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Newnius
2020-04-30 01:10:20 +08:00
parent 54602b87b8
commit 0560bca8f6
2 changed files with 28 additions and 20 deletions
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24
serve.py
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@@ -72,15 +72,10 @@ class Data:
self.data_num = self.data.shape[0]
self.train_num = int(self.data_num * self.config.train_data_rate)
print(self.data)
self.mean = np.mean(self.data, axis=0)
print(1)
self.std = np.std(self.data, axis=0)
print(self.std)
print(self.mean)
self.norm_data = (self.data - self.mean) / self.std
print(2)
self.start_num_in_test = 0
@@ -116,15 +111,26 @@ class Data:
return train_x, valid_x, train_y, valid_y
def get_test_data(self, return_label_data=False):
feature_data = self.norm_data[self.train_num:]
init_data = pd.read_csv(
self.config.train_data_path,
usecols=self.config.feature_and_label_columns
)
data, data_column_name = init_data.values, init_data.columns.tolist()
train_num = 0
mean = np.mean(data, axis=0)
std = np.std(data, axis=0)
norm_data = (data - mean) / std
start_num_in_test = 0
feature_data = norm_data[0:]
self.start_num_in_test = feature_data.shape[0] % self.config.time_step
time_step_size = feature_data.shape[0] // self.config.time_step
test_x = [feature_data[self.start_num_in_test + i * self.config.time_step: self.start_num_in_test + (
test_x = [feature_data[start_num_in_test + i * self.config.time_step: start_num_in_test + (
i + 1) * self.config.time_step]
for i in range(time_step_size)]
if return_label_data:
label_data = self.norm_data[self.train_num + self.start_num_in_test:, self.config.label_in_feature_columns]
label_data = norm_data[train_num + start_num_in_test:, self.config.label_in_feature_columns]
return np.array(test_x), label_data
return np.array(test_x)
@@ -191,7 +197,7 @@ class MyHandler(BaseHTTPRequestHandler):
gpu_model = query.get('gpu_model')[0]
time = query.get('time')[0]
data_gainer = Data(config)
test_X, test_Y = np.array([[job, gpu_model, time]]), np.array([[1,1,1]]) #data_gainer.get_test_data(return_label_data=True)
test_X, test_Y = data_gainer.get_test_data(return_label_data=True)
print(test_X, test_Y)
pred_result = predict(config, test_X)
print(pred_result)