From 9e4f9ba022cf4b96bce6aae4dda30f1ae4d05f2f Mon Sep 17 00:00:00 2001 From: Alex B Date: Wed, 29 Nov 2023 06:58:22 +0100 Subject: [PATCH 1/2] Fix conifgure_optimizers() to meet Lightning requirements --- spacetimeformer/forecaster.py | 6 ++---- .../spacetimeformer_model/spacetimeformer_model.py | 6 +++++- 2 files changed, 7 insertions(+), 5 deletions(-) diff --git a/spacetimeformer/forecaster.py b/spacetimeformer/forecaster.py index 7aebc11..131e336 100644 --- a/spacetimeformer/forecaster.py +++ b/spacetimeformer/forecaster.py @@ -293,10 +293,8 @@ def configure_optimizers(self): ) return { "optimizer": optimizer, - "lr_scheduler": { - "scheduler": scheduler, - "monitor": "val/loss", - }, + "lr_scheduler": scheduler, + "monitor": "val/loss", } @classmethod diff --git a/spacetimeformer/spacetimeformer_model/spacetimeformer_model.py b/spacetimeformer/spacetimeformer_model/spacetimeformer_model.py index dd67676..73f0245 100644 --- a/spacetimeformer/spacetimeformer_model/spacetimeformer_model.py +++ b/spacetimeformer/spacetimeformer_model/spacetimeformer_model.py @@ -326,7 +326,11 @@ def configure_optimizers(self): patience=3, factor=self.decay_factor, ) - return [self.optimizer], [self.scheduler] + return { + "optimizer": self.optimizer, + "lr_scheduler": self.scheduler, + "monitor": "val/loss", + } @classmethod def add_cli(self, parser): From a1729bcec34ef9aed515b63c8ae3951f9cb3ee8a Mon Sep 17 00:00:00 2001 From: Alex Bradbury Date: Tue, 5 Dec 2023 22:52:47 +0000 Subject: [PATCH 2/2] add poetry, add very simple sine wave dataset, smooth some sharp edges --- .python-version | 1 + poetry.lock | 2819 +++++++++++++++++ pyproject.toml | 41 + spacetimeformer/data/csv_dataset.py | 15 +- .../data/sine_waves_with_dates.csv | 731 +++++ .../spacetimeformer_model/nn/encoder.py | 5 + spacetimeformer/train.py | 36 +- 7 files changed, 3644 insertions(+), 4 deletions(-) create mode 100644 .python-version create mode 100644 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--- /dev/null +++ b/pyproject.toml @@ -0,0 +1,41 @@ +[tool.poetry] +name = "spacetimeformer" +version = "0.1.0" +description = "QData Research Library for the Spacetimeformer project" +authors = ["jcg6dn@virginia.edu"] +readme = "README.md" + +[tool.poetry.dependencies] +python = "^3.8" +cython = ">=0.22" +cmdstanpy = "0.9.68" +# https://discourse.mc-stan.org/t/pystan-build-is-not-pep-517-compliant/32971/6 +# https://pystan.readthedocs.io/en/latest/faq.html#how-can-i-run-pystan-on-macos-with-apple-silicon-chips-apple-m1-m2-etc +pystan = ">=2.19.1.1,<2.20.0.0" +numpy = ">=1.15.4" +pandas = ">=1.0.4" +matplotlib = ">=2.0.0" +convertdate = ">=2.1.2" +python-dateutil = ">=2.8.0" +performer-pytorch = "^1.1.4" +tqdm = ">=4.36.1" +nystrom-attention = "^0.0.11" +pytorch-lightning = "1.6" +netcdf4 = "^1.6.5" +scikit-learn = "^1.3.2" +omegaconf = "^2.3.0" +seaborn = "^0.13.0" +opencv-python = "^4.8.1.78" +wandb = "^0.16.0" +einops = "^0.7.0" +chardet = "^5.2.0" +opt-einsum = "^3.3.0" +torchmetrics = "0.5.1" +torch = "1.11.0" +torchvision = "0.12.0" +joblib = "^1.3.2" + + +[build-system] +requires = ["poetry-core"] +build-backend = "poetry.core.masonry.api" diff --git a/spacetimeformer/data/csv_dataset.py b/spacetimeformer/data/csv_dataset.py index c1f9e17..aaba564 100644 --- a/spacetimeformer/data/csv_dataset.py +++ b/spacetimeformer/data/csv_dataset.py @@ -43,7 +43,7 @@ def __init__( if raw_df is None: self.data_path = data_path - assert os.path.exists(self.data_path) + assert os.path.exists(self.data_path), f"data_path not found: ${self.data_path}" raw_df = pd.read_csv( self.data_path, **read_csv_kwargs, @@ -212,6 +212,10 @@ def val_data(self): def test_data(self): return self._test_data + @property + def scaler_obj(self): + return self._scaler + def length(self, split): return { "train": len(self.train_data), @@ -240,6 +244,14 @@ def __init__( self.target_points = target_points self.time_resolution = time_resolution + assert ( + self.series.length(split) + time_resolution * (-target_points - context_points) + 1 > 0 + ), (f"Dataset length for split {split} is negative. Check time_resolution, context_points, and target_points.\n" + f"Dataset length: {self.series.length(split)}\n" + f"Target points: {target_points}\n" + f"Context points: {context_points}\n" + f"Time Resolution: {time_resolution}") + self._slice_start_points = [ i for i in range( @@ -249,6 +261,7 @@ def __init__( + 1, ) ] + print(f"${split} dataset length: {len(self)}") def __len__(self): return len(self._slice_start_points) diff --git a/spacetimeformer/data/sine_waves_with_dates.csv b/spacetimeformer/data/sine_waves_with_dates.csv new file mode 100644 index 0000000..a83005f --- /dev/null +++ b/spacetimeformer/data/sine_waves_with_dates.csv @@ -0,0 +1,731 @@ +Sine Wave 1,Sine Wave 2,Sine Wave 3,Datetime +0.0,0.8660254037844386,0.8660254037844387,2023-01-01 00:00 +0.2079116908177593,0.9510565162951536,0.7431448254773945,2023-01-02 00:00 +0.4067366430758001,0.9945218953682732,0.5877852522924732,2023-01-03 00:00 +0.5877852522924731,0.9945218953682734,0.4067366430758004,2023-01-04 00:00 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+0.5877852522924712,0.994521895368273,0.4067366430757916,2024-12-24 00:00 +0.7431448254773935,0.951056516295152,0.207911690817749,2024-12-25 00:00 +0.8660254037844386,0.8660254037844357,-1.1762799078180474e-14,2024-12-26 00:00 +0.951056516295154,0.7431448254773895,-0.207911690817772,2024-12-27 00:00 +0.9945218953682706,0.5877852522924895,-0.4067366430757871,2024-12-28 00:00 +0.994521895368276,0.4067366430758176,-0.5877852522924625,2024-12-29 00:00 +0.9510565162951607,0.2079116908177767,-0.7431448254773863,2024-12-30 00:00 diff --git a/spacetimeformer/spacetimeformer_model/nn/encoder.py b/spacetimeformer/spacetimeformer_model/nn/encoder.py index 7357941..aa3e27c 100644 --- a/spacetimeformer/spacetimeformer_model/nn/encoder.py +++ b/spacetimeformer/spacetimeformer_model/nn/encoder.py @@ -53,6 +53,11 @@ def forward(self, x, self_mask_seq=None, output_attn=False): if self.local_attention: # attention on tokens of each variable ind. x1 = self.norm1(x) + # assert that second dim of x1 is a multiple of d_yc + assert (x1.shape[1] % self.d_yc == 0), ( + "x1.shape[1] is not a multiple of d_yc. Check that train arg yc_dim matches the number of variables" + f"x1.shape[1] = {x1.shape[1]}, d_yc = {self.d_yc}" + ) x1 = Localize(x1, self.d_yc) # TODO: localize self_mask_seq x1, _ = self.local_attention( diff --git a/spacetimeformer/train.py b/spacetimeformer/train.py index b26b714..25ea0c5 100644 --- a/spacetimeformer/train.py +++ b/spacetimeformer/train.py @@ -4,11 +4,10 @@ import warnings import os import uuid - import pytorch_lightning as pl import torch - import spacetimeformer as stf +import pickle _MODELS = ["spacetimeformer", "mtgnn", "heuristic", "lstm", "lstnet", "linear", "s4"] @@ -19,6 +18,7 @@ "exchange", "precip", "toy2", + "sinewaves", "solar_energy", "syn", "mnist", @@ -105,6 +105,8 @@ def create_parser(): parser.add_argument("--accumulate", type=int, default=1) parser.add_argument("--val_check_interval", type=float, default=1.0) parser.add_argument("--limit_val_batches", type=float, default=1.0) + parser.add_argument("--max_epochs", type=int) + parser.add_argument("--log_every_n_steps", type=int, default=50) parser.add_argument("--no_earlystopping", action="store_true") parser.add_argument("--patience", type=int, default=5) parser.add_argument( @@ -119,6 +121,9 @@ def create_parser(): def create_model(config): + # x_dim time embedding dimension + # yc_dim number of variables in context + # yt_dim number of variables in target x_dim, yc_dim, yt_dim = None, None, None if config.dset == "metr-la": x_dim = 2 @@ -148,6 +153,10 @@ def create_model(config): x_dim = 6 yc_dim = 20 yt_dim = 20 + elif config.dset == "sinewaves": + x_dim = 6 + yc_dim = 3 + yt_dim = 3 elif config.dset == "syn": x_dim = 5 yc_dim = 20 @@ -448,6 +457,7 @@ def create_dset(config): ) INV_SCALER = dset.reverse_scaling SCALER = dset.apply_scaling + SCALER_OBJ = dset.scaler_obj elif config.dset in ["mnist", "cifar"]: if config.dset == "mnist": config.target_points = 28 - config.context_points @@ -575,6 +585,7 @@ def create_dset(config): ) INV_SCALER = dset.reverse_scaling SCALER = dset.apply_scaling + SCALER_OBJ = dset.scaler_obj NULL_VAL = None # PAD_VAL = -32.0 PLOT_VAR_NAMES = target_cols @@ -605,6 +616,7 @@ def create_dset(config): ) INV_SCALER = dset.reverse_scaling SCALER = dset.apply_scaling + SCALER_OBJ = dset.scaler_obj NULL_VAL = None PLOT_VAR_NAMES = ["OT", "p (mbar)", "raining (s)"] PLOT_VAR_IDXS = [20, 0, 15] @@ -627,6 +639,11 @@ def create_dset(config): else: raise ValueError(f"Unrecognized toy dataset {config.dset}") target_cols = [f"D{i}" for i in range(1, 21)] + elif "sinewaves" in config.dset: + target_cols = [ + "Sine Wave 1","Sine Wave 2","Sine Wave 3" + ] + data_path = "./spacetimeformer/data/sine_waves_with_dates.csv" elif config.dset == "exchange": if data_path == "auto": data_path = "./data/exchange_rate_converted.csv" @@ -670,6 +687,7 @@ def create_dset(config): ) INV_SCALER = dset.reverse_scaling SCALER = dset.apply_scaling + SCALER_OBJ = dset.scaler_obj NULL_VAL = None return ( @@ -680,6 +698,7 @@ def create_dset(config): PLOT_VAR_IDXS, PLOT_VAR_NAMES, PAD_VAL, + SCALER_OBJ, ) @@ -770,8 +789,17 @@ def main(args): plot_var_idxs, plot_var_names, pad_val, + scaler_obj, ) = create_dset(args) + # save scaler for inference post-training + with open('scaler_method.pkl', 'wb') as file: + pickle.dump(scaler, file) + with open('fitted_scaler_obj.pkl', 'wb') as file: + pickle.dump(scaler_obj, file) + + assert (len(data_module.test_dataloader()) > 0), "The DataLoader should not be empty, check the Dataset __init__ and __getitem__" + # Model args.null_value = null_val args.pad_value = pad_val @@ -840,8 +868,10 @@ def main(args): gradient_clip_algorithm="norm", overfit_batches=20 if args.debug else 0, accumulate_grad_batches=args.accumulate, - sync_batchnorm=True, + sync_batchnorm=False, #set False on CPU, else "SyncBatchNorm layers only work with GPU modules" limit_val_batches=args.limit_val_batches, + max_epochs=args.max_epochs, + log_every_n_steps=args.log_every_n_steps, **val_control, )