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Configuration error
Configuration error
| """ | |
| Dumps things to tensorboard and console | |
| """ | |
| import os | |
| import warnings | |
| import torchvision.transforms as transforms | |
| from torch.utils.tensorboard import SummaryWriter | |
| def tensor_to_numpy(image): | |
| image_np = (image.numpy() * 255).astype('uint8') | |
| return image_np | |
| def detach_to_cpu(x): | |
| return x.detach().cpu() | |
| def fix_width_trunc(x): | |
| return ('{:.9s}'.format('{:0.9f}'.format(x))) | |
| class TensorboardLogger: | |
| def __init__(self, short_id, id, git_info, flag_occupy_memory, savepath='.'): | |
| self.short_id = short_id | |
| if self.short_id == 'NULL': | |
| self.short_id = 'DEBUG' | |
| if id is None: | |
| self.no_log = True | |
| warnings.warn('Logging has been disbaled.') | |
| else: | |
| self.no_log = False | |
| self.inv_im_trans = transforms.Normalize( | |
| mean=[-0.485/0.229, -0.456/0.224, -0.406/0.225], | |
| std=[1/0.229, 1/0.224, 1/0.225]) | |
| self.inv_seg_trans = transforms.Normalize( | |
| mean=[-0.5/0.5], | |
| std=[1/0.5]) | |
| log_path = os.path.join('.', 'tmp_occupy_memory_saves', '%s' % id) if flag_occupy_memory else os.path.join(savepath, 'saves', '%s' % id) | |
| self.logger = SummaryWriter(log_path) | |
| self.log_string('git', git_info) | |
| def log_scalar(self, tag, x, step): | |
| if self.no_log: | |
| warnings.warn('Logging has been disabled.') | |
| return | |
| self.logger.add_scalar(tag, x, step) | |
| def log_metrics(self, l1_tag, l2_tag, val, step, f=None): | |
| tag = l1_tag + '/' + l2_tag | |
| text = '{:s} - It {:6d} [{:5s}] [{:13}]: {:s}'.format(self.short_id, step, l1_tag.upper(), l2_tag, fix_width_trunc(val)) | |
| print(text) | |
| if f is not None: | |
| f.write(text + '\n') | |
| f.flush() | |
| self.log_scalar(tag, val, step) | |
| def log_im(self, tag, x, step): | |
| if self.no_log: | |
| warnings.warn('Logging has been disabled.') | |
| return | |
| x = detach_to_cpu(x) | |
| x = self.inv_im_trans(x) | |
| x = tensor_to_numpy(x) | |
| self.logger.add_image(tag, x, step) | |
| def log_cv2(self, tag, x, step): | |
| if self.no_log: | |
| warnings.warn('Logging has been disabled.') | |
| return | |
| x = x.transpose((2, 0, 1)) | |
| self.logger.add_image(tag, x, step) | |
| def log_seg(self, tag, x, step): | |
| if self.no_log: | |
| warnings.warn('Logging has been disabled.') | |
| return | |
| x = detach_to_cpu(x) | |
| x = self.inv_seg_trans(x) | |
| x = tensor_to_numpy(x) | |
| self.logger.add_image(tag, x, step) | |
| def log_gray(self, tag, x, step): | |
| if self.no_log: | |
| warnings.warn('Logging has been disabled.') | |
| return | |
| x = detach_to_cpu(x) | |
| x = tensor_to_numpy(x) | |
| self.logger.add_image(tag, x, step) | |
| def log_string(self, tag, x): | |
| print(tag, x) | |
| if self.no_log: | |
| warnings.warn('Logging has been disabled.') | |
| return | |
| self.logger.add_text(tag, x) | |