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5
configs/trainer/cpu.yaml
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5
configs/trainer/cpu.yaml
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defaults:
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- default
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accelerator: cpu
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devices: 1
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configs/trainer/ddp.yaml
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configs/trainer/ddp.yaml
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defaults:
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- default
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strategy: ddp
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accelerator: gpu
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devices: [0,1]
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num_nodes: 1
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sync_batchnorm: True
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configs/trainer/ddp_sim.yaml
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configs/trainer/ddp_sim.yaml
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defaults:
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- default
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# simulate DDP on CPU, useful for debugging
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accelerator: cpu
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devices: 2
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strategy: ddp_spawn
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configs/trainer/default.yaml
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configs/trainer/default.yaml
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_target_: lightning.pytorch.trainer.Trainer
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default_root_dir: ${paths.output_dir}
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max_epochs: -1
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accelerator: gpu
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devices: [0]
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# mixed precision for extra speed-up
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precision: 16-mixed
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# perform a validation loop every N training epochs
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check_val_every_n_epoch: 1
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# set True to to ensure deterministic results
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# makes training slower but gives more reproducibility than just setting seeds
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deterministic: False
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gradient_clip_val: 5.0
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configs/trainer/gpu.yaml
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configs/trainer/gpu.yaml
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defaults:
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- default
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accelerator: gpu
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devices: 1
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5
configs/trainer/mps.yaml
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5
configs/trainer/mps.yaml
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defaults:
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- default
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accelerator: mps
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devices: 1
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