diff --git a/Python/pokedex_ResNet50.py b/Python/pokedex_ResNet50.py
index 80160bc0c7d1903db4b99b96e1df20b3aa394d86..57240386a7cbebc0be2feddffd6b7e94d4baa610 100644
--- a/Python/pokedex_ResNet50.py
+++ b/Python/pokedex_ResNet50.py
@@ -9,16 +9,25 @@ from sklearn.utils.class_weight import compute_class_weight
import numpy as np
import json
import os
+import argparse
# --- GPU Strategy ---
strategy = tf.distribute.MirroredStrategy()
print("Number of GPUs:", strategy.num_replicas_in_sync)
# --- Paths ---
-dataset_path = "/home/padi/Git/pokedex/Combined_Dataset"
-model_output_path = "/home/padi/Git/pokedex/models/ResNet50"
-#dataset_path = "/home/users/d/divia/scratch/Combined_Dataset"
-#model_output_path = "/home/users/d/divia/pokedex/models/ResNet50"
+parser = argparse.ArgumentParser(description="WHERE ?!")
+parser.add_argument("--hpc", choices=["yes", "no"], default="no",
+ help="Use HPC paths if 'yes', otherwise local paths.")
+args = parser.parse_args()
+
+if args.hpc == "yes":
+ dataset_path = "/home/users/d/divia/scratch/Combined_Dataset"
+ model_output_path = "/home/users/d/divia/pokedex/models/ResNet50"
+else:
+ dataset_path = "/home/padi/Git/pokedex/Combined_Dataset"
+ model_output_path = "/home/padi/Git/pokedex/models/ResNet50"
+
os.makedirs(model_output_path, exist_ok=True)
# --- Image settings ---
diff --git a/Python/pokedex_xception.py b/Python/pokedex_xception.py
deleted file mode 100644
index 8584135740b475299f44b6d92427dd2090b321ef..0000000000000000000000000000000000000000
--- a/Python/pokedex_xception.py
+++ /dev/null
@@ -1,136 +0,0 @@
-import tensorflow as tf
-from tensorflow.keras import layers, models, Input
-from tensorflow.keras.callbacks import EarlyStopping
-from tensorflow.keras.preprocessing import image_dataset_from_directory
-from sklearn.utils.class_weight import compute_class_weight
-import numpy as np
-import json
-import os
-
-# --- GPU Strategy ---
-strategy = tf.distribute.MirroredStrategy()
-print("Number of GPUs:", strategy.num_replicas_in_sync)
-
-# --- Paths ---
-dataset_path = "/home/padi/Git/pokedex/Combined_Dataset"
-model_output_path = "/home/padi/Git/pokedex/models/Xception"
-#dataset_path = "/home/users/d/divia/scratch/Combined_Dataset"
-#model_output_path = "/home/users/d/divia/pokedex/models7Xception"
-os.makedirs(model_output_path, exist_ok=True)
-
-# --- Custom Xception-like model ---
-def simple_xception(input_shape, num_classes):
- inputs = Input(shape=input_shape)
-
- x = layers.Rescaling(1.0 / 255)(inputs)
- x = layers.Conv2D(128, 3, strides=2, padding="same")(x)
- x = layers.BatchNormalization()(x)
- x = layers.Activation("relu")(x)
-
- previous_block_activation = x
-
- for size in [256, 512, 728]:
- x = layers.Activation("relu")(x)
- x = layers.SeparableConv2D(size, 3, padding="same")(x)
- x = layers.BatchNormalization()(x)
-
- x = layers.Activation("relu")(x)
- x = layers.SeparableConv2D(size, 3, padding="same")(x)
- x = layers.BatchNormalization()(x)
-
- x = layers.MaxPooling2D(3, strides=2, padding="same")(x)
- residual = layers.Conv2D(size, 1, strides=2, padding="same")(previous_block_activation)
- x = layers.add([x, residual])
- previous_block_activation = x
-
- x = layers.SeparableConv2D(1024, 3, padding="same")(x)
- x = layers.BatchNormalization()(x)
- x = layers.Activation("relu")(x)
-
- x = layers.GlobalAveragePooling2D()(x)
- x = layers.Dropout(0.25)(x)
- outputs = layers.Dense(num_classes, activation='softmax')(x)
-
- return models.Model(inputs, outputs)
-
-# --- Image settings ---
-img_size = (256, 256)
-batch_size = 32
-
-# --- Data Augmentation ---
-data_augmentation = tf.keras.Sequential([
- layers.RandomFlip("horizontal"),
- layers.RandomRotation(0.1),
- layers.RandomZoom(0.1),
- layers.RandomContrast(0.1),
-])
-
-# --- Load datasets ---
-raw_train_ds = image_dataset_from_directory(
- dataset_path,
- image_size=img_size,
- batch_size=batch_size,
- validation_split=0.2,
- subset="training",
- seed=123,
-)
-
-raw_val_ds = image_dataset_from_directory(
- dataset_path,
- image_size=img_size,
- batch_size=batch_size,
- validation_split=0.2,
- subset="validation",
- seed=123,
-)
-
-# Save class names
-class_names = raw_train_ds.class_names
-with open(os.path.join(model_output_path, "class_names.json"), "w") as f:
- json.dump(class_names, f)
-print(f"Detected {len(class_names)} Pokémon classes.")
-
-# --- Compute class weights ---
-print("Computing class weights...")
-all_labels = [label.numpy() for _, label in raw_train_ds.unbatch()]
-class_weights = compute_class_weight(
- class_weight="balanced",
- classes=np.unique(all_labels),
- y=np.array(all_labels)
-)
-class_weight_dict = dict(enumerate(class_weights))
-print("Class weights ready.")
-
-# --- Performance improvements ---
-AUTOTUNE = tf.data.AUTOTUNE
-train_ds = raw_train_ds.map(lambda x, y: (data_augmentation(x), y)).prefetch(AUTOTUNE)
-val_ds = raw_val_ds.prefetch(buffer_size=AUTOTUNE)
-
-# --- Build and compile model ---
-with strategy.scope():
- model = simple_xception((*img_size, 3), num_classes=len(class_names))
- model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])
-
-# --- Callbacks ---
-callbacks = [
- EarlyStopping(monitor='val_loss', patience=3, restore_best_weights=True)
-]
-
-# --- Train the model ---
-model.fit(
- train_ds,
- validation_data=val_ds,
- epochs=20,
- callbacks=callbacks,
- class_weight=class_weight_dict
-)
-
-# --- Save the model ---
-model_h5_path = os.path.join(model_output_path, "pokemon_xception.h5")
-model.save(model_h5_path)
-print(f"Model saved to {model_h5_path}")
-
-# --- Save as TensorFlow SavedModel ---
-saved_model_path = os.path.join(model_output_path, "saved_model")
-tf.saved_model.save(model, saved_model_path)
-print(f"SavedModel exported to {saved_model_path}")
diff --git a/slurm/train_ResNet50.sh b/slurm/train_ResNet50.sh
index bc5f0a07b5df47a771fce34021c57b5d09b4c053..db868da4750f093a0a3bfee4f465e7743425e16c 100644
--- a/slurm/train_ResNet50.sh
+++ b/slurm/train_ResNet50.sh
@@ -15,4 +15,4 @@ module load cuDNN/8.4.1.50-CUDA-11.7.0
module load scikit-learn/1.1.2
# Run your script
-srun python ../Python/pokedex_ResNet50.py
+srun python ../Python/pokedex_ResNet50.py --hpc yes
diff --git a/slurm/train_Xception.sh b/slurm/train_Xception.sh
new file mode 100644
index 0000000000000000000000000000000000000000..bd6e73801f13b0109f013ada8ee5f5aa6ac04b00
--- /dev/null
+++ b/slurm/train_Xception.sh
@@ -0,0 +1,18 @@
+#!/bin/sh
+#SBATCH --job-name=ResNet50
+#SBATCH --output=ResNet50_%j.out
+#SBATCH --partition=shared-gpu
+#SBATCH --gres=gpu:1,VramPerGpu:80G
+#SBATCH --cpus-per-task=2
+#SBATCH --mem=16G
+#SBATCH --time=05:00:00
+#SBATCH --mail-type=FAIL
+
+# Load modules
+module purge
+module load GCC/11.3.0 OpenMPI/4.1.4 TensorFlow/2.11.0-CUDA-11.7.0
+module load cuDNN/8.4.1.50-CUDA-11.7.0
+module load scikit-learn/1.1.2
+
+# Run your script
+srun python ../Python/pokedex_Xception.py --hpc yes