# TensorFlow – How to create a numpy ndarray from a tensor

• Last Updated : 01 Aug, 2020

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

To create a numpy array from Tensor, Tensor is converted to a proto tensor first.

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Method Used:

• make_ndarray: This method accepts a TensorProto as input and returns a numpy array with same content as TensorProto.

Example 1:

## Python3

 `# importing the library``import` `tensorflow as tf`` ` `# Initializing Input``value ``=` `tf.constant([``1``, ``15``, ``10``], dtype ``=` `tf.float64)`` ` `# Printing the Input``print``(``"Value: "``, value)`` ` `# Converting Tensor to TensorProto``proto ``=` `tf.make_tensor_proto(value)`` ` `# Generating numpy array``res ``=` `tf.make_ndarray(proto)`` ` `# Printing the resulting numpy array``print``(``"Result: "``, res)`

Output:

```Value:  tf.Tensor([ 1. 15. 10.], shape=(3, ), dtype=float64)
Result:  [ 1. 15. 10.]

```

Example 2: This example uses a Tensor with shape (2, 2) so the shape of resulting array will be (2, 2).

## Python3

 `# importing the library``import` `tensorflow as tf`` ` `# Initializing Input``value ``=` `tf.constant([[``1``, ``2``], [``3``, ``4``]], dtype ``=` `tf.float64)`` ` `# Printing the Input``print``(``"Value: "``, value)`` ` `# Converting Tensor to TensorProto``proto ``=` `tf.make_tensor_proto(value)`` ` `# Generating numpy array``res ``=` `tf.make_ndarray(proto)`` ` `# Printing the resulting numpy array``print``(``"Result: "``, res)`

Output:

```Value:  tf.Tensor(
[[1. 2.]
[3. 4.]], shape=(2, 2), dtype=float64)
Result:  [[1. 2.]
[3. 4.]]

```

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