ageron

#!/bin/bash -e

echo 'Usage:
1. install git-filter-repo from https://github.com/newren/git-filter-repo
2. make a clean clone of your repository (keep a backup!)
3. cd to the repo and run this script
'

python -c 'input("Are you sure? Press Ctrl-C to cancel or Enter to continue.")'

ageron

ageron

#=
This code comes mostly from the talk "JuliaCon 2019 | Multi-threading in Julia with PARTR":
https://youtu.be/HfiRnfKxI64?t=729

It is a Julia translation of this Go code:
https://github.com/thomas11/csp/blob/f2ec7c4/csp.go#765

I fixed a few errors in the Julia code:
* replaced numPrimes with n
* replaced `if m < m` with `if m < mp`

ageron

public class Vertex {
    var key: String
    public init(key: String) {
        self.key = key
        print("Creating vertex \(key)")
    }
    deinit {
      print("Removing vertex \(key)")
    }
}

ageron

import numpy as np
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, Flatten, Conv2D
from tensorflow.keras.layers import MaxPooling2D, BatchNormalization

keras.backend.clear_session()
np.random.seed(1000)
tf.random.set_seed(1000)

ageron

import numpy as np
import tensorflow as tf
from tensorflow import keras

model = keras.models.Sequential([keras.layers.Dense(1, input_shape=[5])])
optimizer = keras.optimizers.SGD()

def step(model, optimizer, X_batch, y_batch):
    with tf.GradientTape() as tape:
        y_pred = model(X_batch)

ageron

"""
Converts one or more 3D images for red/blue 3D glasses into stereogram images. Example:

Download:
https://www.nasa.gov/sites/default/files/styles/full_width/public/thumbnails/image/nh-ut_stereo_bluered_030619.png

Then run:
python stereogram.py nh-ut_stereo_bluered_030619.png

This will generate:

ageron

import numpy as np
from tensorflow import keras
import traceback

class ResidualBlock(keras.layers.Layer):
    def __init__(self, n_layers, n_neurons, **kwargs):
        super().__init__(**kwargs)
        self.n_layers = n_layers
        self.n_neurons = n_neurons
        self.hidden = [keras.layers.Dense(n_neurons, activation="elu",

ageron

#!/bin/bash

cat <<EOF > install_cuda_10_and_nvidia_driver_384.sh
#!/bin/bash
apt-get update && apt-get install -y --no-install-recommends gnupg2 curl ca-certificates && \
    curl -fsSL https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub | apt-key add - && \
    echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 /" > /etc/apt/sources.list.d/cuda.list && \
    echo "deb https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64 /" > /etc/apt/sources.list.d/nvidia-ml.list

export CUDA_VERSION=10.0.130

ageron

"""
Usage:

>>> for pid, name in search_procs_by_name("python").items():
...     print(pid, name)
...
11882 python3.6
47599 python3.6
51877 python3.6
51924 python3.6