TensorFlow GPU Bellek Hatası: Çözümler ve Kodlar

1import tensorflow as tf
2
3# GPU bellek büyümesini aç
4gpus = tf.config.list_physical_devices('GPU')
5for gpu in gpus:
6tf.config.experimental.set_memory_growth(gpu, True)
7
8print(f"GPU bulundu: {len(gpus)}")

1import tensorflow as tf
2from tensorflow import keras
3
4# Bellek büyümesini etkinleştir
5gpus = tf.config.list_physical_devices('GPU')
6for gpu in gpus:
7tf.config.experimental.set_memory_growth(gpu, True)
8
9# Veri seti
10(x_train, y_train), _ = keras.datasets.cifar10.load_data()
11
12# Batch size'ı küçük tut
13batch_size = 32 # 64 yerine 32
14
15model = keras.Sequential([
16keras.layers.Conv2D(32, 3, activation='relu', input_shape=(32, 32, 3)),
17keras.layers.MaxPooling2D(),
18keras.layers.Flatten(),
19keras.layers.Dense(10, activation='softmax')
20])
21
22model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])
23model.fit(x_train, y_train, batch_size=batch_size, epochs=2)

1import tensorflow as tf
2from tensorflow import keras
3
4# GPU ayarları
5gpus = tf.config.list_physical_devices('GPU')
6for gpu in gpus:
7tf.config.experimental.set_memory_growth(gpu, True)
8
9# Mixed precision policy
10policy = keras.mixed_precision.Policy('mixed_float16')
11keras.mixed_precision.set_global_policy(policy)
12
13# Model (son katman float32 olmalı)
14model = keras.Sequential([
15keras.layers.Dense(256, activation='relu', input_shape=(784,)),
16keras.layers.Dense(128, activation='relu'),
17keras.layers.Dense(10, dtype='float32', activation='softmax')
18])
19
20model.compile(optimizer='adam', loss='sparse_categorical_crossentropy')
21print(f"Compute dtype: {policy.compute_dtype}")
22print(f"Variable dtype: {policy.variable_dtype}")