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πŸ“‘ Simple ExampleΒΆ

  1. πŸ–οΈ Setup environment1 (see Shell Environment):

    source <(curl https://bit.ly/ezpz-utils) && ezpz_setup_env
    
  2. 🐍 Install ezpz (see Python Library):

    python3 -m pip install "git+https://github.com/saforem2/ezpz"
    
  3. πŸš€ Launch any *.py2 from python (see Launch):

    python3 -m ezpz.test
    
    • Output:

      #[🐍 aurora_nre_models_frameworks-2025.0.0](πŸ‘» aurora_nre_models_frameworks-2025.0.0)
      #[05/01/25 @ 10:07:09][x4206c4s1b0n0][/f/d/f/p/s/ezpz][🌱 main][πŸ“¦πŸ“πŸ€·βœ“]
      ; python3 -m ezpz.test
      [W501 10:07:15.372342214 OperatorEntry.cpp:155] Warning: Warning only once for all operators,  other operators may also be overridden.
      Overriding a previously registered kernel for the same operator and the same dispatch key
      operator: aten::_cummax_helper(Tensor self, Tensor(a!) values, Tensor(b!) indices, int dim) -> ()
          registered at /build/pytorch/build/aten/src/ATen/RegisterSchema.cpp:6
      dispatch key: XPU
      previous kernel: registered at /build/pytorch/build/aten/src/ATen/RegisterCPU.cpp:30476
              new kernel: registered at /build/intel-pytorch-extension/build/Release/csrc/gpu/csrc/aten/generated/ATen/RegisterXPU.cpp:2971 (function operator())
      [2025-05-01 10:07:20,655] [INFO] [real_accelerator.py:239:get_accelerator] Setting ds_accelerator to xpu (auto detect)
      [2025-05-01 10:07:23][I][ezpz/launch:95] Job ID: 4575165
      [2025-05-01 10:07:23][I][ezpz/launch:101] Node file: /var/spool/pbs/aux/4575165.aurora-pbs-0001.hostmgmt.cm.aurora.alcf.anl.gov
      [2025-05-01 10:07:23][I][ezpz/launch:116] Building command to execute by piecing together:
              (1) ['launch_cmd'] + (2) ['python'] + (3) ['cmd_to_launch']
      
      1. ['launch_cmd']:
              mpiexec --verbose --envall --np=24 --ppn=12 --hostfile=/var/spool/pbs/aux/4575165.aurora-pbs-0001.hostmgmt.cm.aurora.alcf.anl.gov --cpu-bind=depth --depth=8
      
      2. ['python']:
              /lus/flare/projects/datascience/foremans/projects/saforem2/ezpz/venvs/aurora_nre_models_frameworks-2025.0.0/bin/python3
      
      3. ['cmd_to_launch']:
              -m ezpz.test_dist
      
      [2025-05-01 10:07:23][I][ezpz/launch:134] Took: 0.62 seconds to build command.
      [2025-05-01 10:07:23][I][ezpz/launch:137] Evaluating:
              mpiexec --verbose --envall --np=24 --ppn=12 --hostfile=/var/spool/pbs/aux/4575165.aurora-pbs-0001.hostmgmt.cm.aurora.alcf.anl.gov --cpu-bind=depth --depth=8 /lus/flare/projects/datascience/foremans/projects/saforem2/ezpz/venvs/aurora_nre_models_frameworks-2025.0.0/bin/python3 -m ezpz.test_dist
      [2025-05-01 10:07:23][I][ezpz/launch:159] Filtering for Aurora-specific messages. To view list of filters, run with `EZPZ_LOG_LEVEL=DEBUG`
      Disabling local launch: multi-node application
      Connected to tcp://x4206c4s2b0n0.hostmgmt2206.cm.aurora.alcf.anl.gov:7919
      Launching application 0010057d-0cb6-455d-94ae-505529c389cd
      [2025-05-01 10:07:36][I][ezpz/dist:554] Using get_torch_device_type()='xpu' with backend='ccl'
      [2025-05-01 10:07:36][I][ezpz/dist:987] ['x4206c4s2b0n0'][10/23]
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      [2025-05-01 10:07:37][I][ezpz/dist:987] ['x4206c4s2b0n0'][ 9/23]
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      [2025-05-01 10:07:38][I][ezpz/dist:987] ['x4206c4s1b0n0'][12/23]
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      [2025-05-01 10:07:38][I][ezpz/dist:987] ['x4206c4s1b0n0'][14/23]
      [2025-05-01 10:07:38][I][ezpz/dist:987] ['x4206c4s1b0n0'][20/23]
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      [2025-05-01 10:07:38][I][ezpz/dist:987] ['x4206c4s1b0n0'][22/23]
      [2025-05-01 10:07:38][I][ezpz/dist:987] ['x4206c4s1b0n0'][17/23]
      [2025-05-01 10:07:38][I][ezpz/dist:987] ['x4206c4s1b0n0'][18/23]
      [2025-05-01 10:07:38][I][ezpz/dist:987] ['x4206c4s1b0n0'][19/23]
      [2025-05-01 10:07:38][I][ezpz/dist:936] Using device='xpu' with backend='ddp' + 'ccl' for distributed training.
      [2025-05-01 10:07:38][I][ezpz/dist:987] ['x4206c4s2b0n0'][ 0/23]
      2025:05:01-10:07:38:(49751) |CCL_WARN| value of CCL_LOG_LEVEL changed to be error (default:warn)
      [2025-05-01 10:07:39][I][ezpz/test_dist:398:__main__] model=
      Network(
      (layers): Sequential(
          (0): Linear(in_features=128, out_features=1024, bias=True)
          (1): Linear(in_features=1024, out_features=512, bias=True)
          (2): Linear(in_features=512, out_features=256, bias=True)
          (3): Linear(in_features=256, out_features=128, bias=True)
          (4): Linear(in_features=128, out_features=128, bias=True)
      )
      )
      [2025-05-01 10:07:50][I][ezpz/dist:1185] Setting up wandb from rank=0
      [2025-05-01 10:07:50][I][ezpz/dist:1186] Using=WB PROJECT=ezpz.test_dist
      wandb: Currently logged in as: foremans (aurora_gpt) to https://api.wandb.ai. Use `wandb login --relogin` to force relogin
      wandb: Tracking run with wandb version 0.19.10
      wandb: Run data is saved locally in /lus/flare/projects/datascience/foremans/projects/saforem2/ezpz/wandb/run-20250501_100750-53eys83m
      wandb: Run `wandb offline` to turn off syncing.
      wandb: Syncing run quiet-frog-1566
      wandb: ⭐️ View project at https://wandb.ai/aurora_gpt/ezpz.test_dist
      wandb: πŸš€ View run at https://wandb.ai/aurora_gpt/ezpz.test_dist/runs/53eys83m
      [2025-05-01 10:07:51][I][ezpz/dist:1214] W&B RUN=[quiet-frog-1566](https://wandb.ai/aurora_gpt/ezpz.test_dist/runs/53eys83m)
      [2025-05-01 10:07:51][I][ezpz/dist:1254] Running on machine='Aurora'
      [2025-05-01 10:07:51][I][ezpz/test_dist:221:__main__] config:
      {
      "backend": "DDP",
      "batch_size": 64,
      "cp": 1,
      "dtype": "bfloat16",
      "input_size": 128,
      "layer_sizes": [
          1024,
          512,
          256,
          128
      ],
      "log_freq": 1,
      "output_size": 128,
      "pp": 1,
      "print_freq": 10,
      "pyinstrument_profiler": false,
      "tp": 1,
      "train_iters": 100,
      "warmup": 2
      }
      [2025-05-01 10:07:51][I][ezpz/test_dist:194:__main__] Warmup complete at step 2
      [2025-05-01 10:07:51][I][ezpz/test_dist:172:__main__] iter=10 loss=736.000000 dtf=0.000657 dtb=0.001384
      [2025-05-01 10:07:51][I][ezpz/test_dist:172:__main__] iter=20 loss=676.000000 dtf=0.000563 dtb=0.001285
      [2025-05-01 10:07:51][I][ezpz/test_dist:172:__main__] iter=30 loss=604.000000 dtf=0.000551 dtb=0.001301
      [2025-05-01 10:07:51][I][ezpz/test_dist:172:__main__] iter=40 loss=564.000000 dtf=0.000564 dtb=0.001276
      [2025-05-01 10:07:51][I][ezpz/test_dist:172:__main__] iter=50 loss=520.000000 dtf=0.000564 dtb=0.001240
      [2025-05-01 10:07:51][I][ezpz/test_dist:172:__main__] iter=60 loss=496.000000 dtf=0.000557 dtb=0.001272
      [2025-05-01 10:07:52][I][ezpz/test_dist:172:__main__] iter=70 loss=466.000000 dtf=0.000548 dtb=0.001269
      [2025-05-01 10:07:52][I][ezpz/test_dist:172:__main__] iter=80 loss=432.000000 dtf=0.000550 dtb=0.001254
      [2025-05-01 10:07:52][I][ezpz/test_dist:172:__main__] iter=90 loss=410.000000 dtf=0.000523 dtb=0.001193
      [2025-05-01 10:07:53][I][ezpz/history:721] Saving iter plot to: /lus/flare/projects/datascience/foremans/projects/saforem2/ezpz/outputs/ezpz.test_dist/ezpz.test_dist/plots/mplot
      [2025-05-01 10:07:53][I][ezpz/history:721] Saving loss plot to: /lus/flare/projects/datascience/foremans/projects/saforem2/ezpz/outputs/ezpz.test_dist/ezpz.test_dist/plots/mplot
      [2025-05-01 10:07:54][I][ezpz/history:721] Saving dtf plot to: /lus/flare/projects/datascience/foremans/projects/saforem2/ezpz/outputs/ezpz.test_dist/ezpz.test_dist/plots/mplot
      [2025-05-01 10:07:54][I][ezpz/history:721] Saving dtb plot to: /lus/flare/projects/datascience/foremans/projects/saforem2/ezpz/outputs/ezpz.test_dist/ezpz.test_dist/plots/mplot
      [2025-05-01 10:07:54][I][ezpz/history:618] Saving tplots to /lus/flare/projects/datascience/foremans/projects/saforem2/ezpz/outputs/ezpz.test_dist/ezpz.test_dist/plots/tplot
                          loss [2025-05-01-100754]
          β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
      1528β”€β–Œ                                                     β”‚
          β”‚β–Œ                                                     β”‚
      1337β”€β–Œ                                                     β”‚
          β”‚β–š                                                     β”‚
          │▐                                                     β”‚
      1146─▐                                                     β”‚
          β”‚ β–Œ                                                    β”‚
      955─ β–Œ                                                    β”‚
          β”‚ ▐                                                    β”‚
      764─  β–šβ––                                                  β”‚
          β”‚   ▝▀▄▄▖▗▖                                            β”‚
          β”‚       β–β–˜β–β–šβ–šβ–„β–„β–„β–„                                      β”‚
      573─                β–€β–€β–€β–€β–€β–€β–„β–€β–„β–„ β–„                          β”‚
          β”‚                          β–€ β–€β–€β–€β–€β–€β–€β–šβ–„β–„β–„β–„β–„β–„β––β–—           β”‚
      382─                                         β–β–˜β–€β–€β–€β–€β–€β–€β–„β–„β–„β–šβ–„β”‚
          β””β”¬β”€β”€β”¬β”€β”€β”¬β”€β”€β”¬β”€β”€β”¬β”€β”€β”€β”€β”¬β”€β”€β”¬β”€β”€β”¬β”€β”€β”¬β”€β”€β”€β”¬β”€β”€β”€β”¬β”€β”€β”€β”¬β”€β”€β”¬β”€β”€β”€β”€β”¬β”€β”€β”¬β”€β”€β”¬β”€β”˜
          1  7 12 17 22   31 38 42 48  55  62  69 76   85 89 96
      loss                          iter
      text saved in /lus/flare/projects/datascience/foremans/projects/saforem2/ezpz/outputs/ezpz.test_dist/ezpz.test_dist/plots/tplot/loss.txt
                              dtf [2025-05-01-100754]
              β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
      0.000754─   β–—β–Œ                                             β”‚
              β”‚   β–β–Œ                                             β”‚
      0.000716─   β–β–Œ                                             β”‚
              β”‚β–Œ  β–β–Œ                                             β”‚
              β”‚β–Œ  β–β–Œ              β–Ÿ                              β”‚
      0.000677─▐  β–β–š              β–ˆ                              β”‚
              β”‚β–β–Ÿ β–žβ–         β–—    β–ˆ          β––                   β”‚
      0.000639─ β–˜β–ˆ β–β–žβ–Œ  β–žβ–Œ β–—β–šβ–ˆ    β–ˆ    β–—β–œ β–– β–β–Œ β–– β–—β–Œ   β–—β–Œ         β”‚
              β”‚  β–ˆ β–β–Œβ–Œ  β–Œβ– β–β–β–ˆ    β–›β–žβ–œ  ▐ β–ˆβ–™β–€β–ˆβ–Œβ–β–Œ β–β–™β–š ▖▐▝▀▖  β–—    β”‚
      0.000600─  β–ˆ  β–˜β–Œ  β–Œβ–β–„β–β–β–ˆ    β–Œ ▐  ▐ β–β–œ β–ˆβ–Œβ–β–Œ β–β–ˆβ–β–β–Œβ–  β–Œ  β–ˆ    β”‚
              β”‚  β–ˆ   β–š  β–Œ β–β–β–β–ˆ    β–Œ ▝▖ β–Œ    β–ˆβ–Œβ–β–Œ β–β–ˆ β–€β–Œβ–  β–Œ  β–ˆ    β”‚
              β”‚  β–œ   ▐ β–—β–Œ ▐▐▐▛▄▖  β–Œ  β–Œ β–Œ    β–ˆβ–Œβ–Ÿβ–Œβ–„β–β–ˆ  β–Œβ–  β–Œ  β–ˆ    β”‚
      0.000562─       β–€β–˜β–˜ β–β–Œβ–β–Œ β–β–žβ–€β–˜  β–šβ–žβ–˜    β–œβ–β–ˆβ–β–β–Ÿβ–œ  β–šβ–  β–Œ  β–Œβ–šβ––β–—β––β”‚
              β”‚                β–β–Œ    β–β–Œ       ▝  ▝    β–€  β–šβ––β–—β–Œ β–β–Œβ–Œβ”‚
      0.000523─                                           β–β–€β–Œ  β–˜β–β”‚
              β””β”¬β”€β”€β”¬β”€β”€β”€β”€β”¬β”€β”€β”¬β”€β”€β”€β”¬β”€β”€β”¬β”€β”€β”¬β”€β”€β”¬β”€β”€β”€β”¬β”€β”€β”¬β”€β”€β”€β”¬β”€β”€β”¬β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”¬β”€β”˜
              1  7   17 22  31 36 42 48  55 62  69 76   85   96
      dtf                             iter
      text saved in /lus/flare/projects/datascience/foremans/projects/saforem2/ezpz/outputs/ezpz.test_dist/ezpz.test_dist/plots/tplot/dtf.txt
                          dtf [2025-05-01-100754]
          β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
      27.0─     β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                                           β”‚
          β”‚     β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                                           β”‚
      22.5─     β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                                           β”‚
          β”‚     β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                                           β”‚
          β”‚     β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ           β–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                           β”‚
      18.0─     β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ           β–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                           β”‚
          β”‚     β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ           β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                      β”‚
      13.5─     β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ           β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                      β”‚
          β”‚β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ      β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                      β”‚
      9.0β”€β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ      β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                      β”‚
          β”‚β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                      β”‚
          β”‚β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                      β”‚
      4.5β”€β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                      β”‚
          β”‚β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ”‚
      0.0β”€β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ”‚
          β””β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”˜
      0.000513    0.000576      0.000639     0.000702  0.000765
      freq                           dtf
      text saved in /lus/flare/projects/datascience/foremans/projects/saforem2/ezpz/outputs/ezpz.test_dist/ezpz.test_dist/plots/tplot/dtf-hist.txt
                          dtb [2025-05-01-100754]
              β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
      0.00193─   β–—β–Œ                                              β”‚
              β”‚   β–β–Œ                                              β”‚
      0.00181─   β–β–Œ                                              β”‚
              β”‚   β–β–Œ                                              β”‚
              β”‚   β–β–Œ                                              β”‚
      0.00168─   β–β–Œ                                              β”‚
              β”‚   β–β–Œ                       β––                      β”‚
      0.00156─   β–β–Œ                      β–β–Œ                      β”‚
              β”‚   ▐▝▖      β–Ÿ       β–– β––    β–β–Œ        β–—             β”‚
      0.00143β”€β–Ÿ  ▐ ▝▄  β–—β–— β–ˆ   β––  β–β–Œβ–β–Œ    β–β–Œ        β–›β––β–—β–Œ          β”‚
              β”‚ β–œβ–—β–Ÿ  ▐  β–Œβ–˜β–Œβ–›β–„ β–β–š  β–β–β–žβ–Œ  β–—β–šβ–Ÿβ–β–œ       β–Œβ–šβ–β–Œβ–—β–Œ        β”‚
              β”‚ β–β–Œ   ▐  β–Œ β–šβ–Œβ– ▐▐ ▗▐  β–Œ  ▐   ▐  β–—β–š  ▐  β–ˆβ–Œβ–Œβ–        β”‚
      0.00131─  β–˜   β–β–„β–—β–Œ β–β–Œ β–šβ–Ÿ β–Œβ–ˆβ–  β–Œ  β–ž   ▐▗ β–Ÿβ–  β–ž  β–œβ–Œβ–Œβ–        β”‚
              β”‚        β–˜   β–˜    β–β–Œβ–˜  β–β–€β–œ     β–€β–ž  β–€β–€    ▝ ▝▖  β–žβ–„β–„β–žβ–šβ”‚
      0.00119─                                           β–šβ–„β–„β–Œ β–β–Œ β”‚
              β””β”¬β”€β”€β”¬β”€β”€β”€β”€β”¬β”€β”€β”¬β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”¬β”€β”€β”¬β”€β”€β”€β”¬β”€β”€β”€β”¬β”€β”€β”¬β”€β”€β”¬β”€β”€β”¬β”€β”€β”¬β”€β”€β”€β”€β”¬β”€β”˜
              1  7   17 22   31   42 48  55  62 69 74 80 85   96
      dtb                            iter
      text saved in /lus/flare/projects/datascience/foremans/projects/saforem2/ezpz/outputs/ezpz.test_dist/ezpz.test_dist/plots/tplot/dtb.txt
                          dtb [2025-05-01-100754]
          β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
      31.0─     β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                                           β”‚
          β”‚     β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                                           β”‚
      25.8─     β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                                           β”‚
          β”‚     β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                                           β”‚
          β”‚     β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                                           β”‚
      20.7β”€β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                                      β”‚
          β”‚β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                                β”‚
      15.5β”€β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                                β”‚
          β”‚β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                                β”‚
      10.3β”€β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                                β”‚
          β”‚β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                                β”‚
          β”‚β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                                β”‚
      5.2β”€β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                           β”‚
          β”‚β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                           β”‚
      0.0β”€β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ                 β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ”‚
          β””β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”˜
      0.00115      0.00135       0.00156      0.00176   0.00196
      freq                           dtb
      text saved in /lus/flare/projects/datascience/foremans/projects/saforem2/ezpz/outputs/ezpz.test_dist/ezpz.test_dist/plots/tplot/dtb-hist.txt
      [2025-05-01 10:07:54][I][ezpz/test_dist:188:__main__] dataset=<xarray.Dataset> Size: 3kB
      Dimensions:  (draw: 97)
      Coordinates:
      * draw     (draw) int64 776B 0 1 2 3 4 5 6 7 8 ... 88 89 90 91 92 93 94 95 96
      Data variables:
          iter     (draw) int64 776B 3 4 5 6 7 8 9 10 11 ... 92 93 94 95 96 97 98 99
          loss     (draw) float32 388B 1.528e+03 1.248e+03 1.072e+03 ... 382.0 392.0
          dtf      (draw) float64 776B 0.0007091 0.0006719 ... 0.0005526 0.0005336
          dtb      (draw) float64 776B 0.001446 0.00146 0.001422 ... 0.001251 0.001238
      [2025-05-01 10:07:54][I][ezpz/test_dist:467:__main__] Took: 18.05 seconds
      wandb:
      wandb: πŸš€ View run quiet-frog-1566 at: https://wandb.ai/aurora_gpt/ezpz.test_dist/runs/53eys83m
      wandb: Find logs at: ../../../../../../lus/flare/projects/datascience/foremans/projects/saforem2/ezpz/wandb/run-20250501_100750-53eys83m/logs
      Application 0010057d resources: utime=874s stime=172s maxrss=3840744KB inblock=378318 oublock=1080 minflt=10297842 majflt=32240 nvcsw=292681 nivcsw=1232922
      [2025-05-01 10:07:57][I][ezpz/launch:170] Command took 34.03 seconds to run.
      took: 0h:00m:48s
      

😎 2 ez.


  1. This will πŸͺ„ automagically source ezpz/bin/utils.sh, and (&&) call ezpz_setup_env to setup your python environment. β†©

  2. Technically, we're launching (-m ezpz.launch) the ezpz/test_dist.py a module (-m), in this example. β†©