def provide_input(self) -> List[tf.Tensor]:
with tf.name_scope("loading"):
training_data = get_data_from_tfrecord("./data/train.tfrecord",
self.BATCH_SIZE)
with tf.name_scope("training"):
parameters = self.build_training_graph(training_data)
return parameters
def provide_input(self) -> List[tf.Tensor]:
"""Prepare input data for prediction."""
with tf.name_scope('loading'):
prediction_input, expected_result = get_data_from_tfrecord(
"./data/test.tfrecord", self.BATCH_SIZE, flattened=True).get_next()
with tf.name_scope('pre-processing'):
prediction_input = tf.reshape(
prediction_input, shape=(self.BATCH_SIZE, ModelTrainer.IN_N))
expected_result = tf.reshape(
expected_result, shape=(self.BATCH_SIZE,))
return [prediction_input, expected_result]
