Add neural net class

This commit is contained in:
Paul Schaub 2018-05-29 15:34:05 +02:00
parent 00b95528a7
commit 2be5cdd2ce
Signed by: vanitasvitae
GPG key ID: 62BEE9264BF17311

31
pywatts/neural.py Normal file
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import tensorflow as tf
class Net:
regressor = None
def net(self, feature_cols):
self.regressor = tf.estimator.DNNRegressor(feature_columns=feature_cols,
hidden_units=[50, 50],
model_dir='tf_pywatts_model')
def pywatts_input_fn(X, y=None, num_epochs=None, shuffle=True, batch_size=400):
return tf.estimator.inputs.pandas_input_fn(x=X,
y=y,
num_epochs=num_epochs,
shuffle=shuffle,
batch_size=batch_size)
def train(self, training_data, steps):
self.regressor.train(input_fn=self.pywatts_input_fn(training_data, num_epochs=None, shuffle=True), steps=steps)
def evaluate(self, eval_data):
self.regressor.evaluate(input_fn=self.pywatts_input_fn(eval_data, num_epochs=1, shuffle=False), steps=1)
def predict1h(self, df):
df = df.drop(['month', 'day', 'hour'])
predictions = self.regressor.predict(input_fn=self.pywatts_input_fn(df, num_epochs=1, shuffle=False))