49 lines
1.5 KiB
Python
49 lines
1.5 KiB
Python
# 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.
|
|
r"""Create a dataset for training and evaluating the attention RNN model.
|
|
|
|
Example usage:
|
|
$ bazel build magenta/models/attention_rnn:attention_rnn_create_dataset
|
|
|
|
$ ./bazel-bin/magenta/models/attention_rnn/attention_rnn_create_dataset \
|
|
--input=/tmp/note_sequences.tfrecord \
|
|
--output_dir=/tmp/attention_rnn
|
|
--eval_ratio=0.10
|
|
|
|
See /magenta/models/shared/melody_rnn_create_dataset.py for flag descriptions.
|
|
"""
|
|
|
|
# internal imports
|
|
import tensorflow as tf
|
|
|
|
from magenta.models.attention_rnn import attention_rnn_encoder_decoder
|
|
from magenta.models.shared import melody_rnn_create_dataset
|
|
|
|
|
|
def get_pipeline():
|
|
return melody_rnn_create_dataset.get_pipeline(
|
|
attention_rnn_encoder_decoder.MelodyEncoderDecoder())
|
|
|
|
|
|
def main(unused_argv):
|
|
melody_rnn_create_dataset.run_from_flags(get_pipeline())
|
|
|
|
|
|
def console_entry_point():
|
|
tf.app.run(main)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
console_entry_point()
|