12.12.2018 · The exception changes to AttributeError: 'BatchDataset' object has no attribute 'ndim'. It's like it isn't able to use datasets. I don't know what model.fit(dataset, ...) is doing. In my version, the first two positional arguments to model.fit(...) are x and y.
This dataset provides samples of shape [[2, 1], [2, 2], [2, 3]] and of type ... Session() as sess: AttributeError: 'BatchDataset' object has no attribute ...
change "train dataset.output shapes" to "tf.compat.v1.data.get output shapes(train_dataset)" output_shapes is deprecated in TF2, you can use the compat.v1 ...
I have filelists to iterate over for 5-fold cross validation: train_filelists = [ "more_56_fold_1_train.txt", "more_56_fold_2_train.txt", "more_56_fold_3_train.txt ...
06.12.2021 · Solution. You can get samples by take () function. It returns an iterable object. So you can get items like this: ds_subset = raw_train_ds.take (10) #returns first 10 batch, if the data has batched for data_batch in ds_subset: #do whatever you want with each batch. or if you want to get examples, not batches:
07.04.2020 · 'Tensor' object has no attribute 'is_initialized' when using tensorflow.keras.backend.shape 4 'Sequential' object has no attribute 'loss' - When I used GridSearchCV to tuning my Keras model
25.04.2019 · dataset object has no attribute 'output_shapes' in tensorflow 2.0 alpha version #28148. gandalflee opened this issue Apr 25, 2019 · 10 comments Assignees. Labels. comp:ops TF 2.0 type:support. Comments. Copy link gandalflee commented Apr 25, 2019. Please make sure that this is a documentation issue.