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Description
Describe the bug
CLI parser throws an error when providing a config via yaml flag.
Steps/Code to reproduce bug
App version: commit 01a9a8b
Invocation:
torchrun --standalone --nnodes=1 --nproc_per_node=1 recipe.py --factory 'my_simple_recipe(model_name="meta/llama-3.2-1b-instruct")' --yes --yaml config.yaml -vThe my_simple_recipe recipe is based on /opt/NeMo/nemo/collections/llm/recipes/llama32_1b.py
config.yaml
data:
dataset_root: /workspace/datasets/test_dataset
seq_length: 4096
global_batch_size: 1
micro_batch_size: 1
dataset_kwargs:
prompt_template: '{prompt} {completion}'
truncation_field: prompt
label_key: completion
add_bos: false
add_eos: true
trainer:
accelerator: gpu
max_epochs: 1
limit_val_batches: 1.0
log_every_n_steps: 10
max_steps: 32
strategy:
tensor_model_parallel_size: 1
pipeline_model_parallel_size: 1
context_parallel_size: 1
ckpt_async_save: false
val_check_interval: 1
log:
ckpt:
save_last: link
save_top_k: 1
train_time_interval: null
every_n_train_steps: 2
filename: '{model_name}--{val_loss:.4f}-{step}-{consumed_samples}'
resume:
restore_config:
path: /mount/models/llama32_1b-instruct_2_0
peft:
dim: 32
alpha: 16
model:
config:
seq_length: 4096Error:
nemo_run.cli.cli_parser.UnknownTypeError: Failed to parse 'Error parsing argument: Failed to parse '32' as int: Unsupported type: int (Argument: 32, Context: {'expected_type': 'int'})' as peft.dim=32: {'key': 'peft.dim', 'value': '32', 'expected_type': 'int'} (Argument: Error parsing argument: Failed to parse '32' as int: Unsupported type: int (Argument: 32, Context: {'expected_type': 'int'}), Context: {'expected_type': 'peft.dim=32'})Expected behavior
Should be able to parse config.yaml correctly without errors
Additional context
Possible cause: _resolve_type_checking_annotation() does not resolve the type correctly returning 'int' back instead of int as a type.
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