tf.reduce_join()

tf.reduce_join(inputs, reduction_indices, keep_dims=None, separator=None, name=None)

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:

• inputs: A Tensor of type string. The input to be joined. All reduced indices must have non-zero size.
• reduction_indices: A Tensor of type int32. The dimensions to reduce over. Dimensions are reduced in the order specified. Omitting reduction_indices is equivalent to passing [n-1, n-2, ..., 0]. Negative indices from -n to -1 are supported.
• keep_dims: An optional bool. Defaults to False. If True, retain reduced dimensions with length 1.
• separator: An optional string. Defaults to "". The separator to use when joining.
• name: 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.