TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks.
convert_to_tensor() is used to convert the given value to a Tensor
Syntax: tensorflow.convert_to_tensor( value, dtype, dtype_hint, name )
Parameters:
- value: It is the value that needed to be converted to Tensor.
- dtype(optional): It defines the type of the output Tensor.
- dtype_hint(optional): It is used when dtype is None. In some cases, a caller may not have a dtype in mind when converting to a tensor, so dtype_hint can be used as a soft preference. If the conversion to dtype_hint is not possible, this argument has no effect.
- name(optional): It defines the name for the operation.
Returns: It returns a Tensor.
Example 1: From Python list
Python3
# Importing the libraryimport tensorflow as tf# Initializing the inputl = [1, 2, 3, 4]# Printing the inputprint('l: ', l)# Calculating resultx = tf.convert_to_tensor(l)# Printing the resultprint('x: ', x) |
Output:
l: [1, 2, 3, 4] x: tf.Tensor([1 2 3 4], shape=(4, ), dtype=int32)
Example 2: From Python tuple
Python3
# Importing the libraryimport tensorflow as tf# Initializing the inputl = (1, 2, 3, 4)# Printing the inputprint('l: ', l)# Calculating resultx = tf.convert_to_tensor(l, dtype = tf.float64)# Printing the resultprint('x: ', x) |
Output:
l: (1, 2, 3, 4) x: tf.Tensor([1. 2. 3. 4.], shape=(4, ), dtype=float64)
