tensorflow2 how to print tensor value - numpy

Question

I try to print the actual value of the tensor which is loaded from my custom tfds dataset.
I can't figure out how to do it. I am using Tensorflow2 so the session is no longer encouraged.
I tried using .numpy() tf.print. tf.executing.eagerly() but nothing works. It either prints
just the tensor object showing me the shape or in case of .numpy() it throws the error in the title.
I need the value of tensors and I need to bring it back to numpy in order to debugg the code.
This is how I create the dataset:
class dt(tfds.core.GeneratorBasedBuilder):
''' Dataset builder'''
# DOuble check
VERSION = tfds.core.Version('1.0.0')
RELEASE_NOTES = {
'1.0.0': 'Initial release.',
}
def _info(self) ->tfds.core.DatasetInfo:
'''Dataset metadata'''
return tfds.core.DatasetInfo(
builder=self,
features=tfds.features.FeaturesDict({
"id": tf.int64,
"image": tfds.features.Image(shape=(IMG_HEIGHT, IMG_WIDTH, IMG_CHANNELS), encoding_format='png'),
"mask": tfds.features.Image(shape=(IMG_HEIGHT, IMG_WIDTH, 1), encoding_format='png'),
"label": tfds.features.ClassLabel(names=CLASSES),
}),
supervised_keys=('image', 'mask')
)
def _split_generators(self, dl_manager: tfds.download.DownloadManager):
'''Splitgenerator for train and test splits'''
path = DATASETS_ROOT
return {
"train": self._generate_examples(
images_path=os.path.join(path, "train/rgb"),
masks_path=os.path.join(path, "train/masks")
),
"test": self._generate_examples(
images_path=os.path.join(path, "test/rgb"),
masks_path=os.path.join(path, "test/masks")
)
}
def _generate_examples(self, images_path, masks_path):
'''Generator of examples for each split'''
for i, (image, mask) in enumerate(zip(glob.glob(images_path + "/*.png"), glob.glob(masks_path + "/*.png"))):
yield i, {
"id": i,
"image": image,
"mask": mask,
"label": CLASSES[3],
}
This is how I try to extract the numpy array
def custom_load_X_Y(training=True):
if training:
dt, dt_info = tfds.load("dt", split="train", shuffle_files=True, as_supervised=True, with_info=True)
print(f'EAGERLY {tf.executing_eagerly()}')
print(f'MOde type {type(dt)}')
tf.print(f"aaaaa {dt.numpy()} aaaaaa")
Console output:
Console output

Answer 1

You can print the image dataset by using tfds.show_examples()
import tensorflow_datasets as tfds
ds, ds_info = tfds.load('cifar10', split='train', with_info=True)
fig = tfds.show_examples(ds, ds_info)
output:
For more details please refer to this gist.Thank You.