def reset_val_batches(self):
self.val_batches = int(
np.floor(self.val_input_data.shape[0] / self.batch_size))
if self.val_batches > 0:
self.val_input_batches = self.val_input_data
self.val_output_batches = self.val_output_data
self.val_input_batches = self.val_input_batches[:self.batch_size *
self.val_batches]
self.val_output_batches = self.val_output_batches[:self.
batch_size *
self.val_batches]
else:
self.val_input_batches = np.zeros(
(self.batch_size, self.val_input_data.shape))
self.val_output_batches = np.zeros(
(self.batch_size, self.val_output_data.shape))
self.val_input_batches = data.reshape_1D_input(
self.val_input_batches)
self.val_input_batches[:self.val_input_data.
shape[0]] = self.val_input_data
self.val_output_batches[:self.val_output_data.
shape[0]] = self.val_output_data
if self.frame_work == 'Tensorflow':
self.val_input_batches, self.val_output_batches = data.convert_to_tensorflow_minbatch(
self.val_input_batches, self.val_output_batches,
self.batch_size)
def reshape_1D_input(self):
self.all_input_data = data.reshape_1D_input(self.all_input_data)