From d4ce9f6c3897802cdafab12810056c5552cfef89 Mon Sep 17 00:00:00 2001 From: Phil Wang Date: Fri, 9 Oct 2020 21:50:23 -0700 Subject: [PATCH] save samples and models to ./results path --- .../denoising_diffusion_pytorch.py | 9 ++++++--- sample.png | Bin 1397035 -> 0 bytes setup.py | 2 +- 3 files changed, 7 insertions(+), 4 deletions(-) delete mode 100644 sample.png diff --git a/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py b/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py index e24d2133e..4b73d6c91 100644 --- a/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py +++ b/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py @@ -28,6 +28,9 @@ UPDATE_EMA_EVERY = 10 EXTS = ['jpg', 'jpeg', 'png'] +RESULTS_FOLDER = Path('./results') +RESULTS_FOLDER.mkdir(exist_ok = True) + # helpers functions def exists(x): @@ -497,10 +500,10 @@ def save(self, milestone): 'model': self.model.state_dict(), 'ema': self.ema_model.state_dict() } - torch.save(data, f'./model-{milestone}.pt') + torch.save(data, str(RESULTS_FOLDER / f'model-{milestone}.pt')) def load(self, milestone): - data = torch.load(f'./model-{milestone}.pt') + data = torch.load(str(RESULTS_FOLDER / f'model-{milestone}.pt')) self.step = data['step'] self.model.load_state_dict(data['model']) @@ -527,7 +530,7 @@ def train(self): batches = num_to_groups(36, self.batch_size) all_images_list = list(map(lambda n: self.ema_model.sample(self.image_size, batch_size=n), batches)) all_images = torch.cat(all_images_list, dim=0) - utils.save_image(all_images, f'./sample-{milestone}.png', nrow=6) + utils.save_image(all_images, str(RESULTS_FOLDER / f'sample-{milestone}.png'), nrow=6) self.save(milestone) self.step += 1 diff --git a/sample.png b/sample.png deleted file mode 100644 index ddcb2d73a9463201fb66d1399ce7b31aa95338e6..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 1397035 zcmV)EK)}C=P)d*W6ZgBbDG;mL`IXDk(p#BJ0(exQi*0!jU`H=V96z^1UE9Qa-j?ehF|>y 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@@ -3,7 +3,7 @@ setup( name = 'denoising-diffusion-pytorch', packages = find_packages(), - version = '0.5.0', + version = '0.5.2', license='MIT', description = 'Denoising Diffusion Probabilistic Models - Pytorch', author = 'Phil Wang',