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import torch
import torchaudio.kaldi_io as kio
from torchaudio_unittest import common_utils
class Test_KaldiIO(common_utils.TorchaudioTestCase):
data1 = [[1, 2, 3], [11, 12, 13], [21, 22, 23]]
data2 = [[31, 32, 33], [41, 42, 43], [51, 52, 53]]
def _test_helper(self, file_name, expected_data, fn, expected_dtype):
"""Takes a file_name to the input data and a function fn to extract the
data. It compares the extracted data to the expected_data. The expected_dtype
will be used to check that the extracted data is of the right type.
"""
test_filepath = common_utils.get_asset_path(file_name)
expected_output = {
"key" + str(idx + 1): torch.tensor(val, dtype=expected_dtype) for idx, val in enumerate(expected_data)
}
for key, vec in fn(test_filepath):
self.assertTrue(key in expected_output)
self.assertTrue(isinstance(vec, torch.Tensor))
self.assertEqual(vec.dtype, expected_dtype)
self.assertTrue(torch.all(torch.eq(vec, expected_output[key])))
def test_read_vec_int_ark(self):
self._test_helper("vec_int.ark", self.data1, kio.read_vec_int_ark, torch.int32)
def test_read_vec_flt_ark(self):
self._test_helper("vec_flt.ark", self.data1, kio.read_vec_flt_ark, torch.float32)
def test_read_mat_ark(self):
self._test_helper("mat.ark", [self.data1, self.data2], kio.read_mat_ark, torch.float32)
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