From a1c36d0af122f8da56785d907bd0eb5a09da8855 Mon Sep 17 00:00:00 2001 From: jimheo Date: Tue, 15 Feb 2022 17:57:43 +0900 Subject: [PATCH] Fix the typo uncoditional -> unconditional --- demo/conditional_demo.py | 2 +- demo/ddpm_demo.py | 2 +- demo/unconditional_demo.py | 10 +++++----- docs/en/get_started.md | 4 ++-- docs/en/quick_run.md | 2 +- mmgen/apis/__init__.py | 4 ++-- mmgen/apis/inference.py | 10 +++++----- mmgen/datasets/grow_scale_image_dataset.py | 2 +- mmgen/datasets/unconditional_image_dataset.py | 2 +- tests/test_apis/test_inference.py | 10 +++++----- 10 files changed, 24 insertions(+), 24 deletions(-) diff --git a/demo/conditional_demo.py b/demo/conditional_demo.py index 4c5dd5e75..1a7c9856b 100644 --- a/demo/conditional_demo.py +++ b/demo/conditional_demo.py @@ -21,7 +21,7 @@ def parse_args(): '--save-path', type=str, default='./work_dirs/demos/conditional_samples.png', - help='path to save uncoditional samples') + help='path to save unconditional samples') parser.add_argument( '--device', type=str, default='cuda:0', help='CUDA device id') diff --git a/demo/ddpm_demo.py b/demo/ddpm_demo.py index 015999a41..7bc7666aa 100644 --- a/demo/ddpm_demo.py +++ b/demo/ddpm_demo.py @@ -24,7 +24,7 @@ def parse_args(): '--save-path', type=str, default='./work_dirs/demos/ddpm_samples.png', - help='path to save uncoditional samples') + help='path to save unconditional samples') parser.add_argument( '--device', type=str, default='cuda:0', help='CUDA device id') diff --git a/demo/unconditional_demo.py b/demo/unconditional_demo.py index 4769b581e..508ace649 100644 --- a/demo/unconditional_demo.py +++ b/demo/unconditional_demo.py @@ -9,7 +9,7 @@ # yapf: disable sys.path.append(os.path.abspath(os.path.join(__file__, '../..'))) # isort:skip # noqa -from mmgen.apis import init_model, sample_uncoditional_model # isort:skip # noqa +from mmgen.apis import init_model, sample_unconditional_model # isort:skip # noqa # yapf: enable @@ -21,7 +21,7 @@ def parse_args(): '--save-path', type=str, default='./work_dirs/demos/unconditional_samples.png', - help='path to save uncoditional samples') + help='path to save unconditional samples') parser.add_argument( '--device', type=str, default='cuda:0', help='CUDA device id') @@ -65,9 +65,9 @@ def main(): if args.sample_cfg is None: args.sample_cfg = dict() - results = sample_uncoditional_model(model, args.num_samples, - args.num_batches, args.sample_model, - **args.sample_cfg) + results = sample_unconditional_model(model, args.num_samples, + args.num_batches, args.sample_model, + **args.sample_cfg) results = (results[:, [2, 1, 0]] + 1.) / 2. # save images diff --git a/docs/en/get_started.md b/docs/en/get_started.md index 9e2f724d0..1591426ef 100644 --- a/docs/en/get_started.md +++ b/docs/en/get_started.md @@ -150,7 +150,7 @@ PYTHONPATH="$(dirname $0)/..":$PYTHONPATH To verify whether MMGeneration and the required environment are installed correctly, we can run sample Python code to initialize an unconditional model and use it to generate random samples: ```python -from mmgen.apis import init_model, sample_uncoditional_model +from mmgen.apis import init_model, sample_unconditional_model config_file = 'configs/styleganv2/stylegan2_c2_lsun-church_256_b4x8_800k.py' # you can download this checkpoint in advance and use a local file path. @@ -159,7 +159,7 @@ device = 'cuda:0' # init a generatvie model = init_model(config_file, checkpoint_file, device=device) # sample images -fake_imgs = sample_uncoditional_model(model, 4) +fake_imgs = sample_unconditional_model(model, 4) ``` The above code is supposed to run successfully upon you finish the installation. diff --git a/docs/en/quick_run.md b/docs/en/quick_run.md index 026452c43..d56c441e7 100644 --- a/docs/en/quick_run.md +++ b/docs/en/quick_run.md @@ -16,7 +16,7 @@ MMGeneration provides high-level APIs for sampling images with unconditional GAN ```python import mmcv -from mmgen.apis import init_model, sample_uncoditional_model +from mmgen.apis import init_model, sample_unconditional_model # Specify the path to model config and checkpoint file config_file = 'configs/styleganv2/stylegan2_c2_ffhq_1024_b4x8.py' diff --git a/mmgen/apis/__init__.py b/mmgen/apis/__init__.py index 57cbebba7..d238fa3eb 100644 --- a/mmgen/apis/__init__.py +++ b/mmgen/apis/__init__.py @@ -1,11 +1,11 @@ # Copyright (c) OpenMMLab. All rights reserved. from .inference import (init_model, sample_conditional_model, sample_ddpm_model, sample_img2img_model, - sample_uncoditional_model) + sample_unconditional_model) from .train import set_random_seed, train_model __all__ = [ 'set_random_seed', 'train_model', 'init_model', 'sample_img2img_model', - 'sample_uncoditional_model', 'sample_conditional_model', + 'sample_unconditional_model', 'sample_conditional_model', 'sample_ddpm_model' ] diff --git a/mmgen/apis/inference.py b/mmgen/apis/inference.py index 68f150f5e..377aacd0a 100644 --- a/mmgen/apis/inference.py +++ b/mmgen/apis/inference.py @@ -46,11 +46,11 @@ def init_model(config, checkpoint=None, device='cuda:0', cfg_options=None): @torch.no_grad() -def sample_uncoditional_model(model, - num_samples=16, - num_batches=4, - sample_model='ema', - **kwargs): +def sample_unconditional_model(model, + num_samples=16, + num_batches=4, + sample_model='ema', + **kwargs): """Sampling from unconditional models. Args: diff --git a/mmgen/datasets/grow_scale_image_dataset.py b/mmgen/datasets/grow_scale_image_dataset.py index 7b71bbc5c..fc65aae2d 100644 --- a/mmgen/datasets/grow_scale_image_dataset.py +++ b/mmgen/datasets/grow_scale_image_dataset.py @@ -10,7 +10,7 @@ @DATASETS.register_module() class GrowScaleImgDataset(Dataset): - """Grow Scale Uncoditional Image Dataset. + """Grow Scale Unconditional Image Dataset. This dataset is similar with ``UnconditionalImageDataset``, but offer more dynamic functionalities for the supporting complex algorithms, like diff --git a/mmgen/datasets/unconditional_image_dataset.py b/mmgen/datasets/unconditional_image_dataset.py index 47498b016..2a128f9e7 100644 --- a/mmgen/datasets/unconditional_image_dataset.py +++ b/mmgen/datasets/unconditional_image_dataset.py @@ -10,7 +10,7 @@ @DATASETS.register_module() class UnconditionalImageDataset(Dataset): - """Uncoditional Image Dataset. + """Unconditional Image Dataset. This dataset contains raw images for training unconditional GANs. Given a root dir, we will recursively find all images in this root. The diff --git a/tests/test_apis/test_inference.py b/tests/test_apis/test_inference.py index 3e6d5066e..77499be6d 100644 --- a/tests/test_apis/test_inference.py +++ b/tests/test_apis/test_inference.py @@ -5,7 +5,7 @@ import torch from mmgen.apis import (init_model, sample_ddpm_model, sample_img2img_model, - sample_uncoditional_model) + sample_unconditional_model) class TestSampleUnconditionalModel: @@ -20,22 +20,22 @@ def setup_class(cls): cls.model = init_model(config, checkpoint=None, device='cpu') def test_sample_unconditional_model_cpu(self): - res = sample_uncoditional_model( + res = sample_unconditional_model( self.model, 5, num_batches=2, sample_model='orig') assert res.shape == (5, 3, 64, 64) - res = sample_uncoditional_model( + res = sample_unconditional_model( self.model, 4, num_batches=2, sample_model='orig') assert res.shape == (4, 3, 64, 64) @pytest.mark.skipif(not torch.cuda.is_available(), reason='requires cuda') def test_sample_unconditional_model_cuda(self): model = self.model.cuda() - res = sample_uncoditional_model( + res = sample_unconditional_model( model, 5, num_batches=2, sample_model='orig') assert res.shape == (5, 3, 64, 64) - res = sample_uncoditional_model( + res = sample_unconditional_model( model, 4, num_batches=2, sample_model='orig') assert res.shape == (4, 3, 64, 64)