It looks to me, like some code is trying to handle a tf-tensor as if it was a np-array. Tensors don't have a shape attribute, since their shape is stored as a more complicated object. If you want to get the information, you are used to from np, you'd have to call my_tensor.get_shape ().as_list ().
31.03.2019 · @Arjun-Arvindakshan Either create a new Keras/TF environment and try your code there or try some of the solutions mentioned above in my previous post or completely move to PyTorch. Since your model looks very small, it should be easier to move to PyTorch rather than experimenting with other solutions. But there should be a logical explanation as to which a …
12.06.2019 · Short description TensorSliceDataset is lacking a lot of attributes to make is usable ('make_initializable_iterator', 'output_shapes', 'make initializable_iterator'...). Environment information Operating System: 18.04 Python version: 3.6...
02.07.2016 · Environment info Operating System: BashOn Windows Installed version of CUDA and cuDNN: (doesnt matter CPU version only) If installed from binary pip package, provide: 0.9.0 If installed from sources, provide the commit hash: Steps to rep...
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27.03.2021 · Turns out I just needed to setup a new Python environment on Anaconda and install Tensorflow and Keras. My existing environment was already setup with these, but various other posts mentioned that doing this can help, and it did.
Used in the notebooks. This layer has basic options for managing text in a Keras model. It transforms a batch of strings (one example = one string) into either a list of token indices (one example = 1D tensor of integer token indices) or a dense representation (one example = 1D tensor of float values representing data about the example's tokens).