Tensorflow get static value

In this Python tutorial, we will learn how to get the static value in Python TensorFlow. Also, we will cover the following topics.

• Tensorflow get static value
• TensorFlow get the index of the value
• Tensorflow get value from the tf variable
• TensorFlow get a constant tensor value
• module ‘TensorFlow’ has no attribute ‘get static value’

TensorFlow get static value

• In this section, we will discuss how to get the static value in Python TensorFlow.
• To perform this particular task, we are going to use the tf.get_static_value() function and this function is used to display the constant value from the input tensor.
• In TensorFlow, static values mean constant values and if the static value cannot be measured then it will return none value.

Syntax:

Let’s have a look at the Syntax and understand the working of the tf.get_static_value() function in Python TensorFlow.

tf.get_static_value(
                    tensor,
                    partial=False
                   )

• It consists of a few parameters.
  • tensor: This parameter specifies the input tensor.
  • partial: By default, it takes a false value and if it is true then it will return an array that is partially evaluated and the values cannot be evaluated if it is none.

Return: This method returns the NumPy n-dimensional array and the values will be constant.

Example:

Let’s take an example and check how to get the static value in Python TensorFlow.

Source Code:

import tensorflow as tf

new_tens = tf.constant([[45, 26, 16], [22, 18, 29], [13, 28, 90]])
new_output = tf.get_static_value(new_tens)
print("Static value:",new_output)

In the following given code, we have created the input tensor by using the tf.constant() function and then used the tf.get_static_value() function and pass the input tensor variable ‘new_tens’ as an argument.

Here is the Screenshot of the following given code.

Read: TensorFlow next_batch + Examples

TensorFlow get the index of the value

• Here we are going to understand how to get the index of the value in Python TensorFlow.
• By using the tf. where() function, we can easily get the index of value. This function will help the user to get the indices of multiplexes of y and x.
• This function returns the values either it is from the second input tensor or the first tensor based on the given condition.

Syntax:

Here is the Syntax of tf.where() function in Python TensorFlow.

tf.where(
        condition,
        x=None, 
        y=None, 
        name=None
)

• It consists of a few parameter
  • conditions: This parameter specifies the condition and it must be a dtype bool or integer value.
  • x and y: if it is given then an input tensor that is of the same type has a shape permit with condition and y.
  • name: By default, it takes no value and specifies the name of the operation.

Returns: This method will return the tensor of values.

Example:

Let’s take an example and check how to get the index of the value in Python TensorFlow.

Source Code:

import tensorflow as tf

m = tf.constant([False, False, True, True])  
 
result= tf.where(m).numpy()
print("Get index of value:",result)

• First, we will import the TensorFlow library and then created an input tensor by using the tf.constant() function.
• And within this function, we assigned the boolean values as an argument.
• After that, we have used the tf.where() function to get the index value from the tensor.

Here is the implementation of the following given code.

Read: Gradient descent optimizer TensorFlow

TensorFlow get value from tf.variable()

• In this example, we are going to discuss how to get the value from the tf.variable() function in Python TensorFlow.
• To do this task, we are going to use the tf.variable() function as an input tensor and get the values from arguments.
• In Python Tensorflow, the variables are used to store the parameters or values and the values are constantly modified during training.

Example:

import tensorflow as tf

tf.compat.v1.disable_eager_execution()
new_tensor = tf.Variable([167, 876,567])
tens_init = tf.compat.v1.global_variables_initializer()
with tf.compat.v1.Session() as val:
    val.run(tens_init)
    new_output=val.run(new_tensor)
    print(new_output)

In the following given code, we have created the tf.compat.v1.global_variables_initializer() function and run the session by using the tf.compat.v1.Session() function. Once you will execute this code the output displays the values from the input tensor.

You can refer to the below Screenshot.

Read: Binary Cross Entropy TensorFlow

TensorFlow get a constant tensor value

• In this section, we will discuss how to get a constant tensor value in Python TensorFlow.
• To perform this particular task, we are going to use the tf.constant() function to get the constant values from the input tensor.
• This function is used to declare a constant tensor from a given object.

Syntax:

Here is the Syntax of tf.constant() function in Python TensorFlow

tf.constant(
            value, 
            dtype=None, 
            shape=None, 
            name='Const'
           )

• It consists of a few parameters
  • value: This parameter specifies the values which we want to convert into the tensor.
  • dtype: By default, it takes none values and it defines the type of the output tensor.
  • shape: It specifies the dimension of the resulting tensor.
  • name: By default, it takes const value and specifies the name of the tensor.

Example:

Let’s take an example and check how to get a constant tensor value in Python TensorFlow.

Source Code:

import tensorflow as tf

tf.compat.v1.disable_eager_execution()
new_tensor = tf.constant([34, 29,134,178])
get_val = tf.compat.v1.global_variables_initializer()
with tf.compat.v1.Session() as val:
    val.run(get_val)
    new_output=val.run(new_tensor)
    print(new_output)

Here is the Screenshot of the following given code.

Read: Tensorflow embedding_lookup

Module ‘TensorFlow’ has no attribute ‘get static value’

Here we are going to discuss the error module ‘TensorFlow’ has no attribute ‘get static value’.

Reason: In the old version 1.x, the tf.get static value has been removed and if you are using the latest version of TensorFlow then it works in complex programs.

Example:

import tensorflow as tf

new_tens = tf.constant([[15, 27, 45], [109, 278, 145], [234, 189, 289]])
new_output = tf.get_static_value(new_tens)
print("Static value:",new_output)

Here is the implementation of the following given code.

Solution:

Here is the solution to this error.

In this example, we are going to use the TensorFlow 2.x version.

import tensorflow as tf

new_tens = tf.constant([[15, 27, 45], [109, 278, 145], [234, 189, 289]])
new_output = tf.get_static_value(new_tens)
print("Static value:",new_output)

In the above code, we have imported the TensorFlow library and then created an input tensor by using the tf.constant() function. After that, we used the tf.get_static_value() and assigned the input tensor as an argument. Once you will execute this code the output displays the constant value from the given tensor.

Here is the Output of the following given code.

You may also like to read the following TensorFlow tutorials.

• Batch Normalization TensorFlow
• TensorFlow Natural Language Processing
• TensorFlow clip_by_value – Complete tutorial
• TensorFlow Multiplication – Helpful Guide
• Python TensorFlow random uniform
• Import error no module named TensorFlow

In this Python tutorial, we have learned how to get the static value in Python TensorFlow. Also, we have covered the following topics.

• Tensorflow get static value
• TensorFlow get the index of the value
• TensorFlowget value from the tf variable
• TensorFlow get a constant tensor value
• Module ‘TensorFlow’ has no attribute ‘get static value’