Tensorflow iterate over tensor

In this Python tutorial, we will study how to iterate over tensor in Python TensorFlow using some examples in python. Moreover, we will also cover these topics.

• Tensorflow iterate over tensor
• TensorFlow iterating over tf.tensor is not allowed
• TensorFlow cannot iterate over a scaler tensor

Python TensorFlow iterate over Tensor

• In this section, we will discuss how to iterate over tensor in Python TensorFlow.
• To iterate through a tensor in Python, we can easily use the for loop method and it will iterate through the tensor directly.
• To iterate over tensor defines that we have to print a new line tensor and also it will return the number of elements in the tensor. This method will actually iterate each value from the tensor and display it on the screen.
• To do this task, first, we will create a tensor by using the tf.constant() function.

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 indicates the constant value and it must be an array shape.
  • dtype: By default, it takes none value and specifies the type of the elements.
  • shape: This is an optional parameter and it indicates the dimension of the tensor.
  • name: This parameter indicates the name of the operation and by default, it takes ‘Const’.

Example:

Let’s take an example and check how to iterate over tensor in Python TensorFlow.

Source Code:

import tensorflow as tf

tensor=tf.constant([16,27,78,99,189])
for tensor in tensor:
    print("Iterate tensor:",tensor)

In the above code first, we have imported the TensorFlow library and then use the tf.constant() function for creating a tensor and within this function, we have assigned the integer values.

After creating a tensor, we have used the for loop method to iterate through the tensor directly. Once you will execute this code the output displays the element-wise tensors.

Here is the Screenshot of the following given code.

Example2: By using the tf.data.iterator() method

In Python, this function is defined to iterator the data by using the for loop method.

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

Source Code:

import tensorflow as tf

tensor = tf.data.Dataset.range(4)
for z in tensor:
  print("Iterate tensor:",z)

In the following given code, we have used the tf.data.Dataset.range() function for creating a tensor and within this function we have set the range value that is 4 and it indicates the how many iterations of tensor display on the Output.

Here is the Output of the following given code.

As you can see in the Screenshot the Output displays the iterate tensor.

Read: TensorFlow Tensor to numpy

TensorFlow iterating over tf.tensor is not allowed

Here we are going to discuss the error “TensorFlow iterating over tf.tensor() is not allowed in Python“. Basically, this error statement comes because we have used the list comprehension method and this method is not supported in graph execution.

Example:

import tensorflow as tf

tens = tf.random.uniform(shape=(2,50, 60, 400))
result = tf.shape(tens)
tens = [tens[0][m][n] - tf.reduce_mean(tens[0][m][n]) for n in tf.range(result[2]) for m in tf.range(result[1])]

In the above code, we have imported the TensorFlow library and then used the tf.random.uniform() function. And within this function, we have described the random shape. After that, we have used the list comprehension method and use the for loop and tf.reduce_mean() function.

Here is the execution of the following given code.

As you can see in the Screenshot the output displays the tf.tensor() is not allowed in graph execution.

Let’s see the solution to this error.

import tensorflow as tf

tens = tf.random.uniform(shape=(2,50, 60, 400))
result = tf.shape(tens)
tens = tens - tf.expand_dims(tf.reduce_mean(tens, axis=3), -1)
print(tens)

In the above example, we have used the tf.expand_dims() function instead of the list comprehension method, and within this function, we have assigned the tf.reduce_mean() function. Once you will execute this code the output displays the shape of the tensor.

Here is the Output of the following given code.

Read: Module ‘TensorFlow’ has no attribute ‘session’

TensorFlow cannot iterate over a scaler tensor

In this section, we will discuss the error “TensorFlow cannot iterate over a scaler “tensor” in Python. Basically, this error statement comes when we have used the scaler value in the tf.constant() function for creating a tensor.

Example:

import tensorflow as tf

tensor=tf.constant(1)
for tensor in tensor:
    print("Iterate tensor:",tensor)

In the above code we have imported the TensorFlow library and then used the tf.constant() function and within this function, we have set the ‘1’ as a scaler value and then iterate a tensor by using the for loop method.

Here is the Screenshot of the following given code.

As you can see in the Screenshot the output displays the cannot iterate over a scaler tensor.

Let’s see the solution to this error.

Example:

import tensorflow as tf

tensor=tf.constant([27,34,67,89])
for tensor in tensor:
    print("Iterate tensor:",tensor)

In the following given code we have imported the TensorFlow library and then use the tf.constant() function for creating a tensor and within this function, we have assigned the values in list and iterate through the tensor.

Here is the implementation of the following given code

You may also like to read the following TensorFlow tutorials.

• Python TensorFlow reduce_mean
• TensorFlow mean squared error
• Python TensorFlow reduce_sum
• Python TensorFlow Placeholder
• TensorFlow mean squared error
• TensorFlow clip_by_value

In this Python tutorial, we have learned how to iterate over tensor in Python TensorFlow using some examples in python. Moreover, we have covered these topics.

• Tensorflow iterate over tensor
• TensorFlow iterating over tf.tensor is not allowed
• TensorFlow cannot iterate over a scaler tensor