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import os
from llm_studio.src.utils.config_utils import load_config_yaml
def test_load_config_yaml():
test_directory = os.path.abspath(os.path.join(os.path.dirname(__file__), "../"))
cfg_path = os.path.join(test_directory, "test_data/cfg.yaml")
cfg = load_config_yaml(cfg_path)
assert cfg.experiment_name == "test"
assert cfg.llm_backbone == "EleutherAI/pythia-12b-deduped"
assert cfg.output_directory == "output/user/test/"
assert cfg.architecture.backbone_dtype == "float16"
assert cfg.architecture.force_embedding_gradients is False
assert cfg.architecture.gradient_checkpointing is False
assert cfg.architecture.intermediate_dropout == 0.0
assert cfg.augmentation.token_mask_probability == 0.0
assert cfg.dataset.add_eos_token_to_answer is True
assert cfg.dataset.add_eos_token_to_prompt is True
assert cfg.dataset.answer_column == "output"
assert cfg.dataset.data_sample == 0.1
assert cfg.dataset.data_sample_choice == ["Train", "Validation"]
assert cfg.dataset.mask_prompt_labels is False
assert cfg.dataset.prompt_column == ("instruction",)
assert cfg.dataset.text_answer_separator == "\\n"
assert cfg.dataset.text_prompt_start == ""
assert cfg.dataset.train_dataframe == "data/user/train/train.csv"
assert cfg.dataset.validation_dataframe == "None"
assert cfg.dataset.validation_size == 0.01
assert cfg.dataset.validation_strategy == "automatic"
assert cfg.environment.compile_model is False
assert cfg.environment.find_unused_parameters is False
assert cfg.environment.gpus == ["0"]
assert cfg.environment.mixed_precision is True
assert cfg.environment.number_of_workers == 8
assert cfg.environment.seed == -1
assert cfg.logging.logger == "None"
assert cfg.logging.neptune_project == ""
assert cfg.prediction.batch_size_inference == 0
assert cfg.prediction.do_sample is False
assert cfg.prediction.max_length_inference == 256
assert cfg.prediction.min_length_inference == 2
assert cfg.prediction.num_beams == 2
assert cfg.prediction.repetition_penalty == 1.2
assert cfg.prediction.stop_tokens == ""
assert cfg.prediction.temperature == 0.3
assert cfg.tokenizer.max_length == 144
assert cfg.tokenizer.max_length_answer == 256
assert cfg.tokenizer.max_length_prompt == 256
assert cfg.tokenizer.padding_quantile == 1.0
assert cfg.training.batch_size == 3
assert cfg.training.epochs == 0
assert cfg.training.evaluate_before_training is True
assert cfg.training.evaluation_epochs == 1.0
assert cfg.training.grad_accumulation == 1
assert cfg.training.gradient_clip == 0.0
assert cfg.training.learning_rate == 0.0001
assert cfg.training.lora is True
assert cfg.training.lora_alpha == 16
assert cfg.training.lora_dropout == 0.05
assert cfg.training.lora_r == 4
assert cfg.training.lora_target_modules == ""
assert cfg.training.optimizer == "AdamW"
assert cfg.training.save_best_checkpoint is False
assert cfg.training.schedule == "Cosine"
assert cfg.training.train_validation_data is False
assert cfg.training.warmup_epochs == 0.0
assert cfg.training.weight_decay == 0.0
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