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@ -2,7 +2,6 @@
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34
serve.py
34
serve.py
@ -10,6 +10,7 @@ import numpy as np
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import os
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from sklearn.model_selection import train_test_split
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from model_tensorflow import train, predict
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import csv
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class Config:
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@ -49,7 +50,7 @@ class Config:
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batch_size = 1
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continue_flag = "continue_"
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train_data_path = "./data/stock_data.csv"
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train_data_path = "./data.csv"
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model_save_path = "./checkpoint/"
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figure_save_path = "./figure/"
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do_figure_save = False
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@ -150,9 +151,19 @@ lock = Lock()
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config = Config()
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def train_models(job):
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print("train")
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def train_models(records):
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lock.acquire()
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with open(config.train_data_path, 'w', 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", "Time", "GPU", "Pre", "Main", "Post"])
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for record in records:
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print(record)
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spamwriter.writerow(record)
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np.random.seed(config.random_seed)
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data_gainer = Data(config)
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@ -192,15 +203,14 @@ class MyHandler(BaseHTTPRequestHandler):
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self.wfile.write(bytes(json.dumps(msg), "utf-8"))
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elif req.path == "/train":
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#try:
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job = query.get('job')[0]
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gpu_model = query.get('gpu_model')[0]
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time = query.get('time')[0]
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t = Thread(target=train_models, name='train_models', args=(job,))
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t.start()
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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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try:
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data = query.get('data')[0]
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records = json.load(data)
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t = Thread(target=train_models, name='train_models', args=(records,))
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t.start()
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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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self.send_response(200)
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self.send_header('Content-type', 'application/json')
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self.end_headers()
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