jukebox/prior/autoregressive.py [204:218]:
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        N, D = n_samples, self.input_dims
        if self.y_cond:
            assert y_cond is not None
            assert y_cond.shape == (N, 1, self.width)
        else:
            assert y_cond is None

        if self.x_cond:
            assert x_cond is not None
            assert x_cond.shape == (N, D, self.width) or x_cond.shape == (N, 1, self.width), f"Got {x_cond.shape}, expected ({N}, {D}/{1}, {self.width})"
        else:
            assert x_cond is None
            x_cond = t.zeros((N, 1, self.width), dtype=t.float).cuda()

        with t.no_grad():
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jukebox/prior/autoregressive.py [266:280]:
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        N, D = n_samples, self.input_dims
        if self.y_cond:
            assert y_cond is not None
            assert y_cond.shape == (N, 1, self.width)
        else:
            assert y_cond is None

        if self.x_cond:
            assert x_cond is not None
            assert x_cond.shape == (N, D, self.width) or x_cond.shape == (N, 1, self.width), f"Got {x_cond.shape}, expected ({N}, {D}/{1}, {self.width})"
        else:
            assert x_cond is None
            x_cond = t.zeros((N, 1, self.width), dtype=t.float).cuda()

        with t.no_grad():
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