From ca591b568d22c9f409828a7c33e5e735874905ff Mon Sep 17 00:00:00 2001 From: Felix Dangel Date: Sun, 8 Sep 2024 12:01:47 -0400 Subject: [PATCH 01/30] [DOC] Start writing walkthrough --- docs/walkthrough.md | 1 + example/README.md | 46 +++++++++++++++++++++++++++++++++++++++++++++ example/launch.sh | 2 +- mkdocs.yml | 2 ++ 4 files changed, 50 insertions(+), 1 deletion(-) create mode 120000 docs/walkthrough.md create mode 100644 example/README.md diff --git a/docs/walkthrough.md b/docs/walkthrough.md new file mode 120000 index 0000000..aead760 --- /dev/null +++ b/docs/walkthrough.md @@ -0,0 +1 @@ +../example/README.md \ No newline at end of file diff --git a/example/README.md b/example/README.md new file mode 100644 index 0000000..4282473 --- /dev/null +++ b/example/README.md @@ -0,0 +1,46 @@ +# Walkthrough + +We will operate inside the [`example`](https://github.com/f-dangel/wandb_preempt/tree/main/example) directory: + +```bash +cd example +``` + +/// details | Details of the training script `example/train.py` ([source](https://github.com/f-dangel/wandb_preempt/blob/main/example/train.py)) +```py +--8<-- "example/train.py" +``` +/// + +/// details | Details of the sweep configuration `example/sweep.yaml` ([source](https://github.com/f-dangel/wandb_preempt/blob/main/example/sweep.yaml)) +```yaml +--8<-- "example/sweep.yaml" +``` +/// + +Let's create a sweep: +```bash +wandb sweep sweep.yaml +``` +Output: + +/// details | Details of the SLURM script `example/launch.sh` ([source](https://github.com/f-dangel/wandb_preempt/blob/main/example/launch.sh)) +```sh +--8<-- "example/launch.sh" +``` +/// + +The launch script divides into three parts: + +1. **SLURM configuration:** The first block specifies the SLURM resources and task array we are about to submit (lines starting with `#SBATCH`). The important configurations are + - `--time` (how long will a job run?) + - `--array` (how many jobs will be submitted?), and + - `--signal` specifications (how much time before the limit will we start pre-empting?) + + **These values are optimized demonstration purposes. You definitely want to tweak them for your use case.** + + The other configuration flags are resource-specific, and some like the `--partition=a40` will depend on your cluster. In our script, we will request NVIDIA A40 GPUs because they support mixed-precision training in `bfloat16` and is used by many modern training pipelines. + +2. **Printing details and wandb agent launch** This part executes the `wandb agent` on our sweep and puts it into the background so our launch script can start listening to signals from SLURM. + +3. **Installing a signal handler** diff --git a/example/launch.sh b/example/launch.sh index 3d4ce27..15e95ef 100644 --- a/example/launch.sh +++ b/example/launch.sh @@ -7,7 +7,7 @@ #SBATCH --mem-per-gpu=16G #SBATCH --time=00:04:00 #SBATCH --qos=m5 -#SBATCH --array=0-19 +#SBATCH --array=0-9 #SBATCH --signal=B:SIGUSR1@120 # Send signal SIGUSR1 120 seconds before the job hits the time limit #SBATCH --open-mode=append diff --git a/mkdocs.yml b/mkdocs.yml index 23bea15..0a1f652 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -8,6 +8,7 @@ watch: nav: - Getting Started: index.md - API Documentation: api.md + - Walkthroug Example: walkthrough.md - Developer Notes: develop.md theme: name: material @@ -24,6 +25,7 @@ markdown_extensions: - pymdownx.inlinehilite # code highlighting - pymdownx.snippets # code highlighting - pymdownx.superfences # code highlighting + - pymdownx.blocks.details # fold-able content - footnotes plugins: - mkdocstrings: From 1304ddbaad529fcd02ed2c01b9d4aebff1ec9821 Mon Sep 17 00:00:00 2001 From: Felix Dangel Date: Mon, 9 Sep 2024 15:28:53 -0400 Subject: [PATCH 02/30] [DOC] Progress on walkthrough --- example/README.md | 255 ++++++++++++++++++++++++++++++++++++++++++++- example/sweep.yaml | 2 +- mkdocs.yml | 2 +- 3 files changed, 252 insertions(+), 7 deletions(-) diff --git a/example/README.md b/example/README.md index 4282473..b308990 100644 --- a/example/README.md +++ b/example/README.md @@ -1,28 +1,273 @@ # Walkthrough -We will operate inside the [`example`](https://github.com/f-dangel/wandb_preempt/tree/main/example) directory: +## Overview +This section explains how to create and launch a preempt-able `wandb` sweep on a SLURM cluster. You have to set up three files: + +1. A training script (e.g. `train.py`) that the sweep will execute multiple times using different hyper-parameters. + +2. A `wandb` sweep configuration script (e.g. `sweep.yaml`) that defines the hyper-parameter search space. + +3. A SLURM launch script (e.g. `launch.sh`) which we will use to submit runs on the cluster. + +The repository's [`example`](https://github.com/f-dangel/wandb_preempt/tree/main/example) directory contains examples for each of these files, and here we will demonstrate how to make them work together. We will operate inside the example directory, so let's navigate to it: ```bash cd example ``` +## Training Script + +First up, we need to write a training script that we will sweep over, i.e. call with different hyper-parameters. + +For demonstration purposes, we will train a small CNN on MNIST using SGD, and our goal is to find a good learning rate through random search using a `wandb` sweep. To keep things simple and cheap, we fix a batch size and use a (very) small number of epochs. Finally, we also use a learning rate scheduler and mixed-precision training with a gradient scaler. These are overkill for MNIST, of course. But we want to show how these need to be checkpointed. In summary, we will call the training script using the following pattern: +```bash +python train.py --lr=X +``` +with `X` some floating point number. + +The training script also contains code to checkpoint the training loop at the end of an epoch whenever the Python process receives a `SIGUSR1` signal from the OS. Roughly speaking, we need to create a `Checkpointer` that is responsible for saving and storing checkpoints, listening to signals, and for initiating the job requeue on the cluster. Every time we call the checkpointer's `.step` function, it will save a checkpoint and check whether a signal has been sent that indicates we must pre-empt and requeue. For more details, please expand the code snippet. + /// details | Details of the training script `example/train.py` ([source](https://github.com/f-dangel/wandb_preempt/blob/main/example/train.py)) -```py +```py hl_lines="37-38 40-41" --8<-- "example/train.py" ``` /// +## Sweep Configuration + +Our next goal will be to define and create a sweep. + +For that, we need to write a `.yaml` file which specifies how the training script is called, and how the search space looks like. To learn more, have a look at the [Weights & Biases documentation](https://docs.wandb.ai/guides/sweeps/define-sweep-configuration). + +The following configuration file defines a random search over the learning rate, using a log-uniform search space. Note that you need to modify the `entity` and `project` entries to match with a `wandb` project that you have access to. + /// details | Details of the sweep configuration `example/sweep.yaml` ([source](https://github.com/f-dangel/wandb_preempt/blob/main/example/sweep.yaml)) -```yaml +```yaml hl_lines="1 2" --8<-- "example/sweep.yaml" ``` /// -Let's create a sweep: +Let's create the sweep: ```bash wandb sweep sweep.yaml ``` -Output: +/// details | Output +```sh hl_lines="4" +wandb: Creating sweep from: sweep.yaml +wandb: Creating sweep with ID: aaq70gt8 +wandb: View sweep at: https://wandb.ai/f-dangel-team/quickstart/sweeps/aaq70gt8 +wandb: Run sweep agent with: wandb agent f-dangel-team/quickstart/aaq70gt8 +``` +/// + +The important part of that output is the command in the last line. Copy it for later. + +Navigate to the `wandb` web interface and you should be able to see the sweep: + +![empty sweep](./assets/01_empty_sweep.png) + +**Optional step:** To make sure the configuration file works, I will execute a single run locally on my machine as a sanity check. This step is optional and obviously not recommended if your machine's hardware is not beefy enough (note that I specified the `--count=1` flag to carry out only a single run): + +```bash +wandb agent --count=1 f-dangel-team/quickstart/aaq70gt8 +``` + +/// details | Training script output +``` +wandb: Starting wandb agent ๐Ÿ•ต๏ธ +2024-09-09 15:05:49,720 - wandb.wandb_agent - INFO - Running runs: [] +2024-09-09 15:05:49,962 - wandb.wandb_agent - INFO - Agent received command: run +2024-09-09 15:05:49,963 - wandb.wandb_agent - INFO - Agent starting run with config: + lr: 0.0014109383616700757 + max_epochs: 20 +2024-09-09 15:05:49,966 - wandb.wandb_agent - INFO - About to run command: /usr/bin/env python train.py --lr=0.0014109383616700757 --max_epochs=20 +Environment variables containing 'WANDB' +WANDB_ENTITY: f-dangel-team +WANDB_PROJECT: quickstart +WANDB_SWEEP_ID: aaq70gt8 +WANDB_DIR: ~/wandb_preempt/example +WANDB_RUN_ID: mxgkpzzn +WANDB_SWEEP_PARAM_PATH: ~/wandb_preempt/example/wandb/sweep-aaq70gt8/config-mxgkpzzn.yaml +Agent's run has ID mxgkpzzn and state running. Using resume='allow'. +wandb: Currently logged in as: f-dangel (f-dangel-team). Use `wandb login --relogin` to force relogin +wandb: Tracking run with wandb version 0.17.9 +wandb: Run data is saved locally in ~/wandb_preempt/example/wandb/run-20240909_150552-mxgkpzzn +wandb: Run `wandb offline` to turn off syncing. +wandb: Syncing run colorful-sweep-3 +wandb: โญ๏ธ View project at https://wandb.ai/f-dangel-team/quickstart +wandb: ๐Ÿงน View sweep at https://wandb.ai/f-dangel-team/quickstart/sweeps/aaq70gt8 +wandb: ๐Ÿš€ View run at https://wandb.ai/f-dangel-team/quickstart/runs/mxgkpzzn +2024-09-09 15:05:54,989 - wandb.wandb_agent - INFO - Running runs: ['mxgkpzzn'] +Using SGD with learning rate 0.0014109383616700757. +[0.0 s | 2024-09-09 15:05:55.010675] Creating checkpoint directory: ~/wandb_preempt/example/checkpoints. +[0.0 s | 2024-09-09 15:05:55.010766] SLURM job ID: None, array ID: None, task ID: None +[0.0 s | 2024-09-09 15:05:55.010984] No checkpoint found. Starting from scratch. +Epoch 0, Step 0, Loss 2.31327e+00 +Epoch 0, Step 50, Loss 2.31711e+00 +Epoch 0, Step 100, Loss 2.30655e+00 +Epoch 0, Step 150, Loss 2.30137e+00 +Epoch 0, Step 200, Loss 2.30741e+00 +[2.8 s | 2024-09-09 15:05:57.818613] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000000.pt. +Epoch 1, Step 0, Loss 2.29989e+00 +Epoch 1, Step 50, Loss 2.31124e+00 +Epoch 1, Step 100, Loss 2.30144e+00 +Epoch 1, Step 150, Loss 2.28741e+00 +Epoch 1, Step 200, Loss 2.30759e+00 +[5.5 s | 2024-09-09 15:06:00.536954] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000001.pt. +[5.5 s | 2024-09-09 15:06:00.538081] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000000.pt. +Epoch 2, Step 0, Loss 2.28908e+00 +Epoch 2, Step 50, Loss 2.28920e+00 +Epoch 2, Step 100, Loss 2.29056e+00 +Epoch 2, Step 150, Loss 2.28977e+00 +Epoch 2, Step 200, Loss 2.29214e+00 +[8.2 s | 2024-09-09 15:06:03.259775] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000002.pt. +[8.3 s | 2024-09-09 15:06:03.260907] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000001.pt. +Epoch 3, Step 0, Loss 2.28515e+00 +Epoch 3, Step 50, Loss 2.29505e+00 +Epoch 3, Step 100, Loss 2.28214e+00 +Epoch 3, Step 150, Loss 2.27602e+00 +Epoch 3, Step 200, Loss 2.28020e+00 +[11.0 s | 2024-09-09 15:06:05.982865] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000003.pt. +[11.0 s | 2024-09-09 15:06:05.983939] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000002.pt. +Epoch 4, Step 0, Loss 2.27190e+00 +Epoch 4, Step 50, Loss 2.28208e+00 +Epoch 4, Step 100, Loss 2.27995e+00 +Epoch 4, Step 150, Loss 2.26419e+00 +Epoch 4, Step 200, Loss 2.26638e+00 +[13.7 s | 2024-09-09 15:06:08.706617] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000004.pt. +[13.7 s | 2024-09-09 15:06:08.707936] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000003.pt. +Epoch 5, Step 0, Loss 2.25696e+00 +Epoch 5, Step 50, Loss 2.26390e+00 +Epoch 5, Step 100, Loss 2.25003e+00 +Epoch 5, Step 150, Loss 2.25402e+00 +Epoch 5, Step 200, Loss 2.24690e+00 +[16.4 s | 2024-09-09 15:06:11.447655] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000005.pt. +[16.4 s | 2024-09-09 15:06:11.448819] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000004.pt. +Epoch 6, Step 0, Loss 2.24057e+00 +Epoch 6, Step 50, Loss 2.23889e+00 +Epoch 6, Step 100, Loss 2.24205e+00 +Epoch 6, Step 150, Loss 2.23790e+00 +Epoch 6, Step 200, Loss 2.23253e+00 +[19.2 s | 2024-09-09 15:06:14.191520] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000006.pt. +[19.2 s | 2024-09-09 15:06:14.192684] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000005.pt. +Epoch 7, Step 0, Loss 2.22399e+00 +Epoch 7, Step 50, Loss 2.20625e+00 +Epoch 7, Step 100, Loss 2.20944e+00 +Epoch 7, Step 150, Loss 2.20490e+00 +Epoch 7, Step 200, Loss 2.20541e+00 +[21.9 s | 2024-09-09 15:06:16.919781] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000007.pt. +[21.9 s | 2024-09-09 15:06:16.920934] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000006.pt. +Epoch 8, Step 0, Loss 2.19063e+00 +Epoch 8, Step 50, Loss 2.18892e+00 +Epoch 8, Step 100, Loss 2.17470e+00 +Epoch 8, Step 150, Loss 2.16582e+00 +Epoch 8, Step 200, Loss 2.16229e+00 +[24.6 s | 2024-09-09 15:06:19.642306] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000008.pt. +[24.6 s | 2024-09-09 15:06:19.643417] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000007.pt. +Epoch 9, Step 0, Loss 2.15864e+00 +Epoch 9, Step 50, Loss 2.14666e+00 +Epoch 9, Step 100, Loss 2.13153e+00 +Epoch 9, Step 150, Loss 2.13505e+00 +Epoch 9, Step 200, Loss 2.12925e+00 +[27.3 s | 2024-09-09 15:06:22.357240] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000009.pt. +[27.3 s | 2024-09-09 15:06:22.358962] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000008.pt. +Epoch 10, Step 0, Loss 2.10835e+00 +Epoch 10, Step 50, Loss 2.10394e+00 +Epoch 10, Step 100, Loss 2.09672e+00 +Epoch 10, Step 150, Loss 2.08576e+00 +Epoch 10, Step 200, Loss 2.10477e+00 +[30.1 s | 2024-09-09 15:06:25.068843] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000010.pt. +[30.1 s | 2024-09-09 15:06:25.069888] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000009.pt. +Epoch 11, Step 0, Loss 2.05669e+00 +Epoch 11, Step 50, Loss 2.05382e+00 +Epoch 11, Step 100, Loss 2.03040e+00 +Epoch 11, Step 150, Loss 2.03818e+00 +Epoch 11, Step 200, Loss 2.01292e+00 +[32.8 s | 2024-09-09 15:06:27.767231] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000011.pt. +[32.8 s | 2024-09-09 15:06:27.768345] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000010.pt. +Epoch 12, Step 0, Loss 2.02450e+00 +Epoch 12, Step 50, Loss 1.98715e+00 +Epoch 12, Step 100, Loss 2.00718e+00 +Epoch 12, Step 150, Loss 1.99295e+00 +Epoch 12, Step 200, Loss 1.97624e+00 +[35.6 s | 2024-09-09 15:06:30.564774] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000012.pt. +[35.6 s | 2024-09-09 15:06:30.565946] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000011.pt. +Epoch 13, Step 0, Loss 1.95026e+00 +Epoch 13, Step 50, Loss 1.94186e+00 +Epoch 13, Step 100, Loss 1.94720e+00 +Epoch 13, Step 150, Loss 1.95091e+00 +Epoch 13, Step 200, Loss 1.96935e+00 +[38.3 s | 2024-09-09 15:06:33.267992] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000013.pt. +[38.3 s | 2024-09-09 15:06:33.269097] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000012.pt. +Epoch 14, Step 0, Loss 1.88487e+00 +Epoch 14, Step 50, Loss 1.92402e+00 +Epoch 14, Step 100, Loss 1.93435e+00 +Epoch 14, Step 150, Loss 1.87301e+00 +Epoch 14, Step 200, Loss 1.91263e+00 +[40.9 s | 2024-09-09 15:06:35.931019] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000014.pt. +[40.9 s | 2024-09-09 15:06:35.932336] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000013.pt. +Epoch 15, Step 0, Loss 1.88196e+00 +Epoch 15, Step 50, Loss 1.90995e+00 +Epoch 15, Step 100, Loss 1.86447e+00 +Epoch 15, Step 150, Loss 1.88345e+00 +Epoch 15, Step 200, Loss 1.88344e+00 +[43.6 s | 2024-09-09 15:06:38.633177] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000015.pt. +[43.6 s | 2024-09-09 15:06:38.634305] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000014.pt. +Epoch 16, Step 0, Loss 1.85623e+00 +Epoch 16, Step 50, Loss 1.88199e+00 +Epoch 16, Step 100, Loss 1.84634e+00 +Epoch 16, Step 150, Loss 1.79202e+00 +Epoch 16, Step 200, Loss 1.84115e+00 +[46.4 s | 2024-09-09 15:06:41.416646] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000016.pt. +[46.4 s | 2024-09-09 15:06:41.417763] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000015.pt. +Epoch 17, Step 0, Loss 1.86561e+00 +Epoch 17, Step 50, Loss 1.80409e+00 +Epoch 17, Step 100, Loss 1.81886e+00 +Epoch 17, Step 150, Loss 1.82025e+00 +Epoch 17, Step 200, Loss 1.81553e+00 +[49.2 s | 2024-09-09 15:06:44.194540] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000017.pt. +[49.2 s | 2024-09-09 15:06:44.195673] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000016.pt. +Epoch 18, Step 0, Loss 1.80697e+00 +Epoch 18, Step 50, Loss 1.79723e+00 +Epoch 18, Step 100, Loss 1.83584e+00 +Epoch 18, Step 150, Loss 1.81160e+00 +Epoch 18, Step 200, Loss 1.83512e+00 +[52.5 s | 2024-09-09 15:06:47.510459] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000018.pt. +[52.5 s | 2024-09-09 15:06:47.511873] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000017.pt. +Epoch 19, Step 0, Loss 1.79649e+00 +Epoch 19, Step 50, Loss 1.82962e+00 +Epoch 19, Step 100, Loss 1.80719e+00 +Epoch 19, Step 150, Loss 1.82502e+00 +Epoch 19, Step 200, Loss 1.79152e+00 +[55.3 s | 2024-09-09 15:06:50.269146] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000019.pt. +[55.3 s | 2024-09-09 15:06:50.270317] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000018.pt. +wandb: +wandb: +wandb: Run history: +wandb: loss โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‡โ–ˆโ–‡โ–‡โ–‡โ–‡โ–‡โ–‡โ–†โ–†โ–†โ–†โ–…โ–…โ–…โ–„โ–„โ–„โ–ƒโ–ƒโ–ƒโ–‚โ–ƒโ–‚โ–‚โ–โ–โ–โ–โ–โ–‚โ– +wandb: loss_scale โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ– +wandb: lr โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‡โ–‡โ–‡โ–‡โ–‡โ–‡โ–†โ–†โ–†โ–†โ–…โ–…โ–„โ–„โ–„โ–„โ–ƒโ–ƒโ–ƒโ–ƒโ–‚โ–‚โ–‚โ–‚โ–‚โ–‚โ–โ–โ–โ–โ–โ– +wandb: resumes โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ– +wandb: +wandb: Run summary: +wandb: loss 1.79152 +wandb: loss_scale 1.0 +wandb: lr 1e-05 +wandb: resumes 0 +wandb: +wandb: ๐Ÿš€ View run colorful-sweep-3 at: https://wandb.ai/f-dangel-team/quickstart/runs/mxgkpzzn +wandb: โญ๏ธ View project at: https://wandb.ai/f-dangel-team/quickstart +wandb: Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s) +wandb: Find logs at: ./wandb/run-20240909_150552-mxgkpzzn/logs +wandb: WARNING The new W&B backend becomes opt-out in version 0.18.0; try it out with `wandb.require("core")`! See https://wandb.me/wandb-core for more information. +[61.0 s | 2024-09-09 15:06:56.003246] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/mxgkpzzn_00000019.pt. +2024-09-09 15:07:01,045 - wandb.wandb_agent - INFO - Cleaning up finished run: mxgkpzzn +wandb: Terminating and syncing runs. Press ctrl-c to kill. +``` +/// + +## SLURM Launcher + /// details | Details of the SLURM script `example/launch.sh` ([source](https://github.com/f-dangel/wandb_preempt/blob/main/example/launch.sh)) ```sh diff --git a/example/sweep.yaml b/example/sweep.yaml index a108eb0..c573d7e 100644 --- a/example/sweep.yaml +++ b/example/sweep.yaml @@ -17,4 +17,4 @@ parameters: min: 1e-3 max: 1e-1 max_epochs: - value: 150 + value: 20 diff --git a/mkdocs.yml b/mkdocs.yml index 0a1f652..48b94de 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -8,7 +8,7 @@ watch: nav: - Getting Started: index.md - API Documentation: api.md - - Walkthroug Example: walkthrough.md + - Walkthrough Example: walkthrough.md - Developer Notes: develop.md theme: name: material From 36a808163874d2a2ad948d1a9b33a9b275974daa Mon Sep 17 00:00:00 2001 From: Felix Dangel Date: Mon, 9 Sep 2024 16:17:59 -0400 Subject: [PATCH 03/30] [DOC] More progress --- example/README.md | 17 ++++++++++++++--- example/launch.sh | 6 +++--- 2 files changed, 17 insertions(+), 6 deletions(-) diff --git a/example/README.md b/example/README.md index b308990..dace975 100644 --- a/example/README.md +++ b/example/README.md @@ -66,7 +66,9 @@ Navigate to the `wandb` web interface and you should be able to see the sweep: ![empty sweep](./assets/01_empty_sweep.png) -**Optional step:** To make sure the configuration file works, I will execute a single run locally on my machine as a sanity check. This step is optional and obviously not recommended if your machine's hardware is not beefy enough (note that I specified the `--count=1` flag to carry out only a single run): +### Optional Step: Local Run + +To make sure the configuration file works, I will execute a single run locally on my machine as a sanity check. This step is optional and obviously not recommended if your machine's hardware is not beefy enough (note that I specified the `--count=1` flag to carry out only a single run): ```bash wandb agent --count=1 f-dangel-team/quickstart/aaq70gt8 @@ -266,15 +268,24 @@ wandb: Terminating and syncing runs. Press ctrl-c to kill. ``` /// +On the Weights & Biases web API, we can see the successfully finished run: + +![local run](./assets/02_local_run.png) + ## SLURM Launcher +The last step is to launch multiple jobs on a SLURM cluster. + +For that, we use the following launch script and insert the wandb agent's command into it. We will explain the script in more detail below; for now our focus is to demonstrate how everything works. /// details | Details of the SLURM script `example/launch.sh` ([source](https://github.com/f-dangel/wandb_preempt/blob/main/example/launch.sh)) -```sh +```sh hl_lines="10-12 23" --8<-- "example/launch.sh" ``` /// + +## Details The launch script divides into three parts: 1. **SLURM configuration:** The first block specifies the SLURM resources and task array we are about to submit (lines starting with `#SBATCH`). The important configurations are @@ -282,7 +293,7 @@ The launch script divides into three parts: - `--array` (how many jobs will be submitted?), and - `--signal` specifications (how much time before the limit will we start pre-empting?) - **These values are optimized demonstration purposes. You definitely want to tweak them for your use case.** + **These values are optimized for demonstration purposes. You definitely want to tweak them for your use case.** The other configuration flags are resource-specific, and some like the `--partition=a40` will depend on your cluster. In our script, we will request NVIDIA A40 GPUs because they support mixed-precision training in `bfloat16` and is used by many modern training pipelines. diff --git a/example/launch.sh b/example/launch.sh index 15e95ef..c0daf47 100644 --- a/example/launch.sh +++ b/example/launch.sh @@ -5,11 +5,11 @@ #SBATCH --gres=gpu:1 #SBATCH --cpus-per-gpu=4 #SBATCH --mem-per-gpu=16G -#SBATCH --time=00:04:00 #SBATCH --qos=m5 +#SBATCH --open-mode=append +#SBATCH --time=00:04:00 #SBATCH --array=0-9 #SBATCH --signal=B:SIGUSR1@120 # Send signal SIGUSR1 120 seconds before the job hits the time limit -#SBATCH --open-mode=append echo "Job $SLURM_JOB_NAME ($SLURM_JOB_ID) begins on $(hostname), submitted from $SLURM_SUBMIT_HOST ($SLURM_CLUSTER_NAME)" echo "" @@ -20,7 +20,7 @@ if [ "$SLURM_ARRAY_TASK_COUNT" != "" ]; then fi # NOTE that we need to use srun here, otherwise the Python process won't receive the SIGUSR1 signal -srun --unbuffered wandb agent --count=1 f-dangel-team/quickstart/i75puhon & +srun --unbuffered wandb agent --count=1 f-dangel-team/quickstart/aaq70gt8 & child="$!" # Set up a handler to pass the SIGUSR1 to the python session launched by the agent From a94e461b07c195b0b444e6a774089c90bd217112 Mon Sep 17 00:00:00 2001 From: Felix Dangel Date: Mon, 9 Sep 2024 22:21:19 -0400 Subject: [PATCH 04/30] [ADD] Create new sweep because training script args changed --- docs/README.md | 0 example/launch.sh | 2 +- example/sweep.yaml | 2 +- 3 files changed, 2 insertions(+), 2 deletions(-) delete mode 100644 docs/README.md diff --git a/docs/README.md b/docs/README.md deleted file mode 100644 index e69de29..0000000 diff --git a/example/launch.sh b/example/launch.sh index f265522..9de031b 100644 --- a/example/launch.sh +++ b/example/launch.sh @@ -20,7 +20,7 @@ if [ "$SLURM_ARRAY_TASK_COUNT" != "" ]; then fi # NOTE that we need to use srun here, otherwise the Python process won't receive the SIGUSR1 signal -srun --unbuffered wandb agent --count=1 f-dangel-team/quickstart/aaq70gt8 & +srun --unbuffered wandb agent --count=1 f-dangel-team/quickstart/qmzevsi8 & child="$!" # Set up a handler to pass the SIGUSR1 to the python session launched by the agent diff --git a/example/sweep.yaml b/example/sweep.yaml index c573d7e..0333644 100644 --- a/example/sweep.yaml +++ b/example/sweep.yaml @@ -16,5 +16,5 @@ parameters: distribution: log_uniform_values min: 1e-3 max: 1e-1 - max_epochs: + epochs: value: 20 From a8c24728905351079dbb3f7428d06b8d5907fd49 Mon Sep 17 00:00:00 2001 From: Felix Dangel Date: Mon, 9 Sep 2024 22:28:44 -0400 Subject: [PATCH 05/30] [BUG] Always return tuple in `load_latest_checkpoint` --- example/train.py | 2 +- wandb_preempt/checkpointer.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/example/train.py b/example/train.py index 67ad852..a8e6510 100755 --- a/example/train.py +++ b/example/train.py @@ -82,7 +82,7 @@ def main(args): # NOTE: If existing, load model, optimizer, and learning rate scheduler state from # latest checkpoint, set random number generator states, and recover the epoch to # start training from. Does nothing if there was no checkpoint. - start_epoch = checkpointer.load_latest_checkpoint() + start_epoch, _ = checkpointer.load_latest_checkpoint() # training for epoch in range(start_epoch, args.epochs): diff --git a/wandb_preempt/checkpointer.py b/wandb_preempt/checkpointer.py index 9657be1..ac3cdca 100644 --- a/wandb_preempt/checkpointer.py +++ b/wandb_preempt/checkpointer.py @@ -189,7 +189,7 @@ def load_latest_checkpoint(self) -> Tuple[int, Dict]: loadpath = self.latest_checkpoint() if loadpath is None: self.maybe_print("No checkpoint found. Starting from scratch.") - return 0 + return 0, {} self.maybe_print(f"Loading checkpoint {loadpath}.") 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zkJK+w@%@EWTxslgZ&Yj@96Il8+Z^wWD>5D%JsbD2t;_!Bt#9u$lL!ZQTnjL4wK%ps z&zch)+QQR&zlGU_bYz8*0aeV<_V+e1pTFq}o!$xj-Om13HzHwZ4^Z;arx+W*J6oMa zweGLiuohpiHwFXs`#R=MXLZzFcdvOvOcZ$WOem`v0Zi=-IAx`G+wA)PZ>RD zZF98}(zuJzwDZI;0eK z5_zf!?xS7kyMLAD(;b3;bKpJxGNB>$`@()MoO1Mhh}~vYvDNSoB>j%_wfd2-A6?fF z@;@F-$KSg)>=nR1l1e@asDe@(^ZyF*c?MRwG^lw|pU^$IF(r|b6}xg!Gx4vGh(4CTK&QvalkNKHIM zt2;svdoP(#Du7I4O}g^E!{LJh)>c@v8nU~i@9*Dp0Gtzh6e>r>@A(}bM4jx;m+LO& z@aBFpiNM(zvKg&@|27U517wU@v=JdHf#VxA+g#ZFWFWxN zc_mxpEyaDqg~yQPOIB*ic*%S(8DbfL4A@R0|9 Date: Tue, 10 Sep 2024 15:00:45 -0400 Subject: [PATCH 07/30] [FIX] SLURM array detection --- wandb_preempt/checkpointer.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/wandb_preempt/checkpointer.py b/wandb_preempt/checkpointer.py index ac3cdca..57d50c3 100644 --- a/wandb_preempt/checkpointer.py +++ b/wandb_preempt/checkpointer.py @@ -305,7 +305,7 @@ def maybe_requeue_slurm_job(self): array_id = getenv("SLURM_ARRAY_JOB_ID") task_id = getenv("SLURM_ARRAY_TASK_ID") - uses_array = array_id is None and task_id is None + uses_array = array_id is not None and task_id is not None requeue_id = f"{array_id}_{task_id}" if uses_array else job_id cmd = ["scontrol", "requeue", requeue_id] From 97fb006fa91dcdb8ab3dc6fd25087479eca9a38d Mon Sep 17 00:00:00 2001 From: Scott Lowe Date: Tue, 10 Sep 2024 16:33:58 -0400 Subject: [PATCH 08/30] [DOC] Link to wandb and Slurm webpages --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 698c08b..26a173a 100644 --- a/README.md +++ b/README.md @@ -2,9 +2,9 @@ [![Documentation Status](https://readthedocs.org/projects/wandb-preempt/badge/?version=latest)](https://wandb-preempt.readthedocs.io/en/latest/?badge=latest) -This repository contains a tutorial on how to combine `wandb` sweeps with -Slurm's pre-emption, i.e. how to automatically re-queue and resume runs from a -Weights & Biases sweep on a Slurm cluster. +This repository contains a tutorial on how to combine [wandb](https://wandb.ai/) sweeps +with [Slurm](https://slurm.schedmd.com/)'s pre-emption, i.e. how to automatically +re-queue and resume runs from a Weights & Biases sweep on a Slurm cluster. This is work in progress: From f8418005d9f5ba3b2e1ef15b6d7183acef1d9082 Mon Sep 17 00:00:00 2001 From: Scott Lowe Date: Tue, 10 Sep 2024 16:34:23 -0400 Subject: [PATCH 09/30] [DOC] Fix docstrings --- wandb_preempt/checkpointer.py | 14 ++++++++------ 1 file changed, 8 insertions(+), 6 deletions(-) diff --git a/wandb_preempt/checkpointer.py b/wandb_preempt/checkpointer.py index 57d50c3..0d71b5c 100644 --- a/wandb_preempt/checkpointer.py +++ b/wandb_preempt/checkpointer.py @@ -25,10 +25,10 @@ class Checkpointer: How to use this class: - - Create an instance in your training loop, `checkpointer = Checkpointer(...)`. + - Create an instance of this class `checkpointer = Checkpointer(...)`. - At the end of each epoch, call `checkpointer.step()` to save a checkpoint. - If the job received the `SIGUSR1` signal, the checkpointer will requeue the at - the end of its checkpointing step. + If the job received the `SIGUSR1` or `SIGTERM` signal, the checkpointer will + requeue the Slurm job at the end of its checkpointing step. """ def __init__( @@ -183,8 +183,9 @@ def load_latest_checkpoint(self) -> Tuple[int, Dict]: passed at initialization. Returns: - The epoch number at which training should resume, and the extra information - that was passed by the user as a dictionary to the :meth:`step` function. + epoch: The epoch number at which training should resume. + extra_info: Extra information that was passed by the user to the `step` + function. """ loadpath = self.latest_checkpoint() if loadpath is None: @@ -330,7 +331,8 @@ def step(self, extra_info: Optional[Dict] = None): Args: extra_info: Additional information to save in the checkpoint. This dictionary is returned when loading the latest checkpoint with - :meth:`load_latest_checkpoint`. Default: `None` (empty dictionary). + `checkpointer.load_latest_checkpoint()`. + By default, an empty dictionary is saved. """ self.save_checkpoint({} if extra_info is None else extra_info) # Remove stale checkpoints From 408da2144f4964dd8e9fa5014cff123f4602b433 Mon Sep 17 00:00:00 2001 From: Scott Lowe Date: Tue, 10 Sep 2024 16:37:11 -0400 Subject: [PATCH 10/30] [DOC] Tidy up doc building instructions --- docs/develop.md | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/docs/develop.md b/docs/develop.md index ee089b6..c2cb82d 100644 --- a/docs/develop.md +++ b/docs/develop.md @@ -41,5 +41,9 @@ via `make`: We use the [Google docstring convention](https://sphinxcontrib-napoleon.readthedocs.io/en/latest/example_google.html) -and `mkdocs` which allows using markdown syntax in a docstring to achieve -formatting. To build the docs, run `mkdocs serve` in the repository root. +and [mkdocs](https://www.mkdocs.org/) which allows using markdown syntax in a docstring +to achieve formatting. To build the docs, install the documentation requirements +```bash +pip install -e ."[doc]" +``` +and run `mkdocs serve` from the repository root. From ce204cf2898be8c4d5a4cae724e7e55eec323c03 Mon Sep 17 00:00:00 2001 From: Scott Lowe Date: Tue, 10 Sep 2024 16:49:24 -0400 Subject: [PATCH 11/30] [DOC] Add instructions to clone github repo --- example/README.md | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/example/README.md b/example/README.md index 7de619e..7b1441b 100644 --- a/example/README.md +++ b/example/README.md @@ -12,6 +12,11 @@ This section explains how to create and launch a preempt-able `wandb` sweep on a The repository's [`example`](https://github.com/f-dangel/wandb_preempt/tree/main/example) directory contains examples for each of these files, and here we will demonstrate how to make them work together. We will operate inside the example directory, so let's navigate to it: ```bash +# If you haven't already, you'll need to clone the repository first +git clone git@github.com:f-dangel/wandb_preempt.git +cd wandb_preempt + +# Then navigate to the example directory within the repo cd example ``` From c5b244cf9d2474e12c40677594511ffa7c44a5f2 Mon Sep 17 00:00:00 2001 From: Scott Lowe Date: Tue, 10 Sep 2024 18:12:37 -0400 Subject: [PATCH 12/30] [DOC] Walkthrough improvements --- example/README.md | 39 ++++++++++++++++++++++++--------------- 1 file changed, 24 insertions(+), 15 deletions(-) diff --git a/example/README.md b/example/README.md index 7b1441b..d53cc64 100644 --- a/example/README.md +++ b/example/README.md @@ -2,7 +2,7 @@ ## Overview -This section explains how to create and launch a preempt-able `wandb` sweep on a SLURM cluster. You have to set up three files: +This section explains how to create and launch a preempt-able [wandb sweep](https://docs.wandb.ai/guides/sweeps) on a SLURM cluster. You have to set up three files: 1. A training script (e.g. `train.py`) that the sweep will execute multiple times using different hyper-parameters. @@ -22,15 +22,16 @@ cd example ## Training Script -First up, we need to write a training script that we will sweep over, i.e. call with different hyper-parameters. +First up, we need to write a training script that we will sweep over. The sweep will call this script with different hyper-parameters to find the hyper-parameters that work best. -For demonstration purposes, we will train a small CNN on MNIST using SGD, and our goal is to find a good learning rate through random search using a `wandb` sweep. To keep things simple and cheap, we fix a batch size and use a (very) small number of epochs. Finally, we also use a learning rate scheduler and mixed-precision training with a gradient scaler. These are overkill for MNIST, of course. But we want to show how these need to be checkpointed. In summary, we will call the training script using the following pattern: +For demonstration purposes, we will train a small CNN on MNIST using SGD, and our goal is to find a good learning rate through random search using a `wandb` sweep. To keep things simple and cheap, we fix a batch size and use a (very) small number of epochs. Finally, we also use a learning rate scheduler and mixed-precision training with a gradient scaler. These are overkill for MNIST, of course, but important when training large models so we include them here to show how they are checkpointed too. In summary, we will call the training script using the following pattern: ```bash python train.py --lr=X ``` -with `X` some floating point number. +with `X` being some floating point number that the sweep will search over. -The training script also contains code to checkpoint the training loop at the end of an epoch whenever the Python process receives a `SIGUSR1` signal from the OS. Roughly speaking, we need to create a `Checkpointer` that is responsible for saving and storing checkpoints, listening to signals, and for initiating the job requeue on the cluster. Every time we call the checkpointer's `.step` function, it will save a checkpoint and check whether a signal has been sent that indicates we must pre-empt and requeue. For more details, please expand the code snippet. +The training script also contains code to checkpoint the training loop at the end of an epoch, so we can resume training after our pre-emptable job is interrupted. Roughly speaking, we need to create a `Checkpointer` that is responsible for saving and storing checkpoints, listening to signals from the Slurm process, and for requeuing the job on the cluster if it runs out of time before it is finished. Every time we call the checkpointer's `.step` method, it will save a checkpoint and check whether a signal has been sent by Slurm that indicates our job is about to be killed and so we must preemptively halt it and requeue the job. +For more details, please expand the code snippet below. /// details | Details of the training script `example/train.py` ([source](https://github.com/f-dangel/wandb_preempt/blob/main/example/train.py)) ```py hl_lines="37-38 40-41" @@ -42,9 +43,10 @@ The training script also contains code to checkpoint the training loop at the en Our next goal will be to define and create a sweep. -For that, we need to write a `.yaml` file which specifies how the training script is called, and how the search space looks like. To learn more, have a look at the [Weights & Biases documentation](https://docs.wandb.ai/guides/sweeps/define-sweep-configuration). +For that, we need to write a `.yaml` file which specifies how the training script is called, and what the search space looks like. To learn more, take a look at the [Weights & Biases documentation](https://docs.wandb.ai/guides/sweeps/define-sweep-configuration). -The following configuration file defines a random search over the learning rate, using a log-uniform search space. Note that you need to modify the `entity` and `project` entries to match with a `wandb` project that you have access to. +The following configuration file defines a random search over the learning rate, using a log-uniform density for the search space. +Note that you need to modify the `entity` and `project` entries to match with a `wandb` project that you have access to. /// details | Details of the sweep configuration `example/sweep.yaml` ([source](https://github.com/f-dangel/wandb_preempt/blob/main/example/sweep.yaml)) ```yaml hl_lines="1 2" @@ -52,7 +54,7 @@ The following configuration file defines a random search over the learning rate, ``` /// -Let's create the sweep: +Let's create a sweep using this configuration: ```bash wandb sweep sweep.yaml ``` @@ -65,15 +67,16 @@ wandb: Run sweep agent with: wandb agent f-dangel-team/quickstart/qmzevsi8 ``` /// -The important part of that output is the command in the last line. Copy it for later. +Each sweep has its own ID (you can have more than one sweep in the same project), so to launch jobs in this sweep that we've just recreated, we'll need to launch them using the correct sweep ID. +To do this, note the command in the last line of the outputโ€”copy this to use later. -Navigate to the `wandb` web interface and you should be able to see the sweep: +Navigate to the `wandb` web interface and you should be able to see the sweep now exists: ![empty sweep](./assets/01_empty_sweep.png) ### Optional Step: Local Run -To make sure the configuration file works, I will execute a single run locally on my machine as a sanity check. This step is optional and obviously not recommended if your machine's hardware is not beefy enough (note that I specified the `--count=1` flag to carry out only a single run): +To make sure the configuration file works, I will execute a single run locally on my machine as a sanity check. This step is optional and obviously not recommended if your machine's hardware is not beefy enough (note that I use the command from above, but add the `--count=1` flag to carry out only a single run): ```bash wandb agent --count=1 f-dangel-team/quickstart/aaq70gt8 @@ -273,7 +276,8 @@ On the Weights & Biases web API, we can see the successfully finished run: The last step is to launch multiple jobs on a SLURM cluster. -For that, we use the following launch script and insert the wandb agent's command into it. We will explain the script in more detail below; for now our focus is to launch jobs. +For that, we use the following launch script. If you are running this yourself, you will need to modify the wandb agent command to be the one we copied before, when the wandb sweep was created. Note that we still include the `--count=1` argument, to ensure each Slurm job in the array completes a single task from the sweep. +We will explain the script in more detail below; for now our focus is to launch jobs. /// details | Details of the SLURM script `example/launch.sh` ([source](https://github.com/f-dangel/wandb_preempt/blob/main/example/launch.sh)) ```sh hl_lines="10-12 23" @@ -297,13 +301,18 @@ On the Weights & Biases website, you will see the runs transitioning between the The launch script divides into three parts: 1. **SLURM configuration:** The first block specifies the SLURM resources and task array we are about to submit (lines starting with `#SBATCH`). The important configurations are - - `--time` (how long will a job run?) + - `--time` (how long to request the job will run for?) - `--array` (how many jobs will be submitted?), and - `--signal` specifications (how much time before the limit will we start pre-empting?) - **These values are optimized for demonstration purposes. You definitely want to tweak them for your use case.** + *These values are optimized for demonstration purposes. You definitely want to tweak them for your use case.* - The other configuration flags are resource-specific, and some like the `--partition=a40` will depend on your cluster. In our script, we will request NVIDIA A40 GPUs because they support mixed-precision training in `bfloat16` and is used by many modern training pipelines. + Note that the `--time` request does not need to be the total amount of time the model takes to train, since the `checkpointer` will automatically requeue the job if/when time limit is about to be reached and the training script is still running. + + The `--signal` argument is used to tell the python script that the Slurm job is about to end (using the signal SIGUSR1). The time in the `--signal` argument should be set to (at least) the amount of time (in seconds) between calls to `checkpointer.step()` in your training script. + In the example script, we use an epoch-based training routine, and so the time specified in the signal argument needs to be the amount of time taken to complete one training epoch and save the model, or longer. + + The other configuration flags are resource-specific, and some like the `--partition=a40` will depend on your cluster. In our script, we request NVIDIA A40 GPUs because they support mixed-precision training with `bfloat16` that is used by many modern training pipelines. 2. **Printing details and wandb agent launch** This part executes the `wandb agent` on our sweep and puts it into the background so our launch script can start listening to signals from SLURM. From 65e3391c4c52b953de0a6f2f0e4ec889f2ae30ef Mon Sep 17 00:00:00 2001 From: Scott Lowe Date: Tue, 10 Sep 2024 18:14:16 -0400 Subject: [PATCH 13/30] [MNT] Rename project quickstart -> example-preemptable-sweep --- example/README.md | 16 ++++++++-------- example/launch.sh | 2 +- example/sweep.yaml | 2 +- 3 files changed, 10 insertions(+), 10 deletions(-) diff --git a/example/README.md b/example/README.md index d53cc64..89ee7bd 100644 --- a/example/README.md +++ b/example/README.md @@ -62,8 +62,8 @@ wandb sweep sweep.yaml ```sh hl_lines="4" wandb: Creating sweep from: sweep.yaml wandb: Creating sweep with ID: qmzevsi8 -wandb: View sweep at: https://wandb.ai/f-dangel-team/quickstart/sweeps/qmzevsi8 -wandb: Run sweep agent with: wandb agent f-dangel-team/quickstart/qmzevsi8 +wandb: View sweep at: https://wandb.ai/f-dangel-team/example-preemptable-sweep/sweeps/qmzevsi8 +wandb: Run sweep agent with: wandb agent f-dangel-team/example-preemptable-sweep/qmzevsi8 ``` /// @@ -79,7 +79,7 @@ Navigate to the `wandb` web interface and you should be able to see the sweep no To make sure the configuration file works, I will execute a single run locally on my machine as a sanity check. This step is optional and obviously not recommended if your machine's hardware is not beefy enough (note that I use the command from above, but add the `--count=1` flag to carry out only a single run): ```bash -wandb agent --count=1 f-dangel-team/quickstart/aaq70gt8 +wandb agent --count=1 f-dangel-team/example-preemptable-sweep/aaq70gt8 ``` /// details | Training script output @@ -97,9 +97,9 @@ wandb: Tracking run with wandb version 0.17.9 wandb: Run data is saved locally in ~/wandb_preempt/example/wandb/run-20240909_221710-lmp9ebp1 wandb: Run `wandb offline` to turn off syncing. wandb: Syncing run denim-sweep-1 -wandb: โญ๏ธ View project at https://wandb.ai/f-dangel-team/quickstart -wandb: ๐Ÿงน View sweep at https://wandb.ai/f-dangel-team/quickstart/sweeps/qmzevsi8 -wandb: ๐Ÿš€ View run at https://wandb.ai/f-dangel-team/quickstart/runs/lmp9ebp1 +wandb: โญ๏ธ View project at https://wandb.ai/f-dangel-team/example-preemptable-sweep +wandb: ๐Ÿงน View sweep at https://wandb.ai/f-dangel-team/example-preemptable-sweep/sweeps/qmzevsi8 +wandb: ๐Ÿš€ View run at https://wandb.ai/f-dangel-team/example-preemptable-sweep/runs/lmp9ebp1 Using SGD with learning rate 0.005417051459795853. [0.0 s | 2024-09-09 22:17:14.343841] Creating checkpoint directory: ~/wandb_preempt/example/checkpoints. [0.0 s | 2024-09-09 22:17:14.343944] SLURM job ID: None, array ID: None, task ID: None @@ -257,8 +257,8 @@ wandb: loss_scale 1.0 wandb: lr 3e-05 wandb: resumes 0 wandb: -wandb: ๐Ÿš€ View run denim-sweep-1 at: https://wandb.ai/f-dangel-team/quickstart/runs/lmp9ebp1 -wandb: โญ๏ธ View project at: https://wandb.ai/f-dangel-team/quickstart +wandb: ๐Ÿš€ View run denim-sweep-1 at: https://wandb.ai/f-dangel-team/example-preemptable-sweep/runs/lmp9ebp1 +wandb: โญ๏ธ View project at: https://wandb.ai/f-dangel-team/example-preemptable-sweep wandb: Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s) wandb: Find logs at: ./wandb/run-20240909_221710-lmp9ebp1/logs wandb: WARNING The new W&B backend becomes opt-out in version 0.18.0; try it out with `wandb.require("core")`! See https://wandb.me/wandb-core for more information. diff --git a/example/launch.sh b/example/launch.sh index 9de031b..5ffee29 100644 --- a/example/launch.sh +++ b/example/launch.sh @@ -20,7 +20,7 @@ if [ "$SLURM_ARRAY_TASK_COUNT" != "" ]; then fi # NOTE that we need to use srun here, otherwise the Python process won't receive the SIGUSR1 signal -srun --unbuffered wandb agent --count=1 f-dangel-team/quickstart/qmzevsi8 & +srun --unbuffered wandb agent --count=1 f-dangel-team/example-preemptable-sweep/qmzevsi8 & child="$!" # Set up a handler to pass the SIGUSR1 to the python session launched by the agent diff --git a/example/sweep.yaml b/example/sweep.yaml index 0333644..bd8949d 100644 --- a/example/sweep.yaml +++ b/example/sweep.yaml @@ -1,5 +1,5 @@ entity: f-dangel-team -project: quickstart +project: example-preemptable-sweep name: SGD program: train.py command: From 1433b2772ad4e1ac65260b82e073d31e39155ebb Mon Sep 17 00:00:00 2001 From: Scott Lowe Date: Tue, 10 Sep 2024 18:17:21 -0400 Subject: [PATCH 14/30] [MNT] Use default entity in example sweep --- example/README.md | 2 +- example/sweep.yaml | 1 - 2 files changed, 1 insertion(+), 2 deletions(-) diff --git a/example/README.md b/example/README.md index 89ee7bd..9e3e8a2 100644 --- a/example/README.md +++ b/example/README.md @@ -46,7 +46,7 @@ Our next goal will be to define and create a sweep. For that, we need to write a `.yaml` file which specifies how the training script is called, and what the search space looks like. To learn more, take a look at the [Weights & Biases documentation](https://docs.wandb.ai/guides/sweeps/define-sweep-configuration). The following configuration file defines a random search over the learning rate, using a log-uniform density for the search space. -Note that you need to modify the `entity` and `project` entries to match with a `wandb` project that you have access to. +By default, the example config will create a new project called `example-preemptable-sweep` owned by your default wandb entity (controlled by your [Default team setting](https://wandb.ai/settings)). /// details | Details of the sweep configuration `example/sweep.yaml` ([source](https://github.com/f-dangel/wandb_preempt/blob/main/example/sweep.yaml)) ```yaml hl_lines="1 2" diff --git a/example/sweep.yaml b/example/sweep.yaml index bd8949d..d30fc84 100644 --- a/example/sweep.yaml +++ b/example/sweep.yaml @@ -1,4 +1,3 @@ -entity: f-dangel-team project: example-preemptable-sweep name: SGD program: train.py From de9b69bed8835d92031f7d3e16d44de6393d755f Mon Sep 17 00:00:00 2001 From: Scott Lowe Date: Tue, 10 Sep 2024 19:12:26 -0400 Subject: [PATCH 15/30] [DOC] Need to show remove_checkpoints in API as we use it in example --- docs/api.md | 1 + 1 file changed, 1 insertion(+) diff --git a/docs/api.md b/docs/api.md index e8e6de3..a3da9a5 100644 --- a/docs/api.md +++ b/docs/api.md @@ -4,3 +4,4 @@ - __init__ - load_latest_checkpoint - step + - remove_checkpoints From 095891c953c87cfc2fdc944abdda71e2c2bba934 Mon Sep 17 00:00:00 2001 From: Scott Lowe Date: Tue, 10 Sep 2024 20:58:43 -0400 Subject: [PATCH 16/30] [BUG] Need to load checkpoint step count from file --- wandb_preempt/checkpointer.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/wandb_preempt/checkpointer.py b/wandb_preempt/checkpointer.py index 0d71b5c..ef8efd9 100644 --- a/wandb_preempt/checkpointer.py +++ b/wandb_preempt/checkpointer.py @@ -206,6 +206,7 @@ def load_latest_checkpoint(self) -> Tuple[int, Dict]: self.maybe_print("Loading gradient scaler.") self.scaler.load_state_dict(data["scaler"]) + self.step_count = data["checkpoint_step"] self.num_resumes = data["resumes"] + 1 # restore random number generator states for all devices @@ -216,7 +217,7 @@ def load_latest_checkpoint(self) -> Tuple[int, Dict]: else: set_rng_state(rng_state) - return data["checkpoint_step"] + 1, data["extra_info"] + return self.step_count + 1, data["extra_info"] def remove_checkpoints(self, keep_latest: bool = False): """Remove checkpoints. From fef68fc298eb90b7b502944d0c92b317d30a790a Mon Sep 17 00:00:00 2001 From: Scott Lowe Date: Tue, 10 Sep 2024 21:39:54 -0400 Subject: [PATCH 17/30] [DOC] Update docs --- example/README.md | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/example/README.md b/example/README.md index 9e3e8a2..2783d77 100644 --- a/example/README.md +++ b/example/README.md @@ -13,8 +13,10 @@ This section explains how to create and launch a preempt-able [wandb sweep](http The repository's [`example`](https://github.com/f-dangel/wandb_preempt/tree/main/example) directory contains examples for each of these files, and here we will demonstrate how to make them work together. We will operate inside the example directory, so let's navigate to it: ```bash # If you haven't already, you'll need to clone the repository first -git clone git@github.com:f-dangel/wandb_preempt.git -cd wandb_preempt +git clone git@github.com:f-dangel/wandb_preempt.git && cd wandb_preempt + +# And pip install the package from the repository +pip install -e .[example] # Then navigate to the example directory within the repo cd example @@ -49,7 +51,7 @@ The following configuration file defines a random search over the learning rate, By default, the example config will create a new project called `example-preemptable-sweep` owned by your default wandb entity (controlled by your [Default team setting](https://wandb.ai/settings)). /// details | Details of the sweep configuration `example/sweep.yaml` ([source](https://github.com/f-dangel/wandb_preempt/blob/main/example/sweep.yaml)) -```yaml hl_lines="1 2" +```yaml hl_lines="1" --8<-- "example/sweep.yaml" ``` /// From 71564c6a8316602131100b0e153ef66ff165e50f Mon Sep 17 00:00:00 2001 From: Scott Lowe Date: Tue, 10 Sep 2024 21:42:32 -0400 Subject: [PATCH 18/30] [ENH] Record epoch on wandb.log --- example/train.py | 1 + 1 file changed, 1 insertion(+) diff --git a/example/train.py b/example/train.py index a8e6510..6cd0622 100755 --- a/example/train.py +++ b/example/train.py @@ -101,6 +101,7 @@ def main(args): "loss": loss.item(), "lr": optimizer.param_groups[0]["lr"], "loss_scale": scaler.get_scale(), + "epoch": epoch, "resumes": checkpointer.num_resumes, } ) From fb0e641dc2f4c407288026d74e9fc440eecf34f7 Mon Sep 17 00:00:00 2001 From: Scott Lowe Date: Tue, 10 Sep 2024 22:19:56 -0400 Subject: [PATCH 19/30] [BUG] Don't duplicate lr name with config and measure fields --- example/sweep.yaml | 2 +- example/train.py | 6 +++--- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/example/sweep.yaml b/example/sweep.yaml index d30fc84..dff27dd 100644 --- a/example/sweep.yaml +++ b/example/sweep.yaml @@ -11,7 +11,7 @@ metric: name: loss method: random parameters: - lr: + lr_max: distribution: log_uniform_values min: 1e-3 max: 1e-1 diff --git a/example/train.py b/example/train.py index 6cd0622..5ad7ade 100755 --- a/example/train.py +++ b/example/train.py @@ -26,7 +26,7 @@ def get_parser(): r"""Create argument parser.""" parser = ArgumentParser("Train a simple CNN on MNIST using SGD.") parser.add_argument( - "--lr", type=float, default=0.01, help="Learning rate. Default: %(default)s" + "--lr_max", type=float, default=0.01, help="Learning rate. Default: %(default)s" ) parser.add_argument( "--epochs", type=int, default=10, help="Number of epochs. Default: %(default)s" @@ -62,8 +62,8 @@ def main(args): Linear(50, 10), ).to(DEV) loss_func = CrossEntropyLoss().to(DEV) - print(f"Using SGD with learning rate {args.lr}.") - optimizer = SGD(model.parameters(), lr=args.lr) + print(f"Using SGD with learning rate {args.lr_max}.") + optimizer = SGD(model.parameters(), lr=args.lr_max) lr_scheduler = CosineAnnealingLR(optimizer, T_max=args.epochs) scaler = GradScaler() From 88664d91081ad6511a5a204852684e7189f19ec2 Mon Sep 17 00:00:00 2001 From: Scott Lowe Date: Tue, 10 Sep 2024 22:29:52 -0400 Subject: [PATCH 20/30] [MNT] Import torch.amp instead of deprecated torch.cuda.amp --- example/train.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/example/train.py b/example/train.py index 5ad7ade..520f447 100755 --- a/example/train.py +++ b/example/train.py @@ -8,7 +8,7 @@ import wandb from torch import autocast, bfloat16, cuda, device, manual_seed -from torch.cuda.amp import GradScaler +from torch.amp import GradScaler from torch.nn import Conv2d, CrossEntropyLoss, Flatten, Linear, ReLU, Sequential from torch.optim import SGD from torch.optim.lr_scheduler import CosineAnnealingLR From 1863820541fdc18837ab5f0b62b2c36cfd00a53e Mon Sep 17 00:00:00 2001 From: Scott Lowe Date: Tue, 10 Sep 2024 22:50:51 -0400 Subject: [PATCH 21/30] [MNT] Increase epochs 10 -> 15 --- example/train.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/example/train.py b/example/train.py index 520f447..e183541 100755 --- a/example/train.py +++ b/example/train.py @@ -29,7 +29,7 @@ def get_parser(): "--lr_max", type=float, default=0.01, help="Learning rate. Default: %(default)s" ) parser.add_argument( - "--epochs", type=int, default=10, help="Number of epochs. Default: %(default)s" + "--epochs", type=int, default=15, help="Number of epochs. Default: %(default)s" ) parser.add_argument( "--batch_size", type=int, default=256, help="Batch size. Default: %(default)s" From 289fbb63ee35a05bc30d3b08ff11cd0d8ac813f1 Mon Sep 17 00:00:00 2001 From: Scott Lowe Date: Tue, 10 Sep 2024 23:46:48 -0400 Subject: [PATCH 22/30] [BUG] Need to load step_count with one more than step count because we don't include the increment before saving the checkpoint --- wandb_preempt/checkpointer.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/wandb_preempt/checkpointer.py b/wandb_preempt/checkpointer.py index ef8efd9..1a9f45b 100644 --- a/wandb_preempt/checkpointer.py +++ b/wandb_preempt/checkpointer.py @@ -206,7 +206,7 @@ def load_latest_checkpoint(self) -> Tuple[int, Dict]: self.maybe_print("Loading gradient scaler.") self.scaler.load_state_dict(data["scaler"]) - self.step_count = data["checkpoint_step"] + self.step_count = data["checkpoint_step"] + 1 self.num_resumes = data["resumes"] + 1 # restore random number generator states for all devices @@ -217,7 +217,7 @@ def load_latest_checkpoint(self) -> Tuple[int, Dict]: else: set_rng_state(rng_state) - return self.step_count + 1, data["extra_info"] + return self.step_count, data["extra_info"] def remove_checkpoints(self, keep_latest: bool = False): """Remove checkpoints. From 5e6c505947f8aec4599e199f0235dae9847eba98 Mon Sep 17 00:00:00 2001 From: Scott Lowe Date: Wed, 11 Sep 2024 00:09:48 -0400 Subject: [PATCH 23/30] [DOC] Change to use lr_max in walkthrough --- example/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/example/README.md b/example/README.md index 2783d77..30ae479 100644 --- a/example/README.md +++ b/example/README.md @@ -28,7 +28,7 @@ First up, we need to write a training script that we will sweep over. The sweep For demonstration purposes, we will train a small CNN on MNIST using SGD, and our goal is to find a good learning rate through random search using a `wandb` sweep. To keep things simple and cheap, we fix a batch size and use a (very) small number of epochs. Finally, we also use a learning rate scheduler and mixed-precision training with a gradient scaler. These are overkill for MNIST, of course, but important when training large models so we include them here to show how they are checkpointed too. In summary, we will call the training script using the following pattern: ```bash -python train.py --lr=X +python train.py --lr_max=X ``` with `X` being some floating point number that the sweep will search over. From 7b5c5bd7d4a9d7dae094f7d7f1abaf6c99df89fa Mon Sep 17 00:00:00 2001 From: Scott Lowe Date: Wed, 11 Sep 2024 10:31:34 -0400 Subject: [PATCH 24/30] Revert "[MNT] Import torch.amp instead of deprecated torch.cuda.amp" This reverts commit 88664d91081ad6511a5a204852684e7189f19ec2. --- example/train.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/example/train.py b/example/train.py index e183541..804ff81 100755 --- a/example/train.py +++ b/example/train.py @@ -8,7 +8,7 @@ import wandb from torch import autocast, bfloat16, cuda, device, manual_seed -from torch.amp import GradScaler +from torch.cuda.amp import GradScaler from torch.nn import Conv2d, CrossEntropyLoss, Flatten, Linear, ReLU, Sequential from torch.optim import SGD from torch.optim.lr_scheduler import CosineAnnealingLR From cf45b0a1c506794ff5c49461d9c70ad3dcee6edc Mon Sep 17 00:00:00 2001 From: Scott Lowe Date: Wed, 11 Sep 2024 10:35:43 -0400 Subject: [PATCH 25/30] [MNT] Change preempting print statement --- wandb_preempt/checkpointer.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/wandb_preempt/checkpointer.py b/wandb_preempt/checkpointer.py index 1a9f45b..a2a8c0a 100644 --- a/wandb_preempt/checkpointer.py +++ b/wandb_preempt/checkpointer.py @@ -113,7 +113,8 @@ def mark_preempted(self, sig: int, frame: Optional[FrameType]): frame: The current stack frame. """ self.maybe_print( - f"Got signal {sig}. Marking as pre-empted. This will be the last epoch." + f"Received signal {sig}. Marking as pre-empted and will halt and requeue" + " the job at next call of checkpointer.step()." ) self.marked_preempted = True From de0fad024e63e75ee5da8b2b739e8a962c30b64f Mon Sep 17 00:00:00 2001 From: Felix Dangel Date: Wed, 11 Sep 2024 15:41:30 -0400 Subject: [PATCH 26/30] [DOC] Update README --- README.md | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/README.md b/README.md index 26a173a..d037597 100644 --- a/README.md +++ b/README.md @@ -6,14 +6,14 @@ This repository contains a tutorial on how to combine [wandb](https://wandb.ai/) with [Slurm](https://slurm.schedmd.com/)'s pre-emption, i.e. how to automatically re-queue and resume runs from a Weights & Biases sweep on a Slurm cluster. -This is work in progress: +## Getting started -- TODO Debug failure scenarios - -- TODO Write a self-contained walk-through. - -## Installation +### Installation ```bash pip install git+https://github.com/f-dangel/wandb_preempt.git@main ``` + +### Basic Example + +Please see the [docs](https://wandb-preempt.readthedocs.io/en/latest/walkthrough/). From bbe7c02775c2e31d8b9680cdffa715d7545f54fe Mon Sep 17 00:00:00 2001 From: Felix Dangel Date: Wed, 11 Sep 2024 15:43:07 -0400 Subject: [PATCH 27/30] [DEL] Remove unbuffered flag --- example/launch.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/example/launch.sh b/example/launch.sh index 5ffee29..b92259b 100644 --- a/example/launch.sh +++ b/example/launch.sh @@ -20,7 +20,7 @@ if [ "$SLURM_ARRAY_TASK_COUNT" != "" ]; then fi # NOTE that we need to use srun here, otherwise the Python process won't receive the SIGUSR1 signal -srun --unbuffered wandb agent --count=1 f-dangel-team/example-preemptable-sweep/qmzevsi8 & +srun wandb agent --count=1 f-dangel-team/example-preemptable-sweep/qmzevsi8 & child="$!" # Set up a handler to pass the SIGUSR1 to the python session launched by the agent From ebd88d79fa719cc5b94b37230f71534b393c66bb Mon Sep 17 00:00:00 2001 From: Felix Dangel Date: Wed, 11 Sep 2024 15:45:38 -0400 Subject: [PATCH 28/30] [REF] Same epoch default value (20) for train script and sweep --- example/train.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/example/train.py b/example/train.py index 804ff81..3ebca6f 100755 --- a/example/train.py +++ b/example/train.py @@ -29,7 +29,7 @@ def get_parser(): "--lr_max", type=float, default=0.01, help="Learning rate. Default: %(default)s" ) parser.add_argument( - "--epochs", type=int, default=15, help="Number of epochs. Default: %(default)s" + "--epochs", type=int, default=20, help="Number of epochs. Default: %(default)s" ) parser.add_argument( "--batch_size", type=int, default=256, help="Batch size. Default: %(default)s" From 581806ef13601c0334c18699d43294d5be135a00 Mon Sep 17 00:00:00 2001 From: Felix Dangel Date: Wed, 11 Sep 2024 15:54:05 -0400 Subject: [PATCH 29/30] [ADD] Update sweep id --- example/launch.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/example/launch.sh b/example/launch.sh index b92259b..529d20f 100644 --- a/example/launch.sh +++ b/example/launch.sh @@ -20,7 +20,7 @@ if [ "$SLURM_ARRAY_TASK_COUNT" != "" ]; then fi # NOTE that we need to use srun here, otherwise the Python process won't receive the SIGUSR1 signal -srun wandb agent --count=1 f-dangel-team/example-preemptable-sweep/qmzevsi8 & +srun wandb agent --count=1 f-dangel-team/example-preemptable-sweep/4m89qo6r & child="$!" # Set up a handler to pass the SIGUSR1 to the python session launched by the agent From a2b8f0b1ea400d53c4b1d84aac0d5d405a46cbaf Mon Sep 17 00:00:00 2001 From: Felix Dangel Date: Wed, 11 Sep 2024 16:20:38 -0400 Subject: [PATCH 30/30] [DOC] More screenshots, roughly 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zIvp}uoGdyuy|HfjXmRsQSU$tO(4z<>dp&=8Y^5zUMpNo-+Xp|SjZHP?;#CP#V_{)o z-v$Pb+ROgN6>K}=?=4ZR;U`l(H5KJHG9ndbXX|#d*H+p(|C4KE-G(R96A9{(`4ry= m`Ggro3*$?oU8ade<(j-J2PdOw9Y!elr>A3}ow@h)rT+scvF%|1 literal 0 HcmV?d00001 diff --git a/example/README.md b/example/README.md index 30ae479..32a442e 100644 --- a/example/README.md +++ b/example/README.md @@ -36,7 +36,7 @@ The training script also contains code to checkpoint the training loop at the en For more details, please expand the code snippet below. /// details | Details of the training script `example/train.py` ([source](https://github.com/f-dangel/wandb_preempt/blob/main/example/train.py)) -```py hl_lines="37-38 40-41" +```py --8<-- "example/train.py" ``` /// @@ -63,9 +63,9 @@ wandb sweep sweep.yaml /// details | Output ```sh hl_lines="4" wandb: Creating sweep from: sweep.yaml -wandb: Creating sweep with ID: qmzevsi8 -wandb: View sweep at: https://wandb.ai/f-dangel-team/example-preemptable-sweep/sweeps/qmzevsi8 -wandb: Run sweep agent with: wandb agent f-dangel-team/example-preemptable-sweep/qmzevsi8 +wandb: Creating sweep with ID: 4m89qo6r +wandb: View sweep at: https://wandb.ai/f-dangel-team/example-preemptable-sweep/sweeps/4m89qo6r +wandb: Run sweep agent with: wandb agent f-dangel-team/example-preemptable-sweep/4m89qo6r ``` /// @@ -87,185 +87,187 @@ wandb agent --count=1 f-dangel-team/example-preemptable-sweep/aaq70gt8 /// details | Training script output ``` wandb: Starting wandb agent ๐Ÿ•ต๏ธ -2024-09-09 22:16:59,894 - wandb.wandb_agent - INFO - Running runs: [] -2024-09-09 22:17:00,448 - wandb.wandb_agent - INFO - Agent received command: run -2024-09-09 22:17:00,449 - wandb.wandb_agent - INFO - Agent starting run with config: +2024-09-11 15:50:13,390 - wandb.wandb_agent - INFO - Running runs: [] +2024-09-11 15:50:13,596 - wandb.wandb_agent - INFO - Agent received command: run +2024-09-11 15:50:13,596 - wandb.wandb_agent - INFO - Agent starting run with config: epochs: 20 - lr: 0.005417051459795853 -2024-09-09 22:17:00,452 - wandb.wandb_agent - INFO - About to run command: /usr/bin/env python train.py --epochs=20 --lr=0.005417051459795853 -2024-09-09 22:17:05,473 - wandb.wandb_agent - INFO - Running runs: ['lmp9ebp1'] + lr_max: 0.002046505897436452 +2024-09-11 15:50:13,597 - wandb.wandb_agent - INFO - About to run command: /usr/bin/env python train.py --epochs=20 --lr_max=0.002046505897436452 wandb: Currently logged in as: f-dangel (f-dangel-team). Use `wandb login --relogin` to force relogin +2024-09-11 15:50:18,609 - wandb.wandb_agent - INFO - Running runs: ['2zoz0rl8'] wandb: Tracking run with wandb version 0.17.9 -wandb: Run data is saved locally in ~/wandb_preempt/example/wandb/run-20240909_221710-lmp9ebp1 +wandb: Run data is saved locally in ~/wandb_preempt/example/wandb/run-20240911_155016-2zoz0rl8 wandb: Run `wandb offline` to turn off syncing. -wandb: Syncing run denim-sweep-1 +wandb: Syncing run unique-sweep-1 wandb: โญ๏ธ View project at https://wandb.ai/f-dangel-team/example-preemptable-sweep -wandb: ๐Ÿงน View sweep at https://wandb.ai/f-dangel-team/example-preemptable-sweep/sweeps/qmzevsi8 -wandb: ๐Ÿš€ View run at https://wandb.ai/f-dangel-team/example-preemptable-sweep/runs/lmp9ebp1 -Using SGD with learning rate 0.005417051459795853. -[0.0 s | 2024-09-09 22:17:14.343841] Creating checkpoint directory: ~/wandb_preempt/example/checkpoints. -[0.0 s | 2024-09-09 22:17:14.343944] SLURM job ID: None, array ID: None, task ID: None -[0.0 s | 2024-09-09 22:17:14.344300] No checkpoint found. Starting from scratch. +wandb: ๐Ÿงน View sweep at https://wandb.ai/f-dangel-team/example-preemptable-sweep/sweeps/4m89qo6r +wandb: ๐Ÿš€ View run at https://wandb.ai/f-dangel-team/example-preemptable-sweep/runs/2zoz0rl8 +Using SGD with learning rate 0.002046505897436452. +[0.0 s | 2024-09-11 15:50:19.844072] Creating checkpoint directory: ~/wandb_preempt/example/checkpoints. +[0.0 s | 2024-09-11 15:50:19.844166] SLURM job ID: None, array ID: None, task ID: None +[0.0 s | 2024-09-11 15:50:19.844522] No checkpoint found. Starting from scratch. Epoch 0, Step 0, Loss 2.31327e+00 -Epoch 0, Step 50, Loss 2.31236e+00 -Epoch 0, Step 100, Loss 2.29828e+00 -Epoch 0, Step 150, Loss 2.28944e+00 -Epoch 0, Step 200, Loss 2.28544e+00 -[2.8 s | 2024-09-09 22:17:17.181593] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000000.pt. -Epoch 1, Step 0, Loss 2.27385e+00 -Epoch 1, Step 50, Loss 2.27472e+00 -Epoch 1, Step 100, Loss 2.25237e+00 -Epoch 1, Step 150, Loss 2.22541e+00 -Epoch 1, Step 200, Loss 2.21894e+00 -[5.6 s | 2024-09-09 22:17:19.918572] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000001.pt. -[5.6 s | 2024-09-09 22:17:19.919702] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000000.pt. -Epoch 2, Step 0, Loss 2.15103e+00 -Epoch 2, Step 50, Loss 2.11397e+00 -Epoch 2, Step 100, Loss 2.02360e+00 -Epoch 2, Step 150, Loss 1.89612e+00 -Epoch 2, Step 200, Loss 1.77511e+00 -[8.3 s | 2024-09-09 22:17:22.654042] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000002.pt. -[8.3 s | 2024-09-09 22:17:22.655190] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000001.pt. -Epoch 3, Step 0, Loss 1.64844e+00 -Epoch 3, Step 50, Loss 1.41444e+00 -Epoch 3, Step 100, Loss 1.24010e+00 -Epoch 3, Step 150, Loss 1.09945e+00 -Epoch 3, Step 200, Loss 9.38731e-01 -[11.0 s | 2024-09-09 22:17:25.391665] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000003.pt. -[11.0 s | 2024-09-09 22:17:25.392811] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000002.pt. -Epoch 4, Step 0, Loss 8.39498e-01 -Epoch 4, Step 50, Loss 7.73968e-01 -Epoch 4, Step 100, Loss 7.30065e-01 -Epoch 4, Step 150, Loss 5.72235e-01 -Epoch 4, Step 200, Loss 6.52813e-01 -[13.8 s | 2024-09-09 22:17:28.133137] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000004.pt. -[13.8 s | 2024-09-09 22:17:28.134257] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000003.pt. -Epoch 5, Step 0, Loss 5.88400e-01 -Epoch 5, Step 50, Loss 5.26665e-01 -Epoch 5, Step 100, Loss 5.13180e-01 -Epoch 5, Step 150, Loss 5.11152e-01 -Epoch 5, Step 200, Loss 5.30249e-01 -[16.5 s | 2024-09-09 22:17:30.880319] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000005.pt. -[16.5 s | 2024-09-09 22:17:30.881465] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000004.pt. -Epoch 6, Step 0, Loss 4.68262e-01 -Epoch 6, Step 50, Loss 4.94186e-01 -Epoch 6, Step 100, Loss 5.16372e-01 -Epoch 6, Step 150, Loss 4.25439e-01 -Epoch 6, Step 200, Loss 5.06348e-01 -[19.3 s | 2024-09-09 22:17:33.594644] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000006.pt. -[19.3 s | 2024-09-09 22:17:33.595731] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000005.pt. -Epoch 7, Step 0, Loss 4.81532e-01 -Epoch 7, Step 50, Loss 4.62612e-01 -Epoch 7, Step 100, Loss 4.84398e-01 -Epoch 7, Step 150, Loss 4.34298e-01 -Epoch 7, Step 200, Loss 4.44681e-01 -[21.9 s | 2024-09-09 22:17:36.292046] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000007.pt. -[21.9 s | 2024-09-09 22:17:36.293158] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000006.pt. -Epoch 8, Step 0, Loss 4.52199e-01 -Epoch 8, Step 50, Loss 4.06567e-01 -Epoch 8, Step 100, Loss 3.89836e-01 -Epoch 8, Step 150, Loss 4.20403e-01 -Epoch 8, Step 200, Loss 4.92639e-01 -[24.7 s | 2024-09-09 22:17:39.035341] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000008.pt. -[24.7 s | 2024-09-09 22:17:39.036695] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000007.pt. -Epoch 9, Step 0, Loss 4.22285e-01 -Epoch 9, Step 50, Loss 4.19266e-01 -Epoch 9, Step 100, Loss 3.77887e-01 -Epoch 9, Step 150, Loss 3.27919e-01 -Epoch 9, Step 200, Loss 3.68881e-01 -[27.4 s | 2024-09-09 22:17:41.770130] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000009.pt. -[27.4 s | 2024-09-09 22:17:41.771950] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000008.pt. -Epoch 10, Step 0, Loss 3.94362e-01 -Epoch 10, Step 50, Loss 4.10359e-01 -Epoch 10, Step 100, Loss 3.79892e-01 -Epoch 10, Step 150, Loss 4.42654e-01 -Epoch 10, Step 200, Loss 4.29457e-01 -[30.1 s | 2024-09-09 22:17:44.474406] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000010.pt. -[30.1 s | 2024-09-09 22:17:44.475494] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000009.pt. -Epoch 11, Step 0, Loss 3.87773e-01 -Epoch 11, Step 50, Loss 4.67186e-01 -Epoch 11, Step 100, Loss 3.57660e-01 -Epoch 11, Step 150, Loss 3.54450e-01 -Epoch 11, Step 200, Loss 3.43293e-01 -[32.8 s | 2024-09-09 22:17:47.191162] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000011.pt. -[32.8 s | 2024-09-09 22:17:47.192310] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000010.pt. -Epoch 12, Step 0, Loss 4.69982e-01 -Epoch 12, Step 50, Loss 3.77749e-01 -Epoch 12, Step 100, Loss 4.01224e-01 -Epoch 12, Step 150, Loss 3.48171e-01 -Epoch 12, Step 200, Loss 3.61441e-01 -[35.6 s | 2024-09-09 22:17:49.924267] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000012.pt. -[35.6 s | 2024-09-09 22:17:49.925361] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000011.pt. -Epoch 13, Step 0, Loss 3.35668e-01 -Epoch 13, Step 50, Loss 3.34111e-01 -Epoch 13, Step 100, Loss 3.22253e-01 -Epoch 13, Step 150, Loss 3.37382e-01 -Epoch 13, Step 200, Loss 3.90798e-01 -[38.3 s | 2024-09-09 22:17:52.667451] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000013.pt. -[38.3 s | 2024-09-09 22:17:52.668601] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000012.pt. -Epoch 14, Step 0, Loss 3.83771e-01 -Epoch 14, Step 50, Loss 3.24402e-01 -Epoch 14, Step 100, Loss 3.12806e-01 -Epoch 14, Step 150, Loss 3.40762e-01 -Epoch 14, Step 200, Loss 4.72378e-01 -[41.0 s | 2024-09-09 22:17:55.393290] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000014.pt. -[41.1 s | 2024-09-09 22:17:55.394609] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000013.pt. -Epoch 15, Step 0, Loss 2.78277e-01 -Epoch 15, Step 50, Loss 4.86174e-01 -Epoch 15, Step 100, Loss 3.18030e-01 -Epoch 15, Step 150, Loss 3.39720e-01 -Epoch 15, Step 200, Loss 3.45562e-01 -[43.8 s | 2024-09-09 22:17:58.183117] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000015.pt. -[43.8 s | 2024-09-09 22:17:58.184218] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000014.pt. -Epoch 16, Step 0, Loss 4.09605e-01 -Epoch 16, Step 50, Loss 4.02795e-01 -Epoch 16, Step 100, Loss 3.30050e-01 -Epoch 16, Step 150, Loss 3.29713e-01 -Epoch 16, Step 200, Loss 3.47872e-01 -[46.6 s | 2024-09-09 22:18:00.935960] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000016.pt. -[46.6 s | 2024-09-09 22:18:00.937244] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000015.pt. -Epoch 17, Step 0, Loss 3.61874e-01 -Epoch 17, Step 50, Loss 4.21045e-01 -Epoch 17, Step 100, Loss 3.68629e-01 -Epoch 17, Step 150, Loss 3.50573e-01 -Epoch 17, Step 200, Loss 4.53324e-01 -[49.3 s | 2024-09-09 22:18:03.630036] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000017.pt. -[49.3 s | 2024-09-09 22:18:03.631169] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000016.pt. -Epoch 18, Step 0, Loss 2.75897e-01 -Epoch 18, Step 50, Loss 3.52856e-01 -Epoch 18, Step 100, Loss 3.95981e-01 -Epoch 18, Step 150, Loss 3.01999e-01 -Epoch 18, Step 200, Loss 3.86351e-01 -[52.0 s | 2024-09-09 22:18:06.381923] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000018.pt. -[52.0 s | 2024-09-09 22:18:06.383072] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000017.pt. -Epoch 19, Step 0, Loss 3.14332e-01 -Epoch 19, Step 50, Loss 2.94699e-01 -Epoch 19, Step 100, Loss 2.69020e-01 -Epoch 19, Step 150, Loss 3.27822e-01 -Epoch 19, Step 200, Loss 3.05174e-01 -[54.8 s | 2024-09-09 22:18:09.101715] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000019.pt. -[54.8 s | 2024-09-09 22:18:09.103077] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000018.pt. +Epoch 0, Step 50, Loss 2.31634e+00 +Epoch 0, Step 100, Loss 2.30524e+00 +Epoch 0, Step 150, Loss 2.29960e+00 +Epoch 0, Step 200, Loss 2.30427e+00 +[3.0 s | 2024-09-11 15:50:22.801220] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000000.pt. +Epoch 1, Step 0, Loss 2.29656e+00 +Epoch 1, Step 50, Loss 2.30689e+00 +Epoch 1, Step 100, Loss 2.29662e+00 +Epoch 1, Step 150, Loss 2.28267e+00 +Epoch 1, Step 200, Loss 2.30082e+00 +[5.7 s | 2024-09-11 15:50:25.576881] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000001.pt. +[5.7 s | 2024-09-11 15:50:25.578131] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000000.pt. +Epoch 2, Step 0, Loss 2.28091e+00 +Epoch 2, Step 50, Loss 2.27995e+00 +Epoch 2, Step 100, Loss 2.27886e+00 +Epoch 2, Step 150, Loss 2.27613e+00 +Epoch 2, Step 200, Loss 2.27744e+00 +[8.5 s | 2024-09-11 15:50:28.328779] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000002.pt. +[8.5 s | 2024-09-11 15:50:28.329942] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000001.pt. +Epoch 3, Step 0, Loss 2.27019e+00 +Epoch 3, Step 50, Loss 2.27712e+00 +Epoch 3, Step 100, Loss 2.26028e+00 +Epoch 3, Step 150, Loss 2.25132e+00 +Epoch 3, Step 200, Loss 2.25152e+00 +[11.2 s | 2024-09-11 15:50:31.057194] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000003.pt. +[11.2 s | 2024-09-11 15:50:31.058385] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000002.pt. +Epoch 4, Step 0, Loss 2.23886e+00 +Epoch 4, Step 50, Loss 2.24897e+00 +Epoch 4, Step 100, Loss 2.23878e+00 +Epoch 4, Step 150, Loss 2.21464e+00 +Epoch 4, Step 200, Loss 2.21080e+00 +[14.0 s | 2024-09-11 15:50:33.822246] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000004.pt. +[14.0 s | 2024-09-11 15:50:33.823408] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000003.pt. +Epoch 5, Step 0, Loss 2.19485e+00 +Epoch 5, Step 50, Loss 2.19484e+00 +Epoch 5, Step 100, Loss 2.16891e+00 +Epoch 5, Step 150, Loss 2.16754e+00 +Epoch 5, Step 200, Loss 2.13477e+00 +[16.7 s | 2024-09-11 15:50:36.518798] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000005.pt. +[16.7 s | 2024-09-11 15:50:36.519988] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000004.pt. +Epoch 6, Step 0, Loss 2.12859e+00 +Epoch 6, Step 50, Loss 2.10682e+00 +Epoch 6, Step 100, Loss 2.09931e+00 +Epoch 6, Step 150, Loss 2.08149e+00 +Epoch 6, Step 200, Loss 2.04833e+00 +[19.4 s | 2024-09-11 15:50:39.239762] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000006.pt. +[19.4 s | 2024-09-11 15:50:39.240944] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000005.pt. +Epoch 7, Step 0, Loss 2.02058e+00 +Epoch 7, Step 50, Loss 1.97293e+00 +Epoch 7, Step 100, Loss 1.94745e+00 +Epoch 7, Step 150, Loss 1.90756e+00 +Epoch 7, Step 200, Loss 1.89235e+00 +[22.1 s | 2024-09-11 15:50:41.981751] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000007.pt. +[22.1 s | 2024-09-11 15:50:41.983563] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000006.pt. +Epoch 8, Step 0, Loss 1.82919e+00 +Epoch 8, Step 50, Loss 1.80327e+00 +Epoch 8, Step 100, Loss 1.74424e+00 +Epoch 8, Step 150, Loss 1.68607e+00 +Epoch 8, Step 200, Loss 1.67496e+00 +[25.0 s | 2024-09-11 15:50:44.813117] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000008.pt. +[25.0 s | 2024-09-11 15:50:44.814475] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000007.pt. +Epoch 9, Step 0, Loss 1.62010e+00 +Epoch 9, Step 50, Loss 1.56824e+00 +Epoch 9, Step 100, Loss 1.50516e+00 +Epoch 9, Step 150, Loss 1.48588e+00 +Epoch 9, Step 200, Loss 1.44233e+00 +[27.8 s | 2024-09-11 15:50:47.612270] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000009.pt. +[27.8 s | 2024-09-11 15:50:47.613580] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000008.pt. +Epoch 10, Step 0, Loss 1.37147e+00 +Epoch 10, Step 50, Loss 1.34652e+00 +Epoch 10, Step 100, Loss 1.31548e+00 +Epoch 10, Step 150, Loss 1.31214e+00 +Epoch 10, Step 200, Loss 1.31763e+00 +[30.5 s | 2024-09-11 15:50:50.342514] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000010.pt. +[30.5 s | 2024-09-11 15:50:50.343644] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000009.pt. +Epoch 11, Step 0, Loss 1.18105e+00 +Epoch 11, Step 50, Loss 1.18585e+00 +Epoch 11, Step 100, Loss 1.10869e+00 +Epoch 11, Step 150, Loss 1.08874e+00 +Epoch 11, Step 200, Loss 1.06454e+00 +[33.4 s | 2024-09-11 15:50:53.222490] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000011.pt. +[33.4 s | 2024-09-11 15:50:53.223652] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000010.pt. +Epoch 12, Step 0, Loss 1.13357e+00 +Epoch 12, Step 50, Loss 9.96835e-01 +Epoch 12, Step 100, Loss 1.06371e+00 +Epoch 12, Step 150, Loss 9.63902e-01 +Epoch 12, Step 200, Loss 9.63633e-01 +[36.1 s | 2024-09-11 15:50:55.968639] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000012.pt. +[36.1 s | 2024-09-11 15:50:55.970050] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000011.pt. +Epoch 13, Step 0, Loss 9.34712e-01 +Epoch 13, Step 50, Loss 8.95310e-01 +Epoch 13, Step 100, Loss 9.12703e-01 +Epoch 13, Step 150, Loss 9.39363e-01 +Epoch 13, Step 200, Loss 9.21194e-01 +[38.9 s | 2024-09-11 15:50:58.722370] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000013.pt. +[38.9 s | 2024-09-11 15:50:58.723519] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000012.pt. +Epoch 14, Step 0, Loss 8.49049e-01 +Epoch 14, Step 50, Loss 9.19110e-01 +Epoch 14, Step 100, Loss 8.95127e-01 +Epoch 14, Step 150, Loss 8.37601e-01 +Epoch 14, Step 200, Loss 9.13763e-01 +[41.6 s | 2024-09-11 15:51:01.492518] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000014.pt. +[41.6 s | 2024-09-11 15:51:01.493670] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000013.pt. +Epoch 15, Step 0, Loss 8.37812e-01 +Epoch 15, Step 50, Loss 9.73370e-01 +Epoch 15, Step 100, Loss 7.91447e-01 +Epoch 15, Step 150, Loss 8.27363e-01 +Epoch 15, Step 200, Loss 8.46579e-01 +[44.4 s | 2024-09-11 15:51:04.212638] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000015.pt. +[44.4 s | 2024-09-11 15:51:04.213888] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000014.pt. +Epoch 16, Step 0, Loss 8.59434e-01 +Epoch 16, Step 50, Loss 9.20763e-01 +Epoch 16, Step 100, Loss 7.62155e-01 +Epoch 16, Step 150, Loss 7.71248e-01 +Epoch 16, Step 200, Loss 8.11831e-01 +[47.1 s | 2024-09-11 15:51:06.972560] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000016.pt. +[47.1 s | 2024-09-11 15:51:06.973763] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000015.pt. +Epoch 17, Step 0, Loss 8.56807e-01 +Epoch 17, Step 50, Loss 8.06021e-01 +Epoch 17, Step 100, Loss 8.36283e-01 +Epoch 17, Step 150, Loss 7.88259e-01 +Epoch 17, Step 200, Loss 8.26321e-01 +[49.9 s | 2024-09-11 15:51:09.694183] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000017.pt. +[49.9 s | 2024-09-11 15:51:09.695488] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000016.pt. +Epoch 18, Step 0, Loss 7.45168e-01 +Epoch 18, Step 50, Loss 7.74083e-01 +Epoch 18, Step 100, Loss 8.39497e-01 +Epoch 18, Step 150, Loss 7.77645e-01 +Epoch 18, Step 200, Loss 8.34373e-01 +[52.6 s | 2024-09-11 15:51:12.442971] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000018.pt. +[52.6 s | 2024-09-11 15:51:12.444134] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000017.pt. +Epoch 19, Step 0, Loss 7.31586e-01 +Epoch 19, Step 50, Loss 7.85134e-01 +Epoch 19, Step 100, Loss 7.31892e-01 +Epoch 19, Step 150, Loss 7.79394e-01 +Epoch 19, Step 200, Loss 7.37044e-01 +[55.3 s | 2024-09-11 15:51:15.190555] Saving checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000019.pt. +[55.3 s | 2024-09-11 15:51:15.191727] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000018.pt. wandb: wandb: wandb: Run history: -wandb: loss โ–ˆโ–ˆโ–ˆโ–ˆโ–‡โ–‡โ–†โ–„โ–ƒโ–ƒโ–‚โ–‚โ–‚โ–โ–‚โ–โ–‚โ–โ–โ–โ–โ–‚โ–โ–โ–‚โ–โ–โ–โ–โ–โ–‚โ–โ–โ–โ–โ–โ–โ–โ–โ– +wandb: epoch โ–โ–โ–โ–โ–‚โ–‚โ–‚โ–‚โ–‚โ–‚โ–ƒโ–ƒโ–ƒโ–ƒโ–„โ–„โ–„โ–„โ–„โ–„โ–…โ–…โ–…โ–…โ–…โ–…โ–†โ–†โ–†โ–†โ–‡โ–‡โ–‡โ–‡โ–‡โ–‡โ–ˆโ–ˆโ–ˆโ–ˆ +wandb: loss โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‡โ–‡โ–‡โ–‡โ–‡โ–†โ–†โ–…โ–…โ–„โ–„โ–„โ–ƒโ–ƒโ–ƒโ–‚โ–‚โ–‚โ–‚โ–โ–‚โ–โ–‚โ–โ–โ–โ–โ–โ–โ– wandb: loss_scale โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ– wandb: lr โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–‡โ–‡โ–‡โ–‡โ–‡โ–‡โ–†โ–†โ–†โ–†โ–…โ–…โ–„โ–„โ–„โ–„โ–ƒโ–ƒโ–ƒโ–ƒโ–‚โ–‚โ–‚โ–‚โ–‚โ–‚โ–โ–โ–โ–โ–โ– wandb: resumes โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ– wandb: wandb: Run summary: -wandb: loss 0.30517 +wandb: epoch 19 +wandb: loss 0.73704 wandb: loss_scale 1.0 -wandb: lr 3e-05 +wandb: lr 1e-05 wandb: resumes 0 wandb: -wandb: ๐Ÿš€ View run denim-sweep-1 at: https://wandb.ai/f-dangel-team/example-preemptable-sweep/runs/lmp9ebp1 +wandb: ๐Ÿš€ View run unique-sweep-1 at: https://wandb.ai/f-dangel-team/example-preemptable-sweep/runs/2zoz0rl8 wandb: โญ๏ธ View project at: https://wandb.ai/f-dangel-team/example-preemptable-sweep wandb: Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s) -wandb: Find logs at: ./wandb/run-20240909_221710-lmp9ebp1/logs +wandb: Find logs at: ./wandb/run-20240911_155016-2zoz0rl8/logs wandb: WARNING The new W&B backend becomes opt-out in version 0.18.0; try it out with `wandb.require("core")`! See https://wandb.me/wandb-core for more information. -[62.1 s | 2024-09-09 22:18:16.395233] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-09/lmp9ebp1_00000019.pt. -2024-09-09 22:18:21,429 - wandb.wandb_agent - INFO - Cleaning up finished run: lmp9ebp1 +[60.5 s | 2024-09-11 15:51:20.373116] Removing checkpoint ~/wandb_preempt/example/checkpoints/2024-09-11/2zoz0rl8_00000019.pt. +2024-09-11 15:51:24,319 - wandb.wandb_agent - INFO - Cleaning up finished run: 2zoz0rl8 wandb: Terminating and syncing runs. Press ctrl-c to kill. ``` /// @@ -297,9 +299,20 @@ Use `watch squeue --me` to monitor the job queue. You will observe that the jobs On the Weights & Biases website, you will see the runs transitioning between the states 'Running', 'Preempted', and 'Finished'. Here is an example view: +![slurm run_preempted](./assets/03_slurm_preempted.png) +After full completion, the 'Workspace' tab on Weights & Biases looks as follows (of course, your curves will look slightly different due to sweep's and compute environment's stochastic nature): -## Details +![slurm_run_finished](./assets/04_slurm_finished.png) + +The `resume` panel shows that different runs pre-empted a different number of times. +In total, we now have 1 (local) + 10 (SLURM) = 11 (total) finished runs. + +## Conclusion + +And that is pretty much it. Feel free to stop reading at this point. + +## SLURM Launcher Details The launch script divides into three parts: 1. **SLURM configuration:** The first block specifies the SLURM resources and task array we are about to submit (lines starting with `#SBATCH`). The important configurations are @@ -316,6 +329,6 @@ The launch script divides into three parts: The other configuration flags are resource-specific, and some like the `--partition=a40` will depend on your cluster. In our script, we request NVIDIA A40 GPUs because they support mixed-precision training with `bfloat16` that is used by many modern training pipelines. -2. **Printing details and wandb agent launch** This part executes the `wandb agent` on our sweep and puts it into the background so our launch script can start listening to signals from SLURM. +2. **Printing details and wandb agent launch:** This part executes the `wandb agent` on our sweep and puts it into the background so our launch script can start listening to signals from SLURM. -3. **Installing a signal handler** +3. **Installing a trap handler:** This function will process the signal sent by SLURM and pass it on to the python process, which will then initiate pre-emption and requeueing.

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