From 70aa3e905df053a7e1053369078ba41aec159c30 Mon Sep 17 00:00:00 2001 From: Israel Figueroa Date: Tue, 18 Mar 2025 22:37:06 -0300 Subject: [PATCH] v1 --- TrainerClass.py | 30 +++++++++++++++++------------- 1 file changed, 17 insertions(+), 13 deletions(-) diff --git a/TrainerClass.py b/TrainerClass.py index 6f5d054..4f795fd 100644 --- a/TrainerClass.py +++ b/TrainerClass.py @@ -44,7 +44,7 @@ def get_seed(): class eNoseTrainer: def __init__(self, loader, test_size=0.2, debug=False): - self.ledger = pd.DataFrame(columns=["node", "ts", "Dataset", "Samples", "Target", "Train Size", "Train Ratio", "Model", "Params", "Ratio", "Train mse", "mse", "mae", "rmse"]) + self.ledger = pd.DataFrame(columns=["node", "ts", "Dataset", "Samples", "Target", "Train Size", "Train Ratio", "Model", "Params", "Ratio", "Train mse", "mse", "mae", "rmse", "num_params"]) self.loader = loader self.name = self.loader.label_file self.state = dict() @@ -179,8 +179,8 @@ class eNoseTrainer: Y_pred = model.predict(X_test) mse = mean_squared_error(Y_test, Y_pred) - num_params = model.count_params() # Get number of weights in the model - trial.set_user_attr("num_params", num_params) # Store it in the trial object +# num_params = model.count_params() # Get number of weights in the model +# trial.set_user_attr("num_params", num_params) # Store it in the trial object return mse @@ -371,7 +371,8 @@ class eNoseTrainer: "Train mse": tmse, "mse": mse, "mae": mae, - "rmse": rmse + "rmse": rmse, + "num_params": sum(t.count("\n") for t in optimized_model.get_booster().get_dump()) }] ) self.ledger = pd.concat([self.ledger, newrow], ignore_index=True) self.bar.update() @@ -428,7 +429,8 @@ class eNoseTrainer: "Train mse": tmse, "mse": mse, "mae": mae, - "rmse": rmse + "rmse": rmse, + "num_params": sum(t.count("\n") for t in optimized_model.get_booster().get_dump()) }] ) self.ledger = pd.concat([self.ledger, newrow], ignore_index=True) self.bar.update() @@ -481,7 +483,7 @@ class eNoseTrainer: for trial in study.trials: trial_info = trial.params.copy() trial_info['mse'] = trial.value - trial_info['num_params'] = trial.user_attrs.get("num_params", 0) +# trial_info['num_params'] = trial.user_attrs.get("num_params", 0) trials_data.append(trial_info) df = pd.DataFrame(trials_data) @@ -508,17 +510,18 @@ class eNoseTrainer: newrow = pd.DataFrame( [{"node": node, "ts": ts, "Dataset": dataset, - "Samples": Y_xboost.shape[0], + "Samples": Y_conv1d.shape[0], "Target": self.loader.target, "Train Size": Y_train.shape[0], - "Train Ratio": Y_train.shape[0]/Y_xboost.shape[0], + "Train Ratio": Y_train.shape[0]/Y_conv1d.shape[0], "Ratio": self.ratio, "Model": model_id, "Params": json.dumps(study.best_params), "Train mse": mse_train, "mse": mse_test, "mae": mae_test, - "rmse": rmse_test + "rmse": rmse_test, + "num_params": best_model.count_params() }] ) self.ledger = pd.concat([self.ledger, newrow], ignore_index=True) self.bar.update() @@ -572,7 +575,7 @@ class eNoseTrainer: for trial in study.trials: trial_info = trial.params.copy() trial_info['mse'] = trial.value - trial_info['num_params'] = trial.user_attrs.get("num_params", 0) +# trial_info['num_params'] = trial.user_attrs.get("num_params", 0) trials_data.append(trial_info) df = pd.DataFrame(trials_data) @@ -599,17 +602,18 @@ class eNoseTrainer: newrow = pd.DataFrame( [{"node": node, "ts": ts, "Dataset": dataset, - "Samples": Y_xboost.shape[0], + "Samples": Y_conv1d.shape[0], "Target": self.loader.target, "Train Size": Y_train.shape[0], - "Train Ratio": Y_train.shape[0]/Y_xboost.shape[0], + "Train Ratio": Y_train.shape[0]/Y_conv1d.shape[0], "Ratio": self.ratio, "Model": model_id, "Params": json.dumps(study.best_params), "Train mse": mse_train, "mse": mse_test, "mae": mae_test, - "rmse": rmse_test + "rmse": rmse_test, + "num_params": best_model.count_params() }] ) self.ledger = pd.concat([self.ledger, newrow], ignore_index=True)