dolaameng dolaameng

## Eigen Cheat sheet
// A simple quickref for Eigen. Add anything that's missing.
// Main author: Keir Mierle

#include <Eigen/Dense>

Matrix<double, 3, 3> A;               // Fixed rows and cols. Same as Matrix3d.
Matrix<double, 3, Dynamic> B;         // Fixed rows, dynamic cols.
Matrix<double, Dynamic, Dynamic> C;   // Full dynamic. Same as MatrixXd.
Matrix<double, 3, 3, RowMajor> E;     // Row major; default is column-major.
Matrix3f P, Q, R;                     // 3x3 float matrix.

## test_import.md

      
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                dolaameng
                / test_import.md
            
            
              Created
              November 1, 2017 13:48
                — forked from avloss/test_import.md
            
          
    TensorFlow Serving in 10 minutes!

TensorFlow SERVING is Googles' recommended way to deploy TensorFlow models. Without proper computer engineering background, it can be quite intimidating, even for people who feel comfortable with TensorFlow itself. Few things that I've found particularly hard were:

Tutorial examples have C++ code (which I don't know)
Tutorials have Kubernetes, gRPG, Bezel (some of which I saw for the first time)
It needs to be compiled. That process takes forever!

After all, it worked just fine. Here I present an easiest possible way to deploy your models with TensorFlow Serving. You will have your self-built model running inside TF-Serving by the end of this tutorial. It will be scalable, and you will be able to query it via REST.

  
## urllib-request_basicAuth.py
#!/usr/bin/env python
#
# I tested by Python 3.4.3 on Windows 8.1
# Python 3.4.3 (v3.4.3:9b73f1c3e601, Feb 24 2015, 22:43:06) [MSC v.1600 32 bit (Intel)] on win32

import urllib.request
import getpass

# If you access to url below via Proxy,
# set environment variable 'http_proxy' before execute this.

## mnist_estimator.py
"""Script to illustrate usage of tf.estimator.Estimator in TF v1.3"""
import tensorflow as tf

from tensorflow.examples.tutorials.mnist import input_data as mnist_data
from tensorflow.contrib import slim
from tensorflow.contrib.learn import ModeKeys
from tensorflow.contrib.learn import learn_runner


# Show debugging output
	// A simple quickref for Eigen. Add anything that's missing.
	// Main author: Keir Mierle

	#include <Eigen/Dense>

	Matrix<double, 3, 3> A; // Fixed rows and cols. Same as Matrix3d.
	Matrix<double, 3, Dynamic> B; // Fixed rows, dynamic cols.
	Matrix<double, Dynamic, Dynamic> C; // Full dynamic. Same as MatrixXd.
	Matrix<double, 3, 3, RowMajor> E; // Row major; default is column-major.
	Matrix3f P, Q, R; // 3x3 float matrix.
	#!/usr/bin/env python
	#
	# I tested by Python 3.4.3 on Windows 8.1
	# Python 3.4.3 (v3.4.3:9b73f1c3e601, Feb 24 2015, 22:43:06) [MSC v.1600 32 bit (Intel)] on win32

	import urllib.request
	import getpass

	# If you access to url below via Proxy,
	# set environment variable 'http_proxy' before execute this.
	"""Script to illustrate usage of tf.estimator.Estimator in TF v1.3"""
	import tensorflow as tf

	from tensorflow.examples.tutorials.mnist import input_data as mnist_data
	from tensorflow.contrib import slim
	from tensorflow.contrib.learn import ModeKeys
	from tensorflow.contrib.learn import learn_runner


	# Show debugging output