6 examples of 'torch expand_dims' in Python

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def expand_dims(self, a, axis=-1):
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    return self.xp.expand_dims(a, axis=axis)

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def expand_dims(self, input, axis=None):
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    return np.expand_dims(input, axis=axis)

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def squeeze(self, dim=None):
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    """Return a tensor with all the dimensions of input of size 1 removed.
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    Parameters
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    ----------
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    dim : int, optional
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        The optional dim to remove.
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    Returns
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    -------
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    dragon.vm.torch.Tensor
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        The new tensor.
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    """
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    raise NotImplementedError('Refer torch.ops.tensor.squeeze')

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def unsqueeze3(X):
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    return X.unsqueeze(-1).unsqueeze(-1).unsqueeze(-1)

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def expand_input_dims_for_t2t(t, batched=False):
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    """Expands a plain input tensor for using it in a T2T graph.
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    Args:
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        t: Tensor
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        batched: Whether to expand on the left side
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    Returns:
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      Tensor `t` expanded by 1 dimension on the left and two dimensions
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      on the right.
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    """
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    if not batched:
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        t = tf.expand_dims(t, 0) # Because of batch_size
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    t = tf.expand_dims(t, -1) # Because of modality
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    t = tf.expand_dims(t, -1) # Because of random reason X
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    return t

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def expand_tile_dims(x, depth, axis=1):
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    """Expand and Tile x on axis by depth"""
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    x = tf.expand_dims(x, axis=axis)
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    tile_dims = [1] * x.shape.ndims
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    tile_dims[axis] = depth
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    return tf.tile(x, tile_dims)