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Expose packed: False, set log_peak_memory_stats: True, set compile: False #1872

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Oct 26, 2024
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Expose packed: False, set log_peak_memory_stats: True, set compile: False #1872

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3978d15
add required arguments in configs
Oct 20, 2024
00d09d0
fix incorrect replacement
Oct 20, 2024
bb7648f
remove packed from dpo
Oct 21, 2024
22c84ab
remove packed from dpo
Oct 21, 2024
8acfa75
add comment
Oct 21, 2024
9b47501
add cuda check
Oct 23, 2024
e60eebd
fix lint
Oct 23, 2024
dacc3d2
fixes
Oct 24, 2024
a311232
fix compile typo
Oct 26, 2024
b0b4b14
fix other typos
Oct 26, 2024
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4 changes: 3 additions & 1 deletion recipes/configs/code_llama2/7B_full_low_memory.yaml
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Expand Up @@ -45,7 +45,9 @@ resume_from_checkpoint: False

# Dataset
dataset:
packed: False # Set to true for great speed ups
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Huge nit: can we move this below the _component_ declaration?

That way it reads more as an option for the specific builder.

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Yeah, though like this first time.. But I followed original declaration from issue:

dataset:
packed=False # Set to true for great speed ups

Will be fixed

_component_: torchtune.datasets.alpaca_dataset

seed: null
shuffle: True

Expand Down Expand Up @@ -75,4 +77,4 @@ metric_logger:
_component_: torchtune.training.metric_logging.DiskLogger
log_dir: /tmp/CodeLlama-7b-hf/logs
log_every_n_steps: 1
log_peak_memory_stats: False
log_peak_memory_stats: True
4 changes: 3 additions & 1 deletion recipes/configs/code_llama2/7B_lora_single_device.yaml
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Expand Up @@ -49,7 +49,9 @@ save_adapter_weights_only: False

# Dataset
dataset:
packed: False # Set to true for great speed ups
_component_: torchtune.datasets.alpaca_cleaned_dataset

seed: null
shuffle: True

Expand Down Expand Up @@ -84,7 +86,7 @@ metric_logger:
_component_: torchtune.training.metric_logging.DiskLogger
log_dir: /tmp/CodeLlama-7b-hf/logs
log_every_n_steps: 1
log_peak_memory_stats: False
log_peak_memory_stats: True

# Showcase the usage of PyTorch profiler
# Set enabled to False as it's only needed for debugging training
Expand Down
3 changes: 2 additions & 1 deletion recipes/configs/code_llama2/7B_qlora_single_device.yaml
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Expand Up @@ -49,6 +49,7 @@ save_adapter_weights_only: False

# Dataset
dataset:
packed: False # Set to true for great speed ups
_component_: torchtune.datasets.alpaca_cleaned_dataset
seed: null
shuffle: True
Expand Down Expand Up @@ -84,7 +85,7 @@ metric_logger:
_component_: torchtune.training.metric_logging.DiskLogger
log_dir: /tmp/CodeLlama-7b-hf/logs
log_every_n_steps: 1
log_peak_memory_stats: False
log_peak_memory_stats: True

# Show case the usage of pytorch profiler
# Set enabled to False as it's only needed for debugging training
Expand Down
4 changes: 3 additions & 1 deletion recipes/configs/dev/8B_full_experimental.yaml
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Expand Up @@ -26,6 +26,7 @@ tokenizer:

# Dataset
dataset:
packed: False # Set to true for great speed ups
_component_: torchtune.datasets.alpaca_dataset
seed: null
shuffle: True
Expand Down Expand Up @@ -57,7 +58,7 @@ loss:
_component_: torchtune.modules.loss.CEWithChunkedOutputLoss
max_steps_per_epoch: null
gradient_accumulation_steps: 1

compile: False
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Should we be explicit that this will torch.compile the model and loss? compile seems like a vague name

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@felipemello1 felipemello1 Oct 21, 2024 •
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agreed. I think we can add a comment, similar to packed

compile=False # pytorch compile, set to true for perf/memory improvement

wdyt?

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Add some comment there?

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Ok, will add


# Training env
device: cuda
Expand All @@ -78,3 +79,4 @@ metric_logger:
log_dir: ${output_dir}
output_dir: /tmp/alpaca-llama3-finetune
log_every_n_steps: null
log_peak_memory_stats: True
4 changes: 3 additions & 1 deletion recipes/configs/gemma/2B_full.yaml
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Expand Up @@ -23,6 +23,7 @@ tokenizer:

# Dataset
dataset:
packed: False # Set to true for great speed ups
_component_: torchtune.datasets.alpaca_dataset
seed: null
shuffle: True
Expand Down Expand Up @@ -54,6 +55,7 @@ loss:
_component_: torchtune.modules.loss.CEWithChunkedOutputLoss
max_steps_per_epoch: null
gradient_accumulation_steps: 1
compile: False

# Training env
device: cuda
Expand All @@ -70,4 +72,4 @@ metric_logger:
log_dir: ${output_dir}
output_dir: /tmp/alpaca-gemma-finetune
log_every_n_steps: 1
log_peak_memory_stats: False
log_peak_memory_stats: True
4 changes: 3 additions & 1 deletion recipes/configs/gemma/2B_lora.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -22,6 +22,7 @@ tokenizer:

# Dataset
dataset:
packed: False # Set to true for great speed ups
_component_: torchtune.datasets.alpaca_dataset
seed: null
shuffle: True
Expand Down Expand Up @@ -66,6 +67,7 @@ batch_size: 4
epochs: 3
max_steps_per_epoch: null
gradient_accumulation_steps: 1
compile: False

# Training env
device: cuda
Expand All @@ -82,4 +84,4 @@ metric_logger:
log_dir: ${output_dir}
output_dir: /tmp/alpaca-gemma-lora
log_every_n_steps: 1
log_peak_memory_stats: False
log_peak_memory_stats: True
3 changes: 2 additions & 1 deletion recipes/configs/gemma/2B_lora_single_device.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -22,6 +22,7 @@ tokenizer:

# Dataset
dataset:
packed: False # Set to true for great speed ups
_component_: torchtune.datasets.alpaca_dataset
seed: null
shuffle: True
Expand Down Expand Up @@ -83,7 +84,7 @@ metric_logger:
log_dir: ${output_dir}
output_dir: /tmp/alpaca-gemma-lora
log_every_n_steps: 1
log_peak_memory_stats: False
log_peak_memory_stats: True

# Show case the usage of pytorch profiler
# Set enabled to False as it's only needed for debugging training
Expand Down
3 changes: 2 additions & 1 deletion recipes/configs/gemma/2B_qlora_single_device.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -22,6 +22,7 @@ tokenizer:

# Dataset
dataset:
packed: False # Set to true for great speed ups
_component_: torchtune.datasets.alpaca_dataset
seed: null
shuffle: True
Expand Down Expand Up @@ -83,7 +84,7 @@ metric_logger:
log_dir: ${output_dir}
output_dir: /tmp/alpaca-gemma-lora
log_every_n_steps: 1
log_peak_memory_stats: False
log_peak_memory_stats: True

# Show case the usage of pytorch profiler
# Set enabled to False as it's only needed for debugging training
Expand Down
4 changes: 3 additions & 1 deletion recipes/configs/gemma/7B_full.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -23,6 +23,7 @@ tokenizer:

# Dataset
dataset:
packed: False # Set to true for great speed ups
_component_: torchtune.datasets.alpaca_dataset
seed: null
shuffle: True
Expand Down Expand Up @@ -56,6 +57,7 @@ loss:
_component_: torchtune.modules.loss.CEWithChunkedOutputLoss
max_steps_per_epoch: null
gradient_accumulation_steps: 1
compile: False

# Training env
device: cuda
Expand All @@ -72,4 +74,4 @@ metric_logger:
log_dir: ${output_dir}
output_dir: /tmp/alpaca-gemma-finetune
log_every_n_steps: 1
log_peak_memory_stats: False
log_peak_memory_stats: True
4 changes: 3 additions & 1 deletion recipes/configs/gemma/7B_lora.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -23,6 +23,7 @@ tokenizer:

# Dataset
dataset:
packed: False # Set to true for great speed ups
_component_: torchtune.datasets.alpaca_dataset
seed: null
shuffle: True
Expand Down Expand Up @@ -68,6 +69,7 @@ batch_size: 4
epochs: 3
max_steps_per_epoch: null
gradient_accumulation_steps: 1
compile: False

# Training env
device: cuda
Expand All @@ -84,4 +86,4 @@ metric_logger:
log_dir: ${output_dir}
output_dir: /tmp/alpaca-gemma-lora
log_every_n_steps: 1
log_peak_memory_stats: False
log_peak_memory_stats: True
3 changes: 2 additions & 1 deletion recipes/configs/gemma/7B_lora_single_device.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -22,6 +22,7 @@ tokenizer:

# Dataset
dataset:
packed: False # Set to true for great speed ups
_component_: torchtune.datasets.alpaca_dataset
seed: null
shuffle: True
Expand Down Expand Up @@ -85,7 +86,7 @@ metric_logger:
log_dir: ${output_dir}
output_dir: /tmp/alpaca-gemma-lora
log_every_n_steps: 1
log_peak_memory_stats: False
log_peak_memory_stats: True

# Show case the usage of pytorch profiler
# Set enabled to False as it's only needed for debugging training
Expand Down
3 changes: 2 additions & 1 deletion recipes/configs/gemma/7B_qlora_single_device.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -22,6 +22,7 @@ tokenizer:

# Dataset
dataset:
packed: False # Set to true for great speed ups
_component_: torchtune.datasets.alpaca_dataset
seed: null
shuffle: True
Expand Down Expand Up @@ -85,7 +86,7 @@ metric_logger:
log_dir: ${output_dir}
output_dir: /tmp/alpaca-gemma-lora
log_every_n_steps: 1
log_peak_memory_stats: False
log_peak_memory_stats: True

# Show case the usage of pytorch profiler
# Set enabled to False as it's only needed for debugging training
Expand Down
4 changes: 3 additions & 1 deletion recipes/configs/llama2/13B_full.yaml
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Expand Up @@ -43,6 +43,7 @@ tokenizer:

# Dataset
dataset:
packed: False # Set to true for great speed ups
_component_: torchtune.datasets.alpaca_dataset
seed: null
shuffle: True
Expand All @@ -58,6 +59,7 @@ loss:
_component_: torchtune.modules.loss.CEWithChunkedOutputLoss
max_steps_per_epoch: null
gradient_accumulation_steps: 1
compile: False

# Training env
device: cuda
Expand All @@ -74,4 +76,4 @@ metric_logger:
log_dir: ${output_dir}
output_dir: /tmp/alpaca-llama2-finetune
log_every_n_steps: 1
log_peak_memory_stats: False
log_peak_memory_stats: True
4 changes: 3 additions & 1 deletion recipes/configs/llama2/13B_lora.yaml
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Expand Up @@ -52,6 +52,7 @@ tokenizer:

# Dataset and Sampler
dataset:
packed: False # Set to true for great speed ups
_component_: torchtune.datasets.alpaca_cleaned_dataset
seed: null
shuffle: True
Expand All @@ -74,14 +75,15 @@ loss:
epochs: 1
max_steps_per_epoch: null
gradient_accumulation_steps: 16
compile: False

# Logging
output_dir: /tmp/lora_finetune_output
metric_logger:
_component_: torchtune.training.metric_logging.DiskLogger
log_dir: ${output_dir}
log_every_n_steps: 1
log_peak_memory_stats: False
log_peak_memory_stats: True

# Environment
device: cuda
Expand Down
3 changes: 2 additions & 1 deletion recipes/configs/llama2/13B_qlora_single_device.yaml
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Expand Up @@ -47,6 +47,7 @@ save_adapter_weights_only: False

# Dataset and Sampler
dataset:
packed: False # Set to true for great speed ups
_component_: torchtune.datasets.alpaca_cleaned_dataset
seed: null
shuffle: True
Expand Down Expand Up @@ -77,7 +78,7 @@ metric_logger:
_component_: torchtune.training.metric_logging.DiskLogger
log_dir: ${output_dir}
log_every_n_steps: 1
log_peak_memory_stats: False
log_peak_memory_stats: True

# Environment
device: cuda
Expand Down
3 changes: 2 additions & 1 deletion recipes/configs/llama2/70B_lora.yaml
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Expand Up @@ -52,6 +52,7 @@ save_adapter_weights_only: False

# Dataset and Sampler
dataset:
packed: False # Set to true for great speed ups
_component_: torchtune.datasets.alpaca_dataset
seed: null
shuffle: True
Expand Down Expand Up @@ -81,7 +82,7 @@ metric_logger:
_component_: torchtune.training.metric_logging.DiskLogger
log_dir: ${output_dir}
log_every_n_steps: 1
log_peak_memory_stats: False
log_peak_memory_stats: True

# Environment
device: cuda
Expand Down
3 changes: 2 additions & 1 deletion recipes/configs/llama2/70B_qlora.yaml
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Expand Up @@ -57,6 +57,7 @@ save_adapter_weights_only: False

# Dataset and Sampler
dataset:
packed: False # Set to true for great speed ups
_component_: torchtune.datasets.alpaca_dataset
train_on_input: True
seed: null
Expand Down Expand Up @@ -91,7 +92,7 @@ metric_logger:
_component_: torchtune.training.metric_logging.DiskLogger
log_dir: ${output_dir}
log_every_n_steps: 1
log_peak_memory_stats: False
log_peak_memory_stats: True

# Environment
device: cuda
Expand Down
5 changes: 3 additions & 2 deletions recipes/configs/llama2/7B_full.yaml
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Expand Up @@ -26,6 +26,7 @@ tokenizer:

# Dataset
dataset:
packed: False # Set to true for great speed ups
_component_: torchtune.datasets.alpaca_dataset
seed: null
shuffle: True
Expand Down Expand Up @@ -57,7 +58,7 @@ loss:
_component_: torchtune.modules.loss.CEWithChunkedOutputLoss
max_steps_per_epoch: null
gradient_accumulation_steps: 1

compile: False

# Training env
device: cuda
Expand All @@ -74,4 +75,4 @@ metric_logger:
log_dir: ${output_dir}
output_dir: /tmp/alpaca-llama2-finetune
log_every_n_steps: 1
log_peak_memory_stats: False
log_peak_memory_stats: True
3 changes: 2 additions & 1 deletion recipes/configs/llama2/7B_full_low_memory.yaml
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Expand Up @@ -28,6 +28,7 @@ tokenizer:

# Dataset
dataset:
packed: False # Set to true for great speed ups
_component_: torchtune.datasets.alpaca_dataset
seed: null
shuffle: True
Expand Down Expand Up @@ -79,4 +80,4 @@ metric_logger:
log_dir: ${output_dir}
output_dir: /tmp/alpaca-llama2-finetune
log_every_n_steps: 1
log_peak_memory_stats: False
log_peak_memory_stats: True
7 changes: 4 additions & 3 deletions recipes/configs/llama2/7B_lora.yaml
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Expand Up @@ -49,6 +49,7 @@ save_adapter_weights_only: False

# Dataset and Sampler
dataset:
packed: False # Set to true for great speed ups
_component_: torchtune.datasets.alpaca_cleaned_dataset
seed: null
shuffle: True
Expand Down Expand Up @@ -78,7 +79,7 @@ metric_logger:
_component_: torchtune.training.metric_logging.DiskLogger
log_dir: ${output_dir}
log_every_n_steps: 1
log_peak_memory_stats: False
log_peak_memory_stats: True

# Environment
device: cuda
Expand All @@ -92,14 +93,14 @@ profiler:

enabled: False

#Output directory of trace artifacts
# Output directory of trace artifacts
output_dir: ${output_dir}/profiling_outputs

#`torch.profiler.ProfilerActivity` types to trace
cpu: True
cuda: True

#trace options passed to `torch.profiler.profile`
# trace options passed to `torch.profiler.profile`
profile_memory: False
with_stack: False
record_shapes: True
Expand Down
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