Spaces:
Runtime error
Runtime error
| import tensorflow as tf | |
| from tensorflow.keras import layers,models | |
| (train_images,train_labels),(test_images,test_labels) = tf.keras.datasets.mnist.load_data() | |
| train_images = train_images.reshape((60000, 28, 28, 1)).astype('float32')/255 | |
| test_images = test_images.reshape((10000, 28, 28, 1)).astype('float32')/255 | |
| train_labels = tf.keras.utils.to_categorical(train_labels) | |
| print('train_labels') | |
| test_labels = tf.keras.utils.to_categorical(test_labels) | |
| model = models.Sequential() | |
| model.add(layers.Conv2D(32,(3,3),activation='relu',input_shape=(28,28,1))) | |
| model.add(layers.MaxPooling2D(2,2)) | |
| model.add(layers.Conv2D(64,(3,3),activation='relu')) | |
| model.add(layers.MaxPooling2D(2,2)) | |
| model.add(layers.Conv2D(64,(3,3),activation='relu')) | |
| model.add(layers.Flatten()) | |
| model.add(layers.Dense(64,activation='relu')) | |
| model.add(layers.Dense(10,activation='softmax')) | |
| model.compile(optimizer='adam',loss='categorical_crossentropy',metrics=['accuracy']) | |
| model.fit(train_images,train_labels,epochs=5,batch_size=64,validation_split=0.1) | |
| model.save('model.h5') | |
| print('Here am I') |