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### `tf.reduce_join(inputs, reduction_indices, keep_dims=None, separator=None, name=None)` {#reduce_join}
Joins a string Tensor across the given dimensions.
Computes the string join across dimensions in the given string Tensor of shape
`[d_0, d_1, ..., d_n-1]`. Returns a new Tensor created by joining the input
strings with the given separator (default: empty string). Negative indices are
counted backwards from the end, with `-1` being equivalent to `n - 1`. Passing
an empty `reduction_indices` joins all strings in linear index order and outputs
a scalar string.
For example:
```
# tensor `a` is [["a", "b"], ["c", "d"]]
tf.reduce_join(a, 0) ==> ["ac", "bd"]
tf.reduce_join(a, 1) ==> ["ab", "cd"]
tf.reduce_join(a, -2) = tf.reduce_join(a, 0) ==> ["ac", "bd"]
tf.reduce_join(a, -1) = tf.reduce_join(a, 1) ==> ["ab", "cd"]
tf.reduce_join(a, 0, keep_dims=True) ==> [["ac", "bd"]]
tf.reduce_join(a, 1, keep_dims=True) ==> [["ab"], ["cd"]]
tf.reduce_join(a, 0, separator=".") ==> ["a.c", "b.d"]
tf.reduce_join(a, [0, 1]) ==> ["acbd"]
tf.reduce_join(a, [1, 0]) ==> ["abcd"]
tf.reduce_join(a, []) ==> ["abcd"]
```
##### Args:
* <b>`inputs`</b>: A `Tensor` of type `string`.
The input to be joined. All reduced indices must have non-zero size.
* <b>`reduction_indices`</b>: A `Tensor` of type `int32`.
The dimensions to reduce over. Dimensions are reduced in the
order specified. If `reduction_indices` has higher rank than `1`, it is
flattened. Omitting `reduction_indices` is equivalent to passing
`[n-1, n-2, ..., 0]`. Negative indices from `-n` to `-1` are supported.
* <b>`keep_dims`</b>: An optional `bool`. Defaults to `False`.
If `True`, retain reduced dimensions with length `1`.
* <b>`separator`</b>: An optional `string`. Defaults to `""`.
The separator to use when joining.
* <b>`name`</b>: A name for the operation (optional).
##### Returns:
A `Tensor` of type `string`.
Has shape equal to that of the input with reduced dimensions removed or
set to `1` depending on `keep_dims`.
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