Loss-graph store automatically (iterations == max_batches) at the end of training
| | |
| | | //printf("Tensor Cores - Backward-filter enabled: l->bf_algo = CUDNN_CONVOLUTION_BWD_FILTER_ALGO_WINOGRAD_NONFUSED \n"); |
| | | |
| | | if (fw == 2 && bd == 2 && bf == 2) printf("TF "); |
| | | else if (fw >= 1 && bd >= 1 && bf >= 1) printf("TH "); |
| | | else if (fw == 1 && bd == 1 && bf == 1) printf("TH "); |
| | | } |
| | | } |
| | | #endif |
| | |
| | | args.hue = net.hue; |
| | | |
| | | #ifdef OPENCV |
| | | args.threads = 7; |
| | | args.threads = 3; |
| | | IplImage* img = NULL; |
| | | float max_img_loss = 5; |
| | | int number_of_lines = 100; |
| | |
| | | cvPutText(img, char_buff, pt1, &font, CV_RGB(0, 0, 0)); |
| | | cvShowImage("average loss", img); |
| | | int k = cvWaitKey(20); |
| | | if (k == 's') cvSaveImage("chart.jpg", img, 0); |
| | | if (k == 's' || current_batch == (max_batches-1)) cvSaveImage("chart.jpg", img, 0); |
| | | } |
| | | #endif // OPENCV |
| | | |