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[remove import *][2/n] remove rest of import * in implementations (#690)
# What does this PR do? - see https://github.com/meta-llama/llama-stack/pull/689 <img width="591" alt="image" src="https://github.com/user-attachments/assets/76946a67-7373-43b5-8a03-0ad201aa543b" /> - leaving `tools/builtin.py` to avoid conflicts ## Test Plan - see https://github.com/meta-llama/llama-stack/pull/689 ## Sources Please link relevant resources if necessary. ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Ran pre-commit to handle lint / formatting issues. - [ ] Read the [contributor guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md), Pull Request section? - [ ] Updated relevant documentation. - [ ] Wrote necessary unit or integration tests.
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84 changed files with 824 additions and 321 deletions
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@ -14,11 +14,10 @@ from enum import Enum
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from typing import Any, Callable, Dict, List
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import torch
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from llama_stack.apis.datasets import Datasets
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from llama_stack.apis.common.type_system import * # noqa
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from llama_models.datatypes import Model
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from llama_models.sku_list import resolve_model
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from llama_stack.apis.common.type_system import ParamType
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from llama_stack.apis.common.type_system import ParamType, StringType
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from llama_stack.apis.datasets import Datasets
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from torchtune.models.llama3 import llama3_tokenizer, lora_llama3_8b
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from torchtune.models.llama3._tokenizer import Llama3Tokenizer
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@ -3,11 +3,26 @@
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from datetime import datetime
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from typing import Any, Dict, List, Optional
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from llama_models.schema_utils import webmethod
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from llama_stack.apis.datasetio import DatasetIO
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from llama_stack.apis.datasets import Datasets
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from llama_stack.apis.post_training import (
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AlgorithmConfig,
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DPOAlignmentConfig,
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JobStatus,
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LoraFinetuningConfig,
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PostTrainingJob,
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PostTrainingJobArtifactsResponse,
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PostTrainingJobStatusResponse,
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TrainingConfig,
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)
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from llama_stack.providers.inline.post_training.torchtune.config import (
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TorchtunePostTrainingConfig,
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)
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from llama_stack.apis.post_training import * # noqa
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from llama_stack.providers.inline.post_training.torchtune.recipes.lora_finetuning_single_device import (
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LoraFinetuningSingleDevice,
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)
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@ -14,27 +14,33 @@ from typing import Any, Dict, List, Optional, Tuple
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import torch
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from llama_models.sku_list import resolve_model
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from llama_stack.apis.common.training_types import PostTrainingMetric
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from llama_stack.apis.datasetio import DatasetIO
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from llama_stack.apis.datasets import Datasets
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from llama_stack.apis.post_training import (
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AlgorithmConfig,
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Checkpoint,
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LoraFinetuningConfig,
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OptimizerConfig,
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TrainingConfig,
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)
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from llama_stack.distribution.utils.config_dirs import DEFAULT_CHECKPOINT_DIR
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from llama_stack.providers.inline.post_training.torchtune.common.checkpointer import (
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TorchtuneCheckpointer,
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)
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from torch import nn
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from torchtune import utils as torchtune_utils
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from torchtune.training.metric_logging import DiskLogger
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from tqdm import tqdm
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from llama_stack.apis.post_training import * # noqa
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from llama_stack.distribution.utils.model_utils import model_local_dir
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from llama_stack.providers.inline.post_training.torchtune.common import utils
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from llama_stack.providers.inline.post_training.torchtune.common.checkpointer import (
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TorchtuneCheckpointer,
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)
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from llama_stack.providers.inline.post_training.torchtune.config import (
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TorchtunePostTrainingConfig,
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)
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from llama_stack.providers.inline.post_training.torchtune.datasets.sft import SFTDataset
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from torch import nn
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from torch.optim import Optimizer
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from torch.utils.data import DataLoader, DistributedSampler
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from torchtune import modules, training
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from torchtune import modules, training, utils as torchtune_utils
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from torchtune.data import AlpacaToMessages, padded_collate_sft
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from torchtune.modules.loss import CEWithChunkedOutputLoss
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@ -47,6 +53,8 @@ from torchtune.modules.peft import (
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validate_missing_and_unexpected_for_lora,
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)
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from torchtune.training.lr_schedulers import get_cosine_schedule_with_warmup
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from torchtune.training.metric_logging import DiskLogger
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from tqdm import tqdm
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log = logging.getLogger(__name__)
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