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@ -1,7 +1,10 @@
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29
serve.py
29
serve.py
@ -16,8 +16,8 @@ from io import StringIO
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class Config:
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feature_columns = list(range(0, 8))
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label_columns = [5, 6, 7]
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feature_columns = list(range(0, 2))
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label_columns = [1]
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feature_and_label_columns = feature_columns + label_columns
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label_in_feature_columns = (lambda x, y: [x.index(i) for i in y])(feature_columns, label_columns)
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@ -148,7 +148,7 @@ def draw_yqy(config2, origin_data, predict_norm_data, mean_yqy, std_yqy):
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label_column_num = 3
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loss = \
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np.mean((label_norm_data[config.predict_day:, 5:8] - predict_norm_data[:-config.predict_day]) ** 2, axis=0)
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np.mean((label_norm_data[config.predict_day:, 1:2] - predict_norm_data[:-config.predict_day]) ** 2, axis=0)
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print("The mean squared error of stock {} is ".format(label_name), loss)
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# label_X = range(origin_data.data_num - origin_data.train_num - origin_data.start_num_in_test)
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@ -156,8 +156,8 @@ def draw_yqy(config2, origin_data, predict_norm_data, mean_yqy, std_yqy):
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print("2")
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print(label_norm_data[:, 5:8])
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label_data = label_norm_data[:, 5:8] * std_yqy[5:8] + mean_yqy[5:8]
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print(label_norm_data[:, 1:2])
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label_data = label_norm_data[:, 1:2] * std_yqy[1:2] + mean_yqy[1:2]
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print(label_data)
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print(predict_norm_data)
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@ -213,16 +213,20 @@ class MyHandler(BaseHTTPRequestHandler):
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'post': 0
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}
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data = {
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'seq': query.get('job')[0],
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'value': query.get('model')[0],
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}
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with open(config.train_data_path, 'r') as f:
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df = pd.read_csv(config.train_data_path,
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usecols=['job', 'model', 'time', 'utilCPU', 'utilGPU', 'pre', 'main', 'post'])
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df = pd.read_csv(config.train_data_path, usecols=['seq', 'value'])
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df = df.tail(config.time_step - 1)
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df = df.append(data, ignore_index=True)
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df.to_csv('./data/test_data.csv', index=False)
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np.random.seed(config.random_seed)
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data_gainer = Data(config)
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test_data_yqy = pd.read_csv("./data/test_data.csv", usecols=list(range(0, 8)))
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test_data_yqy = pd.read_csv("./data/test_data.csv", usecols=list(range(0, 2)))
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test_data_values = test_data_yqy.values[:]
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test_X = data_gainer.get_test_data_yqy(test_data_values)
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pred_result = predict(config, test_X)
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@ -250,12 +254,16 @@ class MyHandler(BaseHTTPRequestHandler):
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main = query.get('main')[0]
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post = query.get('post')[0]
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seq = query.get('seq')[0]
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value = query.get('value')[0]
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with open(config.train_data_path, 'a+', newline='') as csvfile:
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spamwriter = csv.writer(
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csvfile, delimiter=',',
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quotechar='|', quoting=csv.QUOTE_MINIMAL
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)
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spamwriter.writerow([job, model, time, utilGPU, utilCPU, pre, main, post])
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# spamwriter.writerow([job, model, time, utilGPU, utilCPU, pre, main, post])
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spamwriter.writerow([seq, value])
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msg = {'code': 1, 'error': "container not exist"}
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except Exception as e:
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msg = {'code': 2, 'error': str(e)}
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@ -319,7 +327,8 @@ if __name__ == '__main__':
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csvfile, delimiter=',',
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quotechar='|', quoting=csv.QUOTE_MINIMAL
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)
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spamwriter.writerow(["job", "model", "time", "utilGPU", "utilCPU", "pre", "main", "post"])
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#spamwriter.writerow(["job", "model", "time", "utilGPU", "utilCPU", "pre", "main", "post"])
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spamwriter.writerow(["seq", "value"])
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# Wait forever for incoming http requests
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server.serve_forever()
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