CODEWITHSUNDEEP
tensorflowkerastensorflow-datasetstf.data.dataset
Olli
Olli

Reputation: 1116

AttributeError: 'Tensor' object has no attribute 'numpy' eager execution is enabled using version 2.4.1

I've been trying to convert a generator I built to a tf.data.dataset. I've come far and now I have something simple like this

def parse_image(filename):
    file = tf.io.read_file(filename) # this will work only with filename as tensor
    image = tf.image.decode_image(file)
    return image

def transform_img(img):
  img = parse_image(img).numpy()
  img = transforms_train(image = img)["image"]
  return img

transform img works as expected when I call it on a filename itself. like:

plt.imshow(transform_img(array_of_filenames[0]))

but when I map it on a dataset

dataset = tf.data.Dataset.from_tensor_slices(array_of_filenames)
dataset = dataset.map(transform_img)

I get the error in the title.

I am doing something silly again aren't I? Thanks for helping!

Upvotes: 0

Views: 746

Answers (1)

Coderji
Coderji

Reputation: 7745

It is not possible to use numpy inside the map function of tensorflow dataset. Otherwise, you need to wrap the function in tf.py_function or tf.numpy_function. So it should look like the following:

dataset = dataset.map(lambda: item: tf.py_function(transform_img, [item], [tf.float32]))

The first argument of py_function is the preprocessing function you want, the second argument is the parameter to pass to the function. The final argument is the dtype of the return of preprocess function. (same applies to tf.numpy_function)

I don't remember reading this in documentation but in a tutorial, you can find it here.

Upvotes: 1

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