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| # Copyright 2022 The MT3 Authors. | |
| # | |
| # 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. | |
| """Tests for run_length_encoding.""" | |
| from mt3 import event_codec | |
| from mt3 import run_length_encoding | |
| import note_seq | |
| import numpy as np | |
| import seqio | |
| import tensorflow as tf | |
| assert_dataset = seqio.test_utils.assert_dataset | |
| codec = event_codec.Codec( | |
| max_shift_steps=100, | |
| steps_per_second=100, | |
| event_ranges=[ | |
| event_codec.EventRange('pitch', note_seq.MIN_MIDI_PITCH, | |
| note_seq.MAX_MIDI_PITCH), | |
| event_codec.EventRange('velocity', 0, 127), | |
| event_codec.EventRange('drum', note_seq.MIN_MIDI_PITCH, | |
| note_seq.MAX_MIDI_PITCH), | |
| event_codec.EventRange('program', note_seq.MIN_MIDI_PROGRAM, | |
| note_seq.MAX_MIDI_PROGRAM), | |
| event_codec.EventRange('tie', 0, 0) | |
| ]) | |
| run_length_encode_shifts = run_length_encoding.run_length_encode_shifts_fn( | |
| codec=codec) | |
| class RunLengthEncodingTest(tf.test.TestCase): | |
| def test_remove_redundant_state_changes(self): | |
| og_dataset = tf.data.Dataset.from_tensors({ | |
| 'targets': [3, 525, 356, 161, 2, 525, 356, 161, 355, 394] | |
| }) | |
| assert_dataset( | |
| run_length_encoding.remove_redundant_state_changes_fn( | |
| codec=codec, | |
| state_change_event_types=['velocity', 'program'])(og_dataset), | |
| { | |
| 'targets': [3, 525, 356, 161, 2, 161, 355, 394], | |
| }) | |
| def test_run_length_encode_shifts(self): | |
| og_dataset = tf.data.Dataset.from_tensors({ | |
| 'targets': [1, 1, 1, 161, 1, 1, 1, 162, 1, 1, 1] | |
| }) | |
| assert_dataset( | |
| run_length_encode_shifts(og_dataset), | |
| { | |
| 'targets': [3, 161, 6, 162], | |
| }) | |
| def test_run_length_encode_shifts_beyond_max_length(self): | |
| og_dataset = tf.data.Dataset.from_tensors({ | |
| 'targets': [1] * 202 + [161, 1, 1, 1] | |
| }) | |
| assert_dataset( | |
| run_length_encode_shifts(og_dataset), | |
| { | |
| 'targets': [100, 100, 2, 161], | |
| }) | |
| def test_run_length_encode_shifts_simultaneous(self): | |
| og_dataset = tf.data.Dataset.from_tensors({ | |
| 'targets': [1, 1, 1, 161, 162, 1, 1, 1] | |
| }) | |
| assert_dataset( | |
| run_length_encode_shifts(og_dataset), | |
| { | |
| 'targets': [3, 161, 162], | |
| }) | |
| def test_merge_run_length_encoded_targets(self): | |
| # pylint: disable=bad-whitespace | |
| targets = np.array([ | |
| [ 3, 161, 162, 5, 163], | |
| [160, 164, 3, 165, 0] | |
| ]) | |
| # pylint: enable=bad-whitespace | |
| merged_targets = run_length_encoding.merge_run_length_encoded_targets( | |
| targets=targets, codec=codec) | |
| expected_merged_targets = [ | |
| 160, 164, 3, 161, 162, 165, 5, 163 | |
| ] | |
| np.testing.assert_array_equal(expected_merged_targets, merged_targets) | |
| if __name__ == '__main__': | |
| tf.test.main() | |