From 2b49283a3c5823f595b474a3c0fbeccdbc42e2e7 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Moritz=20R=2E=20Sch=C3=A4fer?= Date: Wed, 20 Dec 2023 12:37:59 +0100 Subject: [PATCH 01/16] added model loading edge case for `experiment=""` --- apax/train/checkpoints.py | 6 +++++- tests/integration_tests/md/test_model_loading.py | 7 +++++-- 2 files changed, 10 insertions(+), 3 deletions(-) diff --git a/apax/train/checkpoints.py b/apax/train/checkpoints.py index 653b3b84..36077cac 100644 --- a/apax/train/checkpoints.py +++ b/apax/train/checkpoints.py @@ -147,7 +147,11 @@ def restore_single_parameters(model_dir: Path) -> Tuple[Config, FrozenDict]: """ model_dir = Path(model_dir) model_config = parse_config(model_dir / "config.yaml") - model_config.data.directory = model_dir.parent.resolve().as_posix() + + if model_config.data.experiment == "": + model_config.data.directory = model_dir.resolve().as_posix() + else: + model_config.data.directory = model_dir.parent.resolve().as_posix() ckpt_dir = model_config.data.model_version_path return model_config, load_params(ckpt_dir) diff --git a/tests/integration_tests/md/test_model_loading.py b/tests/integration_tests/md/test_model_loading.py index eefc99dd..4f48c17d 100644 --- a/tests/integration_tests/md/test_model_loading.py +++ b/tests/integration_tests/md/test_model_loading.py @@ -22,10 +22,13 @@ def test_model_loading(get_tmp_path, get_sample_input): ckpt = {"model": {"params": params}, "epoch": 0} ckpt_dir1 = pathlib.Path("models/apax_dummy/best") ckpt_dir2 = pathlib.Path("../models/apax_dummy/best").resolve() + ckpt_dir3 = pathlib.Path("models/best") - ckpt_dirs = [ckpt_dir1, ckpt_dir2] - for ckpt_dir in ckpt_dirs: + ckpt_dirs = [ckpt_dir1, ckpt_dir2, ckpt_dir3] + experiments = ["apax_dummy", "apax_dummy", ""] + for ckpt_dir, exp in zip(ckpt_dirs, experiments): ckpt_dir.mkdir(exist_ok=True, parents=True) + model_config.data.experiment = exp model_config.dump_config(ckpt_dir.parent) checkpoints.save_checkpoint( From ecd2759f9d8a057d35d70dccb1cb49c86b38b8d4 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Moritz=20R=2E=20Sch=C3=A4fer?= Date: Wed, 27 Dec 2023 19:36:21 +0100 Subject: [PATCH 02/16] switched model saving to absolute path --- apax/train/checkpoints.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/apax/train/checkpoints.py b/apax/train/checkpoints.py index 36077cac..d4af7c3a 100644 --- a/apax/train/checkpoints.py +++ b/apax/train/checkpoints.py @@ -89,9 +89,9 @@ class CheckpointManager: def __init__(self) -> None: self.async_manager = checkpoints.AsyncManager() - def save_checkpoint(self, ckpt, epoch: int, path: str) -> None: + def save_checkpoint(self, ckpt, epoch: int, path: Path) -> None: checkpoints.save_checkpoint( - ckpt_dir=path, + ckpt_dir=path.resolve(), target=ckpt, step=epoch, overwrite=True, From bbbbd76cc5bb72f541a3a598dae10213cb84e062 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Moritz=20R=2E=20Sch=C3=A4fer?= Date: Thu, 28 Dec 2023 11:24:33 +0100 Subject: [PATCH 03/16] poetry update --- poetry.lock | 2005 ++++++++++++++++++++++++++------------------------- 1 file changed, 1031 insertions(+), 974 deletions(-) diff --git a/poetry.lock b/poetry.lock index 5040ac79..587cf5cd 100644 --- a/poetry.lock +++ b/poetry.lock @@ -24,24 +24,25 @@ files = [ [[package]] name = "annotated-types" -version = "0.5.0" +version = "0.6.0" description = "Reusable constraint types to use with typing.Annotated" optional = false -python-versions = ">=3.7" +python-versions = ">=3.8" files = [ - {file = "annotated_types-0.5.0-py3-none-any.whl", hash = "sha256:58da39888f92c276ad970249761ebea80ba544b77acddaa1a4d6cf78287d45fd"}, - {file = "annotated_types-0.5.0.tar.gz", hash = "sha256:47cdc3490d9ac1506ce92c7aaa76c579dc3509ff11e098fc867e5130ab7be802"}, + {file = "annotated_types-0.6.0-py3-none-any.whl", hash = "sha256:0641064de18ba7a25dee8f96403ebc39113d0cb953a01429249d5c7564666a43"}, + {file = "annotated_types-0.6.0.tar.gz", hash = "sha256:563339e807e53ffd9c267e99fc6d9ea23eb8443c08f112651963e24e22f84a5d"}, ] [[package]] name = "array-record" -version = "0.4.1" +version = "0.5.0" description = "A file format that achieves a new frontier of IO efficiency" optional = false python-versions = ">=3.9" files = [ - 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{file = "znh5md-0.1.7-py3-none-any.whl", hash = "sha256:2d5505738c92c79e2de907acf89956662c94472a350f1ddfd55c509c0cc44960"}, - {file = "znh5md-0.1.7.tar.gz", hash = "sha256:fa437c805da4a7a24d6265f632ebbc36863fd15c952e2ce1a3b2d35c6241e00d"}, + {file = "znh5md-0.1.9-py3-none-any.whl", hash = "sha256:38478627e22bd5e91ccef356275ad25d030c307ddad9c24adf8b8a2b2ebded43"}, + {file = "znh5md-0.1.9.tar.gz", hash = "sha256:d2aa6a48206f26f50595427ea2004e8000d448651415db6c30e2087c2d58772c"}, ] [package.dependencies] From 8e0cd0311dd7e09a6e00d1164eb677a1b6c241e0 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Moritz=20R=2E=20Sch=C3=A4fer?= Date: Thu, 28 Dec 2023 11:33:04 +0100 Subject: [PATCH 04/16] fixed model loading test --- tests/integration_tests/md/test_model_loading.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/integration_tests/md/test_model_loading.py b/tests/integration_tests/md/test_model_loading.py index 4f48c17d..65551b54 100644 --- a/tests/integration_tests/md/test_model_loading.py +++ b/tests/integration_tests/md/test_model_loading.py @@ -21,7 +21,7 @@ def test_model_loading(get_tmp_path, get_sample_input): ckpt = {"model": {"params": params}, "epoch": 0} ckpt_dir1 = pathlib.Path("models/apax_dummy/best") - ckpt_dir2 = pathlib.Path("../models/apax_dummy/best").resolve() + ckpt_dir2 = pathlib.Path("../models/apax_dummy/best") ckpt_dir3 = pathlib.Path("models/best") ckpt_dirs = [ckpt_dir1, ckpt_dir2, ckpt_dir3] @@ -32,7 +32,7 @@ def test_model_loading(get_tmp_path, get_sample_input): model_config.dump_config(ckpt_dir.parent) checkpoints.save_checkpoint( - ckpt_dir=ckpt_dir, + ckpt_dir=ckpt_dir.resolve(), target=ckpt, step=0, overwrite=True, From fc9a75c36fc964b7878afae24e49deee66ed4757 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Moritz=20R=2E=20Sch=C3=A4fer?= Date: Tue, 2 Jan 2024 16:42:03 +0100 Subject: [PATCH 05/16] fixed jaxmd NL not being reallocated when going from matscipy to jaxmd NL and padde_length not getting_initialized --- apax/md/ase_calc.py | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/apax/md/ase_calc.py b/apax/md/ase_calc.py index 63a1dc97..8c17dd42 100644 --- a/apax/md/ase_calc.py +++ b/apax/md/ase_calc.py @@ -112,6 +112,7 @@ def __init__( self.model_config, self.params = restore_parameters(model_dir) self.n_models = check_for_ensemble(self.params) self.padding_factor = padding_factor + self.padded_length = 0 if self.model_config.model.calc_stress: self.implemented_properties.append("stress") @@ -148,6 +149,11 @@ def initialize(self, atoms): self.step = get_step_fn(model, atoms, self.neigbor_from_jax) self.neighbor_fn = neighbor_fn + if self.neigbor_from_jax: + positions = jnp.asarray(atoms.positions, dtype=jnp.float64) + self.neighbors = self.neighbor_fn.allocate(positions) + + def set_neighbours_and_offsets(self, atoms, box): idxs_i, idxs_j, offsets = neighbour_list("ijS", atoms, self.r_max) From b19adfdca55c4a56c0c2d4fb6eb197e0cfffdeb6 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Moritz=20R=2E=20Sch=C3=A4fer?= Date: Tue, 2 Jan 2024 16:42:36 +0100 Subject: [PATCH 06/16] linting --- apax/md/ase_calc.py | 1 - 1 file changed, 1 deletion(-) diff --git a/apax/md/ase_calc.py b/apax/md/ase_calc.py index 8c17dd42..6422b5a5 100644 --- a/apax/md/ase_calc.py +++ b/apax/md/ase_calc.py @@ -153,7 +153,6 @@ def initialize(self, atoms): positions = jnp.asarray(atoms.positions, dtype=jnp.float64) self.neighbors = self.neighbor_fn.allocate(positions) - def set_neighbours_and_offsets(self, atoms, box): idxs_i, idxs_j, offsets = neighbour_list("ijS", atoms, self.r_max) From 1c3e2d5c3b2fd20e8d1ed83acfce58e10c6b7dca Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Moritz=20R=2E=20Sch=C3=A4fer?= Date: Tue, 2 Jan 2024 17:35:41 +0100 Subject: [PATCH 07/16] added fp64 version of clu `Average` --- apax/train/metrics.py | 10 ++++++++-- 1 file changed, 8 insertions(+), 2 deletions(-) diff --git a/apax/train/metrics.py b/apax/train/metrics.py index 151cfe68..e5067b0f 100644 --- a/apax/train/metrics.py +++ b/apax/train/metrics.py @@ -9,7 +9,13 @@ log = logging.getLogger(__name__) -class RootAverage(metrics.Average): +class Averagefp64(metrics.Average): + @classmethod + def empty(cls) -> metrics.Metric: + return cls(total=jnp.array(0, jnp.float64), count=jnp.array(0, jnp.int64)) + + +class RootAverage(Averagefp64): """ Modifies the `compute` method of `metrics.Average` to obtain the root of the average. Meant to be used with `mse_fn`. @@ -59,7 +65,7 @@ def make_single_metric(key: str, reduction: str) -> metrics.Average: if reduction == "rmse": metric = RootAverage else: - metric = metrics.Average + metric = Averagefp64 reduction_fn = reduction_fns[reduction] reduction_fn = partial(reduction_fn, key=key) From 9f21feba4f1df6fc8d8fef89f361a6db328c2249 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Moritz=20R=2E=20Sch=C3=A4fer?= Date: Tue, 2 Jan 2024 17:36:19 +0100 Subject: [PATCH 08/16] added sketch of multi step jit --- apax/data/input_pipeline.py | 16 +++++++++--- apax/train/trainer.py | 49 +++++++++++++++++++++++++------------ 2 files changed, 45 insertions(+), 20 deletions(-) diff --git a/apax/data/input_pipeline.py b/apax/data/input_pipeline.py index 34a9d31f..13410aaa 100644 --- a/apax/data/input_pipeline.py +++ b/apax/data/input_pipeline.py @@ -174,6 +174,7 @@ def __init__( """ self.n_epoch = n_epoch self.batch_size = None + self.n_jit_steps = 1 self.buffer_size = buffer_size max_atoms, max_nbrs = find_largest_system(inputs) @@ -186,6 +187,9 @@ def __init__( def set_batch_size(self, batch_size: int): self.batch_size = self.validate_batch_size(batch_size) + + def batch_multiple_steps(self, n_steps: int): + self.n_jit_steps = n_steps def _check_batch_size(self): if self.batch_size is None: @@ -208,7 +212,7 @@ def steps_per_epoch(self) -> int: number of steps, and all batches have the same length. To do so, some training data are dropped in each epoch. """ - return self.n_data // self.batch_size + return self.n_data // self.batch_size // self.n_jit_steps def init_input(self) -> Dict[str, np.ndarray]: """Returns first batch of inputs and labels to init the model.""" @@ -240,15 +244,19 @@ def shuffle_and_batch(self) -> Iterator[jax.Array]: Iterator that returns inputs and labels of one batch in each step. """ self._check_batch_size() - shuffled_ds = ( + ds = ( self.ds.shuffle(buffer_size=self.buffer_size) .repeat(self.n_epoch) .batch(batch_size=self.batch_size) .map(PadToSpecificSize(self.max_atoms, self.max_nbrs)) ) - shuffled_ds = prefetch_to_single_device(shuffled_ds.as_numpy_iterator(), 2) - return shuffled_ds + if self.n_jit_steps > 1: + print("JIT BATCH") + ds = ds.batch(batch_size=self.n_jit_steps) + + ds = prefetch_to_single_device(ds.as_numpy_iterator(), 2) + return ds def batch(self) -> Iterator[jax.Array]: self._check_batch_size() diff --git a/apax/train/trainer.py b/apax/train/trainer.py index 867ee50e..139d33be 100644 --- a/apax/train/trainer.py +++ b/apax/train/trainer.py @@ -1,12 +1,15 @@ +import functools import logging import time from functools import partial -from typing import Callable +from typing import Callable, Optional import jax import jax.numpy as jnp +from clu import metrics import numpy as np from tqdm import trange +from apax.data.input_pipeline import AtomisticDataset from apax.train.checkpoints import CheckpointManager, load_state @@ -15,16 +18,16 @@ def fit( state, - train_ds, + train_ds: AtomisticDataset, loss_fn, - Metrics, - callbacks, - n_epochs, + Metrics: metrics.Collection, + callbacks: list, + n_epochs: int, ckpt_dir, ckpt_interval: int = 1, - val_ds=None, + val_ds: Optional[AtomisticDataset] =None, sam_rho=0.0, - patience=None, + patience: Optional[int]=None, disable_pbar: bool = False, is_ensemble=False, ): @@ -35,9 +38,13 @@ def fit( best_dir = ckpt_dir / "best" ckpt_manager = CheckpointManager() + n_jitted_steps = 1 + train_step, val_step = make_step_fns( loss_fn, Metrics, model=state.apply_fn, sam_rho=sam_rho, is_ensemble=is_ensemble ) + if n_jitted_steps > 1: + train_step = jax.jit(functools.partial(jax.lax.scan, train_step)) state, start_epoch = load_state(state, latest_dir) if start_epoch >= n_epochs: @@ -45,8 +52,12 @@ def fit( f"n_epochs <= current epoch from checkpoint ({n_epochs} <= {start_epoch})" ) + train_ds.batch_multiple_steps(n_jitted_steps) train_steps_per_epoch = train_ds.steps_per_epoch() batch_train_ds = train_ds.shuffle_and_batch() + # inputs, labels = next(batch_train_ds) + # print(jax.tree_map(lambda x: x.shape, inputs)) + # quit() if val_ds is not None: val_steps_per_epoch = val_ds.steps_per_epoch() @@ -68,12 +79,13 @@ def fit( for batch_idx in range(train_steps_per_epoch): callbacks.on_train_batch_begin(batch=batch_idx) - inputs, labels = next(batch_train_ds) - batch_loss, train_batch_metrics, state = train_step( - state, inputs, labels, train_batch_metrics + batch = next(batch_train_ds) + (state, train_batch_metrics), batch_loss, = train_step( + (state, train_batch_metrics), batch, ) + print(batch_loss) - epoch_loss["train_loss"] += batch_loss + epoch_loss["train_loss"] += jnp.mean(batch_loss) callbacks.on_train_batch_end(batch=batch_idx) epoch_loss["train_loss"] /= train_steps_per_epoch @@ -88,10 +100,10 @@ def fit( epoch_loss.update({"val_loss": 0.0}) val_batch_metrics = Metrics.empty() for batch_idx in range(val_steps_per_epoch): - inputs, labels = next(batch_val_ds) + batch = next(batch_val_ds) batch_loss, val_batch_metrics = val_step( - state.params, inputs, labels, val_batch_metrics + state.params, batch, val_batch_metrics ) epoch_loss["val_loss"] += batch_loss @@ -213,17 +225,22 @@ def update_step(state, inputs, labels): eval_fn = loss_calculator @jax.jit - def train_step(state, inputs, labels, batch_metrics): + def train_step(carry, batch): + state, batch_metrics = carry + inputs, labels = batch loss, predictions, state = update_fn(state, inputs, labels) new_batch_metrics = Metrics.single_from_model_output( label=labels, prediction=predictions ) batch_metrics = batch_metrics.merge(new_batch_metrics) - return loss, batch_metrics, state + + new_carry = (state, batch_metrics) + return new_carry, loss @jax.jit - def val_step(params, inputs, labels, batch_metrics): + def val_step(params, batch, batch_metrics): + inputs, labels = batch loss, predictions = eval_fn(params, inputs, labels) new_batch_metrics = Metrics.single_from_model_output( From 93cb39db912e14e8f119f0e68fa96a83dd1743fc Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Moritz=20R=2E=20Sch=C3=A4fer?= Date: Mon, 8 Jan 2024 22:03:51 +0100 Subject: [PATCH 09/16] applied fix to jaxMD --- apax/md/nvt.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/apax/md/nvt.py b/apax/md/nvt.py index a98561dc..3c07dfe6 100644 --- a/apax/md/nvt.py +++ b/apax/md/nvt.py @@ -271,7 +271,7 @@ def body_fn(i, state): ) ckpt = {"state": state, "step": step} checkpoints.save_checkpoint( - ckpt_dir=ckpt_dir, + ckpt_dir=ckpt_dir.resolve(), target=ckpt, step=step, overwrite=True, From 9d712f464a681d8bc6bb4c3b2ef2bd99c3c4511c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Moritz=20R=2E=20Sch=C3=A4fer?= Date: Mon, 8 Jan 2024 22:06:15 +0100 Subject: [PATCH 10/16] added stress triL loss function --- apax/train/loss.py | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/apax/train/loss.py b/apax/train/loss.py index 56096455..4a8f52e4 100644 --- a/apax/train/loss.py +++ b/apax/train/loss.py @@ -52,6 +52,13 @@ def force_angle_exponential_weight( return (1.0 - dotp) * jnp.exp(-F_0_norm) / divisor +def stress_tril(label, prediction, divisor= 1.0): + idxs = jnp.tril_indices(3) + label_tril = label[:, idxs[0], idxs[1]] + prediction_tril = prediction[:, idxs[0], idxs[1]] + return (label_tril - prediction_tril) ** 2 / divisor + + loss_functions = { "molecules": weighted_squared_error, "structures": weighted_squared_error, @@ -59,6 +66,7 @@ def force_angle_exponential_weight( "cosine_sim": force_angle_loss, "cosine_sim_div_magnitude": force_angle_div_force_label, "cosine_sim_exp_magnitude": force_angle_exponential_weight, + "tril": stress_tril, } @@ -101,6 +109,7 @@ def determine_divisor(self, n_atoms: jnp.array) -> jnp.array: n_atoms, "batch -> batch 1 1" ), "stress_structures": einops.repeat(n_atoms**2, "batch -> batch 1 1"), + "stress_tril": einops.repeat(n_atoms**2, "batch -> batch 1 1"), "stress_vibrations": einops.repeat(n_atoms, "batch -> batch 1 1"), } divisor = divisor_dict.get(divisor_id, jnp.array(1.0)) From 210c06d9d209cd887e750d9592022fb543e0a678 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Moritz=20R=2E=20Sch=C3=A4fer?= Date: Mon, 8 Jan 2024 22:20:41 +0100 Subject: [PATCH 11/16] linting --- apax/data/input_pipeline.py | 2 +- apax/train/trainer.py | 22 +++++++++++----------- 2 files changed, 12 insertions(+), 12 deletions(-) diff --git a/apax/data/input_pipeline.py b/apax/data/input_pipeline.py index 13410aaa..19cf2d92 100644 --- a/apax/data/input_pipeline.py +++ b/apax/data/input_pipeline.py @@ -187,7 +187,7 @@ def __init__( def set_batch_size(self, batch_size: int): self.batch_size = self.validate_batch_size(batch_size) - + def batch_multiple_steps(self, n_steps: int): self.n_jit_steps = n_steps diff --git a/apax/train/trainer.py b/apax/train/trainer.py index 139d33be..b6c47993 100644 --- a/apax/train/trainer.py +++ b/apax/train/trainer.py @@ -6,11 +6,11 @@ import jax import jax.numpy as jnp -from clu import metrics import numpy as np +from clu import metrics from tqdm import trange -from apax.data.input_pipeline import AtomisticDataset +from apax.data.input_pipeline import AtomisticDataset from apax.train.checkpoints import CheckpointManager, load_state log = logging.getLogger(__name__) @@ -25,9 +25,9 @@ def fit( n_epochs: int, ckpt_dir, ckpt_interval: int = 1, - val_ds: Optional[AtomisticDataset] =None, + val_ds: Optional[AtomisticDataset] = None, sam_rho=0.0, - patience: Optional[int]=None, + patience: Optional[int] = None, disable_pbar: bool = False, is_ensemble=False, ): @@ -38,7 +38,7 @@ def fit( best_dir = ckpt_dir / "best" ckpt_manager = CheckpointManager() - n_jitted_steps = 1 + n_jitted_steps = 4 # Move to arg train_step, val_step = make_step_fns( loss_fn, Metrics, model=state.apply_fn, sam_rho=sam_rho, is_ensemble=is_ensemble @@ -55,9 +55,6 @@ def fit( train_ds.batch_multiple_steps(n_jitted_steps) train_steps_per_epoch = train_ds.steps_per_epoch() batch_train_ds = train_ds.shuffle_and_batch() - # inputs, labels = next(batch_train_ds) - # print(jax.tree_map(lambda x: x.shape, inputs)) - # quit() if val_ds is not None: val_steps_per_epoch = val_ds.steps_per_epoch() @@ -80,10 +77,13 @@ def fit( callbacks.on_train_batch_begin(batch=batch_idx) batch = next(batch_train_ds) - (state, train_batch_metrics), batch_loss, = train_step( - (state, train_batch_metrics), batch, + ( + (state, train_batch_metrics), + batch_loss, + ) = train_step( + (state, train_batch_metrics), + batch, ) - print(batch_loss) epoch_loss["train_loss"] += jnp.mean(batch_loss) callbacks.on_train_batch_end(batch=batch_idx) From 0e9a5cfe472327249c7c2f8de2230a9f0a176be8 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Moritz=20R=2E=20Sch=C3=A4fer?= Date: Mon, 8 Jan 2024 22:24:42 +0100 Subject: [PATCH 12/16] added n_jitted_steps to config --- apax/config/train_config.py | 5 +++++ apax/train/run.py | 1 + apax/train/trainer.py | 3 +-- 3 files changed, 7 insertions(+), 2 deletions(-) diff --git a/apax/config/train_config.py b/apax/config/train_config.py index f383af08..d32a58be 100644 --- a/apax/config/train_config.py +++ b/apax/config/train_config.py @@ -279,7 +279,11 @@ class Config(BaseModel, frozen=True, extra="forbid"): ---------- n_epochs: Number of training epochs. + patience: Number of epochs without improvement before trainings gets terminated. seed: Random seed. + n_models: Number of models to be trained at once. + n_jitted_steps: Number of train batches to be processed in a compiled loop. + Can yield singificant speedups for small structures or small batch sizes. data: :class: `Data` configuration. model: :class: `Model` configuration. metrics: List of :class: `metric` configurations. @@ -294,6 +298,7 @@ class Config(BaseModel, frozen=True, extra="forbid"): patience: Optional[PositiveInt] = None seed: int = 1 n_models: int = 1 + n_jitted_steps: int = 1 data: DataConfig model: ModelConfig = ModelConfig() diff --git a/apax/train/run.py b/apax/train/run.py index 36e4e15f..a4015f9a 100644 --- a/apax/train/run.py +++ b/apax/train/run.py @@ -117,4 +117,5 @@ def run(user_config, log_level="error"): patience=config.patience, disable_pbar=config.progress_bar.disable_epoch_pbar, is_ensemble=config.n_models > 1, + n_jitted_steps=config.n_jitted_steps, ) diff --git a/apax/train/trainer.py b/apax/train/trainer.py index b6c47993..684203eb 100644 --- a/apax/train/trainer.py +++ b/apax/train/trainer.py @@ -30,6 +30,7 @@ def fit( patience: Optional[int] = None, disable_pbar: bool = False, is_ensemble=False, + n_jitted_steps=1, ): log.info("Beginning Training") callbacks.on_train_begin() @@ -38,8 +39,6 @@ def fit( best_dir = ckpt_dir / "best" ckpt_manager = CheckpointManager() - n_jitted_steps = 4 # Move to arg - train_step, val_step = make_step_fns( loss_fn, Metrics, model=state.apply_fn, sam_rho=sam_rho, is_ensemble=is_ensemble ) From f3d8a601d88f6930f47b8e1b78e4634708f6c1e2 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Moritz=20R=2E=20Sch=C3=A4fer?= Date: Tue, 9 Jan 2024 10:08:57 +0100 Subject: [PATCH 13/16] linting --- apax/train/trainer.py | 11 ++++------- 1 file changed, 4 insertions(+), 7 deletions(-) diff --git a/apax/train/trainer.py b/apax/train/trainer.py index 684203eb..5a59849b 100644 --- a/apax/train/trainer.py +++ b/apax/train/trainer.py @@ -76,13 +76,10 @@ def fit( callbacks.on_train_batch_begin(batch=batch_idx) batch = next(batch_train_ds) - ( - (state, train_batch_metrics), - batch_loss, - ) = train_step( - (state, train_batch_metrics), - batch, - ) + ((state, train_batch_metrics), batch_loss,) = train_step( + (state, train_batch_metrics), + batch, + ) epoch_loss["train_loss"] += jnp.mean(batch_loss) callbacks.on_train_batch_end(batch=batch_idx) From 4ecd6f9e21c18857473ffc4db5f9916e68d7bac7 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Moritz=20R=2E=20Sch=C3=A4fer?= Date: Tue, 9 Jan 2024 10:10:46 +0100 Subject: [PATCH 14/16] updated linting action versions --- .github/workflows/linting.yaml | 4 ++-- apax/train/trainer.py | 11 +++++++---- 2 files changed, 9 insertions(+), 6 deletions(-) diff --git a/.github/workflows/linting.yaml b/.github/workflows/linting.yaml index 27ee44dd..708b7426 100644 --- a/.github/workflows/linting.yaml +++ b/.github/workflows/linting.yaml @@ -13,7 +13,7 @@ jobs: uses: psf/black@stable with: src: "./apax" - version: "22.10.0" + version: "22.12.0" isort: runs-on: ubuntu-latest @@ -25,7 +25,7 @@ jobs: - name: Install isort run: | - pip install isort==5.10.1 + pip install isort==5.12.0 - name: run isort run: | diff --git a/apax/train/trainer.py b/apax/train/trainer.py index 5a59849b..684203eb 100644 --- a/apax/train/trainer.py +++ b/apax/train/trainer.py @@ -76,10 +76,13 @@ def fit( callbacks.on_train_batch_begin(batch=batch_idx) batch = next(batch_train_ds) - ((state, train_batch_metrics), batch_loss,) = train_step( - (state, train_batch_metrics), - batch, - ) + ( + (state, train_batch_metrics), + batch_loss, + ) = train_step( + (state, train_batch_metrics), + batch, + ) epoch_loss["train_loss"] += jnp.mean(batch_loss) callbacks.on_train_batch_end(batch=batch_idx) From 76bdd87e408cd500f502e9007b819bf94f9c9433 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Moritz=20R=2E=20Sch=C3=A4fer?= Date: Tue, 9 Jan 2024 10:14:51 +0100 Subject: [PATCH 15/16] linting --- apax/train/loss.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/apax/train/loss.py b/apax/train/loss.py index 4a8f52e4..cd28786e 100644 --- a/apax/train/loss.py +++ b/apax/train/loss.py @@ -52,7 +52,7 @@ def force_angle_exponential_weight( return (1.0 - dotp) * jnp.exp(-F_0_norm) / divisor -def stress_tril(label, prediction, divisor= 1.0): +def stress_tril(label, prediction, divisor=1.0): idxs = jnp.tril_indices(3) label_tril = label[:, idxs[0], idxs[1]] prediction_tril = prediction[:, idxs[0], idxs[1]] From e828e5205bc19e29770bc677c911f198656c9bde Mon Sep 17 00:00:00 2001 From: Moritz Schaefer Date: Wed, 10 Jan 2024 14:27:22 +0100 Subject: [PATCH 16/16] removed debug print statement --- apax/data/input_pipeline.py | 1 - 1 file changed, 1 deletion(-) diff --git a/apax/data/input_pipeline.py b/apax/data/input_pipeline.py index 19cf2d92..3e53fa33 100644 --- a/apax/data/input_pipeline.py +++ b/apax/data/input_pipeline.py @@ -252,7 +252,6 @@ def shuffle_and_batch(self) -> Iterator[jax.Array]: ) if self.n_jit_steps > 1: - print("JIT BATCH") ds = ds.batch(batch_size=self.n_jit_steps) ds = prefetch_to_single_device(ds.as_numpy_iterator(), 2)