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(carnd-term1) carnd@ip-172-31-20-28:~/BC-P3$ python model.py
Using TensorFlow backend.
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcublas.so locally
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcudnn.so locally
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcufft.so locally
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcuda.so.1 locally
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcurand.so locally
------------------------------
Parameters
------------------------------
data_dir := data
batch_size := 1000
keep_prob := 0.5
save_best_only := True
test_size := 0.1
nb_epoch := 28
learning_rate := 0.0001
samples_per_epoch := 24000
------------------------------
____________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
====================================================================================================
lambda_1 (Lambda) (None, 66, 200, 3) 0 lambda_input_1[0][0]
____________________________________________________________________________________________________
convolution2d_1 (Convolution2D) (None, 31, 98, 24) 1824 lambda_1[0][0]
____________________________________________________________________________________________________
convolution2d_2 (Convolution2D) (None, 14, 47, 36) 21636 convolution2d_1[0][0]
____________________________________________________________________________________________________
convolution2d_3 (Convolution2D) (None, 5, 22, 48) 43248 convolution2d_2[0][0]
____________________________________________________________________________________________________
convolution2d_4 (Convolution2D) (None, 3, 20, 64) 27712 convolution2d_3[0][0]
____________________________________________________________________________________________________
convolution2d_5 (Convolution2D) (None, 1, 18, 64) 36928 convolution2d_4[0][0]
____________________________________________________________________________________________________
dropout_1 (Dropout) (None, 1, 18, 64) 0 convolution2d_5[0][0]
____________________________________________________________________________________________________
flatten_1 (Flatten) (None, 1152) 0 dropout_1[0][0]
____________________________________________________________________________________________________
dense_1 (Dense) (None, 100) 115300 flatten_1[0][0]
____________________________________________________________________________________________________
dense_2 (Dense) (None, 50) 5050 dense_1[0][0]
____________________________________________________________________________________________________
dense_3 (Dense) (None, 10) 510 dense_2[0][0]
____________________________________________________________________________________________________
dense_4 (Dense) (None, 1) 11 dense_3[0][0]
====================================================================================================
Total params: 252,219
Trainable params: 252,219
Non-trainable params: 0
____________________________________________________________________________________________________\
Epoch 1/28
/home/carnd/BC-P3/utils.py:100: VisibleDeprecationWarning: boolean index did not match indexed array along dimension 0; dimension is 160 but corresponding boolean dimension is 66\
mask[(ym - y1) * (x2 - x1) - (y2 - y1) * (xm - x1) > 0] = 1
I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\
I tensorflow/core/common_runtime/gpu/gpu_device.cc:885] Found device 0 with properties:
name: GRID K520
major: 3 minor: 0 memoryClockRate (GHz) 0.797
pciBusID 0000:00:03.0
Total memory: 3.94GiB
Free memory: 3.91GiB
I tensorflow/core/common_runtime/gpu/gpu_device.cc:906] DMA: 0
I tensorflow/core/common_runtime/gpu/gpu_device.cc:916] 0: Y
I tensorflow/core/common_runtime/gpu/gpu_device.cc:975] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GRID K520, pci bus id: 0000:00:03.0)\
24000/24000 [==============================] - 115s - loss: 0.0589 - val_loss: 0.0169
Epoch 2/28
24000/24000 [==============================] - 102s - loss: 0.0365 - val_loss: 0.0136
Epoch 3/28
24000/24000 [==============================] - 101s - loss: 0.0336 - val_loss: 0.0131
Epoch 4/28
24000/24000 [==============================] - 99s - loss: 0.0317 - val_loss: 0.0131
Epoch 5/28
24000/24000 [==============================] - 101s - loss: 0.0297 - val_loss: 0.0128
Epoch 6/28
24000/24000 [==============================] - 97s - loss: 0.0288 - val_loss: 0.0127
Epoch 7/28
24000/24000 [==============================] - 99s - loss: 0.0286 - val_loss: 0.0133
Epoch 8/28
24000/24000 [==============================] - 97s - loss: 0.0268 - val_loss: 0.0119
Epoch 9/28
24000/24000 [==============================] - 98s - loss: 0.0266 - val_loss: 0.0115
Epoch 10/28
24000/24000 [==============================] - 97s - loss: 0.0258 - val_loss: 0.0120
Epoch 11/28
24000/24000 [==============================] - 98s - loss: 0.0247 - val_loss: 0.0130
Epoch 12/28
24000/24000 [==============================] - 98s - loss: 0.0246 - val_loss: 0.0107
Epoch 13/28
24000/24000 [==============================] - 97s - loss: 0.0244 - val_loss: 0.0104
Epoch 14/28
24000/24000 [==============================] - 97s - loss: 0.0235 - val_loss: 0.0101
Epoch 15/28
24000/24000 [==============================] - 97s - loss: 0.0236 - val_loss: 0.0101
Epoch 16/28
24000/24000 [==============================] - 98s - loss: 0.0236 - val_loss: 0.0111
Epoch 17/28
24000/24000 [==============================] - 97s - loss: 0.0226 - val_loss: 0.0107
Epoch 18/28
24000/24000 [==============================] - 98s - loss: 0.0232 - val_loss: 0.0104
Epoch 19/28
24000/24000 [==============================] - 96s - loss: 0.0229 - val_loss: 0.0107
Epoch 20/28
24000/24000 [==============================] - 97s - loss: 0.0228 - val_loss: 0.0105
Epoch 21/28
24000/24000 [==============================] - 98s - loss: 0.0222 - val_loss: 0.0100
Epoch 22/28
24000/24000 [==============================] - 98s - loss: 0.0226 - val_loss: 0.0099
Epoch 23/28
24000/24000 [==============================] - 98s - loss: 0.0218 - val_loss: 0.0097
Epoch 24/28
24000/24000 [==============================] - 97s - loss: 0.0217 - val_loss: 0.0101
Epoch 25/28
24000/24000 [==============================] - 98s - loss: 0.0214 - val_loss: 0.0095
Epoch 26/28
24000/24000 [==============================] - 98s - loss: 0.0216 - val_loss: 0.0106
Epoch 27/28
24000/24000 [==============================] - 98s - loss: 0.0218 - val_loss: 0.0095
Epoch 28/28
24000/24000 [==============================] - 98s - loss: 0.0213 - val_loss: 0.0106
(carnd-term1) carnd@ip-172-31-20-28:~/BC-P3$