image_augmentation.py does not work

[chappy0205]

I added list5 which is written in page.49 to image_augmentation.py.
And I updated train_ds in list1 in page.45 accoridng to page.50.
However, the following error is dumped when I run the updated list1.

TypeError                                 Traceback (most recent call last)
<ipython-input-36-620ad43f4a23> in <module>()
      4     .shuffle(len(train_dataset), reshuffle_each_iteration=True)
      5     .map(lambda image, label: (image_preprocess_with_augment(image), label_preprocess(label)),
----> 6          num_parallel_calls=tf.data.AUTOTUNE)
      7     .batch(BATCH_SIZE)
      8     .prefetch(8)

10 frames
/usr/local/lib/python3.7/dist-packages/tensorflow/python/autograph/impl/api.py in wrapper(*args, **kwargs)
    693       except Exception as e:  # pylint:disable=broad-except
    694         if hasattr(e, 'ag_error_metadata'):
--> 695           raise e.ag_error_metadata.to_exception(e)
    696         else:
    697           raise

TypeError: in user code:

    <ipython-input-36-620ad43f4a23>:5 None  *
        lambda image, label: (image_preprocess_with_augment(image), label_preprocess(label)),
    <ipython-input-13-d6d29bfe65b7>:16 image_preprocess_with_augment  *
        image = image_augmentation.augment(image, AUGMENT_N, AUGMENT_M)
    /content/drive/My Drive/SoftwareDesign/image_augmentation.py:182 augment  *
        image = augment_funcs[j](image, M)
    /content/drive/My Drive/SoftwareDesign/image_augmentation.py:152 sharpness  *
        image = tfa.image.sharpness(image, factor)
    /usr/local/lib/python3.7/dist-packages/tensorflow_addons/image/color_ops.py:138 sharpness  *
        image = _sharpness_image(image, factor=factor)
    /usr/local/lib/python3.7/dist-packages/tensorflow_addons/image/color_ops.py:101 _sharpness_image  *
        kernel = tf.tile(kernel, [1, 1, image_channels, 1])
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/ops/gen_array_ops.py:11532 tile  **
        "Tile", input=input, multiples=multiples, name=name)
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/op_def_library.py:525 _apply_op_helper
        raise err
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/op_def_library.py:515 _apply_op_helper
        preferred_dtype=default_dtype)
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/profiler/trace.py:163 wrapped
        return func(*args, **kwargs)
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/ops.py:1566 convert_to_tensor
        ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/constant_op.py:346 _constant_tensor_conversion_function
        return constant(v, dtype=dtype, name=name)
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/constant_op.py:272 constant
        allow_broadcast=True)
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/constant_op.py:290 _constant_impl
        allow_broadcast=allow_broadcast))
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_util.py:553 make_tensor_proto
        "supported type." % (type(values), values))

    TypeError: Failed to convert object of type <class 'list'> to Tensor. Contents: [1, 1, None, 1]. Consider casting elements to a supported type.

When I use image_preprocess() instead of image_preprocess_with_augment(), the error was not dumped.
I'm sorry that I don't know why image_preprocess_with_augment() dumps the error.
Could you please tell me the reason and how to fix the issue if possible?

[nadare881]

I can't see all of the code in question, but there seems to be an error because of the differences here.

    <ipython-input-13-d6d29bfe65b7>:16 image_preprocess_with_augment  *
        image = image_augmentation.augment(image, AUGMENT_N, AUGMENT_M)

Would you please refer to the code in List 5 on page 49 and try again?

[tosiyuki]

After removing sharpness from augument_funcs in Listing 5, I was able to run it. Is there anything wrong with the sharpness method?

import random
#augument_funcs = [identity, crop_and_resize, shrink_and_pad, rotate, shear_x, shear_y, translate_xy, change_aspect, auto_contrast, contrast, 
#                  brightness, posterize, mean_blur, median_blur, cutout, sharpness]

augument_funcs = [identity, crop_and_resize, shrink_and_pad, rotate, shear_x, shear_y, translate_xy, change_aspect, auto_contrast, contrast, 
                  brightness, posterize, mean_blur, median_blur, cutout]

@tf.function(experimental_relax_shapes=True)
def augument(image, N, M):
    # argumentをシャッフルしてN個選ぶ
    _, ixs = tf.math.top_k(tf.random.uniform([len(augument_funcs)]), k=N)
    for i in range(N):
        for j in range(len(augument_funcs)):
            if ixs[i] == j:
                image = augument_funcs[j](image, M)
                
    image = tf.clip_by_value(image, 0., 255.)
    return image

[nadare881]

@tosiyuki
The sharpness code posted on github is the same as the one that worked in my environment. I think the cause is probably different, so could you create another thread with the error message?

[chappy0205]

@tosiyuki
Thanks a lot for your comment. I also could complete it after removing sharpness.