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update pwgan generator test
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@@ -22,9 +22,9 @@ def test_pwgan_generator():
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use_causal_conv=False,
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upsample_conditional_features=True,
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upsample_factors=[4, 4, 4, 4])
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dummy_c = torch.rand((4, 80, 64))
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dummy_c = torch.rand((2, 80, 5))
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output = model(dummy_c)
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assert np.all(output.shape == (4, 1, 64 * 256))
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assert np.all(output.shape == (2, 1, 5 * 256)), output.shape
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model.remove_weight_norm()
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output = model.inference(dummy_c)
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assert np.all(output.shape == (4, 1, (64 + 4) * 256))
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assert np.all(output.shape == (2, 1, (5 + 4) * 256))
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