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# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
#
import logging
from typing import Any, Dict
from fairseq2.models.config_loader import StandardModelConfigLoader
from fairseq2.models.loader import StandardModelLoader, load_model
from torch.nn.modules.utils import consume_prefix_in_state_dict_if_present
from lcm.models.base_lcm.builder import (
BASE_LCM_MODEL_TYPE,
BaseLCModelConfig,
create_base_lcm_model,
lcm_archs,
)
from lcm.utils.model_type_registry import ModelTypeConfig, lcm_model_type_registry
logger = logging.getLogger(__name__)
def convert_lcm_checkpoint(
checkpoint: Dict[str, Any], config: BaseLCModelConfig
) -> Dict[str, Any]:
# For DDP checkpoints
# We need to first remove the prefix "module." from state dict keys.
consume_prefix_in_state_dict_if_present(checkpoint["model"], "module.")
return checkpoint
load_base_lcm_config = StandardModelConfigLoader(
family=BASE_LCM_MODEL_TYPE,
config_kls=BaseLCModelConfig,
arch_configs=lcm_archs,
)
load_base_lcm_model = StandardModelLoader(
config_loader=load_base_lcm_config,
factory=create_base_lcm_model,
checkpoint_converter=convert_lcm_checkpoint,
restrict_checkpoints=False,
)
load_model.register(BASE_LCM_MODEL_TYPE, load_base_lcm_model)
lcm_model_type_registry.register(
ModelTypeConfig(
model_type=BASE_LCM_MODEL_TYPE,
config_loader=load_base_lcm_config,
model_factory=create_base_lcm_model,
model_loader=load_base_lcm_model,
)
)
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