All welcome. I am trying to train my first neuron.
When you try to train her - this error appears:
tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating and type: 50 / task: 0 / device: GPU: 0 by allocator
I read, I realized that this is due to the fact that little memory in the video card (GTX 1050 2 gb).
It turns out that I can’t use a video card here at all?
Maybe you can somehow "portions" issue a video card dataset?
Code:
import keras from keras.datasets import mnist from keras.models import Sequential from keras.layers import Dense, Dropout, Flatten from keras.layers import Conv2D, MaxPooling2D from keras import backend as K import numpy as np batch_size = 1 num_classes = 3 epochs = 2 # input image dimensions img_rows, img_cols = 135, 240 dataset = Dataset() x_train, y_train = dataset.LoadDataset() x_train = x_train[0] y_train = y_train[0] x_train = np.array(x_train).reshape(10000, 135, 240, 1) input_shape = (img_rows, img_cols, 1) x_train = x_train.astype('float32') x_train = x_train / 255 model = Sequential() model.add(Conv2D(32, kernel_size=(1, 1), activation='relu', input_shape=input_shape)) model.add(Conv2D(64, (3, 3), activation='relu')) model.add(MaxPooling2D(pool_size=(2, 2))) model.add(Dropout(0.25)) model.add(Flatten()) model.add(Dense(128, activation='relu')) model.add(Dropout(0.5)) model.add(Dense(num_classes, activation='softmax')) model.compile(loss=keras.losses.categorical_crossentropy, optimizer=keras.optimizers.Adadelta(), metrics=['accuracy']) model.fit([x_train], [y_train], batch_size=batch_size, epochs=epochs, verbose=1) model.save("First.model") score = model.evaluate([x_train], [y_train], verbose=0) print('Test loss:', score[0]) print('Test accuracy:', score[1]) 
