diff --git a/.gitignore b/.gitignore index 506ff87..48ec47f 100644 --- a/.gitignore +++ b/.gitignore @@ -1,6 +1,3 @@ -# Data and configs -*.toml - # Logging files *.db wandb/ diff --git a/examples/slac_fel/model.py b/examples/slac_fel/model.py new file mode 100644 index 0000000..249753c --- /dev/null +++ b/examples/slac_fel/model.py @@ -0,0 +1,585 @@ +# examples/slac_fel/model.py +"""SLAC FEL model harness for the BaseSim continuous-learning framework. + +This harness wraps a 7-layer ELU regression network with dropout regularisation, +trained to predict HXR pulse intensity from accelerator settings. The pre-processed +accelerator data is chronologically sorted and sliced into time windows, +each of which is served in order by ``update_data_stream()``. +""" + +from __future__ import annotations + +import gc +import logging +import os +from typing import Any, List, Optional, Tuple + +import torch +import torch.nn.functional as F +from torch import Tensor, nn +from torch.optim import Optimizer +from torch.utils.data import ConcatDataset, DataLoader, WeightedRandomSampler + +from apeiron.config.configuration import Config +from apeiron.model.torch_model_harness import BaseModelHarness + +from examples.slac_fel.utils import ( + FELDataset, + discover_window_files, + load_feature_config, + load_fel_data, + load_scalers, + load_window_file, + make_loader, + split_into_windows, + split_timestamps, +) + + +_log = logging.getLogger(__name__) + + +# ------------------------------------------------------------------------------------------------- +# Neural-network architecture +# Matches FELNeuralNetwork in train_fel_model.py from surrogate repo model arch on 4/20/2026 +# ------------------------------------------------------------------------------------------------- +class FELNet(nn.Module): + """7-layer fully-connected ELU regression network. + Predicts FEL pulse intensity from scaled accelerator inputs.""" + + def __init__(self, input_size=None, output_size=1): + super(FELNet, self).__init__() + + self.net = nn.Sequential( + nn.Linear(input_size, 1024), + nn.ELU(), + nn.Linear(1024, 512), + nn.ELU(), + nn.Linear(512, 256), + nn.ELU(), + nn.Linear(256, 128), + nn.ELU(), + nn.Dropout(p=0.05), + nn.Linear(128, 64), + nn.ELU(), + nn.Dropout(p=0.05), + nn.Linear(64, 32), + nn.ELU(), + nn.Linear(32, 16), + nn.ELU(), + nn.Dropout(p=0.05), + nn.Linear(16, output_size), + nn.Softplus(beta=1.0, threshold=20.0), + ) + + def forward(self, x: Tensor) -> Tensor: + if not torch.isfinite(x).all(): + n_bad = (~torch.isfinite(x)).sum().item() + _log.warning( + "FELNet.forward: %d non-finite values in input. Replacing with 0", + n_bad, + ) + x = torch.nan_to_num(x, nan=0.0, posinf=1e6, neginf=-1e6) + + out = self.net(x) + + # Detect NaN outputs + if not torch.isfinite(out).all(): + if torch.isnan(out).any(): + _log.warning("Model produced NaN predictions. Replacing with 0.") + out = torch.nan_to_num(out, nan=0.0, posinf=1e6, neginf=-1e6) + + return out + + +# --------------------------------------------------------------------------- +# Regression metrics (match MetricFn = Callable[[Tensor, Tensor], Any]) +# --------------------------------------------------------------------------- +@torch.no_grad() +def mse_metric(y_hat: Tensor, y: Tensor) -> Tensor: + """Mean-squared error computed on the batch.""" + return F.mse_loss(y_hat, y) + + +@torch.no_grad() +def mae_metric(y_hat: Tensor, y: Tensor) -> Tensor: + """Mean-absolute error computed on the batch.""" + return F.l1_loss(y_hat, y) + + +# --------------------------------------------------------------------------- +# Model harness +# --------------------------------------------------------------------------- + +# Fraction of each time window reserved for validation +_VAL_FRACTION: float = 0.2 + +# Early stopping for the CL training loop (see SLAC_FEL.cl_should_stop). +# Set _ES_PATIENCE = 0 to disable. Training stops once the monitored validation +# metric has not improved by more than _ES_MIN_DELTA for _ES_PATIENCE consecutive +# checks, where checks happen every _ES_INTERVAL iterations. +_ES_PATIENCE: int = 0 +_ES_INTERVAL: int = 100 +_ES_MIN_DELTA: float = 0.0 + +# Recency weighting for the historical replay buffer (see get_hist_dataloaders). +# Per-sample weight decays as _HIST_RECENCY_DECAY ** window_age, so the most +# recent past window dominates the replay and stale operating points contribute +# progressively less. Set to 1.0 to recover uniform replay over all history +# windows; smaller values (e.g. 0.5) emphasise recent regimes more strongly. +_HIST_RECENCY_DECAY: float = 0.5 + +# Directory containing: input_scaler.pt, output_scaler.pt, feature_config.yml +config_path = "examples/slac_fel/model" + + +class SLAC_FEL(BaseModelHarness): + """Continuous-learning harness for the LCLS FEL regression model. + + The data path (``cfg.data.path``) must point to a directory containing: + + * ``hxr_*.pkl`` – pre-filtered, chronologically-sorted DataFrames. Files + are loaded lazily one at a time as windows are consumed, keeping only + one file's worth of tensors in memory at once. + * **OR** ``data.pkl`` – a single monolithic DataFrame that will be split + into fixed-size windows via ``cfg.data.batch_size`` (legacy fallback). + + The data path (``cfg.model``) must point to a directory containing: + * ``input_scaler.pt`` – BoTorch ``AffineInputTransform`` for inputs + * ``output_scaler.pt`` – BoTorch ``AffineInputTransform`` for the target + * ``feature_config.yml`` – YAML listing input / output variable names + * ``model_pretrained.pt`` (optional) – pretrained checkpoint for the FELNet model + + Each call to :meth:`update_data_stream` advances to the next time window. + """ + + def __init__(self, cfg: Config) -> None: + # ----- scalers & feature config (always needed) ---------------------- + self.input_scaler, self.output_scaler = load_scalers( + config_path, device=cfg.device + ) + self.input_cols, self.output_cols = load_feature_config(config_path) + + # ----- discover per-file windows or fall back to monolithic ---------- + self._window_file_paths = discover_window_files(cfg.data.path) + self._lazy = len(self._window_file_paths) > 0 + + # Dimensions come from the feature config – no data loading needed. + input_size = len(self.input_cols) + output_size = len(self.output_cols) + + if self._lazy: + # Lazy mode: files are loaded one at a time as windows are consumed. + self._file_idx: int = 0 + self._active_windows: List[Tuple[Tensor, Tensor]] = [] + self._active_timestamps: List = [] + self._active_window_idx: int = 0 + # num_windows is unknown until all files are scanned; use -1 as sentinel. + self.num_windows: int = -1 + print( + f"[SLAC-FEL] Lazy loading: {len(self._window_file_paths)} file(s) in " + f"{cfg.data.path} (window_size={cfg.data.batch_size}, " + f"input_dim={input_size}, output_dim={output_size})" + ) + else: + # Legacy mode: single data.pkl split into fixed-size windows. + X, y, timestamps = load_fel_data( + cfg.data.path, config_path, device=cfg.device + ) + print( + f"[SLAC-FEL] Legacy mode: single data file {cfg.data.path} with {X.shape[0]} samples" + ) + self.windows = split_into_windows(X, y, window_size=cfg.data.batch_size) + self.window_timestamps = split_timestamps( + timestamps, window_size=cfg.data.batch_size + ) + self.num_windows = len(self.windows) + print( + f"[SLAC-FEL] Legacy mode: {self.num_windows} windows " + f"(window_size={cfg.data.batch_size}, " + f"input_dim={input_size}, output_dim={output_size})" + ) + + # ----- build model --------------------------------------------------- + pretrained_path = cfg.model.pretrained_path + if pretrained_path: + model = self._load_pretrained_direct( + pretrained_path, input_size, output_size, cfg.device + ) + else: + model = FELNet(input_size=input_size, output_size=output_size) + + super().__init__(cfg=cfg, model=model) + + # ----- eval metrics (regression) ------------------------------------- + self.eval_metrics = {"mae": mae_metric} + self.higher_is_better = {"mae": False} + + # ----- streaming state ----------------------------------------------- + self.window_idx: int = 0 + self.history_windows: List[Tuple[Tensor, Tensor]] = [] + self._current_window: Optional[Tuple[Tensor, Tensor]] = None + self.current_window_timerange: Optional[Tuple[str, str]] = None + + # Cap history to prevent unbounded memory growth + self.max_history_windows: int = 20 + + self._cur_train_loader: Optional[DataLoader] = None + self._cur_val_loader: Optional[DataLoader] = None + + # ----- early-stopping state (per drift event) ------------------------ + self._es_best_metric: Optional[float] = None + self._es_best_state: Optional[dict] = None + self._es_evals_no_improve: int = 0 + + # --------------------------------------------------------------------- # + # Required overrides + # --------------------------------------------------------------------- # + + def get_optmizer(self) -> Optimizer: # noqa: D102 (spelling kept for ABC) + return torch.optim.Adam(self.model.parameters(), lr=self.cfg.train.init_lr) + + def get_criterion(self): # noqa: D102 + return nn.MSELoss() + + def get_stream_dataloader(self): + assert self._cur_val_loader is not None + return self._cur_val_loader + + def get_train_dataloaders(self): + assert self._cur_train_loader is not None and self._cur_val_loader is not None + return self._cur_train_loader, self._cur_val_loader + + def get_hist_dataloaders( + self, + ) -> Tuple[Optional[DataLoader], Optional[DataLoader]]: + """Return loaders over previously-seen time windows, recency-weighted. + + Returns ``(None, None)`` until at least two windows have been served. + + The FEL input->output mapping drifts over time (concept drift), so + replaying every past window with equal weight anchors the model to stale + operating points and hurts current-window accuracy. Instead, the training + (replay) loader draws samples with a :class:`WeightedRandomSampler` whose + per-sample weight decays as ``_HIST_RECENCY_DECAY ** window_age`` (age 0 = + most recent past window). Recent regimes therefore dominate the replay + while older ones still contribute a little to guard against forgetting. + The validation loader stays uniform since it is only used for reporting. + """ + if self.window_idx <= 1: + return None, None + + # Build one view per history window, newest first, together with an + # aligned per-sample recency weight (weights index in the same order the + # ConcatDataset concatenates the views). + hist_train_views: List[FELDataset] = [] + hist_val_views: List[FELDataset] = [] + train_sample_weights: List[float] = [] + + for age, (X_w, y_w) in enumerate(reversed(self.history_windows)): + n = X_w.shape[0] + n_val = max(1, int(n * _VAL_FRACTION)) + n_train = n - n_val + hist_train_views.append(FELDataset(X_w[:n_train], y_w[:n_train])) + hist_val_views.append(FELDataset(X_w[n_train:], y_w[n_train:])) + train_sample_weights.extend([_HIST_RECENCY_DECAY**age] * n_train) + + ds_hist_train: ConcatDataset[Any] = ConcatDataset(hist_train_views) + ds_hist_val: ConcatDataset[Any] = ConcatDataset(hist_val_views) + + bs = self.cfg.train.batch_size + nw = self.cfg.train.num_workers + pin = torch.cuda.is_available() + + hist_sampler = WeightedRandomSampler( + weights=train_sample_weights, + num_samples=len(ds_hist_train), + replacement=True, + ) + + return ( + make_loader( + ds_hist_train, + bs, + shuffle=False, + sampler=hist_sampler, + num_workers=nw, + pin_memory=pin, + ), + make_loader(ds_hist_val, bs, shuffle=False, num_workers=nw, pin_memory=pin), + ) + + def cl_should_stop(self, iter_count: int) -> bool: + """Validation-based early stopping for the CL training loop. + + Every ``_ES_INTERVAL`` iterations the monitored validation metric + (``drift_detection.metric_index`` of :attr:`eval_metrics`) is evaluated. + Training stops once it has failed to improve by more than + ``_ES_MIN_DELTA`` for ``_ES_PATIENCE`` consecutive checks, at which point + the best-scoring weights seen during this drift event are restored. The + state is reset at ``iter_count == 0`` so each drift event stops + independently. Set ``_ES_PATIENCE = 0`` to disable. + """ + if _ES_PATIENCE <= 0: + return False + + # Reset at the start of each drift event's training loop. + if iter_count == 0: + self._es_best_metric = None + self._es_best_state = None + self._es_evals_no_improve = 0 + + if (iter_count + 1) % _ES_INTERVAL != 0: + return False + + metric_idx = self.cfg.drift_detection.metric_index + metric_names = list(self.eval_metrics.keys()) + metric_name = ( + metric_names[metric_idx] + if metric_idx < len(metric_names) + else metric_names[0] + ) + higher_is_better = self.higher_is_better.get(metric_name, True) + + val_metric = self.eval()[metric_idx] + self.model.train() # eval() switched the model into eval mode + + if self._es_best_metric is None: + improved = True + elif higher_is_better: + improved = val_metric > self._es_best_metric + _ES_MIN_DELTA + else: + improved = val_metric < self._es_best_metric - _ES_MIN_DELTA + + if improved: + self._es_best_metric = val_metric + self._es_best_state = { + k: v.detach().cpu().clone() for k, v in self.model.state_dict().items() + } + self._es_evals_no_improve = 0 + return False + + self._es_evals_no_improve += 1 + if self._es_evals_no_improve < _ES_PATIENCE: + return False + + # Patience exhausted: restore the best weights and stop. + if self._es_best_state is not None: + self.model.load_state_dict(self._es_best_state) + _log.info( + "[SLAC-FEL] Early stopping CL at iter %d (best %s=%.4g, no improvement " + "for %d checks).", + iter_count + 1, + metric_name, + self._es_best_metric, + _ES_PATIENCE, + ) + return True + + def _load_active_file(self) -> None: + """Load the next pkl file into ``_active_windows`` / ``_active_timestamps``. + + Wraps around to the first file once all files have been consumed and + frees the previous file's tensors (those no longer referenced by + ``history_windows``) via an explicit GC pass. + """ + if self._file_idx >= len(self._window_file_paths): + print( + f"[SLAC-FEL] All {len(self._window_file_paths)} file(s) exhausted; " + "wrapping around to the first file." + ) + self._file_idx = 0 + + pkl_path = self._window_file_paths[self._file_idx] + print( + f"[SLAC-FEL] Loading file " + f"{self._file_idx + 1}/{len(self._window_file_paths)}: " + f"{os.path.basename(pkl_path)}" + ) + + X_w, y_w, idx = load_window_file( + pkl_path, + self.input_cols, + self.output_cols, + self.input_scaler, + self.output_scaler, + ) + self._active_windows = split_into_windows( + X_w, y_w, window_size=self.cfg.data.batch_size + ) + self._active_timestamps = split_timestamps( + idx, window_size=self.cfg.data.batch_size + ) + self._active_window_idx = 0 + self._file_idx += 1 + gc.collect() + print( + f"[SLAC-FEL] Ready: {len(self._active_windows)} windows from " + f"{os.path.basename(pkl_path)} " + f"({X_w.shape[0]} samples, window_size={self.cfg.data.batch_size})" + ) + + def update_data_stream(self) -> None: + """Advance to the next chronological time window. + + In lazy mode each pkl file is loaded on demand when the current file's + windows are exhausted. In legacy mode all windows are already in memory. + """ + self._dispose_current_loaders() + + # ── Archive the *previous* window into history ──────────────────── + if self._current_window is not None: + self.history_windows.append(self._current_window) + self._current_window = None + # Evict oldest windows when cap is reached + while len(self.history_windows) > self.max_history_windows: + self.history_windows.pop(0) + + # ── Fetch the next window tensors ───────────────────────────────── + if self._lazy: + # Load a new file if we've consumed all windows from the current one. + if self._active_window_idx >= len(self._active_windows): + self._load_active_file() + + X_w, y_w = self._active_windows[self._active_window_idx] + ts = self._active_timestamps[self._active_window_idx] + self._active_window_idx += 1 + window_label = ( + f"{self._file_idx}/{len(self._window_file_paths)} " + f"(win {self._active_window_idx}/{len(self._active_windows)} in file)" + ) + else: + if self.window_idx >= self.num_windows: + print( + f"Warning: All {self.num_windows} time windows exhausted; " + "wrapping around to the first window." + ) + self.window_idx = 0 + + X_w, y_w = self.windows[self.window_idx] + ts = self.window_timestamps[self.window_idx] + window_label = f"{self.window_idx + 1}/{self.num_windows}" + + # Record timestamp range for this window + self.current_window_timerange = (str(ts[0]), str(ts[-1])) + + # Keep a reference so the next call can archive it without reloading + self._current_window = (X_w, y_w) + + # Train / val split (last _VAL_FRACTION chronologically) + n = X_w.shape[0] + n_val = max(1, int(n * _VAL_FRACTION)) + n_train = n - n_val + # Safety: ensure both splits have at least 1 sample + if n_train < 1: + n_train = max(1, n - 1) + n_val = n - n_train + + ds_train = FELDataset(X_w[:n_train], y_w[:n_train]) + ds_val = FELDataset(X_w[n_train:], y_w[n_train:]) + + bs = self.cfg.train.batch_size + nw = self.cfg.train.num_workers + pin = torch.cuda.is_available() + + self._cur_train_loader = make_loader( + ds_train, bs, shuffle=True, num_workers=nw, pin_memory=pin + ) + self._cur_val_loader = make_loader( + ds_val, bs, shuffle=False, num_workers=nw, pin_memory=pin + ) + + print( + f"[SLAC-FEL] Window {window_label}: " + f"{n_train} train / {n_val} val samples " + f"[{self.current_window_timerange[0]} → {self.current_window_timerange[1]}]" + ) + self.window_idx += 1 + + # --------------------------------------------------------------------- # + # Helpers + # --------------------------------------------------------------------- # + + @staticmethod + def _load_pretrained_direct( + path: str, input_size: int, output_size: int, device: str + ) -> FELNet: + """Load a pretrained checkpoint directly with no weight modifications. + + Supports two save formats produced by ``train_fel_model.py``: + + 1. A raw ``nn.Sequential`` (saved via ``torch.save(model.net, ...)``). + The Sequential is wrapped inside a new :class:`FELNet` whose + architecture is defined entirely by the checkpoint. + 2. A ``state_dict`` (plain ``dict``). The input dimension is inferred + from the first Linear layer's weight shape so that :class:`FELNet` + is constructed to match exactly, then ``load_state_dict`` is called + with ``strict=True``. + + Raises: + FileNotFoundError: If *path* does not exist. + RuntimeError: If the checkpoint shapes are incompatible with the + data (e.g. the data has a different number of input features + than the model expects). + """ + state = torch.load(path, map_location=device, weights_only=False) + + if isinstance(state, nn.Sequential): + # Format 1: checkpoint is the raw nn.Sequential + # Infer input/output dims from the first and last Linear layers + first_linear = next(m for m in state.modules() if isinstance(m, nn.Linear)) + last_linear = list(m for m in state.modules() if isinstance(m, nn.Linear))[ + -1 + ] + ckpt_in = first_linear.in_features + ckpt_out = last_linear.out_features + + if ckpt_in != input_size: + raise RuntimeError( + f"Pretrained model expects {ckpt_in} input features but " + f"the data has {input_size}. Ensure the feature_config.yml " + f"and scalers match the checkpoint." + ) + + model = FELNet(input_size=ckpt_in, output_size=ckpt_out) + model.net.load_state_dict(state.state_dict(), strict=True) + print(f"Loaded pretrained FEL model (nn.Sequential) from {path}") + + elif isinstance(state, dict): + # Format 2: checkpoint is a state_dict + # Strip torch.compile artefact from keys + sd = {k.replace("_orig_mod.", ""): v for k, v in state.items()} + + # Infer input dim from the first weight tensor + first_weight_key = next( + k for k in sd if k.endswith(".weight") and sd[k].dim() == 2 + ) + ckpt_in = sd[first_weight_key].shape[1] + + if ckpt_in != input_size: + raise RuntimeError( + f"Pretrained model expects {ckpt_in} input features but " + f"the data has {input_size}. Ensure the feature_config.yml " + f"and scalers match the checkpoint." + ) + + model = FELNet(input_size=ckpt_in, output_size=output_size) + model.load_state_dict(sd, strict=True) + print(f"Loaded pretrained FEL model (state_dict) from {path}") + + else: + raise TypeError( + f"Unexpected checkpoint type {type(state).__name__} from {path}. " + f"Expected nn.Sequential or state_dict." + ) + + return model + + def _dispose_current_loaders(self) -> None: + if self._cur_train_loader is not None: + del self._cur_train_loader + self._cur_train_loader = None + if self._cur_val_loader is not None: + del self._cur_val_loader + self._cur_val_loader = None + gc.collect() diff --git a/examples/slac_fel/model/feature_config.yml b/examples/slac_fel/model/feature_config.yml new file mode 100644 index 0000000..c62e96d --- /dev/null +++ b/examples/slac_fel/model/feature_config.yml @@ -0,0 +1,2743 @@ +device: cpu +input_transformers: +- resources/lcls_fel_input_scaler.pt +input_variables: + QUAD:LI21:211:BACT: + variable_class: TorchScalarVariable + default_value: 6.030075550079346 + read_only: false + value_range: + - 3.2707419395446777 + - 7.083395004272461 + unit: kG + QUAD:LI21:221:BACT: + variable_class: TorchScalarVariable + default_value: -0.22167986631393433 + read_only: false + value_range: + - -0.7424343228340149 + - 0.2432546466588974 + unit: kG + QUAD:LI21:243:BACT: + variable_class: TorchScalarVariable + default_value: -0.0006752711487933993 + read_only: false + value_range: + - -0.0007149674347601831 + - -0.0006156182498671114 + unit: kG-m + QUAD:LI21:251:BACT: + variable_class: TorchScalarVariable + default_value: -0.14767540991306305 + read_only: false + value_range: + - -0.7296757698059082 + - 0.25308719277381897 + unit: kG + QUAD:LI21:271:BACT: + variable_class: TorchScalarVariable + default_value: -6.2067694664001465 + read_only: false + value_range: + - -7.801762104034424 + - -4.287487983703613 + unit: kG + QUAD:LI21:335:BACT: + variable_class: TorchScalarVariable + default_value: -5.328253269195557 + read_only: false + value_range: + - -5.428651332855225 + - -5.321958065032959 + unit: kG + QUAD:LI24:713:BACT: + variable_class: TorchScalarVariable + default_value: 35.41676330566406 + read_only: false + value_range: + - 23.610397338867188 + - 35.42658615112305 + unit: kG + QUAD:LI24:740:BACT: + variable_class: TorchScalarVariable + default_value: -0.0005302699573803693 + read_only: false + value_range: + - -0.9996497631072998 + - 1.100592851638794 + unit: kG + QUAD:LI24:860:BACT: + variable_class: TorchScalarVariable + default_value: 0.4042496532201767 + read_only: false + value_range: + - 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7.27554988861084 + - 7.502200126647949 + unit: mm + USEG:UNDH:4550:GapAct: + variable_class: TorchScalarVariable + default_value: 7.370250225067139 + read_only: false + value_range: + - 7.259799957275391 + - 7.48829984664917 + unit: mm + USEG:UNDH:4650:GapAct: + variable_class: TorchScalarVariable + default_value: 7.40084981918335 + read_only: false + value_range: + - 7.28754997253418 + - 7.523250102996826 + unit: mm + USEG:UNDH:4750:GapAct: + variable_class: TorchScalarVariable + default_value: 7.515850067138672 + read_only: false + value_range: + - 7.395750045776367 + - 7.641449928283691 + unit: mm +model: resources/lcls_fel_final_model_cpu.pt +model_class: TorchModule +output_format: tensor +output_transformers: +- resources/lcls_fel_output_scaler.pt +output_variables: + GDET:FEE1:241:ENRC: + read_only: false + variable_class: TorchScalarVariable + unit: mJ +precision: double diff --git a/examples/slac_fel/model/final_lcls_fel_model.pt b/examples/slac_fel/model/final_lcls_fel_model.pt new file mode 100644 index 0000000..ccb3a28 Binary files /dev/null and b/examples/slac_fel/model/final_lcls_fel_model.pt differ diff --git a/examples/slac_fel/model/lcls_fel_input_scaler.pt b/examples/slac_fel/model/lcls_fel_input_scaler.pt new file mode 100644 index 0000000..60d115f Binary files /dev/null and b/examples/slac_fel/model/lcls_fel_input_scaler.pt differ diff --git a/examples/slac_fel/model/lcls_fel_output_scaler.pt b/examples/slac_fel/model/lcls_fel_output_scaler.pt new file mode 100644 index 0000000..74f25ed Binary files /dev/null and b/examples/slac_fel/model/lcls_fel_output_scaler.pt differ diff --git a/examples/slac_fel/plot_data.ipynb b/examples/slac_fel/plot_data.ipynb new file mode 100644 index 0000000..783321f --- /dev/null +++ b/examples/slac_fel/plot_data.ipynb @@ -0,0 +1,730 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "097db665", + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import sys\n", + "\n", + "import numpy as np\n", + "import pandas as pd\n", + "import torch\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib.dates as mdates\n", + "\n", + "# Make the apeiron package and the example modules importable from the repo root.\n", + "REPO_ROOT = os.path.abspath(\"../..\")\n", + "if REPO_ROOT not in sys.path:\n", + " sys.path.insert(0, REPO_ROOT)\n", + "\n", + "from examples.slac_fel.model import FELNet # noqa: E402\n", + "from examples.slac_fel.utils import ( # noqa: E402\n", + " discover_window_files,\n", + " load_feature_config,\n", + " load_scalers,\n", + " load_window_file,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "21045a91", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "341 input features, target = ['GDET:FEE1:241:ENRC']\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/95j/_penv/torch-penv/lib/python3.13/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", + " from .autonotebook import tqdm as notebook_tqdm\n" + ] + } + ], + "source": [ + "# Paths\n", + "CONFIG_DIR = \"model\" # scalers + feature_config.yml\n", + "# CONFIG_DIR = \"model_full\" # scalers + feature_config.yml\n", + "DATA_DIR = \"data\" # all data_*.pkl windows\n", + "ORIGINAL_MODEL_PATH = \"model/final_lcls_fel_model.pt\" # baseline model\n", + "# ORIGINAL_MODEL_PATH = \"model_full/final_model.pt\" # best full model\n", + "ADAPTED_CKPT_PATH = (\n", + " \"../../output/slac-fel/ewc-ph-kswin-sensitive/\" # last CL checkpoint\n", + ")\n", + "CKPT_TRIGGER = [\n", + " \"data_44.pkl\",\n", + " \"data_54.pkl\",\n", + " \"data_78.pkl\",\n", + " \"data_102.pkl\",\n", + " \"data_125.pkl\",\n", + " \"data_153.pkl\",\n", + " \"data_175.pkl\",\n", + " \"data_231.pkl\",\n", + " \"data_255.pkl\",\n", + " \"data_275.pkl\",\n", + " \"data_305.pkl\",\n", + "]\n", + "FINAL_CKPT = len(CKPT_TRIGGER) - 2\n", + "CKPT_NAME = [f\"drift_adaptation_{i + 1}.pt\" for i in range(len(CKPT_TRIGGER))]\n", + "DEVICE = \"cpu\"\n", + "\n", + "input_cols, output_cols = load_feature_config(CONFIG_DIR)\n", + "input_scaler, output_scaler = load_scalers(CONFIG_DIR, device=DEVICE)\n", + "adapted_out_size = len(output_cols)\n", + "adapted_in_size = len(input_cols)\n", + "print(f\"{len(input_cols)} input features, target = {output_cols}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "8363e917", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loaded original model and adapted checkpoint: drift_adaptation_1.pt\n", + "Loaded original model and adapted checkpoint: drift_adaptation_2.pt\n", + "Loaded original model and adapted checkpoint: drift_adaptation_3.pt\n", + "Loaded original model and adapted checkpoint: drift_adaptation_4.pt\n", + "Loaded original model and adapted checkpoint: drift_adaptation_5.pt\n", + "Loaded original model and adapted checkpoint: drift_adaptation_6.pt\n", + "Loaded original model and adapted checkpoint: drift_adaptation_7.pt\n", + "Loaded original model and adapted checkpoint: drift_adaptation_8.pt\n", + "Loaded original model and adapted checkpoint: drift_adaptation_9.pt\n", + "Loaded original model and adapted checkpoint: drift_adaptation_10.pt\n", + "Loaded original model and adapted checkpoint: drift_adaptation_11.pt\n" + ] + } + ], + "source": [ + "# Load both models.\n", + "# Original baseline is a raw nn.Sequential saved directly.\n", + "original_model = torch.load(\n", + " ORIGINAL_MODEL_PATH, weights_only=False, map_location=DEVICE\n", + ")\n", + "original_model.eval()\n", + "\n", + "# The drift-adaptation checkpoint is a FELNet state_dict.\n", + "adapted_models = []\n", + "for ADAPTED_CKPT in CKPT_NAME:\n", + " adapted_model = FELNet(input_size=adapted_in_size, output_size=adapted_out_size)\n", + " adapted_state = torch.load(\n", + " ADAPTED_CKPT_PATH + ADAPTED_CKPT, weights_only=False, map_location=DEVICE\n", + " )\n", + " adapted_model.load_state_dict(adapted_state, strict=True)\n", + " adapted_model.eval()\n", + " adapted_models.append(adapted_model)\n", + " print(\n", + " \"Loaded original model and adapted checkpoint:\",\n", + " os.path.basename(ADAPTED_CKPT_PATH + ADAPTED_CKPT),\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "727cd6c0", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 308 window files\n", + " processed 50/308 files\n", + " processed 100/308 files\n", + " processed 150/308 files\n", + " processed 200/308 files\n", + " processed 250/308 files\n", + " processed 300/308 files\n", + " processed 308/308 files\n", + "Drift moments: [('data_44.pkl', '2026-03-05 17:08:09.345252096-08:00'), ('data_54.pkl', '2026-03-06 07:05:16.608313088-08:00'), ('data_78.pkl', '2026-03-07 16:07:29.997694720-08:00'), ('data_102.pkl', '2026-03-14 23:17:20.058152192-07:00'), ('data_125.pkl', '2026-03-16 18:59:20.667214848-07:00'), ('data_153.pkl', '2026-03-19 03:32:09.735143424-07:00'), ('data_175.pkl', '2026-03-21 09:45:14.271045376-07:00'), ('data_231.pkl', '2026-03-26 05:41:38.717434112-07:00'), ('data_255.pkl', '2026-03-27 17:10:56.831203840-07:00'), ('data_275.pkl', '2026-03-28 22:20:36.778173440-07:00'), ('data_305.pkl', '2026-03-30 17:56:08.013252096-07:00')]\n", + "Combined timeseries: 1,535,405 samples from 2026-03-04 00:14:32.394081280-08:00 to 2026-03-31 23:59:59.707322368-07:00\n" + ] + }, + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " measurement pred_original pred_adapted \\\n", + "2026-03-04 00:14:32.394081280-08:00 2.205471 1.795648 1.522725 \n", + "2026-03-04 00:14:33.344012288-08:00 2.155539 1.813548 1.540761 \n", + "2026-03-04 00:14:34.302200576-08:00 1.894877 1.797758 1.538688 \n", + "2026-03-04 00:14:35.252262400-08:00 2.154334 1.764821 1.540649 \n", + "2026-03-04 00:14:36.202193408-08:00 2.047306 1.783494 1.546016 \n", + "\n", + " pred_adapt_1 pred_adapt_2 pred_adapt_3 \\\n", + "2026-03-04 00:14:32.394081280-08:00 1.826297 2.210085 1.719352 \n", + "2026-03-04 00:14:33.344012288-08:00 1.873209 2.226486 1.729390 \n", + "2026-03-04 00:14:34.302200576-08:00 1.843170 2.203873 1.716543 \n", + "2026-03-04 00:14:35.252262400-08:00 1.826488 2.177782 1.685544 \n", + "2026-03-04 00:14:36.202193408-08:00 1.804574 2.182158 1.693050 \n", + "\n", + " pred_adapt_4 pred_adapt_5 pred_adapt_6 \\\n", + "2026-03-04 00:14:32.394081280-08:00 1.950470 2.001322 1.695771 \n", + "2026-03-04 00:14:33.344012288-08:00 1.933479 2.003361 1.669382 \n", + "2026-03-04 00:14:34.302200576-08:00 1.940985 2.010351 1.653392 \n", + "2026-03-04 00:14:35.252262400-08:00 1.934601 2.043525 1.675316 \n", + "2026-03-04 00:14:36.202193408-08:00 1.927616 2.058221 1.713584 \n", + "\n", + " pred_adapt_7 pred_adapt_8 pred_adapt_9 \\\n", + "2026-03-04 00:14:32.394081280-08:00 1.378096 1.223320 1.518939 \n", + "2026-03-04 00:14:33.344012288-08:00 1.422185 1.232590 1.513156 \n", + "2026-03-04 00:14:34.302200576-08:00 1.422332 1.232209 1.511173 \n", + "2026-03-04 00:14:35.252262400-08:00 1.428650 1.232872 1.503642 \n", + "2026-03-04 00:14:36.202193408-08:00 1.455493 1.245274 1.515016 \n", + "\n", + " pred_adapt_10 pred_adapt_11 \n", + "2026-03-04 00:14:32.394081280-08:00 1.522725 1.649240 \n", + "2026-03-04 00:14:33.344012288-08:00 1.540761 1.659009 \n", + "2026-03-04 00:14:34.302200576-08:00 1.538688 1.647257 \n", + "2026-03-04 00:14:35.252262400-08:00 1.540649 1.652216 \n", + "2026-03-04 00:14:36.202193408-08:00 1.546016 1.651964 " + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Load every data_*.pkl window, run both models, and accumulate a single timeseries.\n", + "# Files are processed one at a time to keep memory bounded (the full input tensor\n", + "# would otherwise be ~2 GB).\n", + "files = discover_window_files(DATA_DIR)\n", + "print(f\"Found {len(files)} window files\")\n", + "\n", + "times, measurement, pred_original, pred_adapted = [], [], [], []\n", + "\n", + "# Predictions from each adapted checkpoint separately (for per-segment selection).\n", + "pred_adapt_cols = [[] for _ in adapted_models]\n", + "\n", + "# Timestamp at which each drift-trigger window begins, so the plot can mark the\n", + "# moments where a CL checkpoint was created (keyed by file name, in CKPT_TRIGGER order).\n", + "drift_times = {}\n", + "\n", + "with torch.no_grad():\n", + " for i, path in enumerate(files):\n", + " X, y, idx = load_window_file(\n", + " path, input_cols, output_cols, input_scaler, output_scaler\n", + " )\n", + " y_meas = output_scaler.untransform(y).squeeze(-1).numpy()\n", + " y_orig = output_scaler.untransform(original_model(X)).squeeze(-1).numpy()\n", + " y_adapts = [\n", + " output_scaler.untransform(m(X)).squeeze(-1).numpy() for m in adapted_models\n", + " ]\n", + "\n", + " idx_arr = np.asarray(idx)\n", + " times.append(idx_arr)\n", + " measurement.append(y_meas)\n", + " pred_original.append(y_orig)\n", + " for col, ya in zip(pred_adapt_cols, y_adapts):\n", + " col.append(ya)\n", + " # Single-model column (last checkpoint applied everywhere) for the existing plot.\n", + " pred_adapted.append(y_adapts[FINAL_CKPT])\n", + "\n", + " # Record the drift moment (start of the window) for trigger files.\n", + " fname = os.path.basename(path)\n", + " if fname in CKPT_TRIGGER:\n", + " drift_times[fname] = pd.Timestamp(idx_arr[0])\n", + "\n", + " if (i + 1) % 50 == 0 or i == len(files) - 1:\n", + " print(f\" processed {i + 1}/{len(files)} files\")\n", + "\n", + "# Order the drift moments to match CKPT_TRIGGER.\n", + "drift_times = {f: drift_times[f] for f in CKPT_TRIGGER if f in drift_times}\n", + "missing = [f for f in CKPT_TRIGGER if f not in drift_times]\n", + "if missing:\n", + " print(f\" warning: trigger file(s) not found in {DATA_DIR}: {missing}\")\n", + "print(f\"Drift moments: {[(f, str(t)) for f, t in drift_times.items()]}\")\n", + "\n", + "data = {\n", + " \"measurement\": np.concatenate(measurement),\n", + " \"pred_original\": np.concatenate(pred_original),\n", + " \"pred_adapted\": np.concatenate(pred_adapted),\n", + "}\n", + "# One column per adapted checkpoint: pred_adapt_1, pred_adapt_2, ...\n", + "for k, col in enumerate(pred_adapt_cols):\n", + " data[f\"pred_adapt_{k + 1}\"] = np.concatenate(col)\n", + "\n", + "results = pd.DataFrame(\n", + " data,\n", + " index=pd.DatetimeIndex(np.concatenate(times)),\n", + ").sort_index()\n", + "\n", + "print(\n", + " f\"Combined timeseries: {len(results):,} samples \"\n", + " f\"from {results.index.min()} to {results.index.max()}\"\n", + ")\n", + "results.head()" + ] + }, + { + "cell_type": "markdown", + "id": "dd256e6b", + "metadata": {}, + "source": [ + "# Plot: original model vs. last drift-adaptation checkpoint\n", + "\n", + "The full stream is plotted as one continuous timeseries. Raw measurements are shown\n", + "as faint points; the lines are rolling means that make the model comparison legible\n", + "across ~1.5M samples. The y-axis is clipped to the measurement range because the\n", + "original model over-predicts well off-scale (>30 mJ) on this newer data." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "7f1c3000", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "window = 2000 # rolling-mean window (samples)\n", + "min_periods = 200\n", + "downsample = 50 # plot every Nth raw measurement point\n", + "\n", + "roll = results.rolling(window=window, min_periods=min_periods).mean()\n", + "\n", + "fig, ax = plt.subplots(figsize=(15, 7))\n", + "\n", + "raw = results.iloc[::downsample]\n", + "ax.scatter(\n", + " raw.index,\n", + " raw[\"measurement\"],\n", + " s=4,\n", + " color=\"lightgray\",\n", + " alpha=0.4,\n", + " label=\"Measurement (raw)\",\n", + " rasterized=True,\n", + ")\n", + "ax.plot(\n", + " roll.index,\n", + " roll[\"measurement\"],\n", + " color=\"black\",\n", + " lw=1.5,\n", + " label=\"Measurement (rolling mean)\",\n", + ")\n", + "ax.plot(\n", + " roll.index, roll[\"pred_original\"], color=\"dodgerblue\", lw=2, label=\"Original model\"\n", + ")\n", + "ax.plot(\n", + " roll.index,\n", + " roll[\"pred_adapted\"],\n", + " color=\"crimson\",\n", + " lw=2,\n", + " label=\"Adapted model (drift_adaptation)\",\n", + ")\n", + "\n", + "ax.set_xlabel(\"Time\", fontsize=12)\n", + "ax.set_ylabel(\"HXR pulse intensity (mJ) [GDET:FEE1:241:ENRC]\", fontsize=12)\n", + "ax.set_title(\n", + " \"FEL pulse intensity: measurement vs. original and adapted models\", fontsize=13\n", + ")\n", + "ax.set_ylim(\n", + " 0, 8\n", + ") # original model spikes off-scale (>30 mJ); clip to the comparison range\n", + "\n", + "# Highlight drift moments: each vertical line marks where a CL checkpoint was triggered.\n", + "for k, (fname, t) in enumerate(drift_times.items()):\n", + " ax.axvline(\n", + " t,\n", + " color=\"darkgray\",\n", + " ls=\"--\",\n", + " lw=1.8,\n", + " alpha=0.9,\n", + " label=\"Drift detected (checkpoint)\" if k == 0 else None,\n", + " )\n", + " ax.annotate(\n", + " f\"drift {k + 1}\\n{fname}\",\n", + " xy=(t, ax.get_ylim()[1]),\n", + " xytext=(4, -6),\n", + " textcoords=\"offset points\",\n", + " rotation=90,\n", + " va=\"top\",\n", + " ha=\"left\",\n", + " fontsize=8,\n", + " color=\"darkgray\",\n", + " fontweight=\"bold\",\n", + " )\n", + "\n", + "ax.xaxis.set_major_formatter(mdates.DateFormatter(\"%Y-%m-%d\"))\n", + "ax.tick_params(axis=\"x\", rotation=45)\n", + "ax.grid(True, linestyle=\"--\", linewidth=0.5, alpha=0.6)\n", + "ax.legend(fontsize=11, loc=\"upper left\")\n", + "fig.tight_layout()\n", + "\n", + "os.makedirs(\"plotting\", exist_ok=True)\n", + "fig.savefig(\"plotting/model_comparison.png\", dpi=120, bbox_inches=\"tight\")\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "5d929224", + "metadata": {}, + "source": [ + "# Per-segment (time-aware) adapted prediction\n", + "\n", + "The plot above applies a single checkpoint to the whole stream. In a real run, each\n", + "drift event swaps in a new checkpoint that stays active until the next drift. This\n", + "cell instead selects, for every timestamp, the checkpoint that was **live** at that\n", + "moment — original before the first drift, `drift_adaptation_1` between the two drifts,\n", + "`drift_adaptation_2` after the second — and shades each drift regime from its **start**\n", + "(drift onset, solid orange) to its **end** (dashed grey)." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "3bdd1e80", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Original model MAE: 3.5206 mJ\n", + "Chosen checkpoint MAE: 0.4007 mJ\n", + "Per-segment (time-aware) MAE: 0.4054 mJ\n" + ] + } + ], + "source": [ + "# === Per-segment (time-aware) adapted prediction =========================\n", + "# During the run each drift event swaps in a new checkpoint that stays active\n", + "# until the next drift. So the \"adapted\" prediction at time t should come from\n", + "# the checkpoint that was live at t, not from a single checkpoint applied to the\n", + "# whole stream. Segments (chronological), for CKPT_TRIGGER = [data_110, data_238]:\n", + "# [start, drift 1) -> original model (pred_original)\n", + "# [drift 1, drift 2) -> checkpoint 1 (pred_adapt_1)\n", + "# [drift 2, end] -> checkpoint 2 (pred_adapt_2)\n", + "window = 2000\n", + "min_periods = 200\n", + "downsample = 50\n", + "\n", + "idx = results.index\n", + "drift_ts = list(drift_times.values()) # chronological, one per checkpoint\n", + "\n", + "# Start from the original model everywhere, then, walking forward in time, overwrite\n", + "# each region from its drift onset with that checkpoint (later drifts win for later t).\n", + "pred_seg = results[\"pred_original\"].to_numpy().copy()\n", + "for k, t in enumerate(drift_ts):\n", + " mask = np.asarray(idx >= t) # DatetimeIndex comparison -> boolean ndarray\n", + " pred_seg[mask] = results[f\"pred_adapt_{k + 1}\"].to_numpy()[mask]\n", + "results[\"pred_adapted_segmented\"] = pred_seg\n", + "\n", + "# Segment boundaries: [data start, drift 1, drift 2, ..., data end].\n", + "seg_bounds = [idx.min(), *drift_ts, idx.max()]\n", + "seg_names = [\"original\", *[f\"checkpoint {k + 1}\" for k in range(len(drift_ts))]]\n", + "\n", + "roll = results.rolling(window=window, min_periods=min_periods).mean()\n", + "\n", + "fig, ax = plt.subplots(figsize=(15, 7))\n", + "\n", + "raw = results.iloc[::downsample]\n", + "ax.scatter(\n", + " raw.index,\n", + " raw[\"measurement\"],\n", + " s=4,\n", + " color=\"lightgray\",\n", + " alpha=0.4,\n", + " label=\"Measurement (raw)\",\n", + " rasterized=True,\n", + ")\n", + "ax.plot(\n", + " roll.index,\n", + " roll[\"measurement\"],\n", + " color=\"black\",\n", + " lw=1.5,\n", + " label=\"Measurement (rolling mean)\",\n", + ")\n", + "ax.plot(\n", + " roll.index,\n", + " roll[\"pred_original\"],\n", + " color=\"dodgerblue\",\n", + " lw=1.3,\n", + " alpha=0.55,\n", + " label=\"Original model (reference)\",\n", + ")\n", + "ax.plot(\n", + " roll.index,\n", + " roll[\"pred_adapted_segmented\"],\n", + " color=\"crimson\",\n", + " lw=2,\n", + " label=\"Adapted model (per-segment checkpoint)\",\n", + ")\n", + "\n", + "ax.set_ylim(0, 8)\n", + "ymax = ax.get_ylim()[1]\n", + "\n", + "# Shade each segment and mark its start (solid) and end (dashed) so the active\n", + "# checkpoint over each drift regime is explicit.\n", + "seg_colors = [\"none\", \"gold\", \"mediumseagreen\", \"orchid\", \"sandybrown\"]\n", + "for s, (t0, t1, name) in enumerate(zip(seg_bounds[:-1], seg_bounds[1:], seg_names)):\n", + " if s == 0:\n", + " continue # skip the pre-drift (original) region\n", + " ax.axvspan(\n", + " t0,\n", + " t1,\n", + " color=seg_colors[s % len(seg_colors)],\n", + " alpha=0.12,\n", + " label=f\"{name} active\",\n", + " )\n", + " # segment start = drift onset\n", + " ax.axvline(t0, color=\"darkorange\", ls=\"-\", lw=1.8, alpha=0.9)\n", + " ax.annotate(\n", + " f\"start {name}\\n{CKPT_TRIGGER[s - 1]}\",\n", + " xy=(t0, ymax),\n", + " xytext=(4, -6),\n", + " textcoords=\"offset points\",\n", + " rotation=90,\n", + " va=\"top\",\n", + " ha=\"left\",\n", + " fontsize=8,\n", + " color=\"darkorange\",\n", + " fontweight=\"bold\",\n", + " )\n", + " # segment end\n", + " # ax.axvline(t1, color=\"dimgray\", ls=\"--\", lw=1.3, alpha=0.8)\n", + " # ax.annotate(f\"end {name}\", xy=(t1, ymax), xytext=(-10, -6),\n", + " # textcoords=\"offset points\", rotation=90, va=\"top\", ha=\"right\",\n", + " # fontsize=8, color=\"dimgray\")\n", + "\n", + "ax.set_xlabel(\"Time\", fontsize=12)\n", + "ax.set_ylabel(\"HXR pulse intensity (mJ) [GDET:FEE1:241:ENRC]\", fontsize=12)\n", + "ax.set_title(\n", + " \"FEL pulse intensity: per-segment adapted model (checkpoint active per drift regime)\",\n", + " fontsize=13,\n", + ")\n", + "ax.xaxis.set_major_formatter(mdates.DateFormatter(\"%Y-%m-%d\"))\n", + "ax.tick_params(axis=\"x\", rotation=45)\n", + "ax.grid(True, linestyle=\"--\", linewidth=0.5, alpha=0.6)\n", + "ax.legend(fontsize=10, loc=\"upper left\", ncol=2)\n", + "fig.tight_layout()\n", + "\n", + "os.makedirs(\"plotting\", exist_ok=True)\n", + "fig.savefig(\"plotting/model_comparison_segmented.png\", dpi=120, bbox_inches=\"tight\")\n", + "plt.show()\n", + "\n", + "# MAE comparison: per-segment selection vs. single last checkpoint vs. original.\n", + "mae_seg = (results[\"pred_adapted_segmented\"] - results[\"measurement\"]).abs().mean()\n", + "mae_last = (results[\"pred_adapted\"] - results[\"measurement\"]).abs().mean()\n", + "mae_orig = (results[\"pred_original\"] - results[\"measurement\"]).abs().mean()\n", + "print(f\"Original model MAE: {mae_orig:.4f} mJ\")\n", + "print(f\"Chosen checkpoint MAE: {mae_last:.4f} mJ\")\n", + "print(f\"Per-segment (time-aware) MAE: {mae_seg:.4f} mJ\")" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "4de6903c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Original model MAE: 3.5206 mJ\n", + "Adapted model MAE: 0.4007 mJ\n" + ] + } + ], + "source": [ + "# Error summary over the full stream (MAE against the measurement).\n", + "mae_original = (results[\"pred_original\"] - results[\"measurement\"]).abs().mean()\n", + "mae_adapted = (results[\"pred_adapted\"] - results[\"measurement\"]).abs().mean()\n", + "print(f\"Original model MAE: {mae_original:.4f} mJ\")\n", + "print(f\"Adapted model MAE: {mae_adapted:.4f} mJ\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "656b04a2-6f04-4539-816e-25810c7bbeb8", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/examples/slac_fel/slac-fel.toml b/examples/slac_fel/slac-fel.toml new file mode 100644 index 0000000..d689442 --- /dev/null +++ b/examples/slac_fel/slac-fel.toml @@ -0,0 +1,74 @@ +# slac-fel.toml — LCLS FEL continuous-learning experiment +seed = 42 +device = "auto" +multi_gpu = false +verbosity = "DEBUG" + +[model] +name = "fel" +# Set to "" to train from scratch, or point to a saved state_dict .pt file +pretrained_path = "examples/slac_fel/model/final_lcls_fel_model.pt" +max_ckpts = 20 +ckpts_path = "output/slac-fel/" + +[data] +name = "slac-fel" +path = "examples/slac_fel/data" +# Number of samples per time window (smaller = finer drift granularity) +batch_size = 5000 + +[train] +batch_size = 512 +num_workers = 4 +init_lr = 1e-5 +max_iter = 6000 +grad_accumulation_steps = 1 + + +[continual_learning] +update_mode = "ewc_online" +mix_historic_data = true + +# JVP regularization (used when update_mode = "jvp_reg") +jvp_rho_theta = 0.05 +jvp_rho_x = 1.0 +jvp_data_sign = 1.0 + +# EWC (used when update_mode = "ewc_online") +ewc_lambda = 1000.0 +ewc_ema_decay = 0.95 + +# KFAC (used when update_mode = "kfac_online") +kfac_lambda = 1e-2 +kfac_ema_decay = 0.95 + + +[drift_detection] +detector_name = "EnsembleDetector" +ensemble_detectors = ["PageHinkleyDetector", "KSWINDetector"] +ensemble_voting = "any" + +kswin_alpha = 0.05 +kswin_window_size = 20 +kswin_stat_size = 10 + +ph_min_instances = 30 +ph_delta = 0.3 +ph_threshold = 2.0 +ph_alpha = 0.9999 + +metric_index = 0 +detection_interval = 2 +aggregation = "mean" +reset_after_learning = false +max_stream_updates = 307 + + +[logging] +backend = "wandb" +experiment_name = "slac-fel-cl" +#mlflow_tracking_uri = "https://ard-mlflow.slac.stanford.edu/" + +[visualization] +input = "output/slac-fel.csv" + diff --git a/examples/slac_fel/utils.py b/examples/slac_fel/utils.py new file mode 100644 index 0000000..725e326 --- /dev/null +++ b/examples/slac_fel/utils.py @@ -0,0 +1,433 @@ +# examples/slac_fel/utils.py +"""Data-loading utilities for the SLAC FEL continuous-learning example. + +The data pipeline assumes that all heavy cleaning (archive pull, filtering, +exclusion windows, invalid-PV removal, column selection) has already been done +and the results saved as individual pickle files (``data_1.pkl``, +``data_2.pkl``, …). All pickle files are loaded, concatenated into a single +dataset in chronological order, and then split into fixed-size windows +controlled by ``cfg.data.batch_size``. + +If only a single ``data.pkl`` is present (legacy layout), it is loaded in its +entirety and split into fixed-size windows via ``window_size``. + +Expected directory layout (pointed to by ``cfg.data.path``):: + + / + data_1.pkl # pandas DataFrame, datetime-indexed, sorted + data_2.pkl # ... + ... +""" + +from __future__ import annotations + +import glob +import logging +import os +import re +import warnings +from typing import List, Optional, Tuple + +import pandas as pd +import torch +import yaml +from torch import Tensor +from torch.utils.data import DataLoader, Dataset, Sampler + +_log = logging.getLogger(__name__) + + +# --------------------------------------------------------------------------- +# Dataset +# --------------------------------------------------------------------------- +class FELDataset(Dataset): + """Simple dataset wrapping pre-scaled input/output tensors.""" + + def __init__(self, X: Tensor, y: Tensor) -> None: + assert X.shape[0] == y.shape[0], "X and y must have the same number of samples" + self.X = X.float() + self.y = y.float() + + def __len__(self) -> int: + return self.X.shape[0] + + def __getitem__(self, idx: int) -> Tuple[Tensor, Tensor]: + return self.X[idx], self.y[idx] + + +# --------------------------------------------------------------------------- +# DataLoader helper +# --------------------------------------------------------------------------- +def make_loader( + ds: Dataset, + batch_size: int, + shuffle: bool, + num_workers: int = 4, + pin_memory: bool = True, + persistent_workers: bool = True, + prefetch_factor: int = 2, + sampler: Optional[Sampler] = None, +) -> DataLoader: + """Build a ``DataLoader`` from a ``Dataset``. + + Args: + ds: The base dataset. + batch_size: Batch size. + shuffle: Whether to shuffle. Ignored when *sampler* is given. + num_workers: Number of data-loading workers. + pin_memory: Pin CUDA memory for faster transfers. + persistent_workers: Keep worker processes alive between iterations. + prefetch_factor: Samples to prefetch per worker. + sampler: Optional sampler; mutually exclusive with ``shuffle``. When + provided, ``shuffle`` is not passed to the ``DataLoader``. + + Returns: + DataLoader built from *ds* with the given settings. + """ + kwargs: dict = dict(batch_size=batch_size, drop_last=False) + if sampler is not None: + kwargs["sampler"] = sampler + else: + kwargs["shuffle"] = shuffle + if num_workers > 0: + kwargs.update( + dict( + num_workers=num_workers, + pin_memory=pin_memory, + persistent_workers=persistent_workers, + prefetch_factor=prefetch_factor, + ) + ) + return DataLoader(ds, **kwargs) # type: ignore[arg-type] + + +# --------------------------------------------------------------------------- +# Feature-config helpers +# --------------------------------------------------------------------------- +def load_feature_config(data_path: str) -> Tuple[List[str], List[str]]: + """Read ``feature_config.yml`` and return ``(input_cols, output_cols)``. + + The YAML file is expected to have top-level keys ``input_variables`` and + ``output_variables``, each mapping variable names to metadata dicts. + """ + cfg_path = os.path.join(data_path, "feature_config.yml") + with open(cfg_path, "r") as fh: + yml = yaml.safe_load(fh) + input_cols = list(yml["input_variables"].keys()) + output_cols = list(yml["output_variables"].keys()) + return input_cols, output_cols + + +# --------------------------------------------------------------------------- +# Scaler helpers +# --------------------------------------------------------------------------- +def load_scalers( + data_path: str, device: str = "cpu" +) -> Tuple[torch.nn.Module, torch.nn.Module]: + """Load the saved BoTorch ``AffineInputTransform`` scalers. + + Tries the new naming convention (``input_scaler.pt``) first, then + falls back to the legacy names (``lcls_fel_input_scaler.pt``). + + Args: + data_path: Directory containing the scaler ``.pt`` files. + device: Device to map the scalers to. + + Returns: + Tuple of ``(input_scaler, output_scaler)``. + """ + # New names (train_fel_model.py v2) → legacy names (fallback) + input_candidates = ["input_scaler.pt", "lcls_fel_input_scaler.pt"] + output_candidates = ["output_scaler.pt", "lcls_fel_output_scaler.pt"] + + def _load_first(candidates: list[str]) -> torch.nn.Module: + for name in candidates: + path = os.path.join(data_path, name) + if os.path.exists(path): + return torch.load(path, map_location=device, weights_only=False) + raise FileNotFoundError(f"No scaler found in {data_path}; tried {candidates}") + + input_scaler = _load_first(input_candidates) + output_scaler = _load_first(output_candidates) + return input_scaler, output_scaler + + +# --------------------------------------------------------------------------- +# Data loading +# --------------------------------------------------------------------------- +def load_fel_data( + data_path: str, config_path: str, device: str = "cpu" +) -> Tuple[Tensor, Tensor, pd.Index]: + """Load a single ``data.pkl``, apply scalers, and return scaled tensors. + + Note that with the current workflow, prefer :func:`discover_window_files` + + :func:`load_window_file` for per-file lazy loading. + + Args: + data_path: Directory containing ``data.pkl``, scalers, and + ``feature_config.yml``. + config_path: Directory containing ``feature_config.yml`` and scaler files. + device: Device string (used for scaler loading only; tensors stay on + CPU here). + + Returns: + Tuple of ``(X_scaled, y_scaled, timestamps)``. + """ + df: pd.DataFrame = pd.read_pickle(os.path.join(data_path, "data.pkl")) + + # Ensure sorted by time + df = df.sort_index() + + input_cols, output_cols = load_feature_config(config_path) + input_scaler, output_scaler = load_scalers(config_path, device=device) + + # Drop rows with NaN in any input or output column + all_cols = input_cols + output_cols + n_before = len(df) + df = df.dropna(subset=all_cols) + n_dropped = n_before - len(df) + if n_dropped > 0: + pct = 100.0 * n_dropped / n_before + msg = ( + f"[load_fel_data] Dropped {n_dropped}/{n_before} rows " + f"({pct:.1f}%) containing NaN values" + ) + warnings.warn(msg, stacklevel=2) + _log.warning(msg) + + X_raw = torch.as_tensor(df[input_cols].values, dtype=torch.float32) + y_raw = torch.as_tensor(df[output_cols].values, dtype=torch.float32) + + # TODO: maybe import botorch scalers differently to avoid the type: ignore here + X_scaled: Tensor = input_scaler.transform(X_raw) # type: ignore[operator] + y_scaled: Tensor = output_scaler.transform(y_raw) # type: ignore[operator] + + return X_scaled, y_scaled, df.index + + +# --------------------------------------------------------------------------- +# Per-file window discovery & lazy loading +# --------------------------------------------------------------------------- + + +def _natural_sort_key(path: str) -> Tuple[str, int]: + """Sort key that orders ``data_1.pkl`` < ``data_2.pkl`` < ``data_10.pkl``. + + Falls back to lexicographic order if no numeric suffix is found. + """ + basename = os.path.basename(path) + m = re.search(r"(\d+)", basename) + if m: + return (basename[: m.start()], int(m.group(1))) + return (basename, 0) + + +def discover_window_files(data_path: str) -> List[str]: + """Return sorted paths to ``data_*.pkl`` files in *data_path*. + + Files are sorted by the numeric suffix so that ``data_1.pkl`` comes + before ``data_2.pkl`` and ``data_10.pkl``. + + Args: + data_path: Directory to search. + + Returns: + List of absolute paths, one per window file, sorted by numeric suffix. + """ + pattern = os.path.join(data_path, "data_*.pkl") + paths = glob.glob(pattern) + paths.sort(key=_natural_sort_key) + return paths + + +def load_window_file( + pkl_path: str, + input_cols: List[str], + output_cols: List[str], + input_scaler: torch.nn.Module, + output_scaler: torch.nn.Module, +) -> Tuple[Tensor, Tensor, pd.Index]: + """Load a single window pickle, scale, and return ``(X, y, index)`` tensors. + + Args: + pkl_path: Path to a single ``data_.pkl`` file. + input_cols: Column names for input features (from ``feature_config.yml``). + output_cols: Column names for output targets. + input_scaler: Pre-fitted scaler for inputs. + output_scaler: Pre-fitted scaler for outputs. + + Returns: + Tuple ``(X_scaled, y_scaled, index)`` where ``X_scaled`` is + ``[N, n_inputs]`` float32, ``y_scaled`` is ``[N, n_outputs]`` float32, + and ``index`` is the DataFrame index after NaN filtering. + """ + df: pd.DataFrame = pd.read_pickle(pkl_path) + df = df.sort_index() + + # Drop rows with NaN in any input or output column + all_cols = input_cols + output_cols + n_before = len(df) + df = df.dropna(subset=all_cols) + n_dropped = n_before - len(df) + if n_dropped > 0: + pct = 100.0 * n_dropped / n_before + basename = os.path.basename(pkl_path) + msg = ( + f"[load_window_file] {basename}: Dropped {n_dropped}/{n_before} rows " + f"({pct:.1f}%) containing NaN values" + ) + warnings.warn(msg, stacklevel=2) + _log.warning(msg) + + X_raw = torch.as_tensor(df[input_cols].values, dtype=torch.float32) + y_raw = torch.as_tensor(df[output_cols].values, dtype=torch.float32) + + X_scaled: Tensor = input_scaler.transform(X_raw) # type: ignore[operator] + y_scaled: Tensor = output_scaler.transform(y_raw) # type: ignore[operator] + + return X_scaled, y_scaled, df.index + + +def load_all_window_files( + data_path: str, + input_cols: List[str], + output_cols: List[str], + input_scaler: torch.nn.Module, + output_scaler: torch.nn.Module, +) -> Tuple[Tensor, Tensor, pd.Index]: + """Load all ``data_*.pkl`` files, concatenate, and return scaled tensors. + + Each pickle is loaded and scaled individually via :func:`load_window_file`, + then the results are concatenated into a single pair of tensors in + chronological order (files are sorted by numeric suffix). + + Args: + data_path: Directory containing ``data_*.pkl`` files. + input_cols: Column names for input features. + output_cols: Column names for output targets. + input_scaler: Pre-fitted scaler for inputs. + output_scaler: Pre-fitted scaler for outputs. + + Returns: + Tuple ``(X_all, y_all, timestamps)`` with all windows concatenated + along dim 0. ``timestamps`` is the combined DataFrame index + preserving the chronological order of every row. + + Raises: + FileNotFoundError: If no ``data_*.pkl`` files are found in *data_path*. + """ + window_files = discover_window_files(data_path) + if not window_files: + raise FileNotFoundError(f"No data_*.pkl files found in {data_path}") + + X_parts: List[Tensor] = [] + y_parts: List[Tensor] = [] + index_parts: List[pd.Index] = [] + total_samples = 0 + + for pkl_path in window_files: + X_w, y_w, idx = load_window_file( + pkl_path, input_cols, output_cols, input_scaler, output_scaler + ) + X_parts.append(X_w) + y_parts.append(y_w) + index_parts.append(idx) + total_samples += X_w.shape[0] + _log.info( + "[load_all_window_files] Loaded %s: %d samples", + os.path.basename(pkl_path), + X_w.shape[0], + ) + + X_all = torch.cat(X_parts, dim=0) + y_all = torch.cat(y_parts, dim=0) + timestamps = index_parts[0].append(index_parts[1:]) + + _log.info( + "[load_all_window_files] Combined %d files → %d total samples", + len(window_files), + total_samples, + ) + + return X_all, y_all, timestamps + + +# --------------------------------------------------------------------------- +# Windowing +# --------------------------------------------------------------------------- + +# Default number of samples per time window. Can be overridden by the caller. +DEFAULT_WINDOW_SIZE: int = 5000 + + +def split_into_windows( + X: Tensor, + y: Tensor, + window_size: int = DEFAULT_WINDOW_SIZE, + min_window_size: int = 2, +) -> List[Tuple[Tensor, Tensor]]: + """Split chronologically-ordered tensors into non-overlapping windows. + + If the final chunk has fewer than *min_window_size* samples it is merged + into the preceding window so that every window is large enough for a + meaningful train/val split. + + Args: + X: Input features ``[N, D]``. + y: Targets ``[N, T]``. + window_size: Number of samples per window. + min_window_size: Minimum samples in a window. A trailing chunk + smaller than this is merged into the previous window. + + Returns: + List of ``(X_chunk, y_chunk)`` tuples. + """ + n = X.shape[0] + windows: List[Tuple[Tensor, Tensor]] = [] + for start in range(0, n, window_size): + end = min(start + window_size, n) + windows.append((X[start:end], y[start:end])) + + # Merge a too-small trailing window into the previous one + if len(windows) > 1 and windows[-1][0].shape[0] < min_window_size: + prev_X, prev_y = windows[-2] + tail_X, tail_y = windows[-1] + windows[-2] = ( + torch.cat([prev_X, tail_X], dim=0), + torch.cat([prev_y, tail_y], dim=0), + ) + windows.pop() + + return windows + + +def split_timestamps( + timestamps: pd.Index, + window_size: int = DEFAULT_WINDOW_SIZE, + min_window_size: int = 2, +) -> List[pd.Index]: + """Split a timestamp index to match :func:`split_into_windows`. + + Applies the same chunking and merging logic so that + ``split_timestamps(ts, ws)[i]`` aligns row-for-row with + ``split_into_windows(X, y, ws)[i]``. + + Args: + timestamps: Row-aligned index (same length as the tensors). + window_size: Number of samples per window. + min_window_size: Merge trailing chunk if smaller than this. + + Returns: + List of ``pd.Index`` slices, one per window. + """ + n = len(timestamps) + chunks: List[pd.Index] = [] + for start in range(0, n, window_size): + end = min(start + window_size, n) + chunks.append(timestamps[start:end]) + + if len(chunks) > 1 and len(chunks[-1]) < min_window_size: + chunks[-2] = chunks[-2].append(chunks[-1]) + chunks.pop() + + return chunks diff --git a/examples/utils.py b/examples/utils.py index 0cde7b7..213af54 100644 --- a/examples/utils.py +++ b/examples/utils.py @@ -15,6 +15,10 @@ def get_example(cfg: Config) -> BaseModelHarness: from examples.imagenet.model import IMAGENET_VISION return IMAGENET_VISION(cfg=cfg) + elif cfg.data.name == "slac-fel": + from examples.slac_fel.model import SLAC_FEL + + return SLAC_FEL(cfg=cfg) else: raise NotImplementedError( f"Example for dataset {cfg.data.name} is not implemented." diff --git a/poetry.lock b/poetry.lock index f89f9e5..fbf2819 100644 --- a/poetry.lock +++ b/poetry.lock @@ -318,6 +318,36 @@ files = [ {file = "blinker-1.9.0.tar.gz", hash = "sha256:b4ce2265a7abece45e7cc896e98dbebe6cead56bcf805a3d23136d145f5445bf"}, ] +[[package]] +name = "botorch" +version = "0.18.1" +description = "Bayesian Optimization in PyTorch" +optional = false +python-versions = ">=3.11" +groups = ["main"] +files = [ + {file = "botorch-0.18.1-py3-none-any.whl", hash = "sha256:fa1cd4483fbc21087dcc40088b6031661e46ce5fe9d0b47a56ebcd578c260f33"}, + {file = "botorch-0.18.1.tar.gz", hash = "sha256:f3e444efae2622b3ad88a5efe1859583ba2cd0913761f76677a189b2fd1aee99"}, +] + +[package.dependencies] +gpytorch = ">=1.15.2" +linear_operator = ">=0.6.1" +multipledispatch = "*" +ninja = "*" +pyre_extensions = "*" +scipy = "*" +threadpoolctl = "*" +torch = ">=2.4" +typing_extensions = "*" + +[package.extras] +dev = ["botorch[test]", "flake8", 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