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Running
on
CPU Upgrade
Add comma between optimizer, scheduler as reported in https://github.com/huggingface/accelerate/issues/2661
Browse files
code_samples/base/accelerate
CHANGED
@@ -1,7 +1,7 @@
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<pre>
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from accelerate import Accelerator
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accelerator = Accelerator()
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-
train_dataloader, model, optimizer scheduler = accelerator.prepare(
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dataloader, model, optimizer, scheduler
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)
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<pre>
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from accelerate import Accelerator
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accelerator = Accelerator()
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+
train_dataloader, model, optimizer, scheduler = accelerator.prepare(
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dataloader, model, optimizer, scheduler
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)
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code_samples/base/basic
CHANGED
@@ -2,7 +2,7 @@
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<pre>
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+from accelerate import Accelerator
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+accelerator = Accelerator()
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-
+dataloader, model, optimizer scheduler = accelerator.prepare(
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+ dataloader, model, optimizer, scheduler
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+)
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<pre>
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+from accelerate import Accelerator
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+accelerator = Accelerator()
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+
+dataloader, model, optimizer, scheduler = accelerator.prepare(
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+ dataloader, model, optimizer, scheduler
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+)
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code_samples/base/checkpointing
CHANGED
@@ -2,7 +2,7 @@
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<pre>
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from accelerate import Accelerator
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accelerator = Accelerator()
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-
dataloader, model, optimizer scheduler = accelerator.prepare(
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dataloader, model, optimizer, scheduler
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)
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<pre>
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from accelerate import Accelerator
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accelerator = Accelerator()
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+
dataloader, model, optimizer, scheduler = accelerator.prepare(
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dataloader, model, optimizer, scheduler
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)
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code_samples/base/experiment_tracking
CHANGED
@@ -3,7 +3,7 @@
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from accelerate import Accelerator
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-accelerator = Accelerator()
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+accelerator = Accelerator(log_with="wandb")
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-
train_dataloader, model, optimizer scheduler = accelerator.prepare(
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dataloader, model, optimizer, scheduler
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)
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+accelerator.init_trackers()
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from accelerate import Accelerator
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-accelerator = Accelerator()
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+accelerator = Accelerator(log_with="wandb")
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+
train_dataloader, model, optimizer, scheduler = accelerator.prepare(
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dataloader, model, optimizer, scheduler
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)
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+accelerator.init_trackers()
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code_samples/base/gradient_accumulation
CHANGED
@@ -4,7 +4,7 @@ from accelerate import Accelerator
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accelerator = Accelerator(
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+ gradient_accumulation_steps=2,
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)
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-
dataloader, model, optimizer scheduler = accelerator.prepare(
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dataloader, model, optimizer, scheduler
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)
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accelerator = Accelerator(
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+ gradient_accumulation_steps=2,
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)
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+
dataloader, model, optimizer, scheduler = accelerator.prepare(
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dataloader, model, optimizer, scheduler
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)
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