Python – tensorflow.convert_to_tensor()
Last Updated :
06 Mar, 2023
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
import tensorflow as tf
l = [ 1 , 2 , 3 , 4 ]
print ( 'l: ' , l)
x = tf.convert_to_tensor(l)
print ( 'x: ' , x)
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Output:
l: [1, 2, 3, 4]
x: tf.Tensor([1 2 3 4], shape=(4, ), dtype=int32)
Example 2: From Python tuple
Python3
import tensorflow as tf
l = ( 1 , 2 , 3 , 4 )
print ( 'l: ' , l)
x = tf.convert_to_tensor(l, dtype = tf.float64)
print ( 'x: ' , x)
|
Output:
l: (1, 2, 3, 4)
x: tf.Tensor([1. 2. 3. 4.], shape=(4, ), dtype=float64)
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