W4ngatang

''' Script for downloading all GLUE data.

Note: for legal reasons, we are unable to host MRPC.
You can either use the version hosted by the SentEval team, which is already tokenized, 
or you can download the original data from (https://download.microsoft.com/download/D/4/6/D46FF87A-F6B9-4252-AA8B-3604ED519838/MSRParaphraseCorpus.msi) and extract the data from it manually.
For Windows users, you can run the .msi file. For Mac and Linux users, consider an external library such as 'cabextract' (see below for an example).
You should then rename and place specific files in a folder (see below for an example).

mkdir MRPC
cabextract MSRParaphraseCorpus.msi -d MRPC

moodoki

import os, argparse

import tensorflow as tf
from tensorflow.python.framework import graph_util

dir = os.path.dirname(os.path.realpath(__file__))

def freeze_graph(model_folder, output_nodes='y_hat', 
                 output_filename='frozen-graph.pb', 
                 rename_outputs=None):

mauri870

// Tensorflow Serving Go client for the inception model

// go get github.com/golang/protobuf/ptypes/wrappers google.golang.org/grpc
//
// Compile the proto files:
//
// git clone https://github.com/tensorflow/serving.git
// git clone https://github.com/tensorflow/tensorflow.git
//
// mkdir -p vendor

zombiezen

# Copyright 2017 Google Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

WillieMaddox

# -*- coding: utf-8 -*-
import numpy as np
import xml.etree.ElementTree as ET
from pycocotools.coco import COCO


def convert_coco_bbox(size, box):
    dw = 1. / size[0]
    dh = 1. / size[1]
    x = box[0] + box[2] / 2.0

alansouzati

apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: grommet-drone
  namespace: drone
  labels:
    app: grommet-drone
  annotations:
    description: drone with interface
spec:

yaroslavvb

# testing variable order init

import tensorflow as tf

def initialize_all_variables(sess=None):
  """Initializes all uninitialized variables in correct order. Initializers
  are only run for uninitialized variables, so it's safe to run this multiple
  times.

  Args:

yaroslavvb

"""Benchmark tensorflow distributed by adding vector of ones on worker2
to variable on worker1 as fast as possible.

On 2014 macbook, TensorFlow 0.10 this shows

Local rate:       2175.28 MB per second
Distributed rate: 107.13 MB per second

"""

morgangiraud

# Remove anything linked to nvidia
sudo apt-get remove --purge nvidia*
sudo apt-get autoremove

# Search for your driver
apt search nvidia

# Select one driver (the last one is a decent choice)
sudo apt install nvidia-370

harpone

import tensorflow as tf
from tensorflow.python.framework import ops
import numpy as np

# Define custom py_func which takes also a grad op as argument:
def py_func(func, inp, Tout, stateful=True, name=None, grad=None):
    
    # Need to generate a unique name to avoid duplicates:
    rnd_name = 'PyFuncGrad' + str(np.random.randint(0, 1E+8))