cf7ed441052a1514bc7747661011944043d95206,inferno/io/transform/generic.py,AsTorchBatch,tensor_function,#AsTorchBatch#Any#,153

Before Change

    def tensor_function(self, tensor):
        assert isinstance(tensor, np.ndarray)
        if self.dimensionality == 3:
            // We"re dealing with a volume. tensor can either be 3D or 4D
            assert tensor.ndim in [3, 4]
            if tensor.ndim == 3 and self.add_channel_axis_if_necessary:
                // Add channel axis
                return torch.from_numpy(tensor[None, ...])
            else:
                // Channel axis is in already
                return torch.from_numpy(tensor)
        elif self.dimensionality == 2:
            // We"re dealing with an image. tensor can either be 2D or 3D
            assert tensor.ndim in [2, 3]
            if tensor.ndim == 2 and self.add_channel_axis_if_necessary:
                // Add channel axis
                return torch.from_numpy(tensor[None, ...])
            else:
                // Channel axis is in already
                return torch.from_numpy(tensor)
        elif self.dimensionality == 1:
            // We"re dealing with a vector - it has to be 1D
            assert tensor.ndim == 1
            return torch.from_numpy(tensor)
        else:
            raise NotImplementedError

After Change

            raise NotImplementedError

    def tensor_function(self, tensor):
        assert isinstance(tensor, (list, np.ndarray)), "Expected numpy array or list, got %s" % type(tensor)
        if isinstance(tensor, np.ndarray):
            return self._to_batch(tensor)
        else:
            return [self._to_batch(elem) for elem in tensor]

Instances