Commit 07e73105 authored by Natasha Pavlovikj's avatar Natasha Pavlovikj
Browse files

Update conda page and fix broken link

parent f1857029
...@@ -122,6 +122,13 @@ Our new environment is now active, and we can use it. The shell prompt will cha ...@@ -122,6 +122,13 @@ Our new environment is now active, and we can use it. The shell prompt will cha
### Adding and Removing Packages from an Existing Environment ### Adding and Removing Packages from an Existing Environment
{{% notice note %}}
**NOTE:** By default, conda packages are installed in the user's `home` directory.
Since Crane's `home` directories are not writeable from the worker nodes,
the commands for installing, adding and removing conda packages shown here
should be performed on the **login node**, and not as part of an interactive or SLURM job.
{{% /notice %}}
To install additional packages in an environment, use the `install` To install additional packages in an environment, use the `install`
subcommand. Suppose we want to install iPython in our 'mynumpy' subcommand. Suppose we want to install iPython in our 'mynumpy'
environment. While the environment is active, use `install `with no environment. While the environment is active, use `install `with no
...@@ -230,7 +237,7 @@ Jupyter Notebook. To do so, follow the steps below, replacing ...@@ -230,7 +237,7 @@ Jupyter Notebook. To do so, follow the steps below, replacing
server. server.
3. Click the logout button in the top right corner. 3. Click the logout button in the top right corner.
2. Using the command-line environment, load the target conda 2. Using the command-line environment of the **login node**, load the target conda
environment: environment:
{{< highlight bash >}}conda activate myenv{{< /highlight >}} {{< highlight bash >}}conda activate myenv{{< /highlight >}}
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...@@ -153,7 +153,7 @@ srun --pty --mem=4gb --qos=short --gres=gpu --partition=gpu $SHELL ...@@ -153,7 +153,7 @@ srun --pty --mem=4gb --qos=short --gres=gpu --partition=gpu $SHELL
{{% notice info %}} {{% notice info %}}
The `--gres=gpu --partition=gpu` options are used here as the `tensorflow-gpu` image is The `--gres=gpu --partition=gpu` options are used here as the `tensorflow-gpu` image is
GPU enabled. If you are using a non-GPU image, you may omit those options. See the page GPU enabled. If you are using a non-GPU image, you may omit those options. See the page
on [submitting GPU jobs]({{< relref "/guides/submitting_jobs/submitting_cuda_or_openacc_jobs/_index.md" >}}) on [submitting GPU jobs]({{< relref "../../submitting_jobs/submitting_gpu_jobs/" >}})
for more information. for more information.
{{% /notice %}} {{% /notice %}}
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