diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index 7468c77f..db9008f5 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -31,7 +31,7 @@ jobs:
       - run: pip install 'pre-commit<4.0.0'
       - run: pre-commit --version
       - run: pre-commit install
-      - run: pre-commit run --all-files
+      - run: pre-commit run --all-files --show-diff-on-failure
 
   check_docs:
     needs: [linting]
diff --git a/docs/profiling_test.py b/docs/profiling_test.py
index 3c701472..d73816d9 100644
--- a/docs/profiling_test.py
+++ b/docs/profiling_test.py
@@ -83,7 +83,7 @@
         """
         experiment=profiling \
         algorithm=example \
-        resources=one_gpu \
+        resources=gpu \
         hydra.launcher.gres='gpu:a100:1' \
         hydra.launcher.cpus_per_task=4 \
         datamodule.num_workers=8 \
diff --git a/project/algorithms/callbacks/samples_per_second.py b/project/algorithms/callbacks/samples_per_second.py
index 523956b3..4062b480 100644
--- a/project/algorithms/callbacks/samples_per_second.py
+++ b/project/algorithms/callbacks/samples_per_second.py
@@ -57,11 +57,11 @@ def on_shared_batch_end(
         if phase in self.last_step_times:
             elapsed = now - self.last_step_times[phase]
             batch_size = self.get_num_samples(batch)
-            self.log(
+            pl_module.log(
                 f"{phase}/samples_per_second",
                 batch_size / elapsed,
-                module=pl_module,
-                trainer=trainer,
+                # module=pl_module,
+                # trainer=trainer,
                 prog_bar=True,
                 on_step=True,
                 on_epoch=True,
@@ -114,11 +114,11 @@ def on_before_optimizer_step(
             key = "ups"
         else:
             key = f"optimizer_{opt_idx}/ups"
-        self.log(
+        pl_module.log(
             key,
             updates_per_second,
-            module=pl_module,
-            trainer=trainer,
+            # module=pl_module,
+            # trainer=trainer,
             prog_bar=False,
             on_step=True,
         )
diff --git a/project/algorithms/jax_rl_example_test.py b/project/algorithms/jax_rl_example_test.py
index d94d7eb3..e70c17e7 100644
--- a/project/algorithms/jax_rl_example_test.py
+++ b/project/algorithms/jax_rl_example_test.py
@@ -645,6 +645,7 @@ def get_num_samples(self, batch: TrajectoryWithLastObs) -> int:
     def on_fit_end(self, trainer: lightning.Trainer, pl_module: lightning.LightningModule) -> None:
         super().on_fit_end(trainer, pl_module)
 
+    @override
     def log(
         self,
         name: str,
diff --git a/project/configs/__init__.py b/project/configs/__init__.py
index 7584138a..3ce3f441 100644
--- a/project/configs/__init__.py
+++ b/project/configs/__init__.py
@@ -3,17 +3,19 @@
 from __future__ import annotations
 
 from hydra.core.config_store import ConfigStore
+from omegaconf import OmegaConf
 
 from project.configs.algorithm.network import network_store
 from project.configs.algorithm.optimizer import optimizers_store
 from project.configs.config import Config
 from project.configs.datamodule import datamodule_store
-
-# from project.utils.env_vars import REPO_ROOTDIR, SLURM_JOB_ID, SLURM_TMPDIR
+from project.utils.remote_launcher_plugin import RemoteSlurmQueueConf
 
 cs = ConfigStore.instance()
 cs.store(name="base_config", node=Config)
 
+OmegaConf.register_new_resolver("eval", eval)
+
 
 def add_configs_to_hydra_store():
     """Adds all configs to the Hydra Config store."""
@@ -21,6 +23,13 @@ def add_configs_to_hydra_store():
     network_store.add_to_hydra_store()
     optimizers_store.add_to_hydra_store()
 
+    ConfigStore.instance().store(
+        group="hydra/launcher",
+        name="remote_submitit_slurm",
+        node=RemoteSlurmQueueConf,
+        provider="Mila",
+    )
+
 
 # todo: move the algorithm_store.add_to_hydra_store() here?
 
diff --git a/project/configs/cluster/beluga.yaml b/project/configs/cluster/beluga.yaml
new file mode 100644
index 00000000..86463dac
--- /dev/null
+++ b/project/configs/cluster/beluga.yaml
@@ -0,0 +1,12 @@
+# @package _global_
+defaults:
+  - narval
+
+# Use this to specify which remote slurm cluster the job should run on.
+# Remember to also use the resources group to select the resources allocated to the job!
+
+hydra:
+  launcher:
+    executor:
+      cluster_hostname: beluga
+      internet_access_on_compute_nodes: false
diff --git a/project/configs/cluster/cedar.yaml b/project/configs/cluster/cedar.yaml
new file mode 100644
index 00000000..89235bbe
--- /dev/null
+++ b/project/configs/cluster/cedar.yaml
@@ -0,0 +1,12 @@
+# @package _global_
+defaults:
+  - narval
+
+# Use this to specify which remote slurm cluster the job should run on.
+# Remember to also use the resources group to select the resources allocated to the job!
+
+hydra:
+  launcher:
+    executor:
+      cluster_hostname: cedar
+      internet_access_on_compute_nodes: true
diff --git a/project/configs/cluster/current.yaml b/project/configs/cluster/current.yaml
new file mode 100644
index 00000000..a2a3d2da
--- /dev/null
+++ b/project/configs/cluster/current.yaml
@@ -0,0 +1,14 @@
+# @package _global_
+defaults:
+  - override /hydra/launcher: patched_submitit_slurm
+hydra:
+  mode: MULTIRUN
+  run:
+    # output directory, generated dynamically on each run
+    dir: logs/${name}/runs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+  sweep:
+    dir: logs/${name}/multiruns
+    subdir: ${hydra.job.id}
+  launcher:
+    stderr_to_stdout: true
+    submitit_folder: ${hydra.sweep.dir}/%j
diff --git a/project/configs/cluster/mila.yaml b/project/configs/cluster/mila.yaml
new file mode 100644
index 00000000..639dc9ad
--- /dev/null
+++ b/project/configs/cluster/mila.yaml
@@ -0,0 +1,24 @@
+# @package _global_
+defaults:
+  - override /hydra/launcher: remote_submitit_slurm
+
+# Use this to specify which remote slurm cluster the job should run on.
+# Remember to also use the resources group to select the resources allocated to the job!
+hydra:
+  mode: MULTIRUN
+  run:
+    # output directory, generated dynamically on each run
+    dir: logs/${name}/runs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+  sweep:
+    dir: logs/${name}/multiruns
+    subdir: ${hydra.job.id}
+
+  launcher:
+    executor:
+      _target_: remote_slurm_executor.RemoteSlurmExecutor
+      _partial_: true
+      folder: "${hydra.sweep.dir}/%j"
+      cluster_hostname: mila
+      internet_access_on_compute_nodes: true
+
+    stderr_to_stdout: true
diff --git a/project/configs/cluster/narval.yaml b/project/configs/cluster/narval.yaml
new file mode 100644
index 00000000..7e608999
--- /dev/null
+++ b/project/configs/cluster/narval.yaml
@@ -0,0 +1,9 @@
+# @package _global_
+defaults:
+  - mila.yaml
+
+hydra:
+  launcher:
+    executor:
+      cluster_hostname: narval
+      internet_access_on_compute_nodes: false
diff --git a/project/configs/config.yaml b/project/configs/config.yaml
index 2b894931..79d8bae2 100644
--- a/project/configs/config.yaml
+++ b/project/configs/config.yaml
@@ -5,9 +5,9 @@ defaults:
   - optional datamodule: null
   - trainer: default.yaml
   - hydra: default.yaml
-
-  # Allows launching LOTS of runs in parallel on a cluster thanks to the submitit launcher.
   - resources: null
+  # Allows launching LOTS of runs in parallel on a cluster thanks to the submitit launcher.
+  - cluster: null
 
   # experiment configs allow for version control of specific hyperparameters
   # e.g. best hyperparameters for given model and datamodule
diff --git a/project/configs/resources/cpu.yaml b/project/configs/resources/cpu.yaml
new file mode 100644
index 00000000..328da608
--- /dev/null
+++ b/project/configs/resources/cpu.yaml
@@ -0,0 +1,23 @@
+# @package _global_
+defaults:
+  - override /hydra/launcher: patched_submitit_slurm
+trainer:
+  accelerator: cpu
+  devices: auto
+
+hydra:
+  mode: MULTIRUN
+  launcher:
+    nodes: 1
+    tasks_per_node: 1
+    cpus_per_task: 8
+    mem_gb: 16
+    array_parallelism: 16 # max num of jobs to run in parallel
+    # Other things to pass to `sbatch`:
+    additional_parameters:
+      time: 1-00:00:00 # maximum wall time allocated for the job (D-HH:MM:SS)
+
+
+    ## A list of commands to add to the generated sbatch script before running srun:
+    # setup:
+    # - export LD_PRELOAD=/some/folder/with/libraries/
diff --git a/project/configs/resources/gpu.yaml b/project/configs/resources/gpu.yaml
new file mode 100644
index 00000000..39c02c26
--- /dev/null
+++ b/project/configs/resources/gpu.yaml
@@ -0,0 +1,22 @@
+# @package _global_
+defaults:
+  - override /hydra/launcher: patched_submitit_slurm
+
+hydra:
+  mode: MULTIRUN
+  launcher:
+    cpus_per_task: 4
+    gpus_per_task: 1
+    array_parallelism: 16 # max num of jobs to run in parallel
+    # Other things to pass to `sbatch`:
+    additional_parameters:
+      time: 1-00:00:00 # maximum wall time allocated for the job (D-HH:MM:SS)
+      # TODO: It would be better to have those be arguments to the launcher (as is the case in the
+      # RemoteLauncherPlugin), that way we could use only SLURM argument names..
+      nodes: 1
+      mem: 16G
+      ntasks_per_node: 1
+
+    ## A list of commands to add to the generated sbatch script before running srun:
+    # setup:
+    # - export LD_PRELOAD=/some/folder/with/libraries/
diff --git a/project/configs/resources/one_gpu.yaml b/project/configs/resources/one_gpu.yaml
deleted file mode 100644
index 5d684b08..00000000
--- a/project/configs/resources/one_gpu.yaml
+++ /dev/null
@@ -1,26 +0,0 @@
-# @package _global_
-defaults:
-  - override /hydra/launcher: submitit_slurm
-trainer:
-  accelerator: gpu
-  devices: 1
-
-hydra:
-  mode: MULTIRUN
-  launcher:
-    cpus_per_task: 2
-    nodes: 1
-    # TODO: Pack more than one job on a single GPU.
-    tasks_per_node: 1
-    mem_gb: 16
-    array_parallelism: 16  # max num of jobs to run in parallel
-    gres: gpu:1
-    # Other things to pass to `sbatch`:
-    additional_parameters:
-      time: 1-00:00:00  # maximum wall time allocated for the job (D-HH:MM:SS)
-
-    ## A list of commands to add to the generated sbatch script before running srun:
-    setup:
-    - unset CUDA_VISIBLE_DEVICES
-    # - export CUDA_VISIBLE_DEVICES="0"
-    # - export LD_PRELOAD=/some/folder/with/libraries/
diff --git a/project/configs/resources/two_gpus.yaml b/project/configs/resources/two_gpus.yaml
deleted file mode 100644
index 7c8852b5..00000000
--- a/project/configs/resources/two_gpus.yaml
+++ /dev/null
@@ -1,6 +0,0 @@
-# @package _global_
-defaults:
-  - one_gpu.yaml
-hydra:
-  launcher:
-    gres: gpu:rtx8000:2
diff --git a/project/utils/remote_launcher_plugin.py b/project/utils/remote_launcher_plugin.py
new file mode 100644
index 00000000..1eb551b5
--- /dev/null
+++ b/project/utils/remote_launcher_plugin.py
@@ -0,0 +1,284 @@
+# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
+# https://github.com/facebookresearch/hydra/blob/main/examples/plugins/example_launcher_plugin/hydra_plugins/example_launcher_plugin/example_launcher.py
+
+import dataclasses
+import functools
+import logging
+import os
+import warnings
+from collections.abc import Callable, Sequence
+from pathlib import Path
+from typing import Any
+
+import hydra_zen
+from hydra.core.config_store import ConfigStore
+from hydra.core.plugins import Plugins
+from hydra.core.singleton import Singleton
+from hydra.core.utils import JobReturn, filter_overrides
+from hydra.plugins.plugin import Plugin
+from hydra.utils import instantiate
+from hydra_plugins.hydra_submitit_launcher.submitit_launcher import BaseSubmititLauncher
+from omegaconf import DictConfig
+from remote_slurm_executor.slurm_remote import RemoteSlurmExecutor
+from remote_slurm_executor.utils import LoginNode
+
+logger = logging.getLogger(__name__)
+
+
+def _instantiate(self: Plugins, config: DictConfig) -> Plugin:
+    """FIX annoying Hydra thing: plugins have to be in an "approved" `hydra_plugins` namespace?!"""
+    from hydra._internal import utils as internal_utils
+
+    classname = internal_utils._get_cls_name(config, pop=False)
+    try:
+        if classname is None:
+            raise ImportError("class not configured")
+
+        if not self.is_in_toplevel_plugins_module(classname):
+            # NOTE: This is the weirdly strict thing we're patching:
+            # "All plugins must be defined inside the approved top level modules."
+            # "For plugins outside of hydra-core, the approved module is hydra_plugins."
+            # raise RuntimeError(f"Invalid plugin '{classname}': not the hydra_plugins package")
+            plugin = instantiate(config)
+            assert isinstance(plugin, Plugin)
+            return plugin
+
+        if classname not in self.class_name_to_class.keys():
+            raise RuntimeError(f"Unknown plugin class : '{classname}'")
+        clazz = self.class_name_to_class[classname]
+        plugin = instantiate(config=config, _target_=clazz)
+        assert isinstance(plugin, Plugin)
+
+    except ImportError as e:
+        raise ImportError(
+            f"Could not instantiate plugin {classname} : {str(e)}\n\n\tIS THE PLUGIN INSTALLED?\n\n"
+        )
+
+    return plugin
+
+
+Plugins._instantiate = _instantiate
+
+
+class RemoteSlurmLauncher(BaseSubmititLauncher):
+    _EXECUTOR = "remoteslurm"
+
+    def __init__(
+        self,
+        executor: Callable[[], RemoteSlurmExecutor],
+        account: str | None = None,
+        array_parallelism: int = 256,
+        comment: str | None = None,
+        constraint: str | None = None,
+        cpus_per_gpu: int | None = None,
+        cpus_per_task: int | None = None,
+        dependency: str | None = None,
+        exclude: str | None = None,
+        exclusive: bool | None = None,
+        gpus_per_node: int | str | None = None,
+        gpus_per_task: int | str | None = None,
+        gres: str | None = None,
+        # job_name: str = "submitit",
+        job_name: str = "submitit-${hydra.job.name}",
+        mail_type: str | None = None,
+        mail_user: str | None = None,
+        mem: str | None = None,
+        mem_per_cpu: str | None = None,
+        mem_per_gpu: str | None = None,
+        nodelist: str | None = None,
+        nodes: int = 1,
+        ntasks_per_node: int | None = None,
+        num_gpus: int | None = None,
+        partition: str | None = None,
+        qos: str | None = None,
+        setup: list[str] | None = None,
+        signal_delay_s: int = 90,
+        srun_args: list[str] | None = None,
+        stderr_to_stdout: bool = True,  # changed!
+        time: str | int = 5,
+        use_srun: bool = True,
+        wckey: str = "submitit",
+        additional_parameters: dict | None = None,
+        tasks_per_node: int | None = None,
+        mem_gb: int | None = None,
+    ) -> None:
+        setup = setup or []
+        additional_parameters = additional_parameters or {}
+        self.executor = executor()
+        cluster = self.executor.cluster_hostname
+
+        if account is None and len(available_accounts := get_slurm_accounts(cluster)) > 1:
+            # NOTE: tends to favour rrg-*_gpu accounts on DRAC.
+            account = sorted(available_accounts)[-1]
+            warnings.warn(
+                UserWarning(
+                    f"The slurm account to use wasn't passed, and you have multiple accounts on "
+                    f"the {cluster} cluster: {available_accounts}\n"
+                    f"Will use --account={account} when launching jobs."
+                )
+            )
+
+        if setup is not None and (executor_setup := self.executor.parameters.get("setup")):
+            # The executor already has some lines in "setup", don't overwrite those later.
+            setup = executor_setup + setup
+        if mem_gb is not None:
+            assert mem is None, "can't use both mem and mem_gb"
+            mem = f"{mem_gb}GB"
+        if tasks_per_node is not None:
+            assert ntasks_per_node is None, "can't use both tasks_per_node and ntasks_per_node"
+            ntasks_per_node = tasks_per_node
+
+        super().__init__(
+            account=account,
+            array_parallelism=array_parallelism,
+            comment=comment,
+            constraint=constraint,
+            cpus_per_gpu=cpus_per_gpu,
+            cpus_per_task=cpus_per_task,
+            dependency=dependency,
+            exclude=exclude,
+            exclusive=exclusive,
+            gpus_per_node=gpus_per_node,
+            gpus_per_task=gpus_per_task,
+            gres=gres,
+            job_name=job_name,
+            mail_type=mail_type,
+            mail_user=mail_user,
+            mem=mem,
+            mem_per_cpu=mem_per_cpu,
+            mem_per_gpu=mem_per_gpu,
+            nodelist=nodelist,
+            nodes=nodes,
+            num_gpus=num_gpus,
+            partition=partition,
+            qos=qos,
+            setup=setup,
+            signal_delay_s=signal_delay_s,
+            srun_args=srun_args,
+            stderr_to_stdout=stderr_to_stdout,
+            time=time,
+            use_srun=use_srun,
+            wckey=wckey,
+            additional_parameters=additional_parameters,
+        )
+        self.executor.update_parameters(**self.params)
+
+    def launch(
+        self, job_overrides: Sequence[Sequence[str]], initial_job_idx: int
+    ) -> Sequence[JobReturn]:
+        # lazy import to ensure plugin discovery remains fast
+
+        assert self.config is not None
+
+        num_jobs = len(job_overrides)
+        assert num_jobs > 0
+        # specify resources/parameters\
+        # Do *not* overwrite the `setup` if it's already in the executor's parameters!
+
+        # TODO: Make sure that if `launch` is called multiple times, `update_parameters` isn't (or
+        # that it being called multiple times doesn't cause issues).
+
+        logger.info(
+            f"Submitit '{self._EXECUTOR}' sweep output dir : " f"{self.config.hydra.sweep.dir}"
+        )
+        sweep_dir = Path(str(self.config.hydra.sweep.dir))
+        sweep_dir.mkdir(parents=True, exist_ok=True)
+        if "mode" in self.config.hydra.sweep:
+            mode = int(str(self.config.hydra.sweep.mode), 8)
+            os.chmod(sweep_dir, mode=mode)
+
+        job_params: list[tuple[list[str], str, int, str, dict]] = []
+        for idx, overrides in enumerate(job_overrides):
+            idx = initial_job_idx + idx
+            lst = " ".join(filter_overrides(overrides))
+            logger.info(f"\t#{idx} : {lst}")
+            job_params.append(
+                (
+                    list(overrides),
+                    "hydra.sweep.dir",
+                    idx,
+                    f"job_id_for_{idx}",
+                    Singleton.get_state(),
+                )
+            )
+        # NOTE: A bit weird that the executor is pickling itself here, but oh well.
+        jobs = self.executor.map_array(self, *zip(*job_params))
+        print(f"JOB IDS: {[j.job_id for j in jobs]}")
+        # TODO: Here the results of all tasks other than task 0 is ignored. This is bad!
+        # If we have `--ntasks-per-gpu`, then perhaps the other task results are different results
+        # for different seeds, or something similar!
+        return [j.results()[0] for j in jobs]
+
+
+@functools.cache
+def get_slurm_accounts(cluster: str) -> list[str]:
+    """Gets the SLURM accounts of the user using sacctmgr on the slurm cluster."""
+    logger.debug(f"Fetching the list of SLURM accounts available on the {cluster} cluster.")
+    result = LoginNode(cluster).run(
+        "sacctmgr --noheader show associations where user=$USER format=Account%50"
+    )
+    accounts = [line.strip() for line in result.stdout.splitlines()]
+    assert accounts
+    return accounts
+
+
+RemoteSlurmQueueConf = hydra_zen.builds(
+    RemoteSlurmLauncher,
+    populate_full_signature=True,
+    # zen_partial=True,
+    hydra_convert="object",
+    zen_dataclass={"cls_name": "RemoteSlurmQueueConf"},
+)
+
+
+from hydra_plugins.hydra_submitit_launcher.config import SlurmQueueConf  # noqa
+from hydra_plugins.hydra_submitit_launcher.submitit_launcher import SlurmLauncher  # noqa
+# from hydra_plugins.hydra_submitit_launcher. import SlurmLauncher  # noqa
+
+from submitit.slurm.slurm import _make_sbatch_string  # noqa
+
+# Interesting idea: Create the config based on the signature of that function directly.
+_AddedArgumentsConf = hydra_zen.builds(
+    _make_sbatch_string,
+    populate_full_signature=True,
+    hydra_convert="object",
+    zen_exclude=["command", "folder", "map_count"],
+)
+
+
+@dataclasses.dataclass
+class PatchedSlurmQueueConf(_AddedArgumentsConf, SlurmQueueConf):
+    """Adds more SLURM parameters to the config for the SLURM submitit launcher of Hydra."""
+
+    _target_: str = "hydra_plugins.hydra_submitit_launcher.submitit_launcher.SlurmLauncher"  # type: ignore
+
+    signal_delay_s: int = 120
+    """USR1 signal delay before timeout."""
+
+    max_num_timeout: int = 0
+    """Maximum number of retries on job timeout.
+
+    Change this only after you confirmed your code can handle re-submission by properly resuming
+    from the latest stored checkpoint. check the following for more info on slurm_max_num_timeout
+    https://github.com/facebookincubator/submitit/blob/master/docs/checkpointing.md
+    """
+
+    additional_parameters: dict[str, Any] = dataclasses.field(default_factory=dict)
+    """Useful to add parameters which are not currently available in the plugin.
+
+    Eg: {"mail-user": "blublu@fb.com", "mail-type": "BEGIN"}
+    """
+
+    array_parallelism: int = 256
+    """Maximum number of jobs running in parallel."""
+
+    setup: list[str] | None = None
+    """A list of commands to run in sbatch before running srun."""
+
+
+ConfigStore.instance().store(
+    group="hydra/launcher",
+    name="patched_submitit_slurm",
+    node=PatchedSlurmQueueConf,
+    provider="Mila",
+)
diff --git a/project/utils/remote_launcher_plugin_test.py b/project/utils/remote_launcher_plugin_test.py
new file mode 100644
index 00000000..a412bf00
--- /dev/null
+++ b/project/utils/remote_launcher_plugin_test.py
@@ -0,0 +1,118 @@
+# Make a Mock for the remote slurm launcher plugin
+# Use monkeypatch.setattr(project.utils.remote_launcher_plugin, ..., that_mock)
+# Assert That the mock launcher plugin was instantiated
+import os
+import sys
+from pathlib import Path
+from unittest.mock import Mock
+
+import hydra.utils
+import omegaconf
+import pytest
+from hydra import compose, initialize_config_module
+from hydra_plugins.hydra_submitit_launcher.config import SlurmQueueConf
+from hydra_plugins.hydra_submitit_launcher.submitit_launcher import SlurmLauncher
+from milatools.utils.remote_v2 import is_already_logged_in
+
+import project.main
+import project.utils.remote_launcher_plugin
+from project.configs.config_test import CONFIG_DIR
+from project.main import PROJECT_NAME, main
+from project.utils import remote_launcher_plugin
+from project.utils.remote_launcher_plugin import RemoteSlurmLauncher
+
+
+def _yaml_files_in(directory: str | Path, recursive: bool = False):
+    directory = Path(directory)
+    glob = directory.rglob if recursive else directory.glob
+    return list(glob("*.yml")) + list(glob("*.yaml"))
+
+
+cluster_configs = _yaml_files_in(CONFIG_DIR / "cluster")
+resource_configs = _yaml_files_in(CONFIG_DIR / "resources")
+
+
+@pytest.mark.skipif("SLURM_JOB_ID" in os.environ, reason="Can't be run on the cluster just yet.")
+@pytest.mark.parametrize(
+    "overrides",
+    [
+        pytest.param(
+            f"algorithm=example datamodule=cifar10 cluster={cluster.stem} resources={resources.stem}",
+            marks=pytest.mark.skipif(
+                cluster != "mila" and not is_already_logged_in(cluster.stem),
+                reason="Logging in would go through 2FA!",
+            ),
+        )
+        for cluster in cluster_configs
+        for resources in resource_configs
+    ],
+    indirect=True,
+)
+def test_can_load_configs(command_line_arguments: list[str]):
+    """Test that the cluster and resource configs can be loaded without errors."""
+
+    with initialize_config_module(
+        config_module=f"{PROJECT_NAME}.configs",
+        job_name="test",
+        version_base="1.2",
+    ):
+        _config = compose(
+            config_name="config",
+            overrides=command_line_arguments,
+            return_hydra_config=True,
+        )
+
+        launcher_config = _config["hydra"]["launcher"]
+        assert launcher_config["_target_"] in [
+            remote_launcher_plugin.RemoteSlurmQueueConf._target_,
+            SlurmQueueConf._target_,
+        ]
+        # TODO: Also try to instantiate these configs.
+
+        if launcher_config["_target_"] == remote_launcher_plugin.RemoteSlurmQueueConf._target_:
+            with omegaconf.open_dict(launcher_config):
+                launcher_config["executor"]["_synced"] = True  # avoid syncing the code here.
+            launcher = hydra.utils.instantiate(launcher_config)
+            assert isinstance(launcher, remote_launcher_plugin.RemoteSlurmLauncher)
+        else:
+            launcher = hydra.utils.instantiate(launcher_config)
+            assert isinstance(launcher, SlurmLauncher)
+
+
+in_github_CI = os.environ.get("GITHUB_ACTIONS") == "true"
+
+
+@pytest.mark.skipif(
+    in_github_CI,
+    # Fails since it will actually sync the code with git push, and a branch isn't checked out.
+    reason="Can't be run on the CI",
+)
+@pytest.mark.skipif("SLURM_JOB_ID" in os.environ, reason="Shouldn't be run on the cluster.")
+@pytest.mark.slow()
+@pytest.mark.parametrize(
+    "argv",
+    [
+        [
+            "algorithm=example",
+            "datamodule=cifar10",
+            # TODO: The ordering is important here, we can't use `cluster` before `resources`,
+            # otherwise it will use the local launcher!
+            "resources=gpu",
+            "cluster=mila",
+            "+trainer.fast_dev_run=True",
+        ]
+    ],
+)
+def test_run_remote_job(argv: list[str], monkeypatch: pytest.MonkeyPatch):
+    launcher_mock = Mock(spec=RemoteSlurmLauncher, wraps=RemoteSlurmLauncher)
+    launcher_mock.__qualname__ = RemoteSlurmLauncher.__qualname__
+    monkeypatch.setattr(
+        project.utils.remote_launcher_plugin, RemoteSlurmLauncher.__name__, launcher_mock
+    )
+
+    monkeypatch.setattr(sys, "argv", ["project/main.py"] + argv)
+    monkeypatch.setitem(os.environ, "HYDRA_FULL_ERROR", "1")
+
+    main()
+
+    launcher_mock.assert_called_once()
diff --git a/pyproject.toml b/pyproject.toml
index 19ee2ce4..b78d8f6b 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -38,6 +38,7 @@ dependencies = [
     "gymnasium[classic-control]>=0.29.1",
     "mkdocs>=1.6.1",
     "mkdocstrings[python]>=0.26.2",
+    "remote-slurm-executor",
 ]
 readme = "README.md"
 requires-python = ">= 3.10"
@@ -113,7 +114,7 @@ packages = ["project"]
 managed = true
 dev-dependencies = [
     "mktestdocs>=0.2.2",
-    "pre-commit>=3.8.0",
+    "pre-commit<4.0.0",
     "pytest-benchmark>=4.0.0",
     "pytest-cov>=5.0.0",
     "pytest-env>=1.1.3",
@@ -127,6 +128,9 @@ dev-dependencies = [
     "tensor-regression>=0.0.8",
 ]
 
+[tool.uv.sources]
+remote-slurm-executor = { git = "https://github.com/lebrice/remote-slurm-executor", branch = "master" }
+
 # [tool.uv.tasks]
 # serve-docs = "mkdocs serve"
 # check_torch_gpu = "python -c 'import torch; print(torch.cuda.is_available())'"
diff --git a/uv.lock b/uv.lock
index a8ef8e91..c0e2b898 100644
--- a/uv.lock
+++ b/uv.lock
@@ -127,6 +127,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643 },
 ]
 
+[[package]]
+name = "ansicon"
+version = "1.89.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/b6/e2/1c866404ddbd280efedff4a9f15abfe943cb83cde6e895022370f3a61f85/ansicon-1.89.0.tar.gz", hash = "sha256:e4d039def5768a47e4afec8e89e83ec3ae5a26bf00ad851f914d1240b444d2b1", size = 67312 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/75/f9/f1c10e223c7b56a38109a3f2eb4e7fe9a757ea3ed3a166754fb30f65e466/ansicon-1.89.0-py2.py3-none-any.whl", hash = "sha256:f1def52d17f65c2c9682cf8370c03f541f410c1752d6a14029f97318e4b9dfec", size = 63675 },
+]
+
 [[package]]
 name = "antlr4-python3-runtime"
 version = "4.9.3"
@@ -169,6 +178,38 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/ed/20/bc79bc575ba2e2a7f70e8a1155618bb1301eaa5132a8271373a6903f73f8/babel-2.16.0-py3-none-any.whl", hash = "sha256:368b5b98b37c06b7daf6696391c3240c938b37767d4584413e8438c5c435fa8b", size = 9587599 },
 ]
 
+[[package]]
+name = "bcrypt"
+version = "4.2.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/e4/7e/d95e7d96d4828e965891af92e43b52a4cd3395dc1c1ef4ee62748d0471d0/bcrypt-4.2.0.tar.gz", hash = "sha256:cf69eaf5185fd58f268f805b505ce31f9b9fc2d64b376642164e9244540c1221", size = 24294 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/a9/81/4e8f5bc0cd947e91fb720e1737371922854da47a94bc9630454e7b2845f8/bcrypt-4.2.0-cp37-abi3-macosx_10_12_universal2.whl", hash = "sha256:096a15d26ed6ce37a14c1ac1e48119660f21b24cba457f160a4b830f3fe6b5cb", size = 471568 },
+    { url = "https://files.pythonhosted.org/packages/05/d2/1be1e16aedec04bcf8d0156e01b987d16a2063d38e64c3f28030a3427d61/bcrypt-4.2.0-cp37-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c02d944ca89d9b1922ceb8a46460dd17df1ba37ab66feac4870f6862a1533c00", size = 277372 },
+    { url = "https://files.pythonhosted.org/packages/e3/96/7a654027638ad9b7589effb6db77eb63eba64319dfeaf9c0f4ca953e5f76/bcrypt-4.2.0-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1d84cf6d877918620b687b8fd1bf7781d11e8a0998f576c7aa939776b512b98d", size = 273488 },
+    { url = "https://files.pythonhosted.org/packages/46/54/dc7b58abeb4a3d95bab653405935e27ba32f21b812d8ff38f271fb6f7f55/bcrypt-4.2.0-cp37-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:1bb429fedbe0249465cdd85a58e8376f31bb315e484f16e68ca4c786dcc04291", size = 277759 },
+    { url = "https://files.pythonhosted.org/packages/ac/be/da233c5f11fce3f8adec05e8e532b299b64833cc962f49331cdd0e614fa9/bcrypt-4.2.0-cp37-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:655ea221910bcac76ea08aaa76df427ef8625f92e55a8ee44fbf7753dbabb328", size = 273796 },
+    { url = "https://files.pythonhosted.org/packages/b0/b8/8b4add88d55a263cf1c6b8cf66c735280954a04223fcd2880120cc767ac3/bcrypt-4.2.0-cp37-abi3-musllinux_1_1_aarch64.whl", hash = "sha256:1ee38e858bf5d0287c39b7a1fc59eec64bbf880c7d504d3a06a96c16e14058e7", size = 311082 },
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+]
+
 [[package]]
 name = "beautifulsoup4"
 version = "4.12.3"
@@ -215,6 +256,20 @@ wheels = [
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+[[package]]
+name = "blessed"
+version = "1.20.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "jinxed", marker = "platform_system == 'Windows'" },
+    { name = "six" },
+    { name = "wcwidth" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/25/ae/92e9968ad23205389ec6bd82e2d4fca3817f1cdef34e10aa8d529ef8b1d7/blessed-1.20.0.tar.gz", hash = "sha256:2cdd67f8746e048f00df47a2880f4d6acbcdb399031b604e34ba8f71d5787680", size = 6655612 }
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 version = "1.8.2"
@@ -277,6 +332,63 @@ wheels = [
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