TypeError: 'dict_keys' object is not subscriptable (Python) This object lets you convert values to a particular data type, … Inside the class, the __getitem__ method is used to overload the object to make them compatible for accessing elements. 2) The error is indicating that the function or method is not subscriptable; means they are not indexable like a list or sequence. return func (device, token, args) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/ops/script_ops. dataset [0] >>> TypeError: 'TensorSliceDataset' object does not support indexing list (dataset. I suppose it is due to the type of the dataset given to the Trainer (TensorSliceDataset), but I can't figure out what should be the structure and type of the dataset that I should use for language translation. In Python, everything can be seen as an object and one of the ways of creating objects in python is via ‘Class’. 「not subscriptable」は、添字不可という意味で解釈できますが、「subscript」は添字を意味し、「subscription」は添字表記を意味します。. How to Solve TypeError: ‘int’ object is not Subscriptable This is because iterable objects contain a list of objects. You cannot retrieve items from a None value using the subscript operator. static TensorSliceDataset. For example, lists, dictionaries, tuples are all subscriptable objects. For instance, take a look at the following code. We can … Typeerror: type object is not subscriptable ( Steps to Fix) What is ‘int’ object is not subscriptable? The string data type represents an individual or set of characters. 301 TypeError: 'type' object is not subscriptable Tensorflow can be imported. When you define temp_set = {1, 2, 3} it just implies that temp_set contains 3 elements but there's no index that can be obtained 43 py_typecheck.check_type (path, (str, os.PathLike)) TypeError: 'ABCMeta' object is not subscriptable. When we try to concatenate string and integer values, this message tells us that we treat an integer as a subscriptable object. attributeerror: 'tensorslicedataset' object has no attribute 'shape Reproduction instructions randt = tf.random.uniform ( [2000, 80, 5]) dataset = tf.data.Dataset.from_tensor_slices (randt) dataset.batch (20) iter = dataset.make_one_shot_iterator () Link to logs AttributeError: 'TensorSliceDataset' object has no attribute 'make_one_shot_iterator' jackshi0912 closed this as completed on Jun 13, 2019 The API does not support random access, which leads to some major issues trying to implement some common machine learning workflows. 'TensorSliceDataset' object has no attribute {'make Floating-point numbers, like integers, are not iterable objects. Accordingly, sets do not support indexing, slicing, or other sequence-like behavior.