source env.sh
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export DEVICE_ID=$device_id
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echo "Args: days=$days, iter=$iter, log_path=$log_path"
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cd $work_dir
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echo $WORKSPACE
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WORKSPACE=/home/jenkins-slave/workspace/MindSpore_Network_reid_compile_performance
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echo $WORKSPACE
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if [ $stage -le 1 ]; then
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echo ""
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echo "===========Stage 1: Fetching latest mindspore from master==========="
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if [ -d mindspore ]; then
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rm -rf mindspore
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fi
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git clone $ms_master
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fi
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if [ $stage -le 2 ]; then
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echo ""
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echo "===========Stage 2: Building mindspore==========="
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cd $work_dir/mindspore
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bash build.sh -e ascend -j $n_worker -p on
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fi
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if [ $stage -le 3 ]; then
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echo ""
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echo "===========Stage 3: Compiling networks==========="
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cd $work_dir
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mkdir -p $log_path
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# Compiling ReID-8
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# split resource-consuming task from others
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for count in $(seq 1 $iter); do
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echo "[INFO] Compiling ReID-8p, iteration $count"
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if [ -d reid$count ]; then
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rm -rf reid$count
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fi
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mkdir reid$count
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cd reid$count
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bash $work_dir/faceReidToMe/dist_env/env_26/dist_env_26.sh
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for num in {0..7}; do
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cp device_$num/test_reid_stage123_1024node_graphdata_dynamiclossscale_log$num.log $log_path/reid_${count}_${num}.log
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done
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cd $work_dir
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mv reid$count $log_path
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done
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# Compiling BERT
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cd $work_dir
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for count in $(seq 1 $iter); do
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echo "[INFO] Compiling BERT, iteration $count"
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pytest -s mindspore/tests/perf_test/bert/test_bert_train.py::test_bert_train | tee $log_path/bert$count.log
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done
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# Compiling ResNet50
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for count in $(seq 1 $iter); do
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echo "[INFO] Compiling ResNet50, iteration $count"
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pytest -s mindspore/tests/perf_test/test_resnet_train.py::test_train_step | tee $log_path/resnet$count.log
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done
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# Compiling GPT
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for count in $(seq 1 $iter); do
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echo "[INFO] Compiling GPT, iteration $count"
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cd gpt
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bash scripts/run_standalone_train.sh 0 1 $work_dir/gpt_data | tee $log_path/gpt$count.log
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done
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fi
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if [ $stage -le 4 ]; then
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echo ""
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echo "===========Stage 4: Processing log files==========="
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cd $work_dir
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python process_data.py $me_report_path $log_path $iter $log_path/$log_data
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fi
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if [ $stage -le 5 ]; then
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echo ""
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echo "===========Stage 5: Generating reports==========="
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if [ ! -d $log_path/reports ]; then
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mkdir $log_path/reports
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fi
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python generate_report.py $log_path $log_path/$log_data $me_report_path $days
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if [ $ci_mode ]; then
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echo "copying file to artifacts"
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mkdir -p ${WORKSPACE}/archive
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cp $log_path/reports/* ${WORKSPACE}/archive
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fi
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fi
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