aiexperiments-ai-duet/server/magenta/models/lookback_rnn/lookback_rnn_graph.py

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2016-11-11 18:53:51 +00:00
# Copyright 2016 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Provides function to build the lookback RNN model's graph."""
# internal imports
from magenta.common import tf_lib
from magenta.models.shared import melody_rnn_graph
def default_hparams():
return tf_lib.HParams(
batch_size=128,
rnn_layer_sizes=[128, 128],
dropout_keep_prob=0.5,
skip_first_n_losses=0,
clip_norm=5,
initial_learning_rate=0.01,
decay_steps=1000,
decay_rate=0.95)
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)