def testBuildGraphWithAttention(self):
self.hparams.attn_length = 10
g = melody_rnn_graph.build_graph('train',
self.hparams,
self.encoder_decoder,
sequence_example_file='test')
self.assertTrue(isinstance(g, tf.Graph))
def build_graph(mode,
hparams_string,
encoder_decoder,
sequence_example_file=None):
"""Builds the TensorFlow graph.
Args:
mode: 'train', 'eval', or 'generate'. Only mode related ops are added to
the graph.
hparams_string: A string literal of a Python dictionary, where keys are
hyperparameter names and values replace default values. For example:
'{"batch_size":64,"rnn_layer_sizes":[128,128]}'
encoder_decoder: The MelodyEncoderDecoder being used by the model.
sequence_example_file: A string path to a TFRecord file containing
tf.train.SequenceExamples. Only needed for training and evaluation.
Returns:
A tf.Graph instance which contains the TF ops.
Raises:
ValueError: If mode is not 'train', 'eval', or 'generate', or if
sequence_example_file does not match a file when mode is 'train' or
'eval'.
"""
hparams = default_hparams()
hparams = hparams.parse(hparams_string)
return melody_rnn_graph.build_graph(mode, hparams, encoder_decoder,
sequence_example_file)
def testBuildGenerateGraph(self):
self.hparams.temperature = 1.0
g = melody_rnn_graph.build_graph('generate',
self.hparams,
self.encoder_decoder,
sequence_example_file='test')
self.assertTrue(isinstance(g, tf.Graph))
def build_graph(mode, hparams_string, encoder_decoder,
sequence_example_file=None):
"""Builds the TensorFlow graph.
Args:
mode: 'train', 'eval', or 'generate'. Only mode related ops are added to
the graph.
hparams_string: A string literal of a Python dictionary, where keys are
hyperparameter names and values replace default values. For example:
'{"batch_size":64,"rnn_layer_sizes":[128,128]}'
encoder_decoder: The MelodyEncoderDecoder being used by the model.
sequence_example_file: A string path to a TFRecord file containing
tf.train.SequenceExamples. Only needed for training and evaluation.
Returns:
A tf.Graph instance which contains the TF ops.
Raises:
ValueError: If mode is not 'train', 'eval', or 'generate', or if
sequence_example_file does not match a file when mode is 'train' or
'eval'.
"""
hparams = default_hparams()
hparams = hparams.parse(hparams_string)
return melody_rnn_graph.build_graph(mode, hparams, encoder_decoder,
sequence_example_file)
def testBuildEvalGraph(self):
g = melody_rnn_graph.build_graph('eval',
self.hparams,
self.encoder_decoder,
sequence_example_file='test')
self.assertTrue(isinstance(g, tf.Graph))
def testBuildGraphWithAttention(self):
self.hparams.attn_length = 10
g = melody_rnn_graph.build_graph(
'train', self.hparams, self.encoder_decoder,
sequence_example_file='test')
self.assertTrue(isinstance(g, tf.Graph))
def testBuildGenerateGraph(self):
self.hparams.temperature = 1.0
g = melody_rnn_graph.build_graph(
'generate', self.hparams, self.encoder_decoder,
sequence_example_file='test')
self.assertTrue(isinstance(g, tf.Graph))
def testBuildEvalGraph(self):
g = melody_rnn_graph.build_graph(
'eval', self.hparams, self.encoder_decoder,
sequence_example_file='test')
self.assertTrue(isinstance(g, tf.Graph))
