What you can and cannot do with Tensorflow 2.x.
Tensorflow vstack how to#
Output: (, b'B')īased on this solution: ( How to convert a Numpy 2D array with object dtype to a regular 2D array of floats ) if we convert the mixed object type to same (with np.vstack), it works. I couldnt do it with hstack or vstack, so I did it as follows. The Autoencoder dataset is already split between 50000 images for training and 10000 for testing. You will use the CIFAR-10 dataset which contains 60000 32×32 color images. Iterator = dataset.make_initializable_iterator() How to Build an Autoencoder with TensorFlow In this tutorial, you will learn how to build a stacked autoencoder to reconstruct an image.
Asking for help, clarification, or responding to other answers. Without literal_eval the code seems to work, as each of the features are string and not of mixed type: train = pd.read_csv("train.csv", names=CSV_COLUMN_NAMES, header=0, delimiter=",")įeatures,labels = train,train.pop('type')ĭataset = tf._tensor_slices((dict(Features), labels)) Thanks for contributing an answer to Stack Overflow Please be sure to answer the question.Provide details and share your research But avoid. TF can automatically create a tensor from a data frame as long as it has only one data type, in this case it seems to have different data types.
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