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# Python – tensorflow.concat()

• Last Updated : 26 Jun, 2020

TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning  neural networks.

concat() is used to concatenate tensors along one dimension.

Syntax: tensorflow.concat( values, axis, name )

Parameter:

• values: It is a tensor or list of tensor.
• axis: It is 0-D tensor which represents dimension to concatenate.
• name(optional): It defines the name for the operation.

Returns: It returns the concatenated Tensor.

Example 1:

## Python3

 `# Importing the library``import` `tensorflow as tf`` ` `# Initializing the input tensor``t1 ``=` `[[[``1``, ``2``], [``3``, ``4``]], [[``5``, ``6``], [``7``, ``8``]]]``t2 ``=` `[[[``7``, ``4``], [``8``, ``4``]], [[``2``, ``10``], [``15``, ``11``]]]`` ` ` ` `# Printing the input tensor``print``(``'t1: '``, t1)``print``(``'t2: '``, t2)`` ` `# Calculating result``res ``=` `tf.concat([t1, t2], ``2``)`` ` `# Printing the result``print``(``'Result: '``, res)`

Output:

```t1:  [[[1, 2], [3, 4]], [[5, 6], [7, 8]]]
t2:  [[[7, 4], [8, 4]], [[2, 10], [15, 11]]]
Result:  tf.Tensor(
[[[ 1  2  7  4]
[ 3  4  8  4]]

[[ 5  6  2 10]
[ 7  8 15 11]]], shape=(2, 2, 4), dtype=int32)

```

Example 2:

## Python3

 `# Importing the library``import` `tensorflow as tf`` ` `# Initializing the input tensor``t1 ``=` `[[[``1``, ``2``], [``3``, ``4``]], [[``5``, ``6``], [``7``, ``8``]]]``t2 ``=` `[[[``7``, ``4``], [``8``, ``4``]], [[``2``, ``10``], [``15``, ``11``]]]`` ` ` ` `# Printing the input tensor``print``(``'t1: '``, t1)``print``(``'t2: '``, t2)`` ` `# Calculating result``res ``=` `tf.concat([t1, t2], ``1``)`` ` `# Printing the result``print``(``'Result: '``, res)`

Output:

```t1:  [[[1, 2], [3, 4]], [[5, 6], [7, 8]]]
t2:  [[[7, 4], [8, 4]], [[2, 10], [15, 11]]]
Result:  tf.Tensor(
[[[ 1  2]
[ 3  4]
[ 7  4]
[ 8  4]]

[[ 5  6]
[ 7  8]
[ 2 10]
[15 11]]], shape=(2, 4, 2), dtype=int32)

```

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