59 lines
2.1 KiB
Python
59 lines
2.1 KiB
Python
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# Copyright 2016 Google Inc. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Provides function to build the lookback RNN model's graph."""
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# internal imports
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from magenta.common import tf_lib
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from magenta.models.shared import melody_rnn_graph
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def default_hparams():
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return tf_lib.HParams(
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batch_size=128,
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rnn_layer_sizes=[128, 128],
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dropout_keep_prob=0.5,
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skip_first_n_losses=0,
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clip_norm=5,
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initial_learning_rate=0.01,
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decay_steps=1000,
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decay_rate=0.95)
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def build_graph(mode, hparams_string, encoder_decoder,
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sequence_example_file=None):
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"""Builds the TensorFlow graph.
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Args:
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mode: 'train', 'eval', or 'generate'. Only mode related ops are added to
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the graph.
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hparams_string: A string literal of a Python dictionary, where keys are
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hyperparameter names and values replace default values. For example:
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'{"batch_size":64,"rnn_layer_sizes":[128,128]}'
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encoder_decoder: The MelodyEncoderDecoder being used by the model.
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sequence_example_file: A string path to a TFRecord file containing
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tf.train.SequenceExamples. Only needed for training and evaluation.
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Returns:
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A tf.Graph instance which contains the TF ops.
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Raises:
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ValueError: If mode is not 'train', 'eval', or 'generate', or if
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sequence_example_file does not match a file when mode is 'train' or
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'eval'.
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"""
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hparams = default_hparams()
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hparams = hparams.parse(hparams_string)
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return melody_rnn_graph.build_graph(mode, hparams, encoder_decoder,
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sequence_example_file)
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