ReduceJoin

tensorflow C++ API

tensorflow::ops::ReduceJoin

Joins a string Tensor across the given dimensions.

Summary

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.

For example:

`python

tensora` 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"] ```

Arguments:

• scope: A Scope object
• inputs: The input to be joined. All reduced indices must have non-zero size.
• reduction_indices: 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.

Optional attributes (see Attrs):

• keep_dims: If True, retain reduced dimensions with length 1.
• separator: The separator to use when joining.

Returns :

• Output: Has shape equal to that of the input with reduced dimensions removed or set to 1 depending on keep_dims.

ReduceJoin block

Source link : https://github.com/EXPNUNI/enuSpaceTensorflow/blob/master/enuSpaceTensorflow/tf_string.cpp

Argument:

• Scope scope : A Scope object (A scope is generated automatically each page. A scope is not connected.)
• Input input: connect Input node.
• Input reduction_indices: connect Input node.
• ReduceJoin::Attrs attrs : Input attrs in value. ex) keep_dims_ = false;separator_ =;

Return:

• Output output : Output object of ReduceJoin class object.

Result:

• std::vector(Tensor) product_result : Returned object of executed result by calling session.

Using Method