Tensorflow - Revision history

Seide at 17:17, 29 April 2024

2024-04-29T17:17:59Z

← Older revision		Revision as of 17:17, 29 April 2024
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	[https://www.tensorflow.org/ Tensorflow] is a [[Python]] deep learning package from Google. The easiest way to use install it is to build a [[PythonVirtualEnv \| Python virtualenv]] with it in it.		[https://www.tensorflow.org/ Tensorflow] is a [[Python]] deep learning package from Google. The easiest way to use install it is to build a [[PythonVirtualEnv \| Python virtualenv]] with it in it.

	First load GPU modules to allow access to accelerated GPGPU training.		First load GPU modules to allow access to accelerated GPGPU training. You can find the list of Tensorflow versions and their corresponding Python/CUDA/cuDNN requirements here. [https://www.tensorflow.org/install/source#gpu] These modules are appropriate for tensorflow-2.16.1, which is the latest tensorflow release as of April 29, 2024.

	<pre>module add cuda/11.8.0 cudnn/v8.6.0</pre>		<pre>module add Python3/3.9.16 cuda/12.4.1 cudnn/v8.9.7</pre>

	Next you will want to create a virtualenv and source into it. Note that depending on the version of Tensorflow you need, you may also need to load a module for a more recent version of Python3.		Next you will want to create a virtualenv and source into it. Note that depending on the version of Tensorflow you need, you may also need to load a module for a more recent version of Python3.
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	<pre>		<pre>
	(env) $ pip install --upgrade pip		(env) $ pip install --upgrade pip
	~~Collecting pip~~
	~~Downloading https://files.pythonhosted.org/packages/a4/6d/6463d49a933f547439d6b5b98b46af8742cc03ae83543e4d7688c2420f8b/pip-21.3.1-py3-none-any.whl (1.7MB)~~
	~~100% \|████████████████████████████████\| 1.7MB 1.2MB/s~~
	~~Installing collected packages: pip~~
	~~Found existing installation: pip 9.0.3~~
	~~Uninstalling pip-9.0.3:~~
	~~Successfully uninstalled pip-9.0.3~~
	~~Successfully installed pip-21.3.1~~
	</pre>		</pre>

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	<pre>		<pre>
	(env) $ pip install --upgrade tensorflow		(env) $ pip install --upgrade tensorflow
	~~Collecting tensorflow~~
	~~Downloading tensorflow-2.6.2-cp36-cp36m-manylinux2010_x86_64.whl (458.3 MB)~~
	~~\|████████████████████████████████\| 458.3 MB 37 kB/s~~
	~~Collecting gast==0.4.0~~
	~~Downloading gast-0.4.0-py3-none-any.whl (9.8 kB)~~
	~~...~~
	</pre>		</pre>

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	<pre>		<pre>
	(env)[username@hostname:/scratch0/username ] $ python		(env)[username@hostname:/scratch0/username ] $ python
	Python 3.6.8 (~~default~~, ~~Oct 2~~ 2023, 21:12:58)		Python 3.9.16 (main, Feb 28 2023, 09:58:09)
	[GCC 8.5.0 20210514 (Red Hat 8.5.0-18)] on linux		[GCC 8.5.0 20210514 (Red Hat 8.5.0-16)] on linux
	Type "help", "copyright", "credits" or "license" for more information.		Type "help", "copyright", "credits" or "license" for more information.
	>>> import tensorflow as tf		>>> import tensorflow as tf
			2024-04-29 13:14:09.685077: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
			2024-04-29 13:14:09.737280: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
			To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
			2024-04-29 13:14:11.316744: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
	>>> tf.__version__		>>> tf.__version__
	'2.6.2'		'2.16.1'
	</pre>		</pre>

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	</pre>		</pre>

	<b>To use this install after you close the shell you did this install in, you will need to both add the correct [[CUDA]]/cuDNN~~/Python3~~ modules, export the XLA_FLAGS variable (if needed), and activate the virtualenv by the source command. This includes any time you are submitting to [[SLURM]].</b>		<b>To use this install after you close the shell you did this install in, you will need to both add the correct [[CUDA]]/cuDNN modules, export the XLA_FLAGS variable (if needed), and activate the virtualenv by the source command. This includes any time you are submitting to [[SLURM]].</b>

Mbaney at 13:04, 26 October 2023

2023-10-26T13:04:16Z

← Older revision		Revision as of 13:04, 26 October 2023
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	</pre>		</pre>

	<b>To use this install after you close the shell you did this install in, you will need to both add the correct [[CUDA]]/cuDNN modules and activate the virtualenv by the source command. This includes any time you are submitting to [[SLURM]].</b>		<b>To use this install after you close the shell you did this install in, you will need to both add the correct [[CUDA]]/cuDNN/Python3 modules, export the XLA_FLAGS variable (if needed), and activate the virtualenv by the source command. This includes any time you are submitting to [[SLURM]].</b>

Mbaney at 19:34, 25 October 2023

2023-10-25T19:34:16Z

← Older revision		Revision as of 19:34, 25 October 2023
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	Next you will want to create a virtualenv and source into it. Note that depending on the version of Tensorflow you need, you may also need to load a module for a more recent version of Python3.		Next you will want to create a virtualenv and source into it. Note that depending on the version of Tensorflow you need, you may also need to load a module for a more recent version of Python3.

	~~<pre>module load Python3/~~

	<pre>		<pre>

Mbaney at 19:30, 25 October 2023

2023-10-25T19:30:35Z

← Older revision		Revision as of 19:30, 25 October 2023
Line 3:		Line 3:
	First load GPU modules to allow access to accelerated GPGPU training.		First load GPU modules to allow access to accelerated GPGPU training.

	<pre>module add cuda/11.8.0 cudnn/v8.8.0</pre>		<pre>module add cuda/11.8.0 cudnn/v8.6.0</pre>

	Next you will want to create a virtualenv and source into it. Note that depending on the version of Tensorflow you need, you may also need to load a module for a more recent version of Python3.		Next you will want to create a virtualenv and source into it. Note that depending on the version of Tensorflow you need, you may also need to load a module for a more recent version of Python3.

Mbaney at 19:30, 25 October 2023

2023-10-25T19:30:20Z

← Older revision		Revision as of 19:30, 25 October 2023
Line 3:		Line 3:
	First load GPU modules to allow access to accelerated GPGPU training.		First load GPU modules to allow access to accelerated GPGPU training.

	<pre>module add cuda/9.0~~.176~~ cudnn/v7.0.5</pre>		<pre>module add cuda/11.8.0 cudnn/v8.8.0</pre>

	Next you will want to create a virtualenv and source into it.		Next you will want to create a virtualenv and source into it. Note that depending on the version of Tensorflow you need, you may also need to load a module for a more recent version of Python3.

			<pre>module load Python3/

	<pre>		<pre>
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	</pre>		</pre>

	~~The next step is to~~ ensure you have a recent copy of pip in your virtualenv.		Then ensure you have a recent copy of pip in your virtualenv.

	<pre>		<pre>
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	</pre>		</pre>

	Then ~~you can now~~ install the Tensorflow wheel through pip.		Then install the Tensorflow wheel through pip.

	<pre>		<pre>
	(env) $ pip install --upgrade tensorflow~~-gpu~~		(env) $ pip install --upgrade tensorflow
	Collecting tensorflow~~-gpu~~		Collecting tensorflow
	Downloading ~~tensorflow_gpu~~-1.1.0-~~cp27~~-~~cp27mu~~-~~manylinux1_x86_64~~.whl (84.~~1MB~~)		Downloading tensorflow-2.6.2-cp36-cp36m-manylinux2010_x86_64.whl (458.3 MB)
	~~100%~~ \|████████████████████████████████\| 84.~~1MB 15kB~~/s		\|████████████████████████████████\| 458.3 MB 37 kB/s
	Collecting ~~wheel (from tensorflow-gpu)~~		Collecting gast==0.4.0
	Downloading ~~wheel~~-0.29.0-~~py2.~~py3-none-any.whl (~~66kB~~)		Downloading gast-0.4.0-py3-none-any.whl (9.8 kB)
	~~100% \|████████████████████████████████\| 71kB 2.0MB/s~~
	...		...
	</pre>		</pre>

	Finally start up a python shell (or install ipython through pip) and import Tensorflow.		Finally, start up a python shell (or install ipython through pip) and import Tensorflow.

	<pre>		<pre>
	(env)[~~derek~~@~~ramawks76~~:/scratch0/~~derek~~ ] $ python		(env)[username@hostname:/scratch0/username ] $ python
	Python 2.7.5 (default, ~~Aug~~ 2 ~~2016~~, 04:20:16)		Python 3.6.8 (default, Oct 2 2023, 21:12:58)
	[GCC 4.8.5 ~~20150623~~ (Red Hat 4.8.5-4)] on ~~linux2~~		[GCC 8.5.0 20210514 (Red Hat 8.5.0-18)] on linux
	Type "help", "copyright", "credits" or "license" for more information.		Type "help", "copyright", "credits" or "license" for more information.
	>>> import tensorflow as tf		>>> import tensorflow as tf
	>>> tf.__version__		>>> tf.__version__
	'1.1.0'		'2.6.2'
	</pre>		</pre>

	You can then try a more ~~rigourous~~ test by running the following example.		You can then try a more rigorous test by running the following example. Note that you may need to export XLA_FLAGS in your shell: <code>export XLA_FLAGS=--xla_gpu_cuda_data_dir=/opt/common/cuda/cuda-x.x.x</code>
	<pre>		<pre>
	import tensorflow as tf		import tensorflow as tf
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	</pre>		</pre>

	<b>To use this install after you close the shell you did this install in, you will need to both add the correct ~~Cuda~~/cuDNN modules and activate the virtualenv by the source command. This includes any time you are submitting to ~~Slurm or other resource managers~~.</b>		<b>To use this install after you close the shell you did this install in, you will need to both add the correct [[CUDA]]/cuDNN modules and activate the virtualenv by the source command. This includes any time you are submitting to [[SLURM]].</b>

Mbaney at 19:16, 25 October 2023

2023-10-25T19:16:24Z

← Older revision		Revision as of 19:16, 25 October 2023
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	<pre>		<pre>
	(env) $ pip install --upgrade pip		(env) $ pip install --upgrade pip
	Downloading~~/unpacking pip from~~ https://~~pypi~~.~~python~~.org/packages/11/b6/~~abcb525026a4be042b486df43905d6893fb04f05aac21c32c638e939e447~~/pip-9.0.1.~~tar~~.~~gz#md5=35f01da33009719497f01a4ba69d63c9~~		Collecting pip
	~~Downloading~~ pip-9.0.1.~~tar~~.~~gz (1.2MB)~~: ~~1.2MB downloaded~~		Downloading https://files.pythonhosted.org/packages/a4/6d/6463d49a933f547439d6b5b98b46af8742cc03ae83543e4d7688c2420f8b/pip-21.3.1-py3-none-any.whl (1.7MB)
	~~Running setup.py egg_info for package~~ pip		100% \|████████████████████████████████\| 1.7MB 1.2MB/s
	....		Installing collected packages: pip
			Found existing installation: pip 9.0.3
			Uninstalling pip-9.0.3:
			Successfully uninstalled pip-9.0.3
			Successfully installed pip-21.3.1
	</pre>		</pre>

Mbaney at 19:15, 25 October 2023

2023-10-25T19:15:48Z

← Older revision		Revision as of 19:15, 25 October 2023
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	<pre>		<pre>
	$ ~~virtualenv~~ env		$ python3 -m venv env
	~~New python executable in env/bin/python~~
	Installing Setuptools..............................................................................................................................................................................................................................done.
	Installing Pip.....................................................................................................................................................................................................................................................................................................................................done.
	$ source env/bin/activate		$ source env/bin/activate
	(env) $		(env) $

Mbaney at 19:03, 25 October 2023

2023-10-25T19:03:11Z

← Older revision		Revision as of 19:03, 25 October 2023
Line 1:		Line 1:
	Tensorflow is a Python deep learning package from Google. The easiest way to use it is to build a Python virtualenv with it in it.		[https://www.tensorflow.org/ Tensorflow] is a [[Python]] deep learning package from Google. The easiest way to use install it is to build a [[PythonVirtualEnv \| Python virtualenv]] with it in it.

	First load GPU modules to allow access to accelerated GPGPU training.		First load GPU modules to allow access to accelerated GPGPU training.

Mbaney: Created page with "Tensorflow is a Python deep learning package from Google. The easiest way to use it is to build a Python virtualenv with it in it. First load GPU modules to allow access to accelerated GPGPU training.

module add cuda/9.0.176 cudnn/v7.0.5

Next you will want to create a virtualenv and source into it.

 $ virtualenv env New python executable in env/bin/python Installing Setuptools.............................................................................."

2023-08-14T19:37:09Z

Created page with "Tensorflow is a Python deep learning package from Google. The easiest way to use it is to build a Python virtualenv with it in it. First load GPU modules to allow access to accelerated GPGPU training. <pre>module add cuda/9.0.176 cudnn/v7.0.5</pre> Next you will want to create a virtualenv and source into it. <pre> $ virtualenv env New python executable in env/bin/python Installing Setuptools.............................................................................."

New page

Tensorflow is a Python deep learning package from Google. The easiest way to use it is to build a Python virtualenv with it in it.

First load GPU modules to allow access to accelerated GPGPU training.

<pre>module add cuda/9.0.176 cudnn/v7.0.5</pre>

Next you will want to create a virtualenv and source into it.

<pre>
$ virtualenv env
New python executable in env/bin/python
Installing Setuptools..............................................................................................................................................................................................................................done.
Installing Pip.....................................................................................................................................................................................................................................................................................................................................done.
$ source env/bin/activate
(env) $
</pre>

The next step is to ensure you have a recent copy of pip in your virtualenv.

<pre>
(env) $ pip install --upgrade pip
Downloading/unpacking pip from https://pypi.python.org/packages/11/b6/abcb525026a4be042b486df43905d6893fb04f05aac21c32c638e939e447/pip-9.0.1.tar.gz#md5=35f01da33009719497f01a4ba69d63c9
Downloading pip-9.0.1.tar.gz (1.2MB): 1.2MB downloaded
Running setup.py egg_info for package pip
....
</pre>

Then you can now install the Tensorflow wheel through pip.

<pre>
(env) $ pip install --upgrade tensorflow-gpu
Collecting tensorflow-gpu
Downloading tensorflow_gpu-1.1.0-cp27-cp27mu-manylinux1_x86_64.whl (84.1MB)
100% |████████████████████████████████| 84.1MB 15kB/s
Collecting wheel (from tensorflow-gpu)
Downloading wheel-0.29.0-py2.py3-none-any.whl (66kB)
100% |████████████████████████████████| 71kB 2.0MB/s
...
</pre>

Finally start up a python shell (or install ipython through pip) and import Tensorflow.

<pre>
(env)[derek@ramawks76:/scratch0/derek ] $ python
Python 2.7.5 (default, Aug 2 2016, 04:20:16)
[GCC 4.8.5 20150623 (Red Hat 4.8.5-4)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
>>> tf.__version__
'1.1.0'
</pre>

You can then try a more rigourous test by running the following example.
<pre>
import tensorflow as tf
mnist = tf.keras.datasets.mnist

(x_train, y_train),(x_test, y_test) = mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0

model = tf.keras.models.Sequential([
tf.keras.layers.Flatten(),
tf.keras.layers.Dense(512, activation=tf.nn.relu),
tf.keras.layers.Dropout(0.2),
tf.keras.layers.Dense(10, activation=tf.nn.softmax)
])
model.compile(optimizer='adam',
loss='sparse_categorical_crossentropy',
metrics=['accuracy'])

model.fit(x_train, y_train, epochs=5)
model.evaluate(x_test, y_test)
</pre>

<b>To use this install after you close the shell you did this install in, you will need to both add the correct Cuda/cuDNN modules and activate the virtualenv by the source command. This includes any time you are submitting to Slurm or other resource managers.</b>