package code for pip install

Author: yulonglin

README.md

@@ -151,7 +151,7 @@ w = G.mapping(z, c, truncation_psi=0.5, truncation_cutoff=8)
 img = G.synthesis(w, noise_mode='const', force_fp32=True)
 ```
 
-Please refer to [`generate.py`](./generate.py), [`style_mixing.py`](./style_mixing.py), and [`projector.py`](./projector.py) for further examples.
+Please refer to [`generate.py`](stylegan2_ada_pytorch/generate.py), [`style_mixing.py`](stylegan2_ada_pytorch/style_mixing.py), and [`projector.py`](stylegan2_ada_pytorch/projector.py) for further examples.
 
 ## Preparing datasets
 

pyproject.toml

@@ -0,0 +1,6 @@
+[build-system]
+requires = [
+    "setuptools>=42",
+    "wheel"
+]
+build-backend = "setuptools.build_meta"

setup.cfg

@@ -0,0 +1,30 @@
+[metadata]
+name = stylegan2-ada-pytorch
+version = 1.0.0
+description =  StyleGAN2-ADA - Official PyTorch implementation
+long_description = file: README.md
+long_description_content_type = text/markdown
+url = https://github.com/NVlabs/stylegan2-ada-pytorch
+project_urls =
+    Bug Tracker = https://github.com/NVlabs/stylegan2-ada-pytorch/issues
+classifiers =
+    Programming Language :: Python :: 3
+    License :: OSI Approved :: MIT License
+    Operating System :: OS Independent
+
+[options]
+package_dir =
+    = .
+packages = find:
+python_requires = >=3.6
+install_requires =
+    torch >=1.7.0
+    click
+    requests
+    tqdm
+    pyspng
+    ninja
+    imageio-ffmpeg ==0.4.3
+
+[options.packages.find]
+where = .

stylegan2_ada_pytorch/__init__.py

@@ -14,19 +14,17 @@
 import tempfile
 import copy
 import torch
-import dnnlib
 
-import legacy
-from metrics import metric_main
-from metrics import metric_utils
-from torch_utils import training_stats
-from torch_utils import custom_ops
-from torch_utils import misc
+from stylegan2_ada_pytorch import legacy, dnnlib
+from stylegan2_ada_pytorch.metrics import metric_main, metric_utils
+from stylegan2_ada_pytorch.torch_utils import training_stats
+from stylegan2_ada_pytorch.torch_utils import custom_ops, misc
+
 
 #----------------------------------------------------------------------------
 
 def subprocess_fn(rank, args, temp_dir):
-    dnnlib.util.Logger(should_flush=True)
+    stylegan2_ada_pytorch.dnnlib.util.Logger(should_flush=True)
 
     # Init torch.distributed.
     if args.num_gpus > 1:
@@ -61,7 +59,7 @@ def subprocess_fn(rank, args, temp_dir):
             print(f'Calculating {metric}...')
         progress = metric_utils.ProgressMonitor(verbose=args.verbose)
         result_dict = metric_main.calc_metric(metric=metric, G=G, dataset_kwargs=args.dataset_kwargs,
-            num_gpus=args.num_gpus, rank=rank, device=device, progress=progress)
+                                              num_gpus=args.num_gpus, rank=rank, device=device, progress=progress)
         if rank == 0:
             metric_main.report_metric(result_dict, run_dir=args.run_dir, snapshot_pkl=args.network_pkl)
         if rank == 0 and args.verbose:
@@ -128,7 +126,7 @@ def calc_metrics(ctx, network_pkl, metrics, data, mirror, gpus, verbose):
         ppl_zend     Perceptual path length in Z at path endpoints against cropped image.
         ppl_wend     Perceptual path length in W at path endpoints against cropped image.
     """
-    dnnlib.util.Logger(should_flush=True)
+    stylegan2_ada_pytorch.dnnlib.util.Logger(should_flush=True)
 
     # Validate arguments.
     args = dnnlib.EasyDict(metrics=metrics, num_gpus=gpus, network_pkl=network_pkl, verbose=verbose)
@@ -138,11 +136,11 @@ def calc_metrics(ctx, network_pkl, metrics, data, mirror, gpus, verbose):
         ctx.fail('--gpus must be at least 1')
 
     # Load network.
-    if not dnnlib.util.is_url(network_pkl, allow_file_urls=True) and not os.path.isfile(network_pkl):
+    if not stylegan2_ada_pytorch.dnnlib.util.is_url(network_pkl, allow_file_urls=True) and not os.path.isfile(network_pkl):
         ctx.fail('--network must point to a file or URL')
     if args.verbose:
         print(f'Loading network from "{network_pkl}"...')
-    with dnnlib.util.open_url(network_pkl, verbose=args.verbose) as f:
+    with stylegan2_ada_pytorch.dnnlib.util.open_url(network_pkl, verbose=args.verbose) as f:
         network_dict = legacy.load_network_pkl(f)
         args.G = network_dict['G_ema'] # subclass of torch.nn.Module
 

calc_metrics.py renamed to stylegan2_ada_pytorch/calc_metrics.py

@@ -13,12 +13,12 @@
 from typing import List, Optional
 
 import click
-import dnnlib
 import numpy as np
 import PIL.Image
 import torch
 
-import legacy
+from stylegan2_ada_pytorch import legacy, dnnlib
+
 
 #----------------------------------------------------------------------------
 
@@ -80,7 +80,7 @@ def generate_images(
 
     print('Loading networks from "%s"...' % network_pkl)
     device = torch.device('cuda')
-    with dnnlib.util.open_url(network_pkl) as f:
+    with stylegan2_ada_pytorch.dnnlib.util.open_url(network_pkl) as f:
         G = legacy.load_network_pkl(f)['G_ema'].to(device) # type: ignore
 
     os.makedirs(outdir, exist_ok=True)

dataset_tool.py renamed to stylegan2_ada_pytorch/dataset_tool.py

@@ -12,8 +12,9 @@
 import copy
 import numpy as np
 import torch
-import dnnlib
-from torch_utils import misc
+from stylegan2_ada_pytorch import dnnlib
+from stylegan2_ada_pytorch.torch_utils import misc
+
 
 #----------------------------------------------------------------------------
 
@@ -165,7 +166,7 @@ def kwarg(tf_name, default=None, none=None):
     #for name, value in tf_params.items(): print(f'{name:<50s}{list(value.shape)}')
 
     # Convert params.
-    from training import networks
+    from stylegan2_ada_pytorch.training import networks
     G = networks.Generator(**kwargs).eval().requires_grad_(False)
     # pylint: disable=unnecessary-lambda
     _populate_module_params(G,
@@ -262,7 +263,7 @@ def kwarg(tf_name, default=None):
     #for name, value in tf_params.items(): print(f'{name:<50s}{list(value.shape)}')
 
     # Convert params.
-    from training import networks
+    from stylegan2_ada_pytorch.training import networks
     D = networks.Discriminator(**kwargs).eval().requires_grad_(False)
     # pylint: disable=unnecessary-lambda
     _populate_module_params(D,
@@ -305,7 +306,7 @@ def convert_network_pickle(source, dest, force_fp16):
         --dest=stylegan2-cat-config-f.pkl
     """
     print(f'Loading "{source}"...')
-    with dnnlib.util.open_url(source) as f:
+    with stylegan2_ada_pytorch.dnnlib.util.open_url(source) as f:
         data = load_network_pkl(f, force_fp16=force_fp16)
     print(f'Saving "{dest}"...')
     with open(dest, 'wb') as f: