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Invalid argument: Dimension -972891 must be >= 0

I have created a data pipeline using tf.data for speech recognition using the following code snippets: These snippets are borrowed from https://www.tensorflow.org/tutorials/audio/simple_audio#build_and_train_the_model. And my model is defined as below: When I start training process this error appears after a few iterations: Answer I have found that the issue happened in the padding step, I mean I’ve replaced the padding step

Replace just a string’s portion in a list from a dictionary

I am struggling when trying to replace string’s portions from a list, using a dictionary. I have a list with network IPs and subnet masks: My idea is to create a dictionary to replace the subnet masks into prefix masks, for example: I am getting these IPs after using a small code to get IPs from a huge document, and

Counting identical consecutive elements in a list in a continuous manner

Given a list x of number entries, I aim to find the number of identical consecutive entries, where the identical consecutive entries are taken out once counted. For example, if x = [4, 3, 1, 1, 3, 2, 4], the returned solution should be 4: I can use the for loop to count the identical consecutive entries, but efficiently removing

Differrence between install and import in Jupyterlab Notebooks

What is the difference between the install statement and the import statement in Jupyterlab Notebooks? Why can’t we say !pip install pandas or import xlrd for example? [Screenshot of my notebook : https://i.stack.imgur.com/IxNjA.png ] Answer The install command is used to install a python library. In your case you have already installed xlrd, hence the output Requirement already satisfied. The

Can’t convert this text in normal format in python?

I am web-scraping some stuff and i got something like this “735 πš†πš’πš•πš•πš’πšŠπš– πšƒ π™Όπš˜πš›πš›πš’πšœπšœπšŽπš’ π™±πš•πšŸπš, π™³πš˜πš›πšŒπš‘πšŽπšœπšπšŽπš›, 𝙼𝙰 02122 Dorchester MA 02121” how do i convert it to normal text in python? Answer You can run it through Unicode normalization: Here’s a REPL screenshot that demonstrates it works:

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