ColeMurray

FROM python:3.10-slim as sources
RUN apt-get -y update --fix-missing

ENV DEBIAN_FRONTEND=noninteractive

ARG SSH_KEY_PRIV

RUN apt-get update -qq && apt-get install -y git openssh-server

# Authorize SSH Host

ColeMurray

set -euxo

REPO_NAMES=(
"deployer"
"tornado-root-updater"
"tornado-verified-forks"
"tornado-deploy"
"tornado-aggregator"
"tornado-relayer-registry-subgraph"
"tornado-trees"

ColeMurray

NRF5 SDK 17.0.2 ble_cts_c Patch

This patch adds support for local time information characteristic from the Current Time Service.

It adds an additional handle and data structure for storing the local time information.

typedef struct ATTR_PACKED {
    int8_t timezone_offset; // offset from UTC in increments of 15
 uint8_t dst_offset;

ColeMurray

scipy==1.1.0
numpy==1.15.4
opencv-python==3.4.4.19
tqdm==4.28.1

ColeMurray

import logging
from argparse import ArgumentParser

import tensorflow as tf
from scipy.misc import imread
from tensorflow.contrib import predictor

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

ColeMurray

scipy==1.1.0
numpy==1.15.4
opencv-python==3.4.4.19
tqdm==4.28.1

ColeMurray

FROM tensorflow/tensorflow:1.12.0-gpu-py3

RUN apt-get update \
    && apt-get install -y libsm6 libxrender-dev libxext6

ADD $PWD/requirements.txt /requirements.txt
RUN pip3 install -r /requirements.txt

CMD ["/bin/bash"]

ColeMurray

FROM tensorflow/tensorflow:1.12.0-py3

RUN apt-get update \
    && apt-get install -y libsm6 libxrender-dev libxext6

ADD $PWD/requirements.txt /requirements.txt
RUN pip3 install -r /requirements.txt

CMD ["/bin/bash"]

ColeMurray

import argparse

import tensorflow as tf

from medium_age_estimation_tutorial.cnn_estimator import model_fn, serving_fn
from medium_age_estimation_tutorial.dataset import csv_record_input_fn

tf.logging.set_verbosity(tf.logging.INFO)

if __name__ == '__main__':

ColeMurray

import os

import tensorflow as tf


def csv_record_input_fn(img_dir, filenames, img_size=150, repeat_count=-1, shuffle=True,
                        batch_size=16, random=True):
    """
    Creates tensorflow dataset iterator over records from :param{filenames}.