kingspp

# -*- coding: utf-8 -*-
"""
| **@created on:** 11/05/17,
| **@author:** Prathyush SP,
| **@version:** v0.0.1
|
| **Description:**
| DL Module Tests
| **Sphinx Documentation Status:** Complete
|

kingspp

"""
Example TensorFlow script for finetuning a VGG model on your own data.
Uses tf.contrib.data module which is in release v1.2
Based on PyTorch example from Justin Johnson
(https://gist.github.com/jcjohnson/6e41e8512c17eae5da50aebef3378a4c)

Required packages: tensorflow (v1.2)
Download the weights trained on ImageNet for VGG:
```
wget http://download.tensorflow.org/models/vgg_16_2016_08_28.tar.gz

kingspp

'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

kingspp

"""
Requirements
1. Numpy
2. Pympler or a recursive sys.getsizeof()
3. PIL
"""

import numpy as np
from pympler.asizeof import asizeof
import json

kingspp

from tensorflow.examples.tutorials.mnist import input_data
import pandas as pd
import numpy as np

def convert_tensorflow_mnist_train_data_to_csv(path_to_save:str):
    mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)
    data = pd.DataFrame(mnist.train.images)
    label = pd.DataFrame(mnist.train.labels)
    df = pd.concat([data, label], axis=1)
    df.columns = ['D_{}'.format(i) for i in range(784)] + ['L_{}'.format(i) for i in range(10)]

kingspp

import re


def generate_label_from_name(name: str):
    """

    :param name: Name for which label has to be generate
    :return:
    """
    caps_split = sum([list(match) for match in re.findall('([A-Z][^A-Z][a-z]*)|([0-9][A-Z][^A-Z][a-z]*)|([0-9][A-Z][a-z]*)', name)], [])

kingspp

import typing
import tensorflow as tf


def validate_fetch(fetch_ops: typing.Union[str, list, dict, tf.Tensor]):
    if isinstance(fetch_ops, str):
        if not len(fetch_ops) > 0:
            raise Exception("Fetch Op is an empty string")
        return fetch_ops
    elif isinstance(fetch_ops, tf.Tensor):

kingspp

def humanize_time_delta(td_object):
    seconds = td_object
    periods = [
        ('year', 60 * 60 * 24 * 365),
        ('month', 60 * 60 * 24 * 30),
        ('day', 60 * 60 * 24),
        ('hour', 60 * 60),
        ('minute', 60),
        ('second', 1),
        ('milli_second', 1 / 10 ** 3),

kingspp

#!/usr/bin/env bash

# Install Open MPI v4
wget https://download.open-mpi.org/release/open-mpi/v4.0/openmpi-4.0.0.tar.gz
tar -xvf openmpi-4.0.0.tar.gz
cd openmpi-4.0.0
./configure --prefix=/usr/local
make all
sudo make install
sudo ldconfig

kingspp

# Install fish
cd /etc/yum.repos.d/
sudo wget https://download.opensuse.org/repositories/shells:fish:release:2/RedHat_RHEL-6/shells:fish:release:2.repo
sudo yum install fish

# Update locatedb
sudo ionice -c3 updatedb

# Install g++
sudo yum install gcc72-c++