# tf.compat.v1.expand_dims

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.13.1/tensorflow/python/ops/array_ops.py#L312-L382) |

Returns a tensor with a length 1 axis inserted at index `axis`. (deprecated arguments)

    tf.compat.v1.expand_dims(
        input, axis=None, name=None, dim=None
    )

> [!WARNING]
> **Deprecated:** SOME ARGUMENTS ARE DEPRECATED: `(dim)`. They will be removed in a future version. Instructions for updating: Use the `axis` argument instead

Given a tensor `input`, this operation inserts a dimension of length 1 at the
dimension index `axis` of `input`'s shape. The dimension index follows Python
indexing rules: It's zero-based, a negative index it is counted backward
from the end.

This operation is useful to:

- Add an outer "batch" dimension to a single element.
- Align axes for broadcasting.
- To add an inner vector length axis to a tensor of scalars.

#### For example:

If you have a single image of shape `[height, width, channels]`:

    image = tf.zeros([10,10,3])

You can add an outer `batch` axis by passing `axis=0`:

    tf.expand_dims(image, axis=0).shape.as_list()
    [1, 10, 10, 3]

The new axis location matches Python `list.insert(axis, 1)`:

    tf.expand_dims(image, axis=1).shape.as_list()
    [10, 1, 10, 3]

Following standard Python indexing rules, a negative `axis` counts from the
end so `axis=-1` adds an inner most dimension:

    tf.expand_dims(image, -1).shape.as_list()
    [10, 10, 3, 1]

This operation requires that `axis` is a valid index for `input.shape`,
following Python indexing rules:

    -1-tf.rank(input) <= axis <= tf.rank(input)

This operation is related to:

- [`tf.squeeze`](https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/squeeze), which removes dimensions of size 1.
- [`tf.reshape`](https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/reshape), which provides more flexible reshaping capability.
- [`tf.sparse.expand_dims`](https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/sparse/expand_dims), which provides this functionality for [`tf.SparseTensor`](https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/sparse/SparseTensor)

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| ## Args ||
|---|---|
| `input` | A `Tensor`. |
| `axis` | 0-D (scalar). Specifies the dimension index at which to expand the shape of `input`. Must be in the range `[-rank(input) - 1, rank(input)]`. |
| `name` | The name of the output `Tensor` (optional). |
| `dim` | 0-D (scalar). Equivalent to `axis`, to be deprecated. |

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| ## Returns ||
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| A `Tensor` with the same data as `input`, but its shape has an additional dimension of size 1 added. ||

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| ## Raises ||
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| `ValueError` | if either both or neither of `dim` and `axis` are specified. |

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