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Fix speaker encoder test

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This commit is contained in:
Eren Gölge
2021-12-30 15:36:35 +00:00
parent 497332bd46
commit 348b5c96a2
5 changed files with 11 additions and 11 deletions
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tests/aux_tests/test_speaker_encoder.py
+4 -4
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@@ -13,7 +13,7 @@ file_path = get_tests_input_path()
class LSTMSpeakerEncoderTests(unittest.TestCase):
# pylint: disable=R0201
def test_in_out(self):
dummy_input = T.rand(4, 20, 80) # B x T x D
dummy_input = T.rand(4, 80, 20) # B x D x T
dummy_hidden = [T.rand(2, 4, 128), T.rand(2, 4, 128)]
model = LSTMSpeakerEncoder(input_dim=80, proj_dim=256, lstm_dim=768, num_lstm_layers=3)
# computing d vectors
@@ -34,7 +34,7 @@ class LSTMSpeakerEncoderTests(unittest.TestCase):
assert output.type() == "torch.FloatTensor"
assert abs(assert_diff) < 1e-4, f" [!] output_norm has wrong values - {assert_diff}"
# compute d for a given batch
dummy_input = T.rand(1, 240, 80) # B x T x D
dummy_input = T.rand(1, 80, 240) # B x T x D
output = model.compute_embedding(dummy_input, num_frames=160, num_eval=5)
assert output.shape[0] == 1
assert output.shape[1] == 256
@@ -44,7 +44,7 @@ class LSTMSpeakerEncoderTests(unittest.TestCase):
class ResNetSpeakerEncoderTests(unittest.TestCase):
# pylint: disable=R0201
def test_in_out(self):
dummy_input = T.rand(4, 20, 80) # B x T x D
dummy_input = T.rand(4, 80, 20) # B x D x T
dummy_hidden = [T.rand(2, 4, 128), T.rand(2, 4, 128)]
model = ResNetSpeakerEncoder(input_dim=80, proj_dim=256)
# computing d vectors
@@ -61,7 +61,7 @@ class ResNetSpeakerEncoderTests(unittest.TestCase):
assert output.type() == "torch.FloatTensor"
assert abs(assert_diff) < 1e-4, f" [!] output_norm has wrong values - {assert_diff}"
# compute d for a given batch
dummy_input = T.rand(1, 240, 80) # B x T x D
dummy_input = T.rand(1, 80, 240) # B x D x T
output = model.compute_embedding(dummy_input, num_frames=160, num_eval=10)
assert output.shape[0] == 1
assert output.shape[1] == 256