rchgit

#
#  Original solution via StackOverflow:
#    http://stackoverflow.com/questions/35802939/install-only-available-packages-using-conda-install-yes-file-requirements-t
#

#
#  Install via `conda` directly.
#  This will fail to install all
#  dependencies. If one fails,
#  all dependencies will fail to install.

rchgit

# TODO: Verify to link statically some dependencies usually not available in a default instllation of RHEL/CentOS (ex.: libxcb)

###################
## Configuration ##
###################

export FFMPEG_CPU_COUNT=$(nproc)
export FFMPEG_ENABLE="--enable-gpl --enable-version3 --enable-nonfree --enable-runtime-cpudetect --enable-gray --enable-openssl --enable-libfreetype"
export FFMPEG_HOME=/usr/local/src/ffmpeg

rchgit

1324/1324 [==============================] - 1s - loss: 0.0045 - acc: 1.0000 - categorical_accuracy: 1.0000 - top_k_cate
gorical_accuracy: 1.0000 - mean_absolute_error: 9.8899e-04 - mean_squared_error: 1.9106e-05 - val_loss: 0.0102 - val_acc
: 1.0000 - val_categorical_accuracy: 1.0000 - val_top_k_categorical_accuracy: 1.0000 - val_mean_absolute_error: 0.0020 -
 val_mean_squared_error: 3.0197e-04
Epoch 20/50
 128/1324 [=>............................] - ETA: 0s - loss: 0.0035 - acc: 1.0000 - categorical_accuracy: 1.0000 - top_k
 384/1324 [=======>......................] - ETA: 0s - loss: 0.0037 - acc: 1.0000 - categorical_accuracy: 1.0000 - top_k
 640/1324 [=============>................] - ETA: 0s - loss: 0.0042 - acc: 1.0000 - categorical_accuracy: 1.0000 - top_k
 896/1324 [===================>..........] - ETA: 0s - loss: 0.0041 - acc: 1.0000 - categorical_accuracy: 1.0000 - top_k
1152/1324 [=========================>....] - ETA: 0s - loss: 0.0040 - acc: 1.0000 - categorical_accuracy: 1.0000 - top_k

rchgit

rchgit

Contract Killer

The popular open-source contract for web professionals by Stuff & Nonsense

• Originally published: 23rd December 2008
• Revised date: March 15th 2016
• Original post

---

rchgit

import tensorflow as tf
import tflearn
import os
import numpy as np
import time

from collections import deque
from sklearn.model_selection import train_test_split
from tflearn.data_utils import to_categorical

rchgit

import imageio
import os
import numpy as np
import tensorflow as tf
import tflearn
import pickle
from collections import deque
from sklearn.model_selection import train_test_split
from tflearn.data_utils import to_categorical

rchgit

Viewing IPython notebooks in GitLab

GitLab is open source software to collaborate on code (a GitHub clone to run on your own server). Clicking a blob (a file in a repository) in GitLab shows a nice rendering if GitLab supports the file type (e.g., images, Markdown documents), or its content as plain text otherwise. The patch described here adds support to GitLab for rendering IPython notebooks (.ipynb files).

rchgit

import csv
import glob

file_list = glob.glob("*/*.csv")
print(file_list)
for file_name in file_list:
    with open(file_name, "r") as source:
        rdr = csv.reader(source)

        with open(file_name+"-lstm", "w") as result:

rchgit

def load_data(data_dir, labels):
    X_signals_train = np.zeros((1,9))
    X_signals_test = np.zeros((1,9))
    y_train = np.zeros([1,1])
    y_test = np.zeros([1,1])
    for label in labels:
        for root, dirs, files in os.walk(data_dir + "/" + label):
            for filename in files:
                signal = genfromtxt(data_dir + "/" + label + "/" + filename, delimiter=',')
                #print (signal)