Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Fixed soft prompt eval loading bug #3805

Merged
merged 1 commit into from
Mar 7, 2022
Merged

Fixed soft prompt eval loading bug #3805

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
12 changes: 6 additions & 6 deletions examples/nlp/language_modeling/conf/megatron_prompt_tuning_gpt.yaml
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -5,14 +5,14 @@ trainer:
gpus: 1
num_nodes: 1
accelerator: ddp
precision: 32
precision: 16
logger: False # logger provided by exp_manager
checkpoint_callback: False
replace_sampler_ddp: False
max_epochs: null
max_steps: 1000 # consumed_samples = global_step * micro_batch_size * data_parallel_size * accumulate_grad_batches
max_steps: 3000 # consumed_samples = global_step * micro_batch_size * data_parallel_size * accumulate_grad_batches
log_every_n_steps: 10
val_check_interval: 50
val_check_interval: 250
limit_val_batches: 50
limit_test_batches: 500
accumulate_grad_batches: 1 # do not modify, grad acc is automatic for training megatron models
Expand Down Expand Up @@ -43,7 +43,7 @@ model:
# specify micro_batch_size, global_batch_size, and model parallelism
# gradient accumulation will be done automatically based on data_parallel_size
micro_batch_size: 4 # limited by GPU memory
global_batch_size: 16 # will use more micro batches to reach global batch size
global_batch_size: 8 # will use more micro batches to reach global batch size
tensor_model_parallel_size: 1 # intra-layer model parallelism
pipeline_model_parallel_size: 1 # inter-layer model parallelism

Expand Down Expand Up @@ -117,7 +117,7 @@ model:

optim:
name: fused_adam
lr: 2e-4
lr: 1e-5
weight_decay: 0.01
betas:
- 0.9
Expand All @@ -126,4 +126,4 @@ model:
name: CosineAnnealing
warmup_steps: 50
constant_steps: 10
min_lr: 2e-5
min_lr: 1e-6
8 changes: 4 additions & 4 deletions nemo/collections/nlp/models/language_modeling/megatron_gpt_model.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -708,13 +708,13 @@ def setup(self, stage=None):
init_consumed_samples = 0
self.init_consumed_samples = init_consumed_samples

# Initalize soft prompts before loading datasets and training
if self.use_soft_prompts:
self.init_new_prompts()

if stage == 'predict':
return
else:
# Initalize soft prompts before loading datasets and training
if self.use_soft_prompts:
self.init_new_prompts()

# TODO: consider adding a ModelPT guard to check if model is being restored.
# allowing restored models to optionally setup datasets
self.build_train_valid_test_datasets()
Expand Down