I know dataset has output_shapes, but it shows like below: data_set: DatasetV1Adapter shapes: {item_id_hist: (?, ?), tags: (?, ?), client_platform: (?,), en
I want to use tf.data.Dataset.list_files function to feed my datasets. But because the file is not image, I need to load it manually. The problem is tf.data.Dat
I am following the Google Machine Learning Intensive Course. But it uses version 1.x of TensorFlow, so I was planning to change the exercises to be able to run
I am following the Google Machine Learning Intensive Course. But it uses version 1.x of TensorFlow, so I was planning to change the exercises to be able to run
I have a simple code, which DOES work, for training a Keras model in Tensorflow using numpy arrays as features and labels. If I then wrap these numpy arrays usi
I have a large list of numpy arrays that I want to feed into a TensorFlow model. I can not concatenate the lists into one due to RAM memory issues. Below, I hav
I have list of labels corresponding numbers of files in directory example: [1,2,3] train_ds = tf.keras.utils.image_dataset_from_directory( train_path, label
I'm trying to build a simple word generator. However, I encounter some difficulty with the sliding windows. here is my actual code: files = glob("transfdata/*")
I used tfds.load to load Cityscapes dataset. The tf.data.Dataset object is enumerable and returns a dict for each enumeration. I added another value to each dic
I am trying to write a Custom Model in which I am writing a custom train_step function I am creating a 'tf.data.Dataset` from a Custom Datagenerator like tds =
I try to Importing Data I try to load a tfrecords dataset that I created. But I always get this Error. Here is the code: import tensorflow as tf EPOCHS = 10 BA
I am using file_data = tf.data.Dataset.list_files("../*.png") to collect image files for training in TensorFlow, but would like to access the list of gathere
I have a problem to load data using tfds. When I try to load the data I got the following error. ValueError: GCS bucket inaccessible To solve the problem I u