From 4863b9112705e2f9af3b0d3fbd59b5d0a3e900fa Mon Sep 17 00:00:00 2001 From: Jan Kowalczyk Date: Tue, 1 Jul 2025 17:22:29 +0200 Subject: [PATCH] retest implemented and fixed missing center in save data --- Deep-SAD-PyTorch/flake.lock | 192 ------ Deep-SAD-PyTorch/flake.nix | 83 --- Deep-SAD-PyTorch/poetry.lock | 1002 ------------------------------- Deep-SAD-PyTorch/pyproject.toml | 53 +- Deep-SAD-PyTorch/src/DeepSAD.py | 4 +- Deep-SAD-PyTorch/src/main.py | 162 ++++- 6 files changed, 189 insertions(+), 1307 deletions(-) delete mode 100644 Deep-SAD-PyTorch/flake.lock delete mode 100644 Deep-SAD-PyTorch/flake.nix delete mode 100644 Deep-SAD-PyTorch/poetry.lock diff --git a/Deep-SAD-PyTorch/flake.lock b/Deep-SAD-PyTorch/flake.lock deleted file mode 100644 index 238325f..0000000 --- a/Deep-SAD-PyTorch/flake.lock +++ /dev/null @@ -1,192 +0,0 @@ -{ - "nodes": { - "flake-utils": { - "inputs": { - "systems": "systems" - }, - "locked": { - "lastModified": 1710146030, - "narHash": "sha256-SZ5L6eA7HJ/nmkzGG7/ISclqe6oZdOZTNoesiInkXPQ=", - "owner": "numtide", - "repo": "flake-utils", - "rev": "b1d9ab70662946ef0850d488da1c9019f3a9752a", - "type": "github" - }, - "original": { - "owner": "numtide", - "repo": "flake-utils", - "type": "github" - } - }, - "flake-utils_2": { - "inputs": { - "systems": "systems_2" - }, - "locked": { - "lastModified": 1710146030, - "narHash": "sha256-SZ5L6eA7HJ/nmkzGG7/ISclqe6oZdOZTNoesiInkXPQ=", - "owner": "numtide", - "repo": "flake-utils", - "rev": "b1d9ab70662946ef0850d488da1c9019f3a9752a", - "type": "github" - }, - "original": { - "owner": "numtide", - "repo": "flake-utils", - "type": "github" - } - }, - "nix-github-actions": { - "inputs": { - "nixpkgs": [ - "poetry2nix", - "nixpkgs" - ] - }, - "locked": { - "lastModified": 1703863825, - "narHash": "sha256-rXwqjtwiGKJheXB43ybM8NwWB8rO2dSRrEqes0S7F5Y=", - "owner": "nix-community", - "repo": "nix-github-actions", - "rev": "5163432afc817cf8bd1f031418d1869e4c9d5547", - "type": "github" - }, - "original": { - "owner": "nix-community", - "repo": "nix-github-actions", - "type": "github" - } - }, - "nixpkgs": { - "locked": { - "lastModified": 1719327525, - "narHash": "sha256-fPWiFM4aYbK9zGTt3KJ9CwX//iyElRiNHWNj2hk3i0E=", - "owner": "NixOS", - "repo": "nixpkgs", - "rev": "191a3fd9786d09c8d82e89ed68c4463e7be09b3e", - "type": "github" - }, - "original": { - "owner": "NixOS", - "ref": "nixos-unstable-small", - "repo": "nixpkgs", - "type": "github" - } - }, - "nixpkgs-newest": { - "locked": { - "lastModified": 1749285348, - "narHash": "sha256-frdhQvPbmDYaScPFiCnfdh3B/Vh81Uuoo0w5TkWmmjU=", - "owner": "NixOS", - "repo": "nixpkgs", - "rev": "3e3afe5174c561dee0df6f2c2b2236990146329f", - "type": "github" - }, - "original": { - "owner": "NixOS", - "ref": "nixos-unstable", - "repo": "nixpkgs", - "type": "github" - } - }, - "poetry2nix": { - "inputs": { - "flake-utils": "flake-utils_2", - "nix-github-actions": "nix-github-actions", - "nixpkgs": [ - "nixpkgs" - ], - "systems": "systems_3", - "treefmt-nix": "treefmt-nix" - }, - "locked": { - "lastModified": 1719358925, - "narHash": "sha256-ZV/2YB7nyeYCsDm6EMH0EKtlpxuu2ImEd5WrlceNwRE=", - "owner": "nix-community", - "repo": "poetry2nix", - "rev": "bbc1ee74fc1ac4082f617bf32f1c927e759717d2", - "type": "github" - }, - "original": { - "owner": "nix-community", - "repo": "poetry2nix", - "type": "github" - } - }, - "root": { - "inputs": { - "flake-utils": "flake-utils", - "nixpkgs": "nixpkgs", - "nixpkgs-newest": "nixpkgs-newest", - "poetry2nix": "poetry2nix" - } - }, - "systems": { - "locked": { - "lastModified": 1681028828, - "narHash": "sha256-Vy1rq5AaRuLzOxct8nz4T6wlgyUR7zLU309k9mBC768=", - "owner": "nix-systems", - "repo": "default", - "rev": "da67096a3b9bf56a91d16901293e51ba5b49a27e", - "type": "github" - }, - "original": { - "owner": "nix-systems", - "repo": "default", - "type": "github" - } - }, - "systems_2": { - "locked": { - "lastModified": 1681028828, - "narHash": "sha256-Vy1rq5AaRuLzOxct8nz4T6wlgyUR7zLU309k9mBC768=", - "owner": "nix-systems", - "repo": "default", - "rev": "da67096a3b9bf56a91d16901293e51ba5b49a27e", - 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description = "Deepsad devenv with python 3.11"; - - inputs = { - flake-utils.url = "github:numtide/flake-utils"; - nixpkgs.url = "github:NixOS/nixpkgs/nixos-unstable-small"; - # Added newest nixpkgs for an updated poetry package. - nixpkgs-newest.url = "github:NixOS/nixpkgs/nixos-unstable"; - poetry2nix = { - url = "github:nix-community/poetry2nix"; - inputs.nixpkgs.follows = "nixpkgs"; - }; - }; - - outputs = - { - self, - nixpkgs, - nixpkgs-newest, - flake-utils, - poetry2nix, - }: - flake-utils.lib.eachDefaultSystem ( - system: - let - # see https://github.com/nix-community/poetry2nix/tree/master#api for more functions and examples. - pkgs = import nixpkgs { - inherit system; - config.allowUnfree = true; - config.cudaSupport = true; - }; - pkgsNew = nixpkgs-newest.legacyPackages.${system}; - thundersvm = import ./nix/thundersvm.nix { - inherit pkgs; - inherit (pkgs) fetchFromGitHub cmake gcc12Stdenv; - cudaPackages = pkgs.cudaPackages; - }; - - thundersvm-python = import ./nix/thundersvm-python.nix { - inherit pkgs; - pythonPackages = pkgs.python311Packages; - thundersvm = thundersvm; - }; - inherit (poetry2nix.lib.mkPoetry2Nix { inherit pkgs; }) mkPoetryApplication defaultPoetryOverrides; - in - { - packages = { - deepsad = mkPoetryApplication { - projectDir = self; - preferWheels = true; - python = pkgs.python311; - overrides = defaultPoetryOverrides.extend ( - final: prev: { - torch-receptive-field = prev.torch-receptive-field.overridePythonAttrs (old: { - buildInputs = (old.buildInputs or [ ]) ++ [ prev.setuptools ]; - }); - } - ); - }; - default = self.packages.${system}.deepsad; - }; - - devShells.default = pkgs.mkShell { - inputsFrom = [ self.packages.${system}.deepsad ]; - buildInputs = with pkgs.python311Packages; [ - torch-bin - torchvision-bin - thundersvm-python - ]; - #LD_LIBRARY_PATH = with pkgs; lib.makeLibraryPath [ - #pkgs.stdenv.cc.cc - #]; - }; - - devShells.poetry = pkgs.mkShell { - packages = [ - pkgsNew.poetry - pkgs.python311 - ]; - }; - } - ); -} diff --git a/Deep-SAD-PyTorch/poetry.lock b/Deep-SAD-PyTorch/poetry.lock deleted file mode 100644 index f1af788..0000000 --- a/Deep-SAD-PyTorch/poetry.lock +++ /dev/null @@ -1,1002 +0,0 @@ -# This file is automatically @generated by Poetry 2.1.3 and should not be changed by hand. - 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- -[build-system] -requires = ["poetry-core"] -build-backend = "poetry.core.masonry.api" +[tool.uv.sources] +torch-receptive-field = { git = "https://github.com/Fangyh09/pytorch-receptive-field.git" } diff --git a/Deep-SAD-PyTorch/src/DeepSAD.py b/Deep-SAD-PyTorch/src/DeepSAD.py index 4b71d0c..f87ebd7 100644 --- a/Deep-SAD-PyTorch/src/DeepSAD.py +++ b/Deep-SAD-PyTorch/src/DeepSAD.py @@ -126,6 +126,8 @@ class DeepSAD(object): ) # Get the model self.net = self.trainer.train(dataset, self.net, k_fold_idx=k_fold_idx) + + self.c = self.trainer.c.cpu().data.numpy().tolist() # get as list # Store training results including indices self.results["train"]["time"] = self.trainer.train_time self.results["train"]["indices"] = self.trainer.train_indices @@ -333,7 +335,7 @@ class DeepSAD(object): # load autoencoder parameters if specified if load_ae: if self.ae_net is None: - self.ae_net = build_autoencoder(self.net_name) + self.ae_net = build_autoencoder(self.net_name, self.rep_dim) self.ae_net.load_state_dict(model_dict["ae_net_dict"]) def save_results(self, export_pkl): diff --git a/Deep-SAD-PyTorch/src/main.py b/Deep-SAD-PyTorch/src/main.py index 2f48168..4d09886 100644 --- a/Deep-SAD-PyTorch/src/main.py +++ b/Deep-SAD-PyTorch/src/main.py @@ -25,7 +25,8 @@ from utils.visualization.plot_images_grid import plot_images_grid [ "train", "infer", - "ae_elbow_test", # Add new action + "ae_elbow_test", + "retest", ] ), ) @@ -773,6 +774,165 @@ def main( ) else: logger.error(f"Unknown action: {action}") + elif action == "retest": + if ( + not load_model + or not Path(load_model).exists() + or not Path(load_model).is_dir() + ): + logger.error( + "For retest mode a model directory has to be loaded! Pass the --load_model option with the model directory path!" + ) + return + load_model = Path(load_model) + if not load_config: + logger.error( + "For retest mode a config has to be loaded! Pass the --load_config option with the config path!" + ) + return + + dataset = load_dataset( + cfg.settings["dataset_name"], + data_path, + cfg.settings["normal_class"], + cfg.settings["known_outlier_class"], + cfg.settings["n_known_outlier_classes"], + cfg.settings["ratio_known_normal"], + cfg.settings["ratio_known_outlier"], + cfg.settings["ratio_pollution"], + random_state=np.random.RandomState(cfg.settings["seed"]), + k_fold_num=cfg.settings["k_fold_num"], + num_known_normal=cfg.settings["num_known_normal"], + num_known_outlier=cfg.settings["num_known_outlier"], + ) + + train_passes = ( + range(cfg.settings["k_fold_num"]) if cfg.settings["k_fold"] else [None] + ) + + retest_isoforest = True + retest_ocsvm = True + retest_deepsad = True + + for fold_idx in train_passes: + if fold_idx is None: + logger.info("Single train re-testing without k-fold") + deepsad_model_path = load_model / "model_deepsad.tar" + isoforest_model_path = load_model / "model_ocsvm.pkl" + ocsvm_model_path = load_model / "model_isoforest.pkl" + ae_model_path = load_model / "model_ae.tar" + else: + logger.info(f"Fold {fold_idx + 1}/{cfg.settings['k_fold_num']}") + + deepsad_model_path = load_model / f"model_deepsad_{fold_idx}.tar" + isoforest_model_path = load_model / f"model_isoforest_{fold_idx}.pkl" + ocsvm_model_path = load_model / f"model_ocsvm_{fold_idx}.pkl" + ae_model_path = load_model / f"model_ae_{fold_idx}.tar" + + # Check which model files exist and which do not + model_paths = [ + deepsad_model_path, + isoforest_model_path, + ocsvm_model_path, + ae_model_path, + ] + missing_models = [ + path.name + for path in model_paths + if not path.exists() or not path.is_file() + ] + if missing_models: + logger.error( + f"The following model files do not exist: {', '.join(missing_models)}. Please check the load_model path." + ) + return + + # Initialize Isolation Forest model + if retest_isoforest: + Isoforest = IsoForest( + hybrid=False, + n_estimators=cfg.settings["isoforest_n_estimators"], + max_samples=cfg.settings["isoforest_max_samples"], + contamination=cfg.settings["isoforest_contamination"], + n_jobs=cfg.settings["isoforest_n_jobs_model"], + seed=cfg.settings["seed"], + ) + Isoforest.load_model(import_path=isoforest_model_path, device=device) + Isoforest.test( + dataset, + device=device, + n_jobs_dataloader=cfg.settings["n_jobs_dataloader"], + k_fold_idx=fold_idx, + ) + + # Initialize DeepSAD model and set neural network phi + if retest_deepsad: + deepSAD = DeepSAD(cfg.settings["latent_space_dim"], cfg.settings["eta"]) + deepSAD.set_network(cfg.settings["net_name"]) + deepSAD.load_model( + model_path=deepsad_model_path, load_ae=True, map_location=device + ) + logger.info("Loading model from %s." % load_model) + deepSAD.test( + dataset, + device=device, + n_jobs_dataloader=cfg.settings["n_jobs_dataloader"], + k_fold_idx=fold_idx, + ) + + if retest_ocsvm: + ocsvm = OCSVM( + kernel=cfg.settings["ocsvm_kernel"], + nu=cfg.settings["ocsvm_nu"], + hybrid=True, + latent_space_dim=cfg.settings["latent_space_dim"], + ) + ocsvm.load_ae( + net_name=cfg.settings["net_name"], + model_path=ae_model_path, + device=device, + ) + ocsvm.load_model(import_path=ocsvm_model_path) + ocsvm.test( + dataset, + device=device, + n_jobs_dataloader=cfg.settings["n_jobs_dataloader"], + k_fold_idx=fold_idx, + batch_size=256, + ) + + retest_output_path = load_model / "retest_output" + retest_output_path.mkdir(parents=True, exist_ok=True) + + # Save results, model, and configuration + if fold_idx is None: + if retest_deepsad: + deepSAD.save_results( + export_pkl=retest_output_path / "results_deepsad.pkl" + ) + if retest_ocsvm: + ocsvm.save_results( + export_pkl=retest_output_path / "results_ocsvm.pkl" + ) + if retest_isoforest: + Isoforest.save_results( + export_pkl=retest_output_path / "results_isoforest.pkl" + ) + else: + if retest_deepsad: + deepSAD.save_results( + export_pkl=retest_output_path + / f"results_deepsad_{fold_idx}.pkl" + ) + if retest_ocsvm: + ocsvm.save_results( + export_pkl=retest_output_path / f"/results_ocsvm_{fold_idx}.pkl" + ) + if retest_isoforest: + Isoforest.save_results( + export_pkl=retest_output_path + / f"/results_isoforest_{fold_idx}.pkl" + ) if __name__ == "__main__":