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#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import unittest
import torch
from examples.speech_recognition.data import data_utils
class DataUtilsTest(unittest.TestCase):
def test_normalization(self):
sample_len1 = torch.tensor(
[
[
-0.7661,
-1.3889,
-2.0972,
-0.9134,
-0.7071,
-0.9765,
-0.8700,
-0.8283,
0.7512,
1.3211,
2.1532,
2.1174,
1.2800,
1.2633,
1.6147,
1.6322,
2.0723,
3.1522,
3.2852,
2.2309,
2.5569,
2.2183,
2.2862,
1.5886,
0.8773,
0.8725,
1.2662,
0.9899,
1.1069,
1.3926,
1.2795,
1.1199,
1.1477,
1.2687,
1.3843,
1.1903,
0.8355,
1.1367,
1.2639,
1.4707,
]
]
)
out = data_utils.apply_mv_norm(sample_len1)
assert not torch.isnan(out).any()
assert (out == sample_len1).all()