Matheus Tosta matheushent

💭

Building things and repeating

Devops Engineer | Cloud Solutions Architect

matheushent / kubectl-apply-stdin.md

Created February 3, 2023 12:06 — forked from zulhfreelancer/kubectl-apply-stdin.md

How to run "kubectl apply -f" with inline YAML as stdin?

$ kubectl apply -f - <<EOF
<-- insert YAML content here -->
EOF

$ cat file.yaml | kubectl apply -f -

matheushent / stack.py

Created October 20, 2021 00:30

CDK stack example for build WAF rules against CloudFront distribution

	#CDK python WAF with CloudFront and regex and ip set rules (v1.102.0 of CDK and above)

	from aws_cdk import (
	core as cdk,
	aws_cloudfront as cloudfront,
	aws_cloudfront_origins as cloudfront_origins,
	aws_s3 as s3,
	aws_certificatemanager as acm,
	aws_route53 as route53,
	aws_wafv2 as wafv2,

matheushent / pytz-time-zones.py

Created September 7, 2020 16:58 — forked from heyalexej/pytz-time-zones.py

list of pytz time zones

matheushent / issue.py

Last active April 19, 2020 18:53

Stand alone code for tensorflow issue #38518

	import tensorflow_addons as tfa
	import tensorflow as tf

	def get_norm_layer(norm):
	"""Utility function to get the normalization layer
	"""

	if norm == None:
	return lambda: lambda x: x
	elif norm == 'batch_norm':

matheushent / guided_relu.py

Created February 26, 2020 17:51 — forked from falcondai/guided_relu.py

Tensorflow implementation of guided backpropagation through ReLU

	import tensorflow as tf
	from tensorflow.python.framework import ops
	from tensorflow.python.ops import gen_nn_ops

	@ops.RegisterGradient("GuidedRelu")
	def _GuidedReluGrad(op, grad):
	return tf.select(0. < grad, gen_nn_ops._relu_grad(grad, op.outputs[0]), tf.zeros(grad.get_shape()))

	if __name__ == '__main__':
	with tf.Session() as sess:

matheushent / Stacked-AE.py

Created April 6, 2019 15:14

	from tensorflow.examples.tutorials.mnist import input_data
	import matplotlib.pyplot as plt
	import tensorflow as tf
	import numpy as np

	mnist = input_data.read_data_sets('mnist/', one_hot=True)

	X = mnist.train.images

	# 784 -> 128 -> 64 -> 128 -> 784

matheushent / First-GAN.py

Created April 6, 2019 15:12

	import tensorflow as tf
	import matplotlib.pyplot as plt
	from tensorflow.examples.tutorials.mnist import input_data
	import numpy as np

	tf.reset_default_graph()

	mnist = input_data.read_data_sets('mnist/', one_hot=True)

	# Test

matheushent / Hyper-parameter Optimization with Lightgbm using skopt.py

Created February 20, 2019 23:59

Hyper-parameter optimization of xgboost model for Santander competition

	from warnings import filterwarnings
	filterwarnings('ignore')
	import pandas as pd
	import numpy as np

	from lightgbm import LGBMClassifier

	from sklearn.preprocessing import MinMaxScaler
	from sklearn.model_selection import train_test_split
	from sklearn.metrics import roc_auc_score

matheushent / Hyperparameters Optimization - SVHN.py

Last active February 15, 2019 23:33

	import warnings
	warnings.filterwarnings('ignore')
	import pandas as pd
	import numpy as np

	from tensorflow.python.keras import backend as K
	from tensorflow.python.keras.models import Sequential
	from tensorflow.python.keras.layers import InputLayer, Input
	from tensorflow.python.keras.layers import Reshape, MaxPooling2D
	from tensorflow.python.keras.layers import Conv2D, Dense, Flatten, Dropout

matheushent / CMBI.py

Created February 5, 2019 13:16

Iris classification

	from sklearn import datasets

	iris = datasets.load_iris()

	X = iris.data
	y = iris.target

	from sklearn.preprocessing import StandardScaler

	scaler_x = StandardScaler()