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Fix unwrap model #9480

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merged 5 commits into from
Jun 17, 2024
Merged

Fix unwrap model #9480

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ea728c2
fix unwrap model
cuichenx Jun 14, 2024
67b81b8
add O2 to ci test
cuichenx Jun 15, 2024
2bb9605
fix ci test
cuichenx Jun 15, 2024
57d3117
fix ci test
cuichenx Jun 17, 2024
5d27d59
fix ci test
cuichenx Jun 17, 2024
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43 changes: 31 additions & 12 deletions .github/workflows/cicd-main.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -3060,13 +3060,13 @@ jobs:
AFTER_SCRIPT: |
rm -rf /home/TestData/nlp/megatron_ir/working_dir

L2_Megatron_GPT_PEFT_Lora_PP2:
L2_Megatron_GPT_PEFT_Lora_PP2_O2:
needs: [cicd-test-container-setup]
uses: ./.github/workflows/_test_template.yml
with:
RUNNER: self-hosted-azure
SCRIPT: |
rm -rf examples/nlp/language_modeling/gpt_peft_lora_results_pp2
rm -rf /home/TestData/nlp/lora_tuning_pp2

python examples/nlp/language_modeling/tuning/megatron_gpt_finetuning.py \
trainer.devices=2 \
Expand All @@ -3075,11 +3075,12 @@ jobs:
trainer.max_steps=3 \
trainer.val_check_interval=3 \
++trainer.limit_val_batches=2 \
trainer.precision=16 \
exp_manager.exp_dir=examples/nlp/language_modeling/gpt_peft_lora_results_pp2 \
trainer.precision=bf16 \
exp_manager.exp_dir=/home/TestData/nlp/lora_tuning_pp2 \
model.pipeline_model_parallel_size=2 \
model.tensor_model_parallel_size=1 \
model.restore_from_path=/home/TestData/nlp/megatron_gpt/PP2/gpt_pp2_tp1.nemo \
model.restore_from_path=/home/TestData/nlp/megatron_gpt/mcore_45M/megatron_llama.nemo \
model.megatron_amp_O2=True \
model.peft.peft_scheme=lora \
model.answer_only_loss=True \
model.micro_batch_size=1 \
Expand All @@ -3090,10 +3091,28 @@ jobs:
model.data.validation_ds.num_workers=0 \
model.data.validation_ds.file_names=[/home/TestData/nlp/megatron_sft/quarel.jsonl] \
model.data.validation_ds.names=[quarel]

python examples/nlp/language_modeling/tuning/megatron_gpt_generate.py \
model.restore_from_path=/home/TestData/nlp/megatron_gpt/mcore_45M/megatron_llama.nemo \
model.peft.restore_from_path=/home/TestData/nlp/lora_tuning_pp2/megatron_gpt_peft_lora_tuning/checkpoints/megatron_gpt_peft_lora_tuning.nemo \
model.pipeline_model_parallel_size=2 \
model.tensor_model_parallel_size=1 \
trainer.devices=2 \
model.megatron_amp_O2=True \
model.data.test_ds.file_names=[/home/TestData/nlp/megatron_sft/quarel_4.jsonl] \
model.data.test_ds.names=['quarel4'] \
model.global_batch_size=2 \
model.micro_batch_size=1 \
model.data.test_ds.tokens_to_generate=10 \
model.data.test_ds.write_predictions_to_file=True \
model.data.test_ds.output_file_path_prefix='/home/TestData/nlp/lora_tuning_pp2/out' \
inference.greedy=True \
inference.repetition_penalty=1.0 \
inference.outfile_path='/home/TestData/nlp/lora_tuning_pp2/out.jsonl'
AFTER_SCRIPT: |
rm -rf examples/nlp/language_modeling/gpt_peft_lora_results_pp2
rm -rf /home/TestData/nlp/lora_tuning_pp2

L2_Megatron_GPT_PEFT_Lora_TP2:
L2_Megatron_GPT_PEFT_Lora_TP2_O1:
needs: [cicd-test-container-setup]
uses: ./.github/workflows/_test_template.yml
with:
Expand All @@ -3108,11 +3127,11 @@ jobs:
trainer.max_steps=3 \
trainer.val_check_interval=3 \
++trainer.limit_val_batches=2 \
trainer.precision=16 \
trainer.precision=bf16 \
exp_manager.exp_dir=/home/TestData/nlp/lora_tuning_tp2 \
model.pipeline_model_parallel_size=1 \
model.tensor_model_parallel_size=2 \
model.restore_from_path=/home/TestData/nlp/megatron_gpt/TP2/megatron_gpt_tp2.nemo \
model.restore_from_path=/home/TestData/nlp/megatron_gpt/mcore_45M/megatron_llama.nemo \
model.peft.peft_scheme='lora' \
model.answer_only_loss=True \
model.micro_batch_size=1 \
Expand All @@ -3125,7 +3144,7 @@ jobs:
model.data.validation_ds.names=[quarel]

python examples/nlp/language_modeling/tuning/megatron_gpt_generate.py \
model.restore_from_path=/home/TestData/nlp/megatron_gpt/TP2/megatron_gpt_tp2.nemo \
model.restore_from_path=/home/TestData/nlp/megatron_gpt/mcore_45M/megatron_llama.nemo \
model.peft.restore_from_path=/home/TestData/nlp/lora_tuning_tp2/megatron_gpt_peft_lora_tuning/checkpoints/megatron_gpt_peft_lora_tuning.nemo \
model.tensor_model_parallel_size=2 \
trainer.devices=2 \
Expand Down Expand Up @@ -4234,8 +4253,8 @@ jobs:
- L2_Megatron_GPT_Finetuning_PP2
- L2_Megatron_GPT_Finetuning_StarCoder_PP1
- L2_Megatron_GPT_Embedding
- L2_Megatron_GPT_PEFT_Lora_PP2
- L2_Megatron_GPT_PEFT_Lora_TP2
- L2_Megatron_GPT_PEFT_Lora_PP2_O2
- L2_Megatron_GPT_PEFT_Lora_TP2_O1
- L2_Megatron_GPT_Eval
- L2_Megatron_GPT_Eval_PP2
- L2_Megatron_GPT_SFT_Eval_inference_seq_len_greaterThan_training_seq_len
Expand Down
14 changes: 7 additions & 7 deletions nemo/collections/nlp/parts/mixins/nlp_adapter_mixins.py
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Original file line number Diff line number Diff line change
Expand Up @@ -109,11 +109,11 @@ def _get_all_keys(
"""
Returns all the keys in the model
"""
k = [n for n, p in self._unwrap_model().named_parameters()]
k = [n for n, p in self._unwrap_model().named_parameters(prefix="model")]
b = [
n
for n, p in self._unwrap_model().named_buffers()
if n.replace("model.module.", "model.", 1) in self._unwrap_model().state_dict().keys()
for n, p in self._unwrap_model().named_buffers(prefix="model")
if n.replace("model.module.", "model.", 1) in self._unwrap_model().state_dict(prefix="model.").keys()
]
# we include buffers because ptuning representations are cached in a buffer and saved to state_dict for inference time use.
return set(k + b)
Expand Down Expand Up @@ -292,13 +292,13 @@ def setup_optimizer_param_groups(self):
self.freeze(training=True) # Freeze the entire model
if not self.ptuning_only_and_non_first_stage:
opt_params = []
for _, module in self._unwrap_model().named_modules():
for _, module in self._unwrap_model().named_modules(prefix="model"):
if isinstance(module, AdapterModuleMixin) and module.is_adapter_available():
module.set_enabled_adapters(enabled=True)
module.unfreeze_enabled_adapters() # selectively unfreeze the adapter modules.
opt_params += [p for p in module.parameters() if p.requires_grad]

for name, param in self._unwrap_model().named_parameters():
for name, param in self._unwrap_model().named_parameters(prefix="model"):
if name in self.tunable_base_param_keys:
param.requires_grad = True
opt_params += [param]
Expand Down Expand Up @@ -397,11 +397,11 @@ def get_peft_state_dict(self):
"""
Gets the keys associated with the adapters only.
"""
state_dict = self._unwrap_model().state_dict()
state_dict = self._unwrap_model().state_dict(prefix="model.")
peft_state_dict = {}
for k in self.adapter_keys.union(self.tunable_base_param_keys):
# state_dict keys needs to be in non-O2 format and will be corrected in PEFTSaveRestoreConnector if O2=True
new_k = k.replace("module.", "", 1)
new_k = k.replace("model.module.", "model.", 1)
peft_state_dict[new_k] = state_dict[new_k]
return peft_state_dict

Expand Down
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