(batch_size=1, sample_length=64000)
return graph
Load the NSynth autoencoder network.

  Args:
    batch_size: Batch size number of observations to process. [1]
    sample_length: Number of samples in the input audio. [64000]
  Returns:
    graph: The network as a dict with input placeholder in {"X"}
Load the NSynth autoencoder network.
Load the NSynth autoencoder network .
def load_nsynth(batch_size=1, sample_length=64000):
  """Load the NSynth autoencoder network.

  Args:
    batch_size: Batch size number of observations to process. [1]
    sample_length: Number of samples in the input audio. [64000]
  Returns:
    graph: The network as a dict with input placeholder in {"X"}
  """
  config = Config()
  with tf.device("/gpu:0"):
    x = tf.placeholder(tf.float32, shape=[batch_size, sample_length])
    graph = config.build({"wav": x}, is_training=False)
    graph.update({"X": x})
  return graph
def load_nsynth ( batch_size = 1 , sample_length = 64000 ) : config = Config ( ) with tf . device ( "/gpu:0" ) : x = tf . placeholder ( tf . float32 , shape = [ batch_size , sample_length ] ) graph = config . build ( { "wav" : x } , is_training = False ) graph . update ( { "X" : x } ) return graph