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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`.
+