iterator is necessary when you use multiple trainset alternatively for training. for example, training mtcnn requires both wider face and celeba. you have to use iterator rather than a loop. but I have solved the problem buy tf.data.Dataset.iter()
Oct 20, 2019 · gowthamkpr changed the title [TF 2.0] reeatdataset has no attribute 'make_one_shot_iterator' [TF 2.0] repeatdataset has no attribute 'make_one_shot_iterator' Oct 21, 2019 gowthamkpr self-assigned this Oct 21, 2019
[TF 2.0] Dataset has no attribute ‘make_one_shot_iterator’ Fantashit May 5, 2020 7 Comments on [TF 2.0] Dataset has no attribute ‘make_one_shot_iterator’ Please make sure that this is a bug.
'FlatMapDataset' object has no attribute 'make_one_shot_iterator #3. Trying to go though the examples in the documentation, I ran into this error with ...
01.06.2019 · AttributeError: 'BatchDataset' object has no attribute 'make_one_shot_iterator' Describe the expected behavior. Code to reproduce the issue. from __future__ import absolute_import, division, print_function, ...
13.12.2018 · These notes for Keras 2.2.0 say this: With Keras 2.2.0 and TensorFlow 1.8 or higher, you may fit, evaluate and predict using symbolic TensorFlow tensors. The tutorial's version is prior to this, so support for tensorflow datasets was obviously prior. Better support for training models from data tensors in TensorFlow (e.g. Datasets, TFRecords).
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20.10.2019 · As per Release 2.0.0-alpha0, tf.data.Dataset.make_one_shot_iterator() has been deprecate in V1, removed from V2, and added to tf.compat.v1.data.make_one_shot_iterator().
AttributeError: 'BatchDataset' object has no attribute 'make_one_shot_iterator' Describe the expected behavior. Code to reproduce the issue. from __future__ import absolute_import, division, print_function, ...