Python build_graph Exemples

Exemple #1

Fichier : polyphony_rnn_train.py Projet : Kaushikpatnaik/magenta

def main(unused_argv):
  tf.logging.set_verbosity(FLAGS.log)

  if not FLAGS.run_dir:
    tf.logging.fatal('--run_dir required')
    return
  if not FLAGS.sequence_example_file:
    tf.logging.fatal('--sequence_example_file required')
    return

  sequence_example_file = tf.gfile.Glob(
      os.path.expanduser(FLAGS.sequence_example_file))
  run_dir = os.path.expanduser(FLAGS.run_dir)

  config = polyphony_model.default_configs[FLAGS.config]

  mode = 'eval' if FLAGS.eval else 'train'
  graph = events_rnn_graph.build_graph(
      mode, config, sequence_example_file)

  train_dir = os.path.join(run_dir, 'train')
  tf.gfile.MakeDirs(train_dir)
  tf.logging.info('Train dir: %s', train_dir)

  if FLAGS.eval:
    eval_dir = os.path.join(run_dir, 'eval')
    tf.gfile.MakeDirs(eval_dir)
    tf.logging.info('Eval dir: %s', eval_dir)
    events_rnn_train.run_eval(graph, train_dir, eval_dir,
                              FLAGS.num_training_steps, FLAGS.summary_frequency)

  else:
    events_rnn_train.run_training(graph, train_dir, FLAGS.num_training_steps,
                                  FLAGS.summary_frequency)

Exemple #2

Fichier : events_rnn_graph_test.py Projet : YoshikawaMasashi/magenta

 def testBuildGraphCnn(self):
   self.config.hparams.dilated_cnn = True
   self.config.hparams.block_num = 1
   self.config.hparams.block_size = 7
   self.config.hparams.residual_cnl = 32
   self.config.hparams.dilation_cnl = 16
   self.config.hparams.output_cnl = 64
   self.config.hparams.use_gate = True
   self.config.hparams.use_step = True
   g = events_rnn_graph.build_graph(
       'train', self.config, sequence_example_file_paths=['test'])
   self.assertTrue(isinstance(g, tf.Graph))

Exemple #3

Fichier : polyphony_rnn_train.py Projet : eraoul/magenta

def main(unused_argv):
  tf.logging.set_verbosity(FLAGS.log)

  if not FLAGS.run_dir:
    tf.logging.fatal('--run_dir required')
    return
  if not FLAGS.sequence_example_file:
    tf.logging.fatal('--sequence_example_file required')
    return

  sequence_example_file_paths = tf.gfile.Glob(
      os.path.expanduser(FLAGS.sequence_example_file))
  run_dir = os.path.expanduser(FLAGS.run_dir)

  config = polyphony_model.default_configs[FLAGS.config]
  config.hparams.parse(FLAGS.hparams)

  mode = 'eval' if FLAGS.eval else 'train'
  graph = events_rnn_graph.build_graph(
      mode, config, sequence_example_file_paths)

  train_dir = os.path.join(run_dir, 'train')
  tf.gfile.MakeDirs(train_dir)
  tf.logging.info('Train dir: %s', train_dir)

  if FLAGS.eval:
    eval_dir = os.path.join(run_dir, 'eval')
    tf.gfile.MakeDirs(eval_dir)
    tf.logging.info('Eval dir: %s', eval_dir)
    num_batches = (
        (FLAGS.num_eval_examples if FLAGS.num_eval_examples else
         magenta.common.count_records(sequence_example_file_paths)) //
        config.hparams.batch_size)
    events_rnn_train.run_eval(graph, train_dir, eval_dir, num_batches)

  else:
    events_rnn_train.run_training(graph, train_dir, FLAGS.num_training_steps,
                                  FLAGS.summary_frequency,
                                  checkpoints_to_keep=FLAGS.num_checkpoints)

Exemple #4

Fichier : melody_rnn_train.py Projet : xcode2010/generative_audio

def main(unused_argv):
    tf.logging.set_verbosity(FLAGS.log)

    if not FLAGS.run_dir:
        tf.logging.fatal('--run_dir required')
        return
    if not FLAGS.sequence_example_file:
        tf.logging.fatal('--sequence_example_file required')
        return

    sequence_example_file_paths = tf.gfile.Glob(
        os.path.expanduser(FLAGS.sequence_example_file))
    run_dir = os.path.expanduser(FLAGS.run_dir)

    config = melody_rnn_config_flags.config_from_flags()

    mode = 'eval' if FLAGS.eval else 'train'
    graph = events_rnn_graph.build_graph(mode, config,
                                         sequence_example_file_paths)

    train_dir = os.path.join(run_dir, 'train')
    if not os.path.exists(train_dir):
        tf.gfile.MakeDirs(train_dir)
    tf.logging.info('Train dir: %s', train_dir)

    if FLAGS.eval:
        eval_dir = os.path.join(run_dir, 'eval')
        if not os.path.exists(eval_dir):
            tf.gfile.MakeDirs(eval_dir)
        tf.logging.info('Eval dir: %s', eval_dir)
        events_rnn_train.run_eval(graph, train_dir, eval_dir,
                                  FLAGS.num_training_steps,
                                  FLAGS.summary_frequency)

    else:
        events_rnn_train.run_training(graph, train_dir,
                                      FLAGS.num_training_steps,
                                      FLAGS.summary_frequency)

Exemple #5

Fichier : polyphony_rnn_train.py Projet : xcode2010/generative_audio

def main(unused_argv):
    tf.logging.set_verbosity(FLAGS.log)

    if not FLAGS.run_dir:
        tf.logging.fatal('--run_dir required')
        return
    if not FLAGS.sequence_example_file:
        tf.logging.fatal('--sequence_example_file required')
        return

    sequence_example_file = tf.gfile.Glob(
        os.path.expanduser(FLAGS.sequence_example_file))
    run_dir = os.path.expanduser(FLAGS.run_dir)

    config = polyphony_model.default_configs[FLAGS.config]
    config.hparams.parse(FLAGS.hparams)

    mode = 'eval' if FLAGS.eval else 'train'
    graph = events_rnn_graph.build_graph(mode, config, sequence_example_file)

    train_dir = os.path.join(run_dir, 'train')
    tf.gfile.MakeDirs(train_dir)
    tf.logging.info('Train dir: %s', train_dir)

    if FLAGS.eval:
        eval_dir = os.path.join(run_dir, 'eval')
        tf.gfile.MakeDirs(eval_dir)
        tf.logging.info('Eval dir: %s', eval_dir)
        events_rnn_train.run_eval(graph, train_dir, eval_dir,
                                  FLAGS.num_training_steps,
                                  FLAGS.summary_frequency)

    else:
        events_rnn_train.run_training(graph, train_dir,
                                      FLAGS.num_training_steps,
                                      FLAGS.summary_frequency)

Exemple #6

 def _build_graph_for_generation(self):
   return events_rnn_graph.build_graph('generate', self._config)

Exemple #7

Fichier : events_rnn_model.py Projet : memo/magenta

 def _build_graph_for_generation(self):
   return events_rnn_graph.build_graph('generate', self._config)

Exemple #8

Fichier : 56350_events_rnn_graph_test.py Projet : tate11/intelligent-code-completion

 def testBuildGenerateGraph(self):
     g = events_rnn_graph.build_graph('generate', self.config)
     self.assertTrue(isinstance(g, tf.Graph))

Exemple #9

Fichier : 56350_events_rnn_graph_test.py Projet : tate11/intelligent-code-completion

 def testBuildEvalGraph(self):
     g = events_rnn_graph.build_graph(
         'eval',
         self.config,
         sequence_example_file_paths=[self._sequence_file.name])
     self.assertTrue(isinstance(g, tf.Graph))

Exemple #10

Fichier : events_rnn_graph_test.py Projet : gxlcliqi/magenta

 def testBuildGraphWithAttention(self):
   self.config.hparams.attn_length = 10
   g = events_rnn_graph.build_graph(
       'train', self.config, sequence_example_file_paths=['test'])
   self.assertTrue(isinstance(g, tf.Graph))

Exemple #11

Fichier : events_rnn_graph_test.py Projet : gxlcliqi/magenta

 def testBuildTrainGraph(self):
   g = events_rnn_graph.build_graph(
       'train', self.config, sequence_example_file_paths=['test'])
   self.assertTrue(isinstance(g, tf.Graph))

Exemple #12

Fichier : events_rnn_graph_test.py Projet : Kaushikpatnaik/magenta

 def testBuildGraphWithAttention(self):
   self.config.hparams.attn_length = 10
   g = events_rnn_graph.build_graph(
       'train', self.config, sequence_example_file_paths=['test'])
   self.assertTrue(isinstance(g, tf.Graph))

Exemple #13

Fichier : events_rnn_graph_test.py Projet : Kaushikpatnaik/magenta

 def testBuildGenerateGraph(self):
   g = events_rnn_graph.build_graph('generate', self.config)
   self.assertTrue(isinstance(g, tf.Graph))

Exemple #14

Fichier : events_rnn_graph_test.py Projet : Kaushikpatnaik/magenta

 def testBuildEvalGraph(self):
   g = events_rnn_graph.build_graph(
       'eval', self.config, sequence_example_file_paths=['test'])
   self.assertTrue(isinstance(g, tf.Graph))

Exemple #15

Fichier : events_rnn_graph_test.py Projet : eraoul/magenta

 def testBuildTrainGraph(self):
   g = events_rnn_graph.build_graph(
       'train', self.config,
       sequence_example_file_paths=[self._sequence_file.name])
   self.assertTrue(isinstance(g, tf.Graph))

Exemple #16

Fichier : initial_experiments.py Projet : adellelin/ai-music-s2s

from magenta.models.shared.events_rnn_graph import build_graph
from magenta.models.melody_rnn.melody_rnn_sequence_generator import MelodyRnnSequenceGenerator
from magenta.models.melody_rnn.melody_rnn_model import MelodyRnnModel

logging.basicConfig(level=logging.DEBUG)

BUNDLE_NAME = 'attention_rnn'

config = magenta.models.melody_rnn.melody_rnn_model.default_configs[BUNDLE_NAME]
bundle_file = magenta.music.read_bundle_file(os.path.abspath(BUNDLE_NAME+'.mag'))
steps_per_quarter = 4

generator = MelodyRnnSequenceGenerator(
    model=MelodyRnnModel(config),
    details=config.details,
    steps_per_quarter=steps_per_quarter,
    bundle=bundle_file)

generator.create_bundle_file('/Users/mdpicket/Documents/tmp/bundle')
exit()

with tf.Session() as sess:
    graph = build_graph('generate', config)
    writer = tf.summary.FileWriter(logdir='/Users/mdpicket/Documents/tmp',
                                   graph=graph)
    writer.flush()

    with tf.Graph() as graph:
     saver = tf.train.Saver(tf.global_variables())
     saver.save(sess, '/Users/mdpicket/Documents/tmp/model.saver')