deeplake: [BUG] Having issues with training a dataset using tensorflow
ππ Bug Report
βοΈ Current Behavior
I am trying to train an autoencoder model, but running into issues getting it working with TensorFlow
Input Code
- REPL or Repo link if applicable:
foo = view.tensorflow(tensors=['input', 'output'])
history = autoencoder.fit(
x=foo,
epochs=epochs,
batch_size=128,
verbose=0,
callbacks=callbacks
)
βοΈ Environment
Python
version(s):- 3.9.10
OS
: Windows 10IDE
: Jupyter NotebookPackages
: [Tensorflow==2.6.0 - latest
]
About this issue
- Original URL
- State: closed
- Created a year ago
- Comments: 16 (7 by maintainers)
Hey, sorry for the late response. I was refering to tf.Dataset.prefetch(). I can see why the implementation would be so slow if thatβs the underlying implementation.
Thanks for all the help! I love your stuff and am excited to see if I can get a better performance from pytorch
@v2thegreat Thanks for the minimal repro script, will look into it.
Alright! I got the minimal example here:
Please let me know if you have any questions!
I donβt think that itβs an issue with the name. I call my images
input
while I was testing deeplake, and the model is calling its first layerinput
because Iβm using an input layer in tensorflow.I tried what you provided and I got the same issue. Iβll write the minimal example in a few