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I have got a training dataset of 1,000 images but while compiling my code, I came across this error;
Error: ValueError: Empty training data?
What's the possible solution? Thanks
The issue is that there is no validation or test dataset in your directory. Ensure you have data in your validation directory.
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I have a DEM ESRI ASCII raster file that I am trying to run a 2D model with on Flood Modeller software but I keep getting an error that it cannot read the NCOLS.
I have tried to open the file in Python but I get an error saying could not convert string to float.Images show Python error and Flood Modeller log file](https://i.stack.imgur.com/mVoud.jpg)
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Having a df of data, doing:
fig=px.line(df, x='date', y='px', color='description')
The following graph is rendered like the image attached. Is this an expected behavior? How do I make dots connect only in a time-ordered fashion?
Yes, this is observed in plotly plots.
The data is required to be sorted before the plotting.
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I'm trying to solve the OpenAI gym Breakout-V0 with a Deep Q-Network Agent.
Every time when my agent reaches the point where:
The replay_memory is filled enough to start training
The copy_target_network interval is reached for the first time
The target_network predicts for the fist time
Tensorflow throws following error:
Error when checking input: expected dense_3_input to have shape (33600,) but got array with shape (1,)
When I print the shape of the incoming state array just 1 line before i call the predict(state), it confirms that the shape of state is (33600,)
Before this error is shown the model is able to predict_on_batch() inside the training loop with the exact same data (but batched)
Does anybody know how to solve this? I can gladly give more details and information if I'm missing any
Versions:
Python 3.8.7
TensorFlow 2.4.1
Gym 0.18.0
As Dr.Snoopy said, it's a simple solution
Just had to do np.reshape(state, (1, 33600))
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I need to create a code that will take 24 scale values and save them in a txt. file, i then want to be able to recall these values and put them back into the 24 scales. can someone point me in the right direction.
Thanks
First read this :
http://docs.python.org/2/library/stdtypes.html#bltin-file-objects
then write some code and come back with concrete questions if necessary.
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I have a large sparse matrix (lil) implemented in Python with scipy, which comprises of Users on one axis, and songs they played on the other. So each row is a linked list of the songs that user has played.
I need to split each row ( user's songs ) so i have training and test data, but I'm unsure of how to do this. Sorry, im new to python, any help would be greatly appreciated.
I think you need sklearn.cross_validation.train_test_split