# How to Calculate Square Root of Tensors in TensorFlow?

In TensorFlow 2.0 Python Tutorial, We will Learn about the TensorFlow Math Module tf.sqrt() function. We will learn how to calculate the square root of tensors in TensorFlow using tf.sqrt() function.

tf.sqrt() : Calculate Element wise square root of numpy array and TF tensor,
It can be give sqrt of list, tuple, scaler
It allow tf variable/constant/placeholder/SparceMatrix with Specific datatype

Data Type : bfloat16, half, float32, float64, complex64, complex128.

Note: Don’t give ‘int’ data type, tf.sqrt() will through error

Syntax: tf.sqrt(x, name=None)

## Calculate the Square Root using TensorFlow

```import tensorflow as tf
import numpy as np
```

### Square Root of Scaler

```a = 9.0
tf.sqrt(a)
```

### Square Root of List

```l1 = [4.0,9.0,16.0]

tf.sqrt(l1)
```

### Square Root of Tuple

```t1 = (4.0,9.0,16.0)

tf.sqrt(t1)
```

### Square Root of Numpy Array

```npa1 = np.array([4,9,16], dtype = np.float64)

tf.sqrt(npa1)
```
```y = np.ones(6).reshape(2, 1, 3, 1)*4
print("Y: " , y)
tf.sqrt(y)
```

### Square Root of TensorFlow Tensor

```tf.sqrt(tf.convert_to_tensor(4, dtype='float')) # using scaler value
```
```tf.sqrt(tf.convert_to_tensor([4,9,16], dtype='float')) # using list
```

### Square Root of TF Constant Tensor

```tf_ct1 = tf.constant([4,9,16], dtype='float')

tf.sqrt(tf_ct1)
```

### Square Root of TF Variable

```tf_vr1 = tf.Variable([4,9,16], dtype='half')

tf.sqrt(tf_vr1)
```
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