seahrh

// 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

aws sts get-session-token --duration-seconds 36000

seahrh

[pytest]
filterwarnings =
    ignore::DeprecationWarning:tensorflow.*

markers =
    slow: marks tests as slow (deselect with '-m "not slow"')

seahrh

aws s3 cp s3://mybucket/models/ models/ --recursive --exclude "*" --include "*effnetb3-20210330-150641*"

seahrh

{
    "TrainingJobName": "",
    "HyperParameters": {
        "epochs": "40",
        "folds": "5",
        "patience": "4",
        "batch_size": "32",
        "input_shape": "300,300,3",
        "pooling": "avg",
        "hidden_layer_sizes": "100",

seahrh

# 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

seahrh

[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

seahrh

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

import pathlib
from datetime import datetime

ts = datetime.now().strftime('%Y%m%d_%H%M%S')
job_dir = f"models/mlp/{ts}"
pathlib.Path(job_dir).mkdir(parents=True, exist_ok=True)

seahrh

%%time
len1 = len(train)
train["col"] = train["col"].str.strip()
train.drop(train[train["col"].str.len() == 0].index, inplace=True)
len2 = len(train)
print(f"{len1 - len2} rows deleted")