diff --git a/CHANGELOG.md b/CHANGELOG.md index f7fecbd..831a07d 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,10 +1,24 @@ # Change Log +## v0.3.1 + +### Added + +* A [**`pyproject.toml`** +file](https://github.com/sgrvinod/chess-transformers/blob/main/pyproject.toml) has been added in compliance with [PEP 660](https://peps.python.org/pep-0660/). While the inclusion of a `setup.py` file is not deprecated, its use as a command-line tool, such as in the legacy `setup.py develop` method for performing an editable installation is now deprecated. + +### Changed + +* **`chess_transformers.train.datasets.ChessDataset`** was optimized for large datasets. A list of indices for the data split is no longer maintained or indexed in the dataset. +* The `TRAINING_CHECKPOINT` parameter in each of **`chess_transformers.configs.models`** was set to `None` to reflect the correct conditions for beginning training of a model. +* Dynamic shape tracing is disabled for the compilation of [*CT-ED-45*](https://github.com/sgrvinod/chess-transformers#ct-ed-45) to prevent memory leaks as seen in [#16](https://github.com/sgrvinod/chess-transformers/issues/16). +* References to `torch.cuda.amp.GradScaler(...)` have been replaced by `torch.amp.GradScaler(device="cuda", ...)` following its deprecation. + ## v0.3.0 ### Added -* There are 3 new datasets: [ML23c](https://github.com/sgrvinod/chess-transformers#ml23c), [GC22c](https://github.com/sgrvinod/chess-transformers#gc22c), and [ML23d](https://github.com/sgrvinod/chess-transformers#ml23d). +* There are 3 new datasets: [*ML23c*](https://github.com/sgrvinod/chess-transformers#ml23c), [*GC22c*](https://github.com/sgrvinod/chess-transformers#gc22c), and [*ML23d*](https://github.com/sgrvinod/chess-transformers#ml23d). * A new naming convention for datasets is used. Datasets are now named in the format "[*PGN Fileset*][*Filters*]". For example, *LE1222* is now called [*LE22ct*](https://github.com/sgrvinod/chess-transformers#le22ct), where *LE22* is the name of the PGN fileset from which this dataset was derived, and "*c*", "*t*" are filters for games that ended in checkmates and games that used a specific time control respectively. * [*CT-EFT-85*](https://github.com/sgrvinod/chess-transformers#ct-eft-85) is a new trained model with about 85 million parameters. * **`chess_transformers.train.utils.get_lr()`** now accepts new arguments, `schedule` and `decay`, to accomodate a new learning rate schedule: exponential decay after warmup. diff --git a/README.md b/README.md index e8e2c6e..56e84b9 100644 --- a/README.md +++ b/README.md @@ -4,7 +4,7 @@

Chess Transformers

Teaching transformers to play chess

-

Version License

+

Version License


*Chess Transformers* is a library for training transformer models to play chess by learning from human games. diff --git a/chess_transformers/configs/models/CT-E-20.py b/chess_transformers/configs/models/CT-E-20.py index b003bfd..1694f0f 100644 --- a/chess_transformers/configs/models/CT-E-20.py +++ b/chess_transformers/configs/models/CT-E-20.py @@ -94,8 +94,8 @@ pathlib.Path(__file__).parent.parent.parent.resolve() / "checkpoints" / NAME ) # folder containing checkpoints TRAINING_CHECKPOINT = ( - NAME + ".pt" -) # path to model checkpoint to resume training, None if none + None # path to model checkpoint (NAME + ".pt") to resume training, None if none +) CHECKPOINT_AVG_PREFIX = ( "step" # prefix to add to checkpoint name when saving checkpoints for averaging ) diff --git a/chess_transformers/configs/models/CT-ED-45.py b/chess_transformers/configs/models/CT-ED-45.py index d61cf64..81dbcb5 100644 --- a/chess_transformers/configs/models/CT-ED-45.py +++ b/chess_transformers/configs/models/CT-ED-45.py @@ -50,7 +50,7 @@ N_MOVES = 10 # expected maximum length of move sequences in the model, <= MAX_MOVE_SEQUENCE_LENGTH DISABLE_COMPILATION = False # disable model compilation? COMPILATION_MODE = "default" # mode of model compilation (see torch.compile()) -DYNAMIC_COMPILATION = True # expect tensors with dynamic shapes? +DYNAMIC_COMPILATION = False # expect tensors with dynamic shapes? SAMPLING_K = 1 # k in top-k sampling model predictions during play MODEL = ChessTransformer # custom PyTorch model to train @@ -94,8 +94,8 @@ pathlib.Path(__file__).parent.parent.parent.resolve() / "checkpoints" / NAME ) # folder containing checkpoints TRAINING_CHECKPOINT = ( - NAME + ".pt" -) # path to model checkpoint to resume training, None if none + None # path to model checkpoint (NAME + ".pt") to resume training, None if none +) CHECKPOINT_AVG_PREFIX = ( "step" # prefix to add to checkpoint name when saving checkpoints for averaging ) diff --git a/chess_transformers/configs/models/CT-EFT-20.py b/chess_transformers/configs/models/CT-EFT-20.py index 54fb64f..4f2f527 100644 --- a/chess_transformers/configs/models/CT-EFT-20.py +++ b/chess_transformers/configs/models/CT-EFT-20.py @@ -94,8 +94,8 @@ pathlib.Path(__file__).parent.parent.parent.resolve() / "checkpoints" / NAME ) # folder containing checkpoints TRAINING_CHECKPOINT = ( - NAME + ".pt" -) # path to model checkpoint to resume training, None if none + None # path to model checkpoint (NAME + ".pt") to resume training, None if none +) CHECKPOINT_AVG_PREFIX = ( "step" # prefix to add to checkpoint name when saving checkpoints for averaging ) diff --git a/chess_transformers/configs/models/CT-EFT-85.py b/chess_transformers/configs/models/CT-EFT-85.py index 93a3350..32a6850 100644 --- a/chess_transformers/configs/models/CT-EFT-85.py +++ b/chess_transformers/configs/models/CT-EFT-85.py @@ -93,7 +93,9 @@ CHECKPOINT_FOLDER = str( pathlib.Path(__file__).parent.parent.parent.resolve() / "checkpoints" / NAME ) # folder containing checkpoints -TRAINING_CHECKPOINT = None # path to model checkpoint to resume training, None if none +TRAINING_CHECKPOINT = ( + None # path to model checkpoint (NAME + ".pt") to resume training, None if none +) AVERAGE_STEPS = {491000, 492500, 494000, 495500, 497000, 498500, 500000} CHECKPOINT_AVG_PREFIX = ( "step" # prefix to add to checkpoint name when saving checkpoints for averaging diff --git a/chess_transformers/train/datasets.py b/chess_transformers/train/datasets.py index 63a63f8..e2ab8eb 100644 --- a/chess_transformers/train/datasets.py +++ b/chess_transformers/train/datasets.py @@ -34,19 +34,15 @@ def __init__(self, data_folder, h5_file, split, n_moves=None, **unused): # Open table in H5 file self.h5_file = tb.open_file(os.path.join(data_folder, h5_file), mode="r") self.encoded_table = self.h5_file.root.encoded_data + self.split = split # Create indices - # TODO: optimize by using a start_index and not a list of indices if split == "train": - self.indices = list(range(0, self.encoded_table.attrs.val_split_index)) + self.first_index = 0 elif split == "val": - self.indices = list( - range( - self.encoded_table.attrs.val_split_index, self.encoded_table.nrows - ) - ) + self.first_index = self.encoded_table.attrs.val_split_index elif split is None: - self.indices = list(range(0, self.encoded_table.nrows)) + self.first_index = 0 else: raise NotImplementedError @@ -56,33 +52,41 @@ def __init__(self, data_folder, h5_file, split, n_moves=None, **unused): if n_moves is not None: # This is the same as min(MAX_MOVE_SEQUENCE_LENGTH, n_moves) self.n_moves = min( - len(self.encoded_table[self.indices[0]]["moves"]) - 1, n_moves + len(self.encoded_table[self.first_index]["moves"]) - 1, n_moves ) else: - self.n_moves = len(self.encoded_table[self.indices[0]]["moves"]) - 1 + self.n_moves = len(self.encoded_table[self.first_index]["moves"]) - 1 def __getitem__(self, i): - turns = torch.IntTensor([self.encoded_table[self.indices[i]]["turn"]]) + turns = torch.IntTensor([self.encoded_table[self.first_index + i]["turn"]]) white_kingside_castling_rights = torch.IntTensor( - [self.encoded_table[self.indices[i]]["white_kingside_castling_rights"]] + [self.encoded_table[self.first_index + i]["white_kingside_castling_rights"]] ) # (1) white_queenside_castling_rights = torch.IntTensor( - [self.encoded_table[self.indices[i]]["white_queenside_castling_rights"]] + [ + self.encoded_table[self.first_index + i][ + "white_queenside_castling_rights" + ] + ] ) # (1) black_kingside_castling_rights = torch.IntTensor( - [self.encoded_table[self.indices[i]]["black_kingside_castling_rights"]] + [self.encoded_table[self.first_index + i]["black_kingside_castling_rights"]] ) # (1) black_queenside_castling_rights = torch.IntTensor( - [self.encoded_table[self.indices[i]]["black_queenside_castling_rights"]] + [ + self.encoded_table[self.first_index + i][ + "black_queenside_castling_rights" + ] + ] ) # (1) board_position = torch.IntTensor( - self.encoded_table[self.indices[i]]["board_position"] + self.encoded_table[self.first_index + i]["board_position"] ) # (64) moves = torch.LongTensor( - self.encoded_table[self.indices[i]]["moves"][: self.n_moves + 1] + self.encoded_table[self.first_index + i]["moves"][: self.n_moves + 1] ) # (n_moves + 1) length = torch.LongTensor( - [self.encoded_table[self.indices[i]]["length"]] + [self.encoded_table[self.first_index + i]["length"]] ).clamp( max=self.n_moves ) # (1), value <= n_moves @@ -99,7 +103,14 @@ def __getitem__(self, i): } def __len__(self): - return len(self.indices) + if self.split == "train": + return self.encoded_table.attrs.val_split_index + elif self.split == "val": + return self.encoded_table.nrows - self.encoded_table.attrs.val_split_index + elif self.split is None: + return self.encoded_table.nrows + else: + raise NotImplementedError class ChessDatasetFT(Dataset): @@ -175,12 +186,11 @@ def __len__(self): elif self.split == "val": return self.encoded_table.nrows - self.encoded_table.attrs.val_split_index elif self.split is None: - self.encoded_table.nrows + return self.encoded_table.nrows else: raise NotImplementedError - if __name__ == "__main__": # Get configuration parser = argparse.ArgumentParser() diff --git a/chess_transformers/train/train.py b/chess_transformers/train/train.py index b362978..378f22e 100644 --- a/chess_transformers/train/train.py +++ b/chess_transformers/train/train.py @@ -5,7 +5,7 @@ import torch.backends.cudnn as cudnn from tqdm import tqdm -from torch.cuda.amp import GradScaler +from torch.amp import GradScaler from torch.utils.data import DataLoader from torch.utils.tensorboard import SummaryWriter @@ -96,7 +96,7 @@ def train_model(CONFIG): criterion = criterion.to(DEVICE) # AMP scaler - scaler = GradScaler(enabled=CONFIG.USE_AMP) + scaler = GradScaler(device=DEVICE, enabled=CONFIG.USE_AMP) # Find total epochs to train epochs = (CONFIG.N_STEPS // (len(train_loader) // CONFIG.BATCHES_PER_STEP)) + 1 diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..62a4d5e --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,44 @@ +[build-system] +requires = ["setuptools >= 64"] +build-backend = "setuptools.build_meta" + +[project] +name = "chess-transformers" +version = "0.3.1" +description = "Teaching transformers to play chess." +authors = [{ name = "Sagar Vinodababu", email = "sgrvinod@gmail.com" }] +maintainers = [{ name = "Sagar Vinodababu", email = "sgrvinod@gmail.com" }] +readme = "README.md" +requires-python = ">=3.6.0" +dependencies = [ + "beautifulsoup4==4.12.3", + "chess==1.10.0", + "colorama==0.4.5", + "ipython==8.17.2", + "Markdown==3.3.4", + "py_cpuinfo==9.0.0", + "regex==2024.7.24", + "scipy==1.13.1", + "setuptools==69.0.3", + "tables==3.9.2", + "tabulate==0.9.0", + "torch==2.4.0", + "tqdm==4.64.1", + "tensorboard==2.18.0", +] +license = { text = "MIT License" } +keywords = ["transformer", "chess", "pytorch", "deep learning", "chess engine"] +classifiers = [ + "Development Status :: 3 - Alpha", + "Intended Audience :: Science/Research", + "License :: OSI Approved :: MIT License", + "Programming Language :: Python :: 3.12", + "Topic :: Scientific/Engineering :: Artificial Intelligence", +] + +[project.urls] +homepage = "https://github.com/sgrvinod/chess-transformers" +source = "https://github.com/sgrvinod/chess-transformers" +changelog = "https://github.com/sgrvinod/chess-transformers/blob/main/CHANGELOG.md" +releasenotes = "https://github.com/sgrvinod/chess-transformers/releases" +issues = "https://github.com/sgrvinod/chess-transformers/issues" diff --git a/setup.py b/setup.py index 6ef1111..45642b9 100644 --- a/setup.py +++ b/setup.py @@ -1,43 +1,3 @@ from setuptools import setup, find_packages -with open("README.md", mode="r", encoding="utf-8") as readme_file: - readme = readme_file.read() - - -setup( - name="chess-transformers", - version="0.3.0", - author="Sagar Vinodababu", - author_email="sgrvinod@gmail.com", - description="Chess Transformers", - long_description=readme, - long_description_content_type="text/markdown", - license="MIT License", - url="https://github.com/sgrvinod/chess-transformers", - download_url="https://github.com/sgrvinod/chess-transformers", - packages=find_packages(), - python_requires=">=3.6.0", - install_requires=[ - "beautifulsoup4==4.12.3", - "chess==1.10.0", - "colorama==0.4.5", - "ipython==8.17.2", - "Markdown==3.3.4", - "py_cpuinfo==9.0.0", - "regex==2024.7.24", - "scipy==1.13.1", - "setuptools==69.0.3", - "tables==3.9.2", - "tabulate==0.9.0", - "torch==2.4.0", - "tqdm==4.64.1", - ], - classifiers=[ - "Development Status :: 3 - Alpha", - "Intended Audience :: Science/Research", - "License :: OSI Approved :: MIT License", - "Programming Language :: Python :: 3.9", - "Topic :: Scientific/Engineering :: Artificial Intelligence", - ], - keywords="transformer networks chess pytorch deep learning", -) +setup(packages=find_packages())