From 844fb7d1616db7667298d9038aadadc81cedbb58 Mon Sep 17 00:00:00 2001 From: samsja Date: Thu, 10 Aug 2023 16:16:17 +0200 Subject: [PATCH 1/8] feat: add cli to push to hf --- README.md | 5 +++++ textbook/dataset_gen/dataset_gen_cli.py | 14 ++++++++++++++ 2 files changed, 19 insertions(+) diff --git a/README.md b/README.md index 5b9c918..af2eb60 100644 --- a/README.md +++ b/README.md @@ -88,3 +88,8 @@ Once the file are generated you can postprocess the files and save it into a jso python dataset_gen_cli.py filter ./exercises dataset.jsonl ``` +push to hf dataset + +```shell +python dataset_gen.py push "jinaai/code_exercises_40k" dataset.jsonl +``` diff --git a/textbook/dataset_gen/dataset_gen_cli.py b/textbook/dataset_gen/dataset_gen_cli.py index 679b9dc..8172d8a 100644 --- a/textbook/dataset_gen/dataset_gen_cli.py +++ b/textbook/dataset_gen/dataset_gen_cli.py @@ -17,6 +17,7 @@ from textbook.dataset_gen.create_prompts import Topic, Query from textbook.dataset_gen.filtering import load_and_filter_exos +from datasets import Dataset app = Typer() @@ -127,5 +128,18 @@ def filter(exo_path: Path, dataset_file: str): write_results_to_jsonl(dataset_file, exos) +def push(repo_name: str, dataset_file: Path): + with open(dataset_file, "r") as file: + lines = file.readlines() + exercises = [json.loads(line) for line in lines] + + def gen(): + for exo in exercises: + yield exo + + dataset = Dataset.from_generator(gen) + dataset.push_to_hub(repo_name) + + if __name__ == "__main__": app() From 5293410640707adf53cd46550d6a0a242bb03d01 Mon Sep 17 00:00:00 2001 From: samsja Date: Thu, 10 Aug 2023 16:29:13 +0200 Subject: [PATCH 2/8] fix: fix cli --- textbook/dataset_gen/dataset_gen_cli.py | 1 + 1 file changed, 1 insertion(+) diff --git a/textbook/dataset_gen/dataset_gen_cli.py b/textbook/dataset_gen/dataset_gen_cli.py index 8172d8a..baccb09 100644 --- a/textbook/dataset_gen/dataset_gen_cli.py +++ b/textbook/dataset_gen/dataset_gen_cli.py @@ -128,6 +128,7 @@ def filter(exo_path: Path, dataset_file: str): write_results_to_jsonl(dataset_file, exos) +@app.command() def push(repo_name: str, dataset_file: Path): with open(dataset_file, "r") as file: lines = file.readlines() From 4d981b244e054d7ab3f5ec70376906cfd51baa99 Mon Sep 17 00:00:00 2001 From: sami jaghouar Date: Fri, 11 Aug 2023 10:45:50 +0200 Subject: [PATCH 3/8] feat: add hf dataset --- tests/training/integration/test_train.py | 4 +- tests/training/units/test_dataset.py | 6 +- textbook/dataset.py | 73 ++++++++++++++++++++++-- textbook/model.py | 2 - textbook/train.py | 16 ++++-- 5 files changed, 86 insertions(+), 15 deletions(-) diff --git a/tests/training/integration/test_train.py b/tests/training/integration/test_train.py index 60f8297..95a602b 100644 --- a/tests/training/integration/test_train.py +++ b/tests/training/integration/test_train.py @@ -3,9 +3,11 @@ @pytest.mark.parametrize("module", ["Replit", "StarCoder"]) -def test_train(module): +@pytest.mark.parametrize("dataset", ["DummyDataset", "ExerciseDatast"]) +def test_train(module, dataset): train( module=module, + dataset=dataset, debug=True, epochs=1, micro_batch_size=1, diff --git a/tests/training/units/test_dataset.py b/tests/training/units/test_dataset.py index 073831e..2c62d7f 100644 --- a/tests/training/units/test_dataset.py +++ b/tests/training/units/test_dataset.py @@ -1,6 +1,6 @@ import pytest -from textbook.dataset import DummyDataset +from textbook.dataset import DummyDataset, ExerciseDatast from textbook.model import Replit from transformers import PreTrainedTokenizer @@ -13,3 +13,7 @@ def tokenizer() -> PreTrainedTokenizer: def test_tiny_stories(tokenizer): DummyDataset(debug=True, tokenizer=tokenizer) + + +def test_exercises_dataet(tokenizer): + ExerciseDatast(debug=True, tokenizer=tokenizer) diff --git a/textbook/dataset.py b/textbook/dataset.py index 62ba0bf..2c2326b 100644 --- a/textbook/dataset.py +++ b/textbook/dataset.py @@ -1,14 +1,18 @@ from typing import Protocol import random -from datasets import Dataset -from transformers import PreTrainedTokenizer, DataCollatorForLanguageModeling +from datasets import Dataset, load_dataset +from transformers import ( + PreTrainedTokenizer, + DataCollatorForLanguageModeling, + DataCollatorForSeq2Seq, +) from transformers.data.data_collator import DataCollatorMixin class CustomDataset(Protocol): train_dataset: Dataset - eval_dataset: Dataset + test_dataset: Dataset data_collator: DataCollatorMixin def __init__( @@ -44,14 +48,14 @@ def __init__( self.test_dataset = split_dataset["test"] self.train_dataset = self.train_dataset.map( - self._get_tokenize_fn(tokenizer), + self._get_preprocess_fn(tokenizer), batched=True, num_proc=4, remove_columns=self.train_dataset.column_names, ) self.test_dataset = self.test_dataset.map( - self._get_tokenize_fn(tokenizer), + self._get_preprocess_fn(tokenizer), batched=True, num_proc=4, remove_columns=self.test_dataset.column_names, @@ -60,10 +64,67 @@ def __init__( self.data_collator = DataCollatorForLanguageModeling(tokenizer, mlm=False) @staticmethod - def _get_tokenize_fn(tokenizer: PreTrainedTokenizer): + def _get_preprocess_fn(tokenizer: PreTrainedTokenizer): def tokenize_fn(input): return tokenizer( input["text"], ) return tokenize_fn + + +class ExerciseDatast: + def __init__( + self, + tokenizer: PreTrainedTokenizer, + debug: bool = False, + ): + self.debug = debug + + dataset = load_dataset("jinaai/code_exercises_40k")["train"] + + if debug: + dataset = dataset.select(range(10)) + + split_dataset = dataset.train_test_split(test_size=0.1) + + self.train_dataset = split_dataset["train"] + self.test_dataset = split_dataset["test"] + + self.train_dataset = self.train_dataset.map( + self._get_preprocess_fn(tokenizer), + batched=False, + num_proc=4, + remove_columns=self.train_dataset.column_names, + ) + + self.test_dataset = self.test_dataset.map( + self._get_preprocess_fn(tokenizer), + batched=False, + num_proc=4, + remove_columns=self.test_dataset.column_names, + ) + + self.data_collator = DataCollatorForSeq2Seq( + tokenizer, pad_to_multiple_of=8, return_tensors="pt", padding=True + ) + + @staticmethod + def _get_preprocess_fn(tokenizer: PreTrainedTokenizer): + def tokenize_fn(input): + input_problem = input["problem"] + input_solution = input["solution"] + + inputs = tokenizer(input_problem) + targets = tokenizer(input_solution) + inputs["labels"] = [-100] * len(inputs["input_ids"]) + targets[ + "input_ids" + ] # we don't train on the problem tokens + inputs["input_ids"] = inputs["input_ids"] + targets["input_ids"] + inputs["attention_mask"] = ( + inputs["attention_mask"] + targets["attention_mask"] + ) + + return inputs + + return tokenize_fn diff --git a/textbook/model.py b/textbook/model.py index c9601a3..fc6e731 100644 --- a/textbook/model.py +++ b/textbook/model.py @@ -48,7 +48,6 @@ def _init_tokenizer(self): self.tokenizer = AutoTokenizer.from_pretrained( self.base_model, trust_remote_code=True ) - self.tokenizer.padding_side = "left" # Allow batched inference self.tokenizer.pad_token = self.tokenizer.eos_token @@ -78,5 +77,4 @@ def _init_tokenizer(self): self.tokenizer = AutoTokenizer.from_pretrained( self.base_model, ) - self.tokenizer.padding_side = "left" # Allow batched inference self.tokenizer.pad_token = self.tokenizer.eos_token diff --git a/textbook/train.py b/textbook/train.py index 0c16f08..b1536ca 100644 --- a/textbook/train.py +++ b/textbook/train.py @@ -5,7 +5,7 @@ import torch -from textbook.dataset import DummyDataset +from textbook.dataset import CustomDataset from textbook.evaluate import evaluate from textbook.model import BaseModule @@ -37,6 +37,7 @@ def wrapper(*args, **kwargs): def train( *, module: str = "StarCoder", + dataset: str = "ExerciseDatast", epochs: int = 1, micro_batch_size: int = 1, batch_size: int = 1, @@ -54,12 +55,17 @@ def train( eval_size: Optional[int] = None, eval_max_new_tokens: int = 512, ): + module_cls: Type[BaseModule] = getattr(import_module("textbook.model"), module) module_instance = module_cls(debug=debug) model = torch.compile(module_instance.model) model = module_instance.model tokenizer = module_instance.tokenizer - dataset = DummyDataset(tokenizer=tokenizer, debug=debug) + + dataset_cls: Type[CustomDataset] = getattr( + import_module("textbook.dataset"), dataset + ) + dataset_instance = dataset_cls(tokenizer=tokenizer, debug=debug) if debug: wandb_run_name = "debug" @@ -84,8 +90,8 @@ def train( trainer = transformers.Trainer( model=model, - train_dataset=dataset.train_dataset, - eval_dataset=dataset.test_dataset, + train_dataset=dataset_instance.train_dataset, + eval_dataset=dataset_instance.test_dataset, args=transformers.TrainingArguments( per_device_train_batch_size=micro_batch_size, gradient_accumulation_steps=batch_size // micro_batch_size, @@ -104,7 +110,7 @@ def train( run_name=wandb_run_name if use_wandb else None, remove_unused_columns=False, ), - data_collator=dataset.data_collator, + data_collator=dataset_instance.data_collator, ) trainer.train() From 58a136a59fe55131118706fa09d355eca7d7b412 Mon Sep 17 00:00:00 2001 From: sami jaghouar Date: Fri, 11 Aug 2023 10:56:54 +0200 Subject: [PATCH 4/8] feat: add hf dataset --- README.md | 2 +- textbook/train.py | 1 - 2 files changed, 1 insertion(+), 2 deletions(-) diff --git a/README.md b/README.md index af2eb60..8421547 100644 --- a/README.md +++ b/README.md @@ -91,5 +91,5 @@ python dataset_gen_cli.py filter ./exercises dataset.jsonl push to hf dataset ```shell -python dataset_gen.py push "jinaai/code_exercises_40k" dataset.jsonl +python dataset_gen_cli.py push "jinaai/code_exercises_40k" dataset.jsonl ``` diff --git a/textbook/train.py b/textbook/train.py index b1536ca..4552588 100644 --- a/textbook/train.py +++ b/textbook/train.py @@ -55,7 +55,6 @@ def train( eval_size: Optional[int] = None, eval_max_new_tokens: int = 512, ): - module_cls: Type[BaseModule] = getattr(import_module("textbook.model"), module) module_instance = module_cls(debug=debug) model = torch.compile(module_instance.model) From 3f2e59461a0bb0d55cd4cd94e0d34011327f651b Mon Sep 17 00:00:00 2001 From: sami jaghouar Date: Fri, 11 Aug 2023 11:10:22 +0200 Subject: [PATCH 5/8] feat: tune param --- textbook/train.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/textbook/train.py b/textbook/train.py index 4552588..d7d03a2 100644 --- a/textbook/train.py +++ b/textbook/train.py @@ -94,7 +94,8 @@ def train( args=transformers.TrainingArguments( per_device_train_batch_size=micro_batch_size, gradient_accumulation_steps=batch_size // micro_batch_size, - optim="adamw_torch", + optim="paged_adamw_8bit", + gradient_checkpointing=True, warmup_steps=100, num_train_epochs=epochs, learning_rate=learning_rate, From d230dae59b2cabdc6f3cc020148a4eee240a3d40 Mon Sep 17 00:00:00 2001 From: sami jaghouar Date: Fri, 11 Aug 2023 11:14:53 +0200 Subject: [PATCH 6/8] feat: update dependency --- poetry.lock | 1066 ++++++++++++++++++++++++++------------------------- 1 file changed, 534 insertions(+), 532 deletions(-) diff --git a/poetry.lock b/poetry.lock index 4b5d15b..1f41b29 100644 --- a/poetry.lock +++ b/poetry.lock @@ -282,13 +282,13 @@ test = ["astroid", "pytest"] [[package]] name = "async-lru" -version = "2.0.3" +version = "2.0.4" description = "Simple LRU cache for asyncio" optional = false python-versions = ">=3.8" files = [ - {file = "async-lru-2.0.3.tar.gz", hash = "sha256:b714c9d1415fca4e264da72a9e2abc66880ce7430e03a973341f88ea4c0d4869"}, - {file = "async_lru-2.0.3-py3-none-any.whl", hash = "sha256:00c0a8899c20b9c88663a47732689ff98189c9fa08ad9f734d7722f934d250b1"}, + {file = "async-lru-2.0.4.tar.gz", hash = "sha256:b8a59a5df60805ff63220b2a0c5b5393da5521b113cd5465a44eb037d81a5627"}, + {file = "async_lru-2.0.4-py3-none-any.whl", hash = "sha256:ff02944ce3c288c5be660c42dbcca0742b32c3b279d6dceda655190240b99224"}, ] [package.dependencies] @@ -296,13 +296,13 @@ typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.11\""} [[package]] name 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b/textbook/train.py index d7d03a2..c53db77 100644 --- a/textbook/train.py +++ b/textbook/train.py @@ -83,7 +83,7 @@ def train( use_wandb = local_rank == 0 and use_wandb if use_wandb: - run = wandb.init(wandb_project, **dict(config=config_to_log)) # type: ignore + run = wandb.init(project=wandb_project, **dict(config=config_to_log)) # type: ignore else: run = None # type: ignore From 0f695c8222b6f83e4ba876b98d270876f1898360 Mon Sep 17 00:00:00 2001 From: sami jaghouar Date: Fri, 11 Aug 2023 12:58:24 +0200 Subject: [PATCH 8/8] fix: fix optim --- textbook/train.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/textbook/train.py b/textbook/train.py index c53db77..ae05549 100644 --- a/textbook/train.py +++ b/textbook/train.py @@ -94,8 +94,8 @@ def train( args=transformers.TrainingArguments( per_device_train_batch_size=micro_batch_size, gradient_accumulation_steps=batch_size // micro_batch_size, - optim="paged_adamw_8bit", - gradient_checkpointing=True, + optim="adamw_torch", + # gradient_checkpointing=True, warmup_steps=100, num_train_epochs=epochs, learning_rate=learning_rate,