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a/turbo_alignment/cherry_picks/multimodal.py b/turbo_alignment/cherry_picks/multimodal.py index 80c6022..ba1c536 100755 --- a/turbo_alignment/cherry_picks/multimodal.py +++ b/turbo_alignment/cherry_picks/multimodal.py @@ -1,10 +1,10 @@ from typing import Iterable import torch +import wandb from PIL import Image from transformers import PreTrainedTokenizerBase -import wandb from turbo_alignment.cherry_picks.base import CherryPickCallbackBase from turbo_alignment.dataset.multimodal import InferenceMultimodalDataset from turbo_alignment.generators.multimodal import MultimodalGenerator diff --git a/turbo_alignment/common/data/io.py b/turbo_alignment/common/data/io.py index f1c738f..fe62323 100755 --- a/turbo_alignment/common/data/io.py +++ b/turbo_alignment/common/data/io.py @@ -18,8 +18,8 @@ def read_jsonl(path: Path): return [json.loads(line) for line in f] -def write_jsonl(records: Any, path: Path) -> None: - with path.open('w', encoding='utf-8') as f: +def write_jsonl(records: Any, path: Path, mode='w') -> None: + with path.open(mode, encoding='utf-8') as f: for r in records: f.write(json.dumps(r, ensure_ascii=False) + '\n') diff --git a/turbo_alignment/common/logging/weights_and_biases.py b/turbo_alignment/common/logging/weights_and_biases.py index 112e585..3b5bdfd 100755 --- a/turbo_alignment/common/logging/weights_and_biases.py +++ b/turbo_alignment/common/logging/weights_and_biases.py @@ -1,9 +1,9 @@ from typing import Any +import wandb from wandb.sdk.lib.disabled import RunDisabled from wandb.sdk.wandb_run import Run -import wandb from turbo_alignment.settings.logging.weights_and_biases import WandbSettings diff --git a/turbo_alignment/common/tf/callbacks/logging.py b/turbo_alignment/common/tf/callbacks/logging.py index 8f90288..5623c14 100755 --- a/turbo_alignment/common/tf/callbacks/logging.py +++ b/turbo_alignment/common/tf/callbacks/logging.py @@ -3,6 +3,7 @@ import numpy as np import pandas as pd +import wandb from clearml import Task from transformers import ( TrainerCallback, @@ -13,7 +14,6 @@ from wandb.sdk.lib.disabled import RunDisabled from wandb.sdk.wandb_run import Run -import wandb from turbo_alignment.common.logging import get_project_logger logger = get_project_logger() diff --git a/turbo_alignment/common/tf/special_tokens_setter.py b/turbo_alignment/common/tf/special_tokens_setter.py index b1aaeb6..bc42b26 100755 --- a/turbo_alignment/common/tf/special_tokens_setter.py +++ b/turbo_alignment/common/tf/special_tokens_setter.py @@ -13,12 +13,12 @@ def __init__(self, tokenizer: PreTrainedTokenizerBase, special_tokens_settings: self._special_tokens_settings = special_tokens_settings self._special_tokens_already_set: bool = False - def setBOS(self, bos_token: str) -> None: + def setBOS(self, bos_token: str | None) -> None: if self._tokenizer.bos_token_id is None: logger.info('Model does not have bos_token_id') - self._tokenizer.add_special_tokens(special_tokens_dict={'bos_token': bos_token}) - assert self._tokenizer.bos_token_id is not None - logger.info(f'Created bos_token_id = {self._tokenizer.bos_token_id}') + if bos_token is not None: + self._tokenizer.add_special_tokens(special_tokens_dict={'bos_token': bos_token}) + logger.info(f'Created bos_token_id = {self._tokenizer.bos_token_id}') else: logger.info(f'Model has bos_token_id = {self._tokenizer.bos_token_id}') @@ -94,9 +94,10 @@ def set_custom_tokens(self, tokens: list[str]) -> None: assert added_tokens == len(tokens) def setup_model_config(self, model: PreTrainedModel) -> None: - model.config.bos_token_id = self._tokenizer.bos_token_id model.config.eos_token_id = self._tokenizer.eos_token_id + if self._tokenizer.bos_token_id is not None: + model.config.bos_token_id = self._tokenizer.bos_token_id if self._tokenizer.pad_token_id is not None: model.config.pad_token_id = self._tokenizer.pad_token_id if self._tokenizer.sep_token_id is not None: diff --git a/turbo_alignment/dataset/chat/chat.py b/turbo_alignment/dataset/chat/chat.py index 5a20c4c..049d266 100755 --- a/turbo_alignment/dataset/chat/chat.py +++ b/turbo_alignment/dataset/chat/chat.py @@ -247,8 +247,9 @@ def _truncate_and_merge( input_ids = input_ids[cut_index:] labels = labels[-len(input_ids) :] - input_ids = np.concatenate((np.array([self.tokenizer.bos_token_id]), input_ids)) - labels = np.concatenate((np.array([DISABLE_LOSS_LABEL]), labels)) + if self.tokenizer.bos_token_id is not None: + input_ids = np.concatenate((np.array([self.tokenizer.bos_token_id]), input_ids)) + labels = np.concatenate((np.array([DISABLE_LOSS_LABEL]), labels)) return input_ids, labels, conversation.get_prompt_repr(left_bound, right_bound) diff --git a/turbo_alignment/pipelines/inference/chat.py b/turbo_alignment/pipelines/inference/chat.py index 93b975c..6adf016 100755 --- a/turbo_alignment/pipelines/inference/chat.py +++ b/turbo_alignment/pipelines/inference/chat.py @@ -44,6 +44,7 @@ def _get_single_inference_settings( dtype='bfloat16', tensor_parallel_size=model_inference_settings.tensor_parallel_size, enable_lora=enable_lora, + gpu_memory_utilization=0.95, ) else: diff --git a/turbo_alignment/settings/pipelines/train/dpo.py b/turbo_alignment/settings/pipelines/train/dpo.py index bc85133..c08b8b8 100755 --- a/turbo_alignment/settings/pipelines/train/dpo.py +++ b/turbo_alignment/settings/pipelines/train/dpo.py @@ -26,6 +26,7 @@ class DPOLossesType(str, Enum): APO_DOWN = 'apo_down' ASFT = 'asft' DPOP = 'dpop' + NCA_PAIR = 'nca_pair' class DPOLossSettings(ExtraFieldsNotAllowedBaseModel): @@ -93,6 +94,10 @@ class DPOPLossSettings(DPOLossSettings): lam: float = 0.1 +class NCAPairLossSettings(DPOLossSettings): + loss_type: Literal[DPOLossesType.NCA_PAIR] + + class SyncRefModelSettings(ExtraFieldsNotAllowedBaseModel): sync_ref_model: bool = False alpha: float = 1.0 @@ -114,6 +119,7 @@ class DPOTrainerSettings(TrainerSettings): | APOZeroLossSettings | APODownLossSettings | DPOPLossSettings + | NCAPairLossSettings ) sync_ref_settings: SyncRefModelSettings use_ref_model: bool = True diff --git a/turbo_alignment/settings/tf/special_tokens_setter.py b/turbo_alignment/settings/tf/special_tokens_setter.py index fc6ab7e..ae5f506 100755 --- a/turbo_alignment/settings/tf/special_tokens_setter.py +++ b/turbo_alignment/settings/tf/special_tokens_setter.py @@ -2,7 +2,7 @@ class SpecialTokensSettings(ExtraFieldsNotAllowedBaseModel): - bos_token: str + bos_token: str | None eos_token: str pad_token: str | None = None unk_token: str | None = None diff --git a/turbo_alignment/trainers/dpo.py b/turbo_alignment/trainers/dpo.py index ef3288f..4d14091 100755 --- a/turbo_alignment/trainers/dpo.py +++ b/turbo_alignment/trainers/dpo.py @@ -33,6 +33,7 @@ HingeLossSettings, IPOLossSettings, KTOLossSettings, + NCAPairLossSettings, ORPOLossSettings, SigmoidLossSettings, SigmoidLossWithMarginSettings, @@ -456,6 +457,35 @@ def compute_loss( return loss, chosen_rewards, rejected_rewards +@DPOLossRegistry.register(DPOLossesType.NCA_PAIR) +class NCAPairLoss(DPOLossRegistry): + def __init__(self, *args, beta: float = 0.1, **kwargs) -> None: + self.beta = beta + super().__init__(*args, **kwargs) + + def compute_loss( + self, + policy_chosen_logps: torch.FloatTensor, + policy_rejected_logps: torch.FloatTensor, + reference_chosen_logps: torch.FloatTensor, + reference_rejected_logps: torch.FloatTensor, + precomputed_margins: torch.FloatTensor | None, + ) -> tuple[torch.Tensor, torch.Tensor, torch.Tensor]: + chosen_logratios = policy_chosen_logps - reference_chosen_logps + rejected_logratios = policy_rejected_logps - reference_rejected_logps + + chosen_rewards = self.beta * (policy_chosen_logps - reference_chosen_logps).detach() + rejected_rewards = self.beta * (policy_rejected_logps - reference_rejected_logps).detach() + + loss = ( + -F.logsigmoid(chosen_logratios * self.beta) + - 0.5 * F.logsigmoid(-chosen_logratios * self.beta) + - 0.5 * F.logsigmoid(-rejected_logratios * self.beta) + ) + + return loss, chosen_rewards, rejected_rewards + + @dataclass class DPOTrainingArguments(TrainingArguments): loss_settings: ( @@ -473,6 +503,7 @@ class DPOTrainingArguments(TrainingArguments): | APOZeroLossSettings | APODownLossSettings | DPOPLossSettings + | NCAPairLossSettings ) = field( default_factory=SigmoidLossSettings(loss_type=DPOLossesType.SIGMOID) ) # type: ignore[call-overload] @@ -574,14 +605,12 @@ def dpo_loss( policy_rejected_logps: torch.Tensor, reference_chosen_logps: torch.Tensor, reference_rejected_logps: torch.Tensor, - precomputed_margins: torch.Tensor | None, ) -> tuple[torch.Tensor, torch.Tensor, torch.Tensor]: return self.dpo_loss_registry.compute_loss( policy_chosen_logps=policy_chosen_logps, policy_rejected_logps=policy_rejected_logps, reference_chosen_logps=reference_chosen_logps, reference_rejected_logps=reference_rejected_logps, - precomputed_margins=precomputed_margins, ) def _get_batch_logps( @@ -780,9 +809,6 @@ def _compute_metrics( metrics[f'{prefix_name}grad_term'] = ( (self.dpo_loss_registry.beta * F.sigmoid(rejected_rewards - chosen_rewards)).detach().cpu().mean().item() ) - metrics[f'{prefix_name}grad_term_std'] = ( - (self.dpo_loss_registry.beta * F.sigmoid(rejected_rewards - chosen_rewards)).detach().cpu().std().item() - ) return metrics @@ -822,6 +848,7 @@ def compute_loss( model: PreTrainedModel | nn.Module, inputs: dict[str, torch.Tensor | Any], return_outputs=False, + num_items_in_batch=None, ) -> torch.Tensor | tuple[torch.Tensor, dict[str, float]]: loss, metrics = self.get_batch_metrics(model, inputs, train_eval='train') diff --git a/turbo_alignment/trainers/rm.py b/turbo_alignment/trainers/rm.py index 46d9326..ccaf996 100755 --- a/turbo_alignment/trainers/rm.py +++ b/turbo_alignment/trainers/rm.py @@ -31,7 +31,13 @@ def concatenated_forward(self, model: nn.Module, batch: dict[str, Any]) -> tuple return chosen_rewards, rejected_rewards - def compute_loss(self, model, inputs, return_outputs=False) -> tuple[torch.Tensor, dict[str, Any]] | torch.Tensor: + def compute_loss( + self, + model, + inputs, + return_outputs=False, + num_items_in_batch=None, + ) -> tuple[torch.Tensor, dict[str, Any]] | torch.Tensor: rewards_w, rewards_l = self.concatenated_forward(model, inputs) loss = -torch.nn.functional.logsigmoid(rewards_w - rewards_l).mean()