X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?p=pysvrt.git;a=blobdiff_plain;f=cnn-svrt.py;h=63b11ee4c33831bd0ec8236f7892554bcab0b47a;hp=0d4b31364832ffed5005a29fb1b2b627f74cfd17;hb=4c7ff07760d015a2efad8b7eb0bd44dd9acc9106;hpb=91b12f8980a69a99fd6bbdc9b6f6a422dd8cd15a diff --git a/cnn-svrt.py b/cnn-svrt.py index 0d4b313..63b11ee 100755 --- a/cnn-svrt.py +++ b/cnn-svrt.py @@ -41,7 +41,7 @@ from torchvision import datasets, transforms, utils # SVRT -import vignette_set +import svrtset ###################################################################### @@ -77,6 +77,10 @@ parser.add_argument('--test_loaded_models', type = distutils.util.strtobool, default = 'False', help = 'Should we compute the test errors of loaded models') +parser.add_argument('--problems', + type = str, default = '1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23', + help = 'What problems to process') + args = parser.parse_args() ###################################################################### @@ -247,6 +251,22 @@ def int_to_suffix(n): else: return str(n) +class vignette_logger(): + def __init__(self, delay_min = 60): + self.start_t = time.time() + self.last_t = self.start_t + self.delay_min = delay_min + + def __call__(self, n, m): + t = time.time() + if t > self.last_t + self.delay_min: + dt = (t - self.start_t) / m + log_string('sample_generation {:d} / {:d}'.format( + m, + n), ' [ETA ' + time.ctime(time.time() + dt * (n - m)) + ']' + ) + self.last_t = t + ###################################################################### if args.nb_train_samples%args.batch_size > 0 or args.nb_test_samples%args.batch_size > 0: @@ -255,12 +275,12 @@ if args.nb_train_samples%args.batch_size > 0 or args.nb_test_samples%args.batch_ if args.compress_vignettes: log_string('using_compressed_vignettes') - VignetteSet = vignette_set.CompressedVignetteSet + VignetteSet = svrtset.CompressedVignetteSet else: log_string('using_uncompressed_vignettes') - VignetteSet = vignette_set.VignetteSet + VignetteSet = svrtset.VignetteSet -for problem_number in range(1, 24): +for problem_number in map(int, args.problems.split(',')): log_string('############### problem ' + str(problem_number) + ' ###############') @@ -300,7 +320,8 @@ for problem_number in range(1, 24): train_set = VignetteSet(problem_number, args.nb_train_samples, args.batch_size, - cuda = torch.cuda.is_available()) + cuda = torch.cuda.is_available(), + logger = vignette_logger()) log_string('data_generation {:0.2f} samples / s'.format( train_set.nb_samples / (time.time() - t))