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54 lines
2.0 KiB
Python
54 lines
2.0 KiB
Python
# Copyright (c) 2022, NVIDIA CORPORATION. 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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import pytest
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import torch
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from nemo.collections.tts.parts.utils.helpers import regulate_len, sort_tensor, unsort_tensor
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def sample_duration_input(max_length=64, group_size=2, batch_size=3):
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generator = torch.Generator()
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generator.manual_seed(0)
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lengths = torch.randint(max_length // 4, max_length - 7, (batch_size,), generator=generator)
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durs = torch.ones(batch_size, max_length) * group_size
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durs[0, lengths[0]] += 1
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durs[2, lengths[2]] -= 1
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enc = torch.randint(16, 64, (batch_size, max_length, 17))
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return durs, enc, lengths
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@pytest.mark.unit
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def test_sort_unsort():
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durs_in, enc_in, dur_lens = sample_duration_input(batch_size=13)
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print("In: ", enc_in)
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sorted_enc, sorted_len, sorted_ids = sort_tensor(enc_in, dur_lens)
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unsorted_enc = unsort_tensor(sorted_enc, sorted_ids)
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print("Out: ", unsorted_enc)
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assert torch.all(unsorted_enc == enc_in)
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@pytest.mark.unit
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def test_regulate_len():
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group_size = 2
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durs_in, enc_in, dur_lens = sample_duration_input(group_size=group_size)
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enc_out, lens_out = regulate_len(durs_in, enc_in, group_size=group_size, dur_lens=dur_lens)
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# make sure lens_out are rounded
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sum_diff = lens_out - torch.mul(lens_out // group_size, group_size)
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assert sum_diff.sum(dim=0) == 0
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# make sure all round-ups are <= group_size
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diff = lens_out - durs_in.sum(dim=1)
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assert torch.max(diff) < group_size
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