(self, z, batch_size=None)
return run_with_batch(self.sess, m.x_mean, m.z, z, batch_size)
Decode from given latant space vectors `z`.

    Args:
      z: A numpy array of latent space vectors.
      batch_size: (Optional) a integer to indication batch size for computation
          which is useful if the sampling requires lots of GPU memory.

    Returns:
      A numpy array, the dataspace points from decoding.
Decode from given latant space vectors `z`.
Decode from given latant space vectors z .
def decode(self, z, batch_size=None):
    """Decode from given latant space vectors `z`.

    Args:
      z: A numpy array of latent space vectors.
      batch_size: (Optional) a integer to indication batch size for computation
          which is useful if the sampling requires lots of GPU memory.

    Returns:
      A numpy array, the dataspace points from decoding.
    """
    m = self.m
    batch_size = batch_size or self.DEFAULT_BATCH_SIZE
    return run_with_batch(self.sess, m.x_mean, m.z, z, batch_size)
def decode ( self , z , batch_size = None ) : m = self . m batch_size = batch_size or self . DEFAULT_BATCH_SIZE return run_with_batch ( self . sess , m . x_mean , m . z , z , batch_size )