Attributeerror: Module ‘tensorflow’ has no attribute ‘sparse_tensor_to_dense’

In this TensorFlow tutorial, I will show how to fix the error Attributeerror: Module ‘tensorflow’ has no attribute ‘sparse_tensor_to_dense’.

I got this error when I upgraded my tensorflow to the latest version and ran my project. So here I will explain what this error means and the method you can use to solve this error.

By the end of this tutorial, you will be able to solve this kind of error smoothly.

Attributeerror: Module ‘tensorflow’ has no attribute ‘sparse_tensor_to_dense’

The error means you are trying to access the sparse_tensor_to_dense function in the TensorFlow module, but it doesn’t exist, or TensorFlow doesn’t find this function within its module.

First, let me show you how this error can occur.

import tensorflow as tf

input_tensor = tf.sparse_tensor_to_dense(dense_shape=[2, 2],values=[67, 18, 14],indices =[[1, 0],[0, 3],[2, 0]])
print(input_tensor)
Attributeerror Module 'tensorflow' has no attribute 'sparse_tensor_to_dense'

You get the error because you are trying to access the sparse_tensor_to_dense() function.

Here, I want to tell you that you made a mistake while calling the function, and the mistake is that you specified the wrong name of the function; it should be the sparse_to_dense() function.

So, the first solution is to change the function to sparse_to_dense(), as shown below.

import tensorflow as tf

input_tensor = tf.sparse_to_dense(dense_shape=[2, 2],values=[67, 18, 14],indices =[[1, 0],[0, 3],[2, 0]])
print(input_tensor)
Fixed Function Name in Attributeerror Module 'tensorflow' has no attribute 'sparse_tensor_to_dense'

Unfortunately, you again get the error ‘AttributeError: module ‘tensorflow’ has no attribute ‘sparse_to_dense”. But don’t worry, you have written everything correctly; there is a small issue: the tensorflow version you are using.

So that means the above code is compatible with Tensorflow version 1.x, but here, you may have updated your tensorflow version 2.x and are using the code compatible only with Tensorflow version 1.x.

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Here is the solution: import tensorflow.compat.v1 module to use sparse_to_dense() function, the complete syntax is given below.

tf.compat.v1.sparse_to_dense(
    sparse_indices,
    output_shape,
    sparse_values,
    default_value=0,
    validate_indices=True,
    name=None
)

Where parameters are:

  • sparse_indices: a tensor of type int32 or int64 that is one and two-dimensional. The whole index where sparse values[i] will be stored is contained in the sparse indices[i] array.
  • output_shape: It defines the shape of the dense output tensor.
  • sparse_values: It is used for all sparse indices.
  • default_value: It defines the same type as sparse values, a 0-D Tensor. For indices not listed in sparse indices, a value should be set. Zero is the default.
  • validate_indices: By default, it takes the true value and will check the condition. If true, the indices are checked to ensure they are sorted.

Let’s take an example where we will create a sparse tensor and convert this tensor to a dense tensor using the tensorflow. compact.v1.sparse_to_dense() function.

import tensorflow.compat.v1 as tf

input_tensor = tf.sparse.SparseTensor(indices=[[1, 0], [1, 1], [0, 1], [3, 0], [2, 1]],
                                      values=[45, 20, 24, 19, 25],
                                      dense_shape=[5, 4])

new_input = tf.constant([90, 80, 60, 17, 2])
inputs = [new_input, input_tensor]


input_tensor_reordered = tf.sparse.reorder(input_tensor)

result = tf.compat.v1.sparse_to_dense(sparse_indices=input_tensor_reordered.indices,
                                      output_shape=input_tensor_reordered.dense_shape,
                                      default_value=0,
                                      sparse_values=input_tensor_reordered.values)

print("sparse_dense:", result)
Second Solution Attributeerror Module 'tensorflow' has no attribute 'sparse_tensor_to_dense'

In the above code, we first created a sparse tensor using the tf.sparse.SparseTensor(), and within this function, we assigned the values and dense_shape() as an argument.

Then, we reorder the input_tensor using the tf.sparse.reorder() function. Next, we used the tf.compat.v1.sparse_to_dense() function to get the dense tensor. As a result, you can see the dense tensor.

Lastly, you can use the to_dense() function from the tensorflow.sparse module in the latest version of tensorflow.

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For example, run the below code.

import tensorflow as tf

input_tensor = tf.sparse.SparseTensor(indices=[[1, 0], [1, 1], [0, 1], [3, 0], [2, 1]],
                                      values=[45, 20, 24, 19, 25],
                                      dense_shape=[5, 4])

new_input = tf.constant([90, 80, 60, 17, 2])
inputs = [new_input, input_tensor]

input_tensor_reordered = tf.sparse.reorder(input_tensor)

result = tf.sparse.to_dense(sp_input=input_tensor_reordered)

print("sparse_dense:", result)
Third Solution Attributeerror Module 'tensorflow' has no attribute 'sparse_tensor_to_dense'

Here, the function to_dense is used from the submodule tf.sparse in the latest version of tensorflow.

This is how you can fix the error Attributeerror: Module ‘tensorflow’ has no attribute ‘sparse_tensor_to_dense’.

Conclusion

You learned how to resolve the error Attributeerror: Module ‘tensorflow’ has no attribute ‘sparse_tensor_to_dense’.

To solve this error, you learned that compatibility mode can be used where you have access function of the older tensorflow library version.

Also, you learned how to solve this error in the latest version of tensorflow by accessing the to_dense() function from the tf.sparse module.

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