diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index d07ccd9..d07ffae 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -10,7 +10,7 @@ repos: - id: check-added-large-files - repo: https://github.com/astral-sh/ruff-pre-commit # Ruff version. - rev: 'v0.11.6' + rev: 'v0.11.13' hooks: - id: ruff args: [--fix, --exit-non-zero-on-fix] diff --git a/explain.py b/explain.py index 3579282..af7b0eb 100644 --- a/explain.py +++ b/explain.py @@ -46,7 +46,9 @@ def update_sample(samples, N, sample): ) # Load the trained model -model = tf.keras.models.load_model(os.path.join(args.input_dir, "nn_model_sherlock.keras")) +model = tf.keras.models.load_model( + os.path.join(args.input_dir, "nn_model_sherlock.keras") +) # Produce a randomly sample of background from the training data background = [] diff --git a/train.py b/train.py index a6856f7..ca89da7 100644 --- a/train.py +++ b/train.py @@ -51,31 +51,31 @@ regex_model1 = BatchNormalization(axis=1)(regex_model_input) regex_model2 = Dense( 1000, - activation='relu', + activation="relu", kernel_regularizer=tf.keras.regularizers.l2(0.0001), )(regex_model1) regex_model3 = Dropout(0.35)(regex_model2) regex_model4 = Dense( 1000, - activation='relu', + activation="relu", kernel_regularizer=tf.keras.regularizers.l2(0.0001), )(regex_model3) merged_model2 = BatchNormalization(axis=1)(regex_model4) merged_model3 = Dense( 500, - activation='relu', + activation="relu", kernel_regularizer=tf.keras.regularizers.l2(0.0001), )(merged_model2) merged_model4 = Dropout(0.35)(merged_model3) merged_model5 = Dense( 500, - activation='relu', + activation="relu", kernel_regularizer=tf.keras.regularizers.l2(0.0001), )(merged_model4) merged_model_output = Dense( len(le.classes_), - activation='softmax', + activation="softmax", kernel_regularizer=tf.keras.regularizers.l2(0.0001), )(merged_model5)