forked from mindspore-Ecosystem/mindspore
105 lines
3.6 KiB
Python
105 lines
3.6 KiB
Python
# 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 matplotlib.ticker as ticker
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import matplotlib.pyplot as plt
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import openpyxl as opx
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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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