Using the DevBox - Revision history

Ed: /* DIGITS */

2020-10-30T17:00:04Z

DIGITS

Ed: /* Working in Tensorflow */

2019-05-16T01:34:05Z

Working in Tensorflow

Ed at 00:46, 16 May 2019

2019-05-16T00:46:01Z

Ed at 23:38, 15 May 2019

2019-05-15T23:38:55Z

Ed at 23:37, 15 May 2019

2019-05-15T23:37:11Z

Ed: Created page with "==Accessing the DevBox== Connect to the DevBox by SSH over the internal network. It is on: 192.168.2.202 Username: researcher *Password hint: littleamount It has a /bulk s..."

2019-05-15T20:57:08Z

Created page with "==Accessing the DevBox== Connect to the DevBox by SSH over the internal network. It is on: *192.168.2.202 *Username: researcher *Password hint: littleamount It has a /bulk s..."

New page

==Accessing the DevBox==

Connect to the DevBox by SSH over the internal network. It is on:
*192.168.2.202
*Username: researcher
*Password hint: littleamount

It has a /bulk samba share that can be mounted from the RDP. Follow the instructions on [[Help:Access RDP Server]].

==Specification==

{{:DIGITS DevBox}}

==Working in Tensorflow==

After you've connected to the box as researcher, you should be in /home/researcher. If not, cd there. Then load the virtual environment:
source ./venv/bin/activate

Test tensorflow:
python -c "import tensorflow as tf; tf.enable_eager_execution(); print(tf.reduce_sum(tf.random_normal([1000, 1000])))"

@@ Line 37: / Line 37: @@
 ==DIGITS==
 As root run:
@@ Line 42: / Line 44: @@
 Then browse to http://192.168.2.202:5000

← Older revision		Revision as of 01:34, 16 May 2019
Line 31:		Line 31:

	The code for MNIST.py is in E:\projects\tensorflow.		The code for MNIST.py is in E:\projects\tensorflow.
		+
		+	===Word2Vec===
		+
		+	There's a nice Word2Vec guide with code and data here: https://www.tensorflow.org/tutorials/representation/word2vec

	==DIGITS==		==DIGITS==

@@ Line 20: / Line 20: @@
   python -c "import tensorflow as tf; tf.enable_eager_execution(); print(tf.reduce_sum(tf.random_normal([1000, 1000])))"
-==Sample CNN Projects==
+===Sample CNN Projects===
 There are some nice Tensorflow CNN tutorials online:
@@ Line 31: / Line 31: @@
 The code for MNIST.py is in E:\projects\tensorflow.

@@ Line 20: / Line 20: @@
   python -c "import tensorflow as tf; tf.enable_eager_execution(); print(tf.reduce_sum(tf.random_normal([1000, 1000])))"
-==Sample CNN Projects===
+==Sample CNN Projects==
 There are some nice Tensorflow CNN tutorials online:

← Older revision		Revision as of 23:37, 15 May 2019
Line 19:		Line 19:
	Test tensorflow:		Test tensorflow:
	python -c "import tensorflow as tf; tf.enable_eager_execution(); print(tf.reduce_sum(tf.random_normal([1000, 1000])))"		python -c "import tensorflow as tf; tf.enable_eager_execution(); print(tf.reduce_sum(tf.random_normal([1000, 1000])))"
		+
		+	==Sample CNN Projects===
		+
		+	There are some nice Tensorflow CNN tutorials online:
		+	*https://www.tensorflow.org/tutorials/estimators/cnn
		+	*https://www.tensorflow.org/alpha/tutorials/images/intro_to_cnns
		+	*https://www.tensorflow.org/tutorials/images/deep_cnn
		+
		+	Some of which use standard datasets:
		+	*https://medium.com/tensorflow/introducing-tensorflow-datasets-c7f01f7e19f3
		+
		+	The code for MNIST.py is in E:\projects\tensorflow.