I have windows 11 installed and using tensorflow 2.12 on wsl.
CUDA Version: 11.8 is installed
I can train deep neural networks successfully with my GPU. However, when I try to use CNN network, system crashes. As an example; I can train mnist database with below code
import tensorflow as tf
from tensorflow import keras
mnist = keras.datasets.mnist
(train_images, train_labels), (test_images, test_labels) = mnist.load_data()
train_images = train_images / 255.0
test_images = test_images / 255.0
model = keras.Sequential([
keras.layers.Flatten(input_shape=(28, 28)),
keras.layers.Dense(128, activation=‘relu’),
keras.layers.Dense(10, activation=‘softmax’)
])
model.compile(optimizer=‘adam’, loss=‘sparse_categorical_crossentropy’, metrics=[‘accuracy’])
model.fit(train_images, train_labels, epochs=5)
test_loss, test_acc = model.evaluate(test_images, test_labels)
print(‘Test accuracy:’, test_acc)
----------------------------CNN IMPLEMENTATION------------------
However, kernel dies when I run below code
import tensorflow as tf
from tensorflow import keras
mnist = keras.datasets.mnist
(train_images, train_labels), (test_images, test_labels) = mnist.load_data()
train_images = train_images.reshape(-1, 28, 28, 1)
test_images = test_images.reshape(-1, 28, 28, 1)
train_images = train_images / 255.0
test_images = test_images / 255.0
model = keras.Sequential([
keras.layers.Conv2D(32, (3, 3), activation=‘relu’, input_shape=(28, 28, 1)),
keras.layers.MaxPooling2D((2, 2)),
keras.layers.Flatten(),
keras.layers.Dense(128, activation=‘relu’),
keras.layers.Dense(10, activation=‘softmax’)
])
model.compile(optimizer=‘adam’, loss=‘sparse_categorical_crossentropy’, metrics=[‘accuracy’])
model.fit(train_images, train_labels, epochs=5)
test_loss, test_acc = model.evaluate(test_images, test_labels)
print(‘Test accuracy:’, test_acc)
