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"""Moses baselines training utilities."""
from dataclasses import dataclass, field
from typing import Any, Dict
from ..core import TrainingPipeline, TrainingPipelineArguments
[docs]class MosesTrainingPipeline(TrainingPipeline):
"""PyTorch lightining training pipelines."""
[docs] def train( # type: ignore
self,
training_args: Dict[str, Any],
model_args: Dict[str, Any],
common_args: Dict[str, Any],
) -> None:
"""Generic training function for GuacaMol Baselines training.
Args:
training_args: training arguments passed to the configuration.
model_args: model arguments passed to the configuration.
common_args: common arguments passed to the configuration.
Raises:
NotImplementedError: the generic trainer does not implement the pipeline.
"""
raise NotImplementedError
[docs]@dataclass
class MosesDataArguments(TrainingPipelineArguments):
"""Arguments related to Moses data loading."""
__name__ = "dataset_args"
train_load: str = field(
metadata={"help": "Input data in csv format used for training."}
)
val_load: str = field(
metadata={"help": "Input data in csv format used for validation."}
)
[docs]@dataclass
class MosesTrainingArguments(TrainingPipelineArguments):
"""Arguments related to Moses trainer."""
__name__ = "training_args"
model_save: str = field(metadata={"help": "Path where the trained model is saved."})
log_file: str = field(metadata={"help": "Path where to save the the logs."})
config_save: str = field(metadata={"help": "Path for the config."})
vocab_save: str = field(metadata={"help": "Path to save the model vocabulary."})
save_frequency: int = field(
default=1, metadata={"help": "How often to save the model."}
)
seed: int = field(
default=0, metadata={"help": "Seed used for random number generation."}
)
device: str = field(
default="cpu",
metadata={"help": "Device to run: 'cpu' or 'cuda:<device number>'"},
)
[docs]@dataclass
class MosesSavingArguments(TrainingPipelineArguments):
"""Saving arguments related to PaccMann trainer."""
__name__ = "saving_args"
model_path: str = field(metadata={"help": "Path where the model is stored."})
config_path: str = field(metadata={"help": "Path where the config is stored."})
vocab_path: str = field(metadata={"help": "Path where the vocab is stored."})