ML Environment - Revision history

Chris: /* Using the CCN Lab ML Environment */

2022-07-26T20:44:15Z

Using the CCN Lab ML Environment

← Older revision		Revision as of 16:44, 26 July 2022
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	#*To list all other environments that you can activate<br><code>conda info --envs</code>		#*To list all other environments that you can activate<br><code>conda info --envs</code>
	#*To list all the packages installed in your current environment:<br><code>conda list</code>		#*To list all the packages installed in your current environment:<br><code>conda list</code>
	#If <code>'''conda list'''</code> doesn't include a bunch of tensorflow libraries, install it using pip:<br><code>pip install tensorflow</code>		#If <code>'''conda list'''</code> output doesn't include a bunch of tensorflow libraries, install it using pip:<br><code>pip install tensorflow</code>
			#*Other libraries may have to be installed separately by each user using pip. For example:<br><code>pip install sklearn</code>

	=Setting up your own ML environment=		=Setting up your own ML environment=

Chris: /* Using the CCN Lab ML Environment */

2022-07-26T20:42:00Z

Using the CCN Lab ML Environment

← Older revision		Revision as of 16:42, 26 July 2022
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	#*To list all other environments that you can activate<br><code>conda info --envs</code>		#*To list all other environments that you can activate<br><code>conda info --envs</code>
	#*To list all the packages installed in your current environment:<br><code>conda list</code>		#*To list all the packages installed in your current environment:<br><code>conda list</code>
	#~~It appears everyone has to~~ install ~~tensorflow individually~~ using pip<br><code>pip install tensorflow</code>		#If <code>'''conda list'''</code> doesn't include a bunch of tensorflow libraries, install it using pip:<br><code>pip install tensorflow</code>

	=Setting up your own ML environment=		=Setting up your own ML environment=

Chris: /* Using the CCN Lab ML Environment */

2022-07-26T20:38:59Z

Using the CCN Lab ML Environment

← Older revision		Revision as of 16:38, 26 July 2022
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	#run the following command:<br><code>conda init bash</code>		#run the following command:<br><code>conda init bash</code>
	#log out, log back in. Now your shell prompt will look like:<br><code>(base) user@host:~$</code>		#log out, log back in. Now your shell prompt will look like:<br><code>(base) user@host:~$</code>
			#*To toggle it on:<br><code>conda activate /data/tf</code>
	~~Now you can toggle the base and tensorflow python environments, and any other environments that might get added down the road.~~		#*To toggle it off:<br><code>conda deactivate</code>
	#To toggle it on:<br><code>conda activate /data/tf</code>		#*To list all other environments that you can activate<br><code>conda info --envs</code>
	#To toggle it off:<br><code>conda deactivate</code>		#*To list all the packages installed in your current environment:<br><code>conda list</code>
	#To list all other environments that you can activate<br><code>conda info --envs</code>		#It appears everyone has to install tensorflow individually using pip<br><code>pip install tensorflow</code>
	#To list all the packages installed in your current environment:<br><code>conda list</code>

	=Setting up your own ML environment=		=Setting up your own ML environment=

Chris: /* Using the CCN Lab ML Environment */

2022-07-26T17:32:44Z

Using the CCN Lab ML Environment

← Older revision		Revision as of 13:32, 26 July 2022
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	Now you can toggle the base and tensorflow python environments, and any other environments that might get added down the road.		Now you can toggle the base and tensorflow python environments, and any other environments that might get added down the road.
	#To toggle it on:<br><code>conda activate /data/tf</code>		#To toggle it on:<br><code>conda activate /data/tf</code>
	#To toggle it off:<br><code>conda deactivate</~~conda~~>		#To toggle it off:<br><code>conda deactivate</code>
	#To list all other environments that you can activate<br><code>conda info --envs</code>		#To list all other environments that you can activate<br><code>conda info --envs</code>
	#To list all the packages installed in your current environment:<br><code>conda list</code>		#To list all the packages installed in your current environment:<br><code>conda list</code>

Chris: /* Using the CCN Lab ML Environment */

2022-07-26T17:32:22Z

Using the CCN Lab ML Environment

← Older revision		Revision as of 13:32, 26 July 2022
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	#To toggle it on:<br><code>conda activate /data/tf</code>		#To toggle it on:<br><code>conda activate /data/tf</code>
	#To toggle it off:<br><code>conda deactivate</conda>		#To toggle it off:<br><code>conda deactivate</conda>
	#To list all other environments that you can activate<br><~~source~~>conda info --envs</~~source~~>		#To list all other environments that you can activate<br><code>conda info --envs</code>
	#To list all the packages installed in your current environment:<br><code>conda list</code>		#To list all the packages installed in your current environment:<br><code>conda list</code>

Chris: /* Using the CCN Lab ML Environment */

2022-07-26T17:31:48Z

Using the CCN Lab ML Environment

← Older revision		Revision as of 13:31, 26 July 2022
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	The lab primarily uses a Linux environment. We have several workstations running the latest version of [https://ubuntu.com/download Ubuntu]. Our machine learning (ML) research is primarily carried out using Google's [https://www.tensorflow.org/ TensorFlow] libraries, written for Python. Workstations with powerful GPUs can use CUDA for GPU acceleration.		The lab primarily uses a Linux environment. We have several workstations running the latest version of [https://ubuntu.com/download Ubuntu]. Our machine learning (ML) research is primarily carried out using Google's [https://www.tensorflow.org/ TensorFlow] libraries, written for Python. Workstations with powerful GPUs can use CUDA for GPU acceleration.
	=Using the CCN Lab ML Environment=		=Using the CCN Lab ML Environment=
	To avoid clashes between different releases of Python, Tensorflow and whatever libraries are required for a particular ML application, we'll be using Virtual Environments. We have a Python 2.9 virtual environment, which is like a sandbox that all our ML libraries can be installed into and toggled on/off without disrupting anything else. There is a one-time setup procedure every individual user will have to complete:		To avoid clashes between different releases of Python, Tensorflow and whatever libraries are required for a particular ML application, we'll be using Virtual Environments. We have a Python 2.9 virtual environment, which is like a sandbox that all our ML libraries can be installed into and toggled on/off without disrupting anything else. '''There is a one-time setup procedure every individual user will have to complete:'''

	#ssh or open a terminal on ws03		#ssh or open a terminal on ws03
	#run the following command:<br><code>conda init bash</code>		#run the following command:<br><code>conda init bash</code>
	#log out, log back in. Now your shell prompt will look like:<br><code>(base) user@host:~$</code>		#log out, log back in. Now your shell prompt will look like:<br><code>(base) user@host:~$</code>
	Now you can toggle the base and tensorflow python environments.
			Now you can toggle the base and tensorflow python environments, and any other environments that might get added down the road.
	#To toggle it on:<br><code>conda activate /data/tf</code>		#To toggle it on:<br><code>conda activate /data/tf</code>
	#To toggle it off:<br><code>conda deactivate</conda>		#To toggle it off:<br><code>conda deactivate</conda>

Chris: /* Using the CCN Lab ML Environment */

2022-07-26T17:30:53Z

Using the CCN Lab ML Environment

← Older revision		Revision as of 13:30, 26 July 2022
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	#run the following command:<br><code>conda init bash</code>		#run the following command:<br><code>conda init bash</code>
	#log out, log back in. Now your shell prompt will look like:<br><code>(base) user@host:~$</code>		#log out, log back in. Now your shell prompt will look like:<br><code>(base) user@host:~$</code>
	#~~I have created the tf environment in~~ /data/tf. To ~~activate~~ it:<br><code>conda activate /~~data/tf~~</code>		Now you can toggle the base and tensorflow python environments.
			#To toggle it on:<br><code>conda activate /data/tf</code>
			#To toggle it off:<br><code>conda deactivate</conda>
			#To list all other environments that you can activate<br><source>conda info --envs</source>
			#To list all the packages installed in your current environment:<br><code>conda list</code>

	=Setting up your own ML environment=		=Setting up your own ML environment=

Chris: /* Using the CCN Lab ML Environment */

2022-07-26T17:13:21Z

Using the CCN Lab ML Environment

← Older revision		Revision as of 13:13, 26 July 2022
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	#ssh or open a terminal on ws03		#ssh or open a terminal on ws03
	#run the following command:<br><code>conda init bash</code>		#run the following command:<br><code>conda init bash</code>
	#log out, log back in. Now your shell prompt will look like:		#log out, log back in. Now your shell prompt will look like:<br><code>(base) user@host:~$</code>
	(base) user@host:~$		#I have created the tf environment in /data/tf. To activate it:<br><code>conda activate /data/tf</code>
	#I have created the tf environment in /data/tf. To activate it:
	conda activate /data/tf

	=Setting up your own ML environment=		=Setting up your own ML environment=

Chris: /* Using the CCN Lab ML Environment */

2022-07-26T17:12:46Z

Using the CCN Lab ML Environment

← Older revision		Revision as of 13:12, 26 July 2022
Line 4:		Line 4:

	#ssh or open a terminal on ws03		#ssh or open a terminal on ws03
	#run the following command:		#run the following command:<br><code>conda init bash</code>
	conda init bash
	#log out, log back in. Now your shell prompt will look like:		#log out, log back in. Now your shell prompt will look like:
	(base) user@host:~$		(base) user@host:~$

Chris: /* Using the CCN Lab ML Environment */

2022-07-26T17:12:19Z

Using the CCN Lab ML Environment

← Older revision		Revision as of 13:12, 26 July 2022
Line 1:		Line 1:
	The lab primarily uses a Linux environment. We have several workstations running the latest version of [https://ubuntu.com/download Ubuntu]. Our machine learning (ML) research is primarily carried out using Google's [https://www.tensorflow.org/ TensorFlow] libraries, written for Python. Workstations with powerful GPUs can use CUDA for GPU acceleration.		The lab primarily uses a Linux environment. We have several workstations running the latest version of [https://ubuntu.com/download Ubuntu]. Our machine learning (ML) research is primarily carried out using Google's [https://www.tensorflow.org/ TensorFlow] libraries, written for Python. Workstations with powerful GPUs can use CUDA for GPU acceleration.
	=Using the CCN Lab ML Environment=		=Using the CCN Lab ML Environment=
	To avoid clashes between different releases of Python, Tensorflow and whatever libraries are required for a particular ML application, we'll be using Virtual Environments. ~~CASET has set up~~ a Python 2.9 environment ~~for us~~. There is a one-time setup procedure every individual user will have to complete:		To avoid clashes between different releases of Python, Tensorflow and whatever libraries are required for a particular ML application, we'll be using Virtual Environments. We have a Python 2.9 virtual environment, which is like a sandbox that all our ML libraries can be installed into and toggled on/off without disrupting anything else. There is a one-time setup procedure every individual user will have to complete:

	#ssh or open a terminal on ws03		#ssh or open a terminal on ws03
	#run ~~<code>~~conda init bash~~</code>~~		#run the following command:
			conda init bash
	#log out, log back in. Now your shell prompt will look like:		#log out, log back in. Now your shell prompt will look like:
	(base) user@host:~$		(base) user@host:~$
			#I have created the tf environment in /data/tf. To activate it:
			conda activate /data/tf

	=Setting up your own ML environment=		=Setting up your own ML environment=