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| pd.set_option("use_inf_as_na", True) | |
| pd.set_option("max_info_columns", 9999) | |
| pd.set_option("display.max_columns", 9999) | |
| pd.set_option("display.max_rows", 9999) | |
| pd.set_option('max_colwidth', 9999) |
seahrh
/ config
Created
May 6, 2021 03:04
— forked from pksunkara/config
Sample of git config file (Example .gitconfig) (Place them in $XDG_CONFIG_HOME/git)
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| [user] | |
| name = Pavan Kumar Sunkara | |
| email = [email protected] | |
| username = pksunkara | |
| [core] | |
| editor = vim | |
| whitespace = fix,-indent-with-non-tab,trailing-space,cr-at-eol | |
| pager = delta | |
| [sendemail] | |
| smtpencryption = tls |
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| # If you come from bash you might have to change your $PATH. | |
| # export PATH=$HOME/bin:/usr/local/bin:$PATH | |
| # Path to your oh-my-zsh installation. | |
| export ZSH=$HOME/.oh-my-zsh | |
| # Set name of the theme to load --- if set to "random", it will | |
| # load a random theme each time oh-my-zsh is loaded, in which case, | |
| # to know which specific one was loaded, run: echo $RANDOM_THEME | |
| # See https://github.com/ohmyzsh/ohmyzsh/wiki/Themes |
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| { | |
| "TrainingJobName": "", | |
| "HyperParameters": { | |
| "epochs": "40", | |
| "folds": "5", | |
| "patience": "4", | |
| "batch_size": "32", | |
| "input_shape": "300,300,3", | |
| "pooling": "avg", | |
| "hidden_layer_sizes": "100", |
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| aws s3 cp s3://mybucket/models/ models/ --recursive --exclude "*" --include "*effnetb3-20210330-150641*" |
seahrh
/ pytest.ini
Last active
July 12, 2021 06:55
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| [pytest] | |
| filterwarnings = | |
| ignore::DeprecationWarning:tensorflow.* | |
| markers = | |
| slow: marks tests as slow (deselect with '-m "not slow"') |
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| aws sts get-session-token --duration-seconds 36000 |
seahrh
/ gmock-matchers_test.cc
Created
February 28, 2021 08:22
how to use matchers in googletest - ref: https://chromium.googlesource.com/external/gmock/+/refs/heads/master/test/gmock-matchers_test.cc
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| // Copyright 2007, Google Inc. | |
| // All rights reserved. | |
| // | |
| // Redistribution and use in source and binary forms, with or without | |
| // modification, are permitted provided that the following conditions are | |
| // met: | |
| // | |
| // * Redistributions of source code must retain the above copyright | |
| // notice, this list of conditions and the following disclaimer. | |
| // * Redistributions in binary form must reproduce the above |
seahrh
/ fast_predict.py
Last active
February 13, 2021 03:33
Faster than Keras model.predict. If you are using tf.keras.Model and predicting via the functional call (as done in Jane Street: Neural Network Starter and other Notebooks), try using:
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| model.call = tf.function(model.call, experimental_relax_shapes=True) | |
| for (test_df, pred_df) in tqdm(env.iter_test()): | |
| pred = model(data, training = False).numpy() |
seahrh
/ ls_summarize.sh
Created
February 4, 2021 06:46
aws s3 -Rlah recursive list files with file size
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| aws s3 ls --summarize --human-readable --recursive s3://mybucket/mydir/ |