From 007f4f7314eabd9cc3a2b0d11889de49ad3c682a Mon Sep 17 00:00:00 2001 From: Vladimir Repin <32306715+mezotaken@users.noreply.github.com> Date: Sat, 12 Nov 2022 15:12:15 +0300 Subject: Tests cleaned up --- launch.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) (limited to 'launch.py') diff --git a/launch.py b/launch.py index 8e65676d..6822a01d 100644 --- a/launch.py +++ b/launch.py @@ -229,6 +229,9 @@ def prepare_enviroment(): def tests(argv): if "--api" not in argv: argv.append("--api") + if "--ckpt" not in argv: + argv.append("--ckpt") + argv.append("./test/test_files/empty.pt") print(f"Launching Web UI in another process for testing with arguments: {' '.join(argv[1:])}") @@ -236,7 +239,7 @@ def tests(argv): proc = subprocess.Popen([sys.executable, *argv], stdout=stdout, stderr=stderr) import test.server_poll - test.server_poll.run_tests() + test.server_poll.run_tests(proc) print(f"Stopping Web UI process with id {proc.pid}") proc.kill() -- cgit v1.2.3 From 93d6c0209ae55632b72751cf82740e32a0cd81bc Mon Sep 17 00:00:00 2001 From: Vladimir Repin <32306715+mezotaken@users.noreply.github.com> Date: Mon, 14 Nov 2022 13:39:22 +0300 Subject: Tests separated for github-actions CI --- .github/workflows/run_tests.yaml | 26 ++++++++++++ launch.py | 36 ++++++++++------ test/advanced_features/__init__.py | 0 test/advanced_features/extras_test.py | 29 +++++++++++++ test/advanced_features/txt2img_test.py | 47 +++++++++++++++++++++ test/basic_features/__init__.py | 0 test/basic_features/img2img_test.py | 55 ++++++++++++++++++++++++ test/basic_features/txt2img_test.py | 72 ++++++++++++++++++++++++++++++++ test/basic_features/utils_test.py | 67 ++++++++++++++++++++++++++++++ test/extras_test.py | 29 ------------- test/img2img_test.py | 59 -------------------------- test/server_poll.py | 6 ++- test/txt2img_test.py | 76 ---------------------------------- test/utils_test.py | 63 ---------------------------- 14 files changed, 324 insertions(+), 241 deletions(-) create mode 100644 .github/workflows/run_tests.yaml create mode 100644 test/advanced_features/__init__.py create mode 100644 test/advanced_features/extras_test.py create mode 100644 test/advanced_features/txt2img_test.py create mode 100644 test/basic_features/__init__.py create mode 100644 test/basic_features/img2img_test.py create mode 100644 test/basic_features/txt2img_test.py create mode 100644 test/basic_features/utils_test.py delete mode 100644 test/extras_test.py delete mode 100644 test/img2img_test.py delete mode 100644 test/txt2img_test.py delete mode 100644 test/utils_test.py (limited to 'launch.py') diff --git a/.github/workflows/run_tests.yaml b/.github/workflows/run_tests.yaml new file mode 100644 index 00000000..a56a8110 --- /dev/null +++ b/.github/workflows/run_tests.yaml @@ -0,0 +1,26 @@ +name: Run tests on CPU with empty model + +on: + - push + - pull_request + +jobs: + test: + runs-on: ubuntu-latest + steps: + - name: Checkout Code + uses: actions/checkout@v3 + - name: Set up Python 3.10 + uses: actions/setup-python@v3 + with: + python-version: 3.10.6 + - uses: actions/cache@v2 + with: + path: ~/.cache/pip + key: ${{ runner.os }}-pip-${{ hashFiles('**/requirements.txt') }} + restore-keys: | + ${{ runner.os }}-pip- + - name: Run tests + run: | + export COMMANDLINE_ARGS="--tests basic_features --no-half --disable-opt-split-attention --use-cpu all" + python launch.py diff --git a/launch.py b/launch.py index 6822a01d..d0f502c2 100644 --- a/launch.py +++ b/launch.py @@ -17,6 +17,19 @@ def extract_arg(args, name): return [x for x in args if x != name], name in args +def extract_opt(args, name): + opt = None + is_present = False + if name in args: + is_present = True + idx = args.index(name) + del args[idx] + if idx < len(args) and args[idx][0] != "-": + opt = args[idx] + del args[idx] + return args, is_present, opt + + def run(command, desc=None, errdesc=None, custom_env=None): if desc is not None: print(desc) @@ -151,12 +164,11 @@ def prepare_enviroment(): blip_commit_hash = os.environ.get('BLIP_COMMIT_HASH', "48211a1594f1321b00f14c9f7a5b4813144b2fb9") sys.argv += shlex.split(commandline_args) - test_argv = [x for x in sys.argv if x != '--tests'] sys.argv, skip_torch_cuda_test = extract_arg(sys.argv, '--skip-torch-cuda-test') sys.argv, reinstall_xformers = extract_arg(sys.argv, '--reinstall-xformers') sys.argv, update_check = extract_arg(sys.argv, '--update-check') - sys.argv, run_tests = extract_arg(sys.argv, '--tests') + sys.argv, run_tests, test_dir = extract_opt(sys.argv, '--tests') xformers = '--xformers' in sys.argv deepdanbooru = '--deepdanbooru' in sys.argv ngrok = '--ngrok' in sys.argv @@ -222,24 +234,24 @@ def prepare_enviroment(): exit(0) if run_tests: - tests(test_argv) + tests(test_dir) exit(0) -def tests(argv): - if "--api" not in argv: - argv.append("--api") - if "--ckpt" not in argv: - argv.append("--ckpt") - argv.append("./test/test_files/empty.pt") +def tests(test_dir): + if "--api" not in sys.argv: + sys.argv.append("--api") + if "--ckpt" not in sys.argv: + sys.argv.append("--ckpt") + sys.argv.append("./test/test_files/empty.pt") - print(f"Launching Web UI in another process for testing with arguments: {' '.join(argv[1:])}") + print(f"Launching Web UI in another process for testing with arguments: {' '.join(sys.argv[1:])}") with open('test/stdout.txt', "w", encoding="utf8") as stdout, open('test/stderr.txt', "w", encoding="utf8") as stderr: - proc = subprocess.Popen([sys.executable, *argv], stdout=stdout, stderr=stderr) + proc = subprocess.Popen([sys.executable, *sys.argv], stdout=stdout, stderr=stderr) import test.server_poll - test.server_poll.run_tests(proc) + test.server_poll.run_tests(proc, test_dir) print(f"Stopping Web UI process with id {proc.pid}") proc.kill() diff --git a/test/advanced_features/__init__.py b/test/advanced_features/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/test/advanced_features/extras_test.py b/test/advanced_features/extras_test.py new file mode 100644 index 00000000..8763f8ed --- /dev/null +++ b/test/advanced_features/extras_test.py @@ -0,0 +1,29 @@ +import unittest + + +class TestExtrasWorking(unittest.TestCase): + def setUp(self): + self.url_img2img = "http://localhost:7860/sdapi/v1/extra-single-image" + self.simple_extras = { + "resize_mode": 0, + "show_extras_results": True, + "gfpgan_visibility": 0, + "codeformer_visibility": 0, + "codeformer_weight": 0, + "upscaling_resize": 2, + "upscaling_resize_w": 128, + "upscaling_resize_h": 128, + "upscaling_crop": True, + "upscaler_1": "None", + "upscaler_2": "None", + "extras_upscaler_2_visibility": 0, + "image": "" + } + + +class TestExtrasCorrectness(unittest.TestCase): + pass + + +if __name__ == "__main__": + unittest.main() diff --git a/test/advanced_features/txt2img_test.py b/test/advanced_features/txt2img_test.py new file mode 100644 index 00000000..36ed7b9a --- /dev/null +++ b/test/advanced_features/txt2img_test.py @@ -0,0 +1,47 @@ +import unittest +import requests + + +class TestTxt2ImgWorking(unittest.TestCase): + def setUp(self): + self.url_txt2img = "http://localhost:7860/sdapi/v1/txt2img" + self.simple_txt2img = { + "enable_hr": False, + "denoising_strength": 0, + "firstphase_width": 0, + "firstphase_height": 0, + "prompt": "example prompt", + "styles": [], + "seed": -1, + "subseed": -1, + "subseed_strength": 0, + "seed_resize_from_h": -1, + "seed_resize_from_w": -1, + "batch_size": 1, + "n_iter": 1, + "steps": 3, + "cfg_scale": 7, + "width": 64, + "height": 64, + "restore_faces": False, + "tiling": False, + "negative_prompt": "", + "eta": 0, + "s_churn": 0, + "s_tmax": 0, + "s_tmin": 0, + "s_noise": 1, + "sampler_index": "Euler a" + } + + def test_txt2img_with_restore_faces_performed(self): + self.simple_txt2img["restore_faces"] = True + self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200) + + +class TestTxt2ImgCorrectness(unittest.TestCase): + pass + + +if __name__ == "__main__": + unittest.main() diff --git a/test/basic_features/__init__.py b/test/basic_features/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/test/basic_features/img2img_test.py b/test/basic_features/img2img_test.py new file mode 100644 index 00000000..0a9c1e8a --- /dev/null +++ b/test/basic_features/img2img_test.py @@ -0,0 +1,55 @@ +import unittest +import requests +from gradio.processing_utils import encode_pil_to_base64 +from PIL import Image + + +class TestImg2ImgWorking(unittest.TestCase): + def setUp(self): + self.url_img2img = "http://localhost:7860/sdapi/v1/img2img" + self.simple_img2img = { + "init_images": [encode_pil_to_base64(Image.open(r"test/test_files/img2img_basic.png"))], + "resize_mode": 0, + "denoising_strength": 0.75, + "mask": None, + "mask_blur": 4, + "inpainting_fill": 0, + "inpaint_full_res": False, + "inpaint_full_res_padding": 0, + "inpainting_mask_invert": 0, + "prompt": "example prompt", + "styles": [], + "seed": -1, + "subseed": -1, + "subseed_strength": 0, + "seed_resize_from_h": -1, + "seed_resize_from_w": -1, + "batch_size": 1, + "n_iter": 1, + "steps": 3, + "cfg_scale": 7, + "width": 64, + "height": 64, + "restore_faces": False, + "tiling": False, + "negative_prompt": "", + "eta": 0, + "s_churn": 0, + "s_tmax": 0, + "s_tmin": 0, + "s_noise": 1, + "override_settings": {}, + "sampler_index": "Euler a", + "include_init_images": False + } + + def test_img2img_simple_performed(self): + self.assertEqual(requests.post(self.url_img2img, json=self.simple_img2img).status_code, 200) + + def test_inpainting_masked_performed(self): + self.simple_img2img["mask"] = encode_pil_to_base64(Image.open(r"test/test_files/mask_basic.png")) + self.assertEqual(requests.post(self.url_img2img, json=self.simple_img2img).status_code, 200) + + +if __name__ == "__main__": + unittest.main() diff --git a/test/basic_features/txt2img_test.py b/test/basic_features/txt2img_test.py new file mode 100644 index 00000000..fe4af999 --- /dev/null +++ b/test/basic_features/txt2img_test.py @@ -0,0 +1,72 @@ +import unittest +import requests + + +class TestTxt2ImgWorking(unittest.TestCase): + def setUp(self): + self.url_txt2img = "http://localhost:7860/sdapi/v1/txt2img" + self.simple_txt2img = { + "enable_hr": False, + "denoising_strength": 0, + "firstphase_width": 0, + "firstphase_height": 0, + "prompt": "example prompt", + "styles": [], + "seed": -1, + "subseed": -1, + "subseed_strength": 0, + "seed_resize_from_h": -1, + "seed_resize_from_w": -1, + "batch_size": 1, + "n_iter": 1, + "steps": 3, + "cfg_scale": 7, + "width": 64, + "height": 64, + "restore_faces": False, + "tiling": False, + "negative_prompt": "", + "eta": 0, + "s_churn": 0, + "s_tmax": 0, + "s_tmin": 0, + "s_noise": 1, + "sampler_index": "Euler a" + } + + def test_txt2img_simple_performed(self): + self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200) + + def test_txt2img_with_negative_prompt_performed(self): + self.simple_txt2img["negative_prompt"] = "example negative prompt" + self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200) + + def test_txt2img_not_square_image_performed(self): + self.simple_txt2img["height"] = 128 + self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200) + + def test_txt2img_with_hrfix_performed(self): + self.simple_txt2img["enable_hr"] = True + self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200) + + def test_txt2img_with_restore_faces_performed(self): + self.simple_txt2img["restore_faces"] = True + self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200) + + def test_txt2img_with_tiling_performed(self): + self.simple_txt2img["tiling"] = True + self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200) + + def test_txt2img_with_vanilla_sampler_performed(self): + self.simple_txt2img["sampler_index"] = "PLMS" + self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200) + self.simple_txt2img["sampler_index"] = "DDIM" + self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200) + + def test_txt2img_multiple_batches_performed(self): + self.simple_txt2img["n_iter"] = 2 + self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200) + + +if __name__ == "__main__": + unittest.main() diff --git a/test/basic_features/utils_test.py b/test/basic_features/utils_test.py new file mode 100644 index 00000000..9706db8b --- /dev/null +++ b/test/basic_features/utils_test.py @@ -0,0 +1,67 @@ +import unittest +import requests + +class UtilsTests(unittest.TestCase): + def setUp(self): + self.url_options = "http://localhost:7860/sdapi/v1/options" + self.url_cmd_flags = "http://localhost:7860/sdapi/v1/cmd-flags" + self.url_samplers = "http://localhost:7860/sdapi/v1/samplers" + self.url_upscalers = "http://localhost:7860/sdapi/v1/upscalers" + self.url_sd_models = "http://localhost:7860/sdapi/v1/sd-models" + self.url_hypernetworks = "http://localhost:7860/sdapi/v1/hypernetworks" + self.url_face_restorers = "http://localhost:7860/sdapi/v1/face-restorers" + self.url_realesrgan_models = "http://localhost:7860/sdapi/v1/realesrgan-models" + self.url_prompt_styles = "http://localhost:7860/sdapi/v1/prompt-styles" + self.url_artist_categories = "http://localhost:7860/sdapi/v1/artist-categories" + self.url_artists = "http://localhost:7860/sdapi/v1/artists" + + def test_options_get(self): + self.assertEqual(requests.get(self.url_options).status_code, 200) + + # def test_options_write(self): + # response = requests.get(self.url_options) + # self.assertEqual(response.status_code, 200) + + # pre_value = response.json()["send_seed"] + + # self.assertEqual(requests.post(self.url_options, json={"send_seed":not pre_value}).status_code, 200) + + # response = requests.get(self.url_options) + # self.assertEqual(response.status_code, 200) + # self.assertEqual(response.json()["send_seed"], not pre_value) + + # requests.post(self.url_options, json={"send_seed": pre_value}) + + def test_cmd_flags(self): + self.assertEqual(requests.get(self.url_cmd_flags).status_code, 200) + + def test_samplers(self): + self.assertEqual(requests.get(self.url_samplers).status_code, 200) + + def test_upscalers(self): + self.assertEqual(requests.get(self.url_upscalers).status_code, 200) + + def test_sd_models(self): + self.assertEqual(requests.get(self.url_sd_models).status_code, 200) + + def test_hypernetworks(self): + self.assertEqual(requests.get(self.url_hypernetworks).status_code, 200) + + def test_face_restorers(self): + self.assertEqual(requests.get(self.url_face_restorers).status_code, 200) + + def test_realesrgan_models(self): + self.assertEqual(requests.get(self.url_realesrgan_models).status_code, 200) + + def test_prompt_styles(self): + self.assertEqual(requests.get(self.url_prompt_styles).status_code, 200) + + def test_artist_categories(self): + self.assertEqual(requests.get(self.url_artist_categories).status_code, 200) + + def test_artists(self): + self.assertEqual(requests.get(self.url_artists).status_code, 200) + + +if __name__ == "__main__": + unittest.main() diff --git a/test/extras_test.py b/test/extras_test.py deleted file mode 100644 index 9b8ce0f0..00000000 --- a/test/extras_test.py +++ /dev/null @@ -1,29 +0,0 @@ -import unittest - - -class TestExtrasWorking(unittest.TestCase): - def setUp(self): - self.url_img2img = "http://localhost:7860/sdapi/v1/extra-single-image" - self.simple_extras = { - "resize_mode": 0, - "show_extras_results": True, - "gfpgan_visibility": 0, - "codeformer_visibility": 0, - "codeformer_weight": 0, - "upscaling_resize": 2, - "upscaling_resize_w": 512, - "upscaling_resize_h": 512, - "upscaling_crop": True, - "upscaler_1": "None", - "upscaler_2": "None", - "extras_upscaler_2_visibility": 0, - "image": "" - } - - -class TestExtrasCorrectness(unittest.TestCase): - pass - - -if __name__ == "__main__": - unittest.main() diff --git a/test/img2img_test.py b/test/img2img_test.py deleted file mode 100644 index 012a9580..00000000 --- a/test/img2img_test.py +++ /dev/null @@ -1,59 +0,0 @@ -import unittest -import requests -from gradio.processing_utils import encode_pil_to_base64 -from PIL import Image - - -class TestImg2ImgWorking(unittest.TestCase): - def setUp(self): - self.url_img2img = "http://localhost:7860/sdapi/v1/img2img" - self.simple_img2img = { - "init_images": [encode_pil_to_base64(Image.open(r"test/test_files/img2img_basic.png"))], - "resize_mode": 0, - "denoising_strength": 0.75, - "mask": None, - "mask_blur": 4, - "inpainting_fill": 0, - "inpaint_full_res": False, - "inpaint_full_res_padding": 0, - "inpainting_mask_invert": 0, - "prompt": "example prompt", - "styles": [], - "seed": -1, - "subseed": -1, - "subseed_strength": 0, - "seed_resize_from_h": -1, - "seed_resize_from_w": -1, - "batch_size": 1, - "n_iter": 1, - "steps": 3, - "cfg_scale": 7, - "width": 64, - "height": 64, - "restore_faces": False, - "tiling": False, - "negative_prompt": "", - "eta": 0, - "s_churn": 0, - "s_tmax": 0, - "s_tmin": 0, - "s_noise": 1, - "override_settings": {}, - "sampler_index": "Euler a", - "include_init_images": False - } - - def test_img2img_simple_performed(self): - self.assertEqual(requests.post(self.url_img2img, json=self.simple_img2img).status_code, 200) - - def test_inpainting_masked_performed(self): - self.simple_img2img["mask"] = encode_pil_to_base64(Image.open(r"test/test_files/mask_basic.png")) - self.assertEqual(requests.post(self.url_img2img, json=self.simple_img2img).status_code, 200) - - -class TestImg2ImgCorrectness(unittest.TestCase): - pass - - -if __name__ == "__main__": - unittest.main() diff --git a/test/server_poll.py b/test/server_poll.py index 8e63b450..c71e906a 100644 --- a/test/server_poll.py +++ b/test/server_poll.py @@ -3,7 +3,7 @@ import requests import time -def run_tests(proc): +def run_tests(proc, test_dir): timeout_threshold = 240 start_time = time.time() while time.time()-start_time < timeout_threshold: @@ -14,7 +14,9 @@ def run_tests(proc): if proc.poll() is not None: break if proc.poll() is None: - suite = unittest.TestLoader().discover('', pattern='*_test.py') + if test_dir is None: + test_dir = "" + suite = unittest.TestLoader().discover(test_dir, pattern="*_test.py", top_level_dir="test") result = unittest.TextTestRunner(verbosity=2).run(suite) else: print("Launch unsuccessful") diff --git a/test/txt2img_test.py b/test/txt2img_test.py deleted file mode 100644 index ce752085..00000000 --- a/test/txt2img_test.py +++ /dev/null @@ -1,76 +0,0 @@ -import unittest -import requests - - -class TestTxt2ImgWorking(unittest.TestCase): - def setUp(self): - self.url_txt2img = "http://localhost:7860/sdapi/v1/txt2img" - self.simple_txt2img = { - "enable_hr": False, - "denoising_strength": 0, - "firstphase_width": 0, - "firstphase_height": 0, - "prompt": "example prompt", - "styles": [], - "seed": -1, - "subseed": -1, - "subseed_strength": 0, - "seed_resize_from_h": -1, - "seed_resize_from_w": -1, - "batch_size": 1, - "n_iter": 1, - "steps": 3, - "cfg_scale": 7, - "width": 64, - "height": 64, - "restore_faces": False, - "tiling": False, - "negative_prompt": "", - "eta": 0, - "s_churn": 0, - "s_tmax": 0, - "s_tmin": 0, - "s_noise": 1, - "sampler_index": "Euler a" - } - - def test_txt2img_simple_performed(self): - self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200) - - def test_txt2img_with_negative_prompt_performed(self): - self.simple_txt2img["negative_prompt"] = "example negative prompt" - self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200) - - def test_txt2img_not_square_image_performed(self): - self.simple_txt2img["height"] = 128 - self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200) - - def test_txt2img_with_hrfix_performed(self): - self.simple_txt2img["enable_hr"] = True - self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200) - - def test_txt2img_with_restore_faces_performed(self): - self.simple_txt2img["restore_faces"] = True - self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200) - - def test_txt2img_with_tiling_performed(self): - self.simple_txt2img["tiling"] = True - self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200) - - def test_txt2img_with_vanilla_sampler_performed(self): - self.simple_txt2img["sampler_index"] = "PLMS" - self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200) - self.simple_txt2img["sampler_index"] = "DDIM" - self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200) - - def test_txt2img_multiple_batches_performed(self): - self.simple_txt2img["n_iter"] = 2 - self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200) - - -class TestTxt2ImgCorrectness(unittest.TestCase): - pass - - -if __name__ == "__main__": - unittest.main() diff --git a/test/utils_test.py b/test/utils_test.py deleted file mode 100644 index be9e6bf8..00000000 --- a/test/utils_test.py +++ /dev/null @@ -1,63 +0,0 @@ -import unittest -import requests - -class UtilsTests(unittest.TestCase): - def setUp(self): - self.url_options = "http://localhost:7860/sdapi/v1/options" - self.url_cmd_flags = "http://localhost:7860/sdapi/v1/cmd-flags" - self.url_samplers = "http://localhost:7860/sdapi/v1/samplers" - self.url_upscalers = "http://localhost:7860/sdapi/v1/upscalers" - self.url_sd_models = "http://localhost:7860/sdapi/v1/sd-models" - self.url_hypernetworks = "http://localhost:7860/sdapi/v1/hypernetworks" - self.url_face_restorers = "http://localhost:7860/sdapi/v1/face-restorers" - self.url_realesrgan_models = "http://localhost:7860/sdapi/v1/realesrgan-models" - self.url_prompt_styles = "http://localhost:7860/sdapi/v1/prompt-styles" - self.url_artist_categories = "http://localhost:7860/sdapi/v1/artist-categories" - self.url_artists = "http://localhost:7860/sdapi/v1/artists" - - def test_options_get(self): - self.assertEqual(requests.get(self.url_options).status_code, 200) - - # def test_options_write(self): - # response = requests.get(self.url_options) - # self.assertEqual(response.status_code, 200) - - # pre_value = response.json()["send_seed"] - - # self.assertEqual(requests.post(self.url_options, json={"send_seed":not pre_value}).status_code, 200) - - # response = requests.get(self.url_options) - # self.assertEqual(response.status_code, 200) - # self.assertEqual(response.json()["send_seed"], not pre_value) - - # requests.post(self.url_options, json={"send_seed": pre_value}) - - def test_cmd_flags(self): - self.assertEqual(requests.get(self.url_cmd_flags).status_code, 200) - - def test_samplers(self): - self.assertEqual(requests.get(self.url_samplers).status_code, 200) - - def test_upscalers(self): - self.assertEqual(requests.get(self.url_upscalers).status_code, 200) - - def test_sd_models(self): - self.assertEqual(requests.get(self.url_sd_models).status_code, 200) - - def test_hypernetworks(self): - self.assertEqual(requests.get(self.url_hypernetworks).status_code, 200) - - def test_face_restorers(self): - self.assertEqual(requests.get(self.url_face_restorers).status_code, 200) - - def test_realesrgan_models(self): - self.assertEqual(requests.get(self.url_realesrgan_models).status_code, 200) - - def test_prompt_styles(self): - self.assertEqual(requests.get(self.url_prompt_styles).status_code, 200) - - def test_artist_categories(self): - self.assertEqual(requests.get(self.url_artist_categories).status_code, 200) - - def test_artists(self): - self.assertEqual(requests.get(self.url_artists).status_code, 200) \ No newline at end of file -- cgit v1.2.3 From 0646040667b59526ac8346d53efd14dc0e75b01e Mon Sep 17 00:00:00 2001 From: Vladimir Repin <32306715+mezotaken@users.noreply.github.com> Date: Mon, 14 Nov 2022 14:36:07 +0300 Subject: Propagate test error and try it without localhost --- launch.py | 7 ++++--- test/advanced_features/extras_test.py | 2 +- test/advanced_features/txt2img_test.py | 2 +- test/basic_features/img2img_test.py | 2 +- test/basic_features/txt2img_test.py | 2 +- test/basic_features/utils_test.py | 22 +++++++++++----------- test/server_poll.py | 4 +++- 7 files changed, 22 insertions(+), 19 deletions(-) (limited to 'launch.py') diff --git a/launch.py b/launch.py index d0f502c2..8ed1dffc 100644 --- a/launch.py +++ b/launch.py @@ -234,8 +234,8 @@ def prepare_enviroment(): exit(0) if run_tests: - tests(test_dir) - exit(0) + exitcode = tests(test_dir) + exit(exitcode) def tests(test_dir): @@ -251,10 +251,11 @@ def tests(test_dir): proc = subprocess.Popen([sys.executable, *sys.argv], stdout=stdout, stderr=stderr) import test.server_poll - test.server_poll.run_tests(proc, test_dir) + exitcode = test.server_poll.run_tests(proc, test_dir) print(f"Stopping Web UI process with id {proc.pid}") proc.kill() + return exitcode def start(): diff --git a/test/advanced_features/extras_test.py b/test/advanced_features/extras_test.py index 8763f8ed..abdd5aa2 100644 --- a/test/advanced_features/extras_test.py +++ b/test/advanced_features/extras_test.py @@ -3,7 +3,7 @@ import unittest class TestExtrasWorking(unittest.TestCase): def setUp(self): - self.url_img2img = "http://localhost:7860/sdapi/v1/extra-single-image" + self.url_img2img = "http://127.0.0.1:7860/sdapi/v1/extra-single-image" self.simple_extras = { "resize_mode": 0, "show_extras_results": True, diff --git a/test/advanced_features/txt2img_test.py b/test/advanced_features/txt2img_test.py index 36ed7b9a..6ab5a242 100644 --- a/test/advanced_features/txt2img_test.py +++ b/test/advanced_features/txt2img_test.py @@ -4,7 +4,7 @@ import requests class TestTxt2ImgWorking(unittest.TestCase): def setUp(self): - self.url_txt2img = "http://localhost:7860/sdapi/v1/txt2img" + self.url_txt2img = "http://127.0.0.1:7860/sdapi/v1/txt2img" self.simple_txt2img = { "enable_hr": False, "denoising_strength": 0, diff --git a/test/basic_features/img2img_test.py b/test/basic_features/img2img_test.py index 0a9c1e8a..b9a34113 100644 --- a/test/basic_features/img2img_test.py +++ b/test/basic_features/img2img_test.py @@ -6,7 +6,7 @@ from PIL import Image class TestImg2ImgWorking(unittest.TestCase): def setUp(self): - self.url_img2img = "http://localhost:7860/sdapi/v1/img2img" + self.url_img2img = "http://127.0.0.1:7860/sdapi/v1/img2img" self.simple_img2img = { "init_images": [encode_pil_to_base64(Image.open(r"test/test_files/img2img_basic.png"))], "resize_mode": 0, diff --git a/test/basic_features/txt2img_test.py b/test/basic_features/txt2img_test.py index fe4af999..0be675d9 100644 --- a/test/basic_features/txt2img_test.py +++ b/test/basic_features/txt2img_test.py @@ -4,7 +4,7 @@ import requests class TestTxt2ImgWorking(unittest.TestCase): def setUp(self): - self.url_txt2img = "http://localhost:7860/sdapi/v1/txt2img" + self.url_txt2img = "http://127.0.0.1:7860/sdapi/v1/txt2img" self.simple_txt2img = { "enable_hr": False, "denoising_strength": 0, diff --git a/test/basic_features/utils_test.py b/test/basic_features/utils_test.py index 9706db8b..592f7619 100644 --- a/test/basic_features/utils_test.py +++ b/test/basic_features/utils_test.py @@ -3,17 +3,17 @@ import requests class UtilsTests(unittest.TestCase): def setUp(self): - self.url_options = "http://localhost:7860/sdapi/v1/options" - self.url_cmd_flags = "http://localhost:7860/sdapi/v1/cmd-flags" - self.url_samplers = "http://localhost:7860/sdapi/v1/samplers" - self.url_upscalers = "http://localhost:7860/sdapi/v1/upscalers" - self.url_sd_models = "http://localhost:7860/sdapi/v1/sd-models" - self.url_hypernetworks = "http://localhost:7860/sdapi/v1/hypernetworks" - self.url_face_restorers = "http://localhost:7860/sdapi/v1/face-restorers" - self.url_realesrgan_models = "http://localhost:7860/sdapi/v1/realesrgan-models" - self.url_prompt_styles = "http://localhost:7860/sdapi/v1/prompt-styles" - self.url_artist_categories = "http://localhost:7860/sdapi/v1/artist-categories" - self.url_artists = "http://localhost:7860/sdapi/v1/artists" + self.url_options = "http://127.0.0.1:7860/sdapi/v1/options" + self.url_cmd_flags = "http://127.0.0.1:7860/sdapi/v1/cmd-flags" + self.url_samplers = "http://127.0.0.1:7860/sdapi/v1/samplers" + self.url_upscalers = "http://127.0.0.1:7860/sdapi/v1/upscalers" + self.url_sd_models = "http://127.0.0.1:7860/sdapi/v1/sd-models" + self.url_hypernetworks = "http://127.0.0.1:7860/sdapi/v1/hypernetworks" + self.url_face_restorers = "http://127.0.0.1:7860/sdapi/v1/face-restorers" + self.url_realesrgan_models = "http://127.0.0.1:7860/sdapi/v1/realesrgan-models" + self.url_prompt_styles = "http://127.0.0.1:7860/sdapi/v1/prompt-styles" + self.url_artist_categories = "http://127.0.0.1:7860/sdapi/v1/artist-categories" + self.url_artists = "http://127.0.0.1:7860/sdapi/v1/artists" def test_options_get(self): self.assertEqual(requests.get(self.url_options).status_code, 200) diff --git a/test/server_poll.py b/test/server_poll.py index c71e906a..028fd476 100644 --- a/test/server_poll.py +++ b/test/server_poll.py @@ -8,7 +8,7 @@ def run_tests(proc, test_dir): start_time = time.time() while time.time()-start_time < timeout_threshold: try: - requests.head("http://localhost:7860/") + requests.head("http://127.0.0.1:7860/") break except requests.exceptions.ConnectionError: if proc.poll() is not None: @@ -18,5 +18,7 @@ def run_tests(proc, test_dir): test_dir = "" suite = unittest.TestLoader().discover(test_dir, pattern="*_test.py", top_level_dir="test") result = unittest.TextTestRunner(verbosity=2).run(suite) + return len(result.failures) else: print("Launch unsuccessful") + return 1 -- cgit v1.2.3 From 9e4f68acad4697fdf10004eb85d3f6f769c2c70b Mon Sep 17 00:00:00 2001 From: Vladimir Repin <32306715+mezotaken@users.noreply.github.com> Date: Mon, 14 Nov 2022 18:40:15 +0300 Subject: Stop exporting cl args and upload stdout and stderr as artifacts --- .github/workflows/run_tests.yaml | 11 +++++++++-- launch.py | 2 ++ test/advanced_features/extras_test.py | 2 +- test/advanced_features/txt2img_test.py | 2 +- test/basic_features/img2img_test.py | 2 +- test/basic_features/txt2img_test.py | 2 +- test/basic_features/utils_test.py | 22 +++++++++++----------- test/server_poll.py | 2 +- 8 files changed, 27 insertions(+), 18 deletions(-) (limited to 'launch.py') diff --git a/.github/workflows/run_tests.yaml b/.github/workflows/run_tests.yaml index 223a31b9..558b0c61 100644 --- a/.github/workflows/run_tests.yaml +++ b/.github/workflows/run_tests.yaml @@ -22,5 +22,12 @@ jobs: ${{ runner.os }}-pip- - name: Run tests run: | - export COMMANDLINE_ARGS="--tests basic_features --no-half --disable-opt-split-attention --use-cpu all --skip-torch-cuda-test --port 80" - python launch.py + python launch.py --tests basic_features --no-half --disable-opt-split-attention --use-cpu all --skip-torch-cuda-test + - name: Upload main app stdout-stderr + uses: actions/upload-artifact@v3 + if: always() + with: + name: stdout-stderr + path: | + ./test/stdout.txt + ./test/stderr.txt diff --git a/launch.py b/launch.py index 8ed1dffc..ed21d0e6 100644 --- a/launch.py +++ b/launch.py @@ -244,6 +244,8 @@ def tests(test_dir): if "--ckpt" not in sys.argv: sys.argv.append("--ckpt") sys.argv.append("./test/test_files/empty.pt") + if "--skip-torch-cuda-test" not in sys.argv: + sys.argv.append("--skip-torch-cuda-test") print(f"Launching Web UI in another process for testing with arguments: {' '.join(sys.argv[1:])}") diff --git a/test/advanced_features/extras_test.py b/test/advanced_features/extras_test.py index 4b8ae25a..8763f8ed 100644 --- a/test/advanced_features/extras_test.py +++ b/test/advanced_features/extras_test.py @@ -3,7 +3,7 @@ import unittest class TestExtrasWorking(unittest.TestCase): def setUp(self): - self.url_img2img = "http://localhost:80/sdapi/v1/extra-single-image" + self.url_img2img = "http://localhost:7860/sdapi/v1/extra-single-image" self.simple_extras = { "resize_mode": 0, "show_extras_results": True, diff --git a/test/advanced_features/txt2img_test.py b/test/advanced_features/txt2img_test.py index e6c3531a..36ed7b9a 100644 --- a/test/advanced_features/txt2img_test.py +++ b/test/advanced_features/txt2img_test.py @@ -4,7 +4,7 @@ import requests class TestTxt2ImgWorking(unittest.TestCase): def setUp(self): - self.url_txt2img = "http://localhost:80/sdapi/v1/txt2img" + self.url_txt2img = "http://localhost:7860/sdapi/v1/txt2img" self.simple_txt2img = { "enable_hr": False, "denoising_strength": 0, diff --git a/test/basic_features/img2img_test.py b/test/basic_features/img2img_test.py index c4c9a90f..0a9c1e8a 100644 --- a/test/basic_features/img2img_test.py +++ b/test/basic_features/img2img_test.py @@ -6,7 +6,7 @@ from PIL import Image class TestImg2ImgWorking(unittest.TestCase): def setUp(self): - self.url_img2img = "http://localhost:80/sdapi/v1/img2img" + self.url_img2img = "http://localhost:7860/sdapi/v1/img2img" self.simple_img2img = { "init_images": [encode_pil_to_base64(Image.open(r"test/test_files/img2img_basic.png"))], "resize_mode": 0, diff --git a/test/basic_features/txt2img_test.py b/test/basic_features/txt2img_test.py index 4f1fc77d..fe4af999 100644 --- a/test/basic_features/txt2img_test.py +++ b/test/basic_features/txt2img_test.py @@ -4,7 +4,7 @@ import requests class TestTxt2ImgWorking(unittest.TestCase): def setUp(self): - self.url_txt2img = "http://localhost:80/sdapi/v1/txt2img" + self.url_txt2img = "http://localhost:7860/sdapi/v1/txt2img" self.simple_txt2img = { "enable_hr": False, "denoising_strength": 0, diff --git a/test/basic_features/utils_test.py b/test/basic_features/utils_test.py index fdb72b9a..9706db8b 100644 --- a/test/basic_features/utils_test.py +++ b/test/basic_features/utils_test.py @@ -3,17 +3,17 @@ import requests class UtilsTests(unittest.TestCase): def setUp(self): - self.url_options = "http://localhost:80/sdapi/v1/options" - self.url_cmd_flags = "http://localhost:80/sdapi/v1/cmd-flags" - self.url_samplers = "http://localhost:80/sdapi/v1/samplers" - self.url_upscalers = "http://localhost:80/sdapi/v1/upscalers" - self.url_sd_models = "http://localhost:80/sdapi/v1/sd-models" - self.url_hypernetworks = "http://localhost:80/sdapi/v1/hypernetworks" - self.url_face_restorers = "http://localhost:80/sdapi/v1/face-restorers" - self.url_realesrgan_models = "http://localhost:80/sdapi/v1/realesrgan-models" - self.url_prompt_styles = "http://localhost:80/sdapi/v1/prompt-styles" - self.url_artist_categories = "http://localhost:80/sdapi/v1/artist-categories" - self.url_artists = "http://localhost:80/sdapi/v1/artists" + self.url_options = "http://localhost:7860/sdapi/v1/options" + self.url_cmd_flags = "http://localhost:7860/sdapi/v1/cmd-flags" + self.url_samplers = "http://localhost:7860/sdapi/v1/samplers" + self.url_upscalers = "http://localhost:7860/sdapi/v1/upscalers" + self.url_sd_models = "http://localhost:7860/sdapi/v1/sd-models" + self.url_hypernetworks = "http://localhost:7860/sdapi/v1/hypernetworks" + self.url_face_restorers = "http://localhost:7860/sdapi/v1/face-restorers" + self.url_realesrgan_models = "http://localhost:7860/sdapi/v1/realesrgan-models" + self.url_prompt_styles = "http://localhost:7860/sdapi/v1/prompt-styles" + self.url_artist_categories = "http://localhost:7860/sdapi/v1/artist-categories" + self.url_artists = "http://localhost:7860/sdapi/v1/artists" def test_options_get(self): self.assertEqual(requests.get(self.url_options).status_code, 200) diff --git a/test/server_poll.py b/test/server_poll.py index e4462b6c..d4df697b 100644 --- a/test/server_poll.py +++ b/test/server_poll.py @@ -8,7 +8,7 @@ def run_tests(proc, test_dir): start_time = time.time() while time.time()-start_time < timeout_threshold: try: - requests.head("http://localhost:80/") + requests.head("http://localhost:7860/") break except requests.exceptions.ConnectionError: if proc.poll() is not None: -- cgit v1.2.3 From ce6911158b5b2f9cf79b405a1f368f875492044d Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 26 Nov 2022 16:10:46 +0300 Subject: Add support Stable Diffusion 2.0 --- README.md | 21 +- launch.py | 12 +- modules/paths.py | 2 +- modules/sd_hijack.py | 297 +++--------------------- modules/sd_hijack_clip.py | 301 +++++++++++++++++++++++++ modules/sd_hijack_inpainting.py | 20 +- modules/sd_hijack_open_clip.py | 37 +++ modules/sd_samplers.py | 14 +- modules/shared.py | 34 ++- modules/textual_inversion/textual_inversion.py | 7 +- modules/ui.py | 13 +- requirements.txt | 1 + requirements_versions.txt | 1 + v1-inference.yaml | 70 ++++++ webui.py | 5 +- 15 files changed, 504 insertions(+), 331 deletions(-) create mode 100644 modules/sd_hijack_clip.py create mode 100644 modules/sd_hijack_open_clip.py create mode 100644 v1-inference.yaml (limited to 'launch.py') diff --git a/README.md b/README.md index 5f5ab3aa..8a4ffade 100644 --- a/README.md +++ b/README.md @@ -84,26 +84,7 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web - API - Support for dedicated [inpainting model](https://github.com/runwayml/stable-diffusion#inpainting-with-stable-diffusion) by RunwayML. - via extension: [Aesthetic Gradients](https://github.com/AUTOMATIC1111/stable-diffusion-webui-aesthetic-gradients), a way to generate images with a specific aesthetic by using clip images embds (implementation of [https://github.com/vicgalle/stable-diffusion-aesthetic-gradients](https://github.com/vicgalle/stable-diffusion-aesthetic-gradients)) - -## Where are Aesthetic Gradients?!?! -Aesthetic Gradients are now an extension. You can install it using git: - -```commandline -git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui-aesthetic-gradients extensions/aesthetic-gradients -``` - -After running this command, make sure that you have `aesthetic-gradients` dir in webui's `extensions` directory and restart -the UI. The interface for Aesthetic Gradients should appear exactly the same as it was. - -## Where is History/Image browser?!?! -Image browser is now an extension. You can install it using git: - -```commandline -git clone https://github.com/yfszzx/stable-diffusion-webui-images-browser extensions/images-browser -``` - -After running this command, make sure that you have `images-browser` dir in webui's `extensions` directory and restart -the UI. The interface for Image browser should appear exactly the same as it was. +- [Stable Diffusion 2.0](https://github.com/Stability-AI/stablediffusion) support - see [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#stable-diffusion-20) for instructions ## Installation and Running Make sure the required [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) are met and follow the instructions available for both [NVidia](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs) (recommended) and [AMD](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs) GPUs. diff --git a/launch.py b/launch.py index d2f1055c..b1626cb5 100644 --- a/launch.py +++ b/launch.py @@ -134,18 +134,19 @@ def prepare_enviroment(): gfpgan_package = os.environ.get('GFPGAN_PACKAGE', "git+https://github.com/TencentARC/GFPGAN.git@8d2447a2d918f8eba5a4a01463fd48e45126a379") clip_package = os.environ.get('CLIP_PACKAGE', "git+https://github.com/openai/CLIP.git@d50d76daa670286dd6cacf3bcd80b5e4823fc8e1") + openclip_package = os.environ.get('OPENCLIP_PACKAGE', "git+https://github.com/mlfoundations/open_clip.git@bb6e834e9c70d9c27d0dc3ecedeebeaeb1ffad6b") xformers_windows_package = os.environ.get('XFORMERS_WINDOWS_PACKAGE', 'https://github.com/C43H66N12O12S2/stable-diffusion-webui/releases/download/f/xformers-0.0.14.dev0-cp310-cp310-win_amd64.whl') - stable_diffusion_repo = os.environ.get('STABLE_DIFFUSION_REPO', "https://github.com/CompVis/stable-diffusion.git") + stable_diffusion_repo = os.environ.get('STABLE_DIFFUSION_REPO', "https://github.com/Stability-AI/stablediffusion.git") taming_transformers_repo = os.environ.get('TAMING_TRANSFORMERS_REPO', "https://github.com/CompVis/taming-transformers.git") k_diffusion_repo = os.environ.get('K_DIFFUSION_REPO', 'https://github.com/crowsonkb/k-diffusion.git') codeformer_repo = os.environ.get('CODEFORMER_REPO', 'https://github.com/sczhou/CodeFormer.git') blip_repo = os.environ.get('BLIP_REPO', 'https://github.com/salesforce/BLIP.git') - stable_diffusion_commit_hash = os.environ.get('STABLE_DIFFUSION_COMMIT_HASH', "69ae4b35e0a0f6ee1af8bb9a5d0016ccb27e36dc") + stable_diffusion_commit_hash = os.environ.get('STABLE_DIFFUSION_COMMIT_HASH', "47b6b607fdd31875c9279cd2f4f16b92e4ea958e") taming_transformers_commit_hash = os.environ.get('TAMING_TRANSFORMERS_COMMIT_HASH', "24268930bf1dce879235a7fddd0b2355b84d7ea6") - k_diffusion_commit_hash = os.environ.get('K_DIFFUSION_COMMIT_HASH', "60e5042ca0da89c14d1dd59d73883280f8fce991") + k_diffusion_commit_hash = os.environ.get('K_DIFFUSION_COMMIT_HASH', "5b3af030dd83e0297272d861c19477735d0317ec") codeformer_commit_hash = os.environ.get('CODEFORMER_COMMIT_HASH', "c5b4593074ba6214284d6acd5f1719b6c5d739af") blip_commit_hash = os.environ.get('BLIP_COMMIT_HASH', "48211a1594f1321b00f14c9f7a5b4813144b2fb9") @@ -179,6 +180,9 @@ def prepare_enviroment(): if not is_installed("clip"): run_pip(f"install {clip_package}", "clip") + if not is_installed("open_clip"): + run_pip(f"install {openclip_package}", "open_clip") + if (not is_installed("xformers") or reinstall_xformers) and xformers: if platform.system() == "Windows": if platform.python_version().startswith("3.10"): @@ -196,7 +200,7 @@ def prepare_enviroment(): os.makedirs(dir_repos, exist_ok=True) - git_clone(stable_diffusion_repo, repo_dir('stable-diffusion'), "Stable Diffusion", stable_diffusion_commit_hash) + git_clone(stable_diffusion_repo, repo_dir('stable-diffusion-stability-ai'), "Stable Diffusion", stable_diffusion_commit_hash) git_clone(taming_transformers_repo, repo_dir('taming-transformers'), "Taming Transformers", taming_transformers_commit_hash) git_clone(k_diffusion_repo, repo_dir('k-diffusion'), "K-diffusion", k_diffusion_commit_hash) git_clone(codeformer_repo, repo_dir('CodeFormer'), "CodeFormer", codeformer_commit_hash) diff --git a/modules/paths.py b/modules/paths.py index 1e7a2fbc..4dd03a35 100644 --- a/modules/paths.py +++ b/modules/paths.py @@ -9,7 +9,7 @@ sys.path.insert(0, script_path) # search for directory of stable diffusion in following places sd_path = None -possible_sd_paths = [os.path.join(script_path, 'repositories/stable-diffusion'), '.', os.path.dirname(script_path)] +possible_sd_paths = [os.path.join(script_path, 'repositories/stable-diffusion-stability-ai'), '.', os.path.dirname(script_path)] for possible_sd_path in possible_sd_paths: if os.path.exists(os.path.join(possible_sd_path, 'ldm/models/diffusion/ddpm.py')): sd_path = os.path.abspath(possible_sd_path) diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index eaedac13..d5243fd3 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -9,18 +9,29 @@ from torch.nn.functional import silu import modules.textual_inversion.textual_inversion from modules import prompt_parser, devices, sd_hijack_optimizations, shared -from modules.shared import opts, device, cmd_opts +from modules.shared import cmd_opts +from modules import sd_hijack_clip, sd_hijack_open_clip + from modules.sd_hijack_optimizations import invokeAI_mps_available import ldm.modules.attention import ldm.modules.diffusionmodules.model import ldm.models.diffusion.ddim import ldm.models.diffusion.plms +import ldm.modules.encoders.modules attention_CrossAttention_forward = ldm.modules.attention.CrossAttention.forward diffusionmodules_model_nonlinearity = ldm.modules.diffusionmodules.model.nonlinearity diffusionmodules_model_AttnBlock_forward = ldm.modules.diffusionmodules.model.AttnBlock.forward +# new memory efficient cross attention blocks do not support hypernets and we already +# have memory efficient cross attention anyway, so this disables SD2.0's memory efficient cross attention +ldm.modules.attention.MemoryEfficientCrossAttention = ldm.modules.attention.CrossAttention +ldm.modules.attention.BasicTransformerBlock.ATTENTION_MODES["softmax-xformers"] = ldm.modules.attention.CrossAttention + +# silence new console spam from SD2 +ldm.modules.attention.print = lambda *args: None +ldm.modules.diffusionmodules.model.print = lambda *args: None def apply_optimizations(): undo_optimizations() @@ -49,16 +60,11 @@ def apply_optimizations(): def undo_optimizations(): - from modules.hypernetworks import hypernetwork - - ldm.modules.attention.CrossAttention.forward = hypernetwork.attention_CrossAttention_forward + ldm.modules.attention.CrossAttention.forward = attention_CrossAttention_forward # this stops hypernets from working ldm.modules.diffusionmodules.model.nonlinearity = diffusionmodules_model_nonlinearity ldm.modules.diffusionmodules.model.AttnBlock.forward = diffusionmodules_model_AttnBlock_forward -def get_target_prompt_token_count(token_count): - return math.ceil(max(token_count, 1) / 75) * 75 - class StableDiffusionModelHijack: fixes = None @@ -70,10 +76,13 @@ class StableDiffusionModelHijack: embedding_db = modules.textual_inversion.textual_inversion.EmbeddingDatabase(cmd_opts.embeddings_dir) def hijack(self, m): - model_embeddings = m.cond_stage_model.transformer.text_model.embeddings - - model_embeddings.token_embedding = EmbeddingsWithFixes(model_embeddings.token_embedding, self) - m.cond_stage_model = FrozenCLIPEmbedderWithCustomWords(m.cond_stage_model, self) + if type(m.cond_stage_model) == ldm.modules.encoders.modules.FrozenCLIPEmbedder: + model_embeddings = m.cond_stage_model.transformer.text_model.embeddings + model_embeddings.token_embedding = EmbeddingsWithFixes(model_embeddings.token_embedding, self) + m.cond_stage_model = sd_hijack_clip.FrozenCLIPEmbedderWithCustomWords(m.cond_stage_model, self) + elif type(m.cond_stage_model) == ldm.modules.encoders.modules.FrozenOpenCLIPEmbedder: + m.cond_stage_model.model.token_embedding = EmbeddingsWithFixes(m.cond_stage_model.model.token_embedding, self) + m.cond_stage_model = sd_hijack_open_clip.FrozenOpenCLIPEmbedderWithCustomWords(m.cond_stage_model, self) self.clip = m.cond_stage_model @@ -89,12 +98,15 @@ class StableDiffusionModelHijack: self.layers = flatten(m) def undo_hijack(self, m): - if type(m.cond_stage_model) == FrozenCLIPEmbedderWithCustomWords: + if type(m.cond_stage_model) == sd_hijack_clip.FrozenCLIPEmbedderWithCustomWords: m.cond_stage_model = m.cond_stage_model.wrapped - model_embeddings = m.cond_stage_model.transformer.text_model.embeddings - if type(model_embeddings.token_embedding) == EmbeddingsWithFixes: - model_embeddings.token_embedding = model_embeddings.token_embedding.wrapped + model_embeddings = m.cond_stage_model.transformer.text_model.embeddings + if type(model_embeddings.token_embedding) == EmbeddingsWithFixes: + model_embeddings.token_embedding = model_embeddings.token_embedding.wrapped + elif type(m.cond_stage_model) == sd_hijack_open_clip.FrozenOpenCLIPEmbedderWithCustomWords: + m.cond_stage_model.wrapped.model.token_embedding = m.cond_stage_model.wrapped.model.token_embedding.wrapped + m.cond_stage_model = m.cond_stage_model.wrapped self.apply_circular(False) self.layers = None @@ -114,261 +126,8 @@ class StableDiffusionModelHijack: def tokenize(self, text): _, remade_batch_tokens, _, _, _, token_count = self.clip.process_text([text]) - return remade_batch_tokens[0], token_count, get_target_prompt_token_count(token_count) - - -class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): - def __init__(self, wrapped, hijack): - super().__init__() - self.wrapped = wrapped - self.hijack: StableDiffusionModelHijack = hijack - self.tokenizer = wrapped.tokenizer - self.token_mults = {} - - self.comma_token = [v for k, v in self.tokenizer.get_vocab().items() if k == ','][0] - - tokens_with_parens = [(k, v) for k, v in self.tokenizer.get_vocab().items() if '(' in k or ')' in k or '[' in k or ']' in k] - for text, ident in tokens_with_parens: - mult = 1.0 - for c in text: - if c == '[': - mult /= 1.1 - if c == ']': - mult *= 1.1 - if c == '(': - mult *= 1.1 - if c == ')': - mult /= 1.1 - - if mult != 1.0: - self.token_mults[ident] = mult - - def tokenize_line(self, line, used_custom_terms, hijack_comments): - id_end = self.wrapped.tokenizer.eos_token_id - - if opts.enable_emphasis: - parsed = prompt_parser.parse_prompt_attention(line) - else: - parsed = [[line, 1.0]] - - tokenized = self.wrapped.tokenizer([text for text, _ in parsed], truncation=False, add_special_tokens=False)["input_ids"] - - fixes = [] - remade_tokens = [] - multipliers = [] - last_comma = -1 - - for tokens, (text, weight) in zip(tokenized, parsed): - i = 0 - while i < len(tokens): - token = tokens[i] - - embedding, embedding_length_in_tokens = self.hijack.embedding_db.find_embedding_at_position(tokens, i) - - if token == self.comma_token: - last_comma = len(remade_tokens) - elif opts.comma_padding_backtrack != 0 and max(len(remade_tokens), 1) % 75 == 0 and last_comma != -1 and len(remade_tokens) - last_comma <= opts.comma_padding_backtrack: - last_comma += 1 - reloc_tokens = remade_tokens[last_comma:] - reloc_mults = multipliers[last_comma:] - - remade_tokens = remade_tokens[:last_comma] - length = len(remade_tokens) - - rem = int(math.ceil(length / 75)) * 75 - length - remade_tokens += [id_end] * rem + reloc_tokens - multipliers = multipliers[:last_comma] + [1.0] * rem + reloc_mults - - if embedding is None: - remade_tokens.append(token) - multipliers.append(weight) - i += 1 - else: - emb_len = int(embedding.vec.shape[0]) - iteration = len(remade_tokens) // 75 - if (len(remade_tokens) + emb_len) // 75 != iteration: - rem = (75 * (iteration + 1) - len(remade_tokens)) - remade_tokens += [id_end] * rem - multipliers += [1.0] * rem - iteration += 1 - fixes.append((iteration, (len(remade_tokens) % 75, embedding))) - remade_tokens += [0] * emb_len - multipliers += [weight] * emb_len - used_custom_terms.append((embedding.name, embedding.checksum())) - i += embedding_length_in_tokens - - token_count = len(remade_tokens) - prompt_target_length = get_target_prompt_token_count(token_count) - tokens_to_add = prompt_target_length - len(remade_tokens) - - remade_tokens = remade_tokens + [id_end] * tokens_to_add - multipliers = multipliers + [1.0] * tokens_to_add - - return remade_tokens, fixes, multipliers, token_count - - def process_text(self, texts): - used_custom_terms = [] - remade_batch_tokens = [] - hijack_comments = [] - hijack_fixes = [] - token_count = 0 - - cache = {} - batch_multipliers = [] - for line in texts: - if line in cache: - remade_tokens, fixes, multipliers = cache[line] - else: - remade_tokens, fixes, multipliers, current_token_count = self.tokenize_line(line, used_custom_terms, hijack_comments) - token_count = max(current_token_count, token_count) - - cache[line] = (remade_tokens, fixes, multipliers) - - remade_batch_tokens.append(remade_tokens) - hijack_fixes.append(fixes) - batch_multipliers.append(multipliers) - - return batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count - - def process_text_old(self, text): - id_start = self.wrapped.tokenizer.bos_token_id - id_end = self.wrapped.tokenizer.eos_token_id - maxlen = self.wrapped.max_length # you get to stay at 77 - used_custom_terms = [] - remade_batch_tokens = [] - overflowing_words = [] - hijack_comments = [] - hijack_fixes = [] - token_count = 0 - - cache = {} - batch_tokens = self.wrapped.tokenizer(text, truncation=False, add_special_tokens=False)["input_ids"] - batch_multipliers = [] - for tokens in batch_tokens: - tuple_tokens = tuple(tokens) - - if tuple_tokens in cache: - remade_tokens, fixes, multipliers = cache[tuple_tokens] - else: - fixes = [] - remade_tokens = [] - multipliers = [] - mult = 1.0 - - i = 0 - while i < len(tokens): - token = tokens[i] - - embedding, embedding_length_in_tokens = self.hijack.embedding_db.find_embedding_at_position(tokens, i) - - mult_change = self.token_mults.get(token) if opts.enable_emphasis else None - if mult_change is not None: - mult *= mult_change - i += 1 - elif embedding is None: - remade_tokens.append(token) - multipliers.append(mult) - i += 1 - else: - emb_len = int(embedding.vec.shape[0]) - fixes.append((len(remade_tokens), embedding)) - remade_tokens += [0] * emb_len - multipliers += [mult] * emb_len - used_custom_terms.append((embedding.name, embedding.checksum())) - i += embedding_length_in_tokens - - if len(remade_tokens) > maxlen - 2: - vocab = {v: k for k, v in self.wrapped.tokenizer.get_vocab().items()} - ovf = remade_tokens[maxlen - 2:] - overflowing_words = [vocab.get(int(x), "") for x in ovf] - overflowing_text = self.wrapped.tokenizer.convert_tokens_to_string(''.join(overflowing_words)) - hijack_comments.append(f"Warning: too many input tokens; some ({len(overflowing_words)}) have been truncated:\n{overflowing_text}\n") - - token_count = len(remade_tokens) - remade_tokens = remade_tokens + [id_end] * (maxlen - 2 - len(remade_tokens)) - remade_tokens = [id_start] + remade_tokens[0:maxlen - 2] + [id_end] - cache[tuple_tokens] = (remade_tokens, fixes, multipliers) - - multipliers = multipliers + [1.0] * (maxlen - 2 - len(multipliers)) - multipliers = [1.0] + multipliers[0:maxlen - 2] + [1.0] - - remade_batch_tokens.append(remade_tokens) - hijack_fixes.append(fixes) - batch_multipliers.append(multipliers) - return batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count - - def forward(self, text): - use_old = opts.use_old_emphasis_implementation - if use_old: - batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count = self.process_text_old(text) - else: - batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count = self.process_text(text) - - self.hijack.comments += hijack_comments - - if len(used_custom_terms) > 0: - self.hijack.comments.append("Used embeddings: " + ", ".join([f'{word} [{checksum}]' for word, checksum in used_custom_terms])) - - if use_old: - self.hijack.fixes = hijack_fixes - return self.process_tokens(remade_batch_tokens, batch_multipliers) - - z = None - i = 0 - while max(map(len, remade_batch_tokens)) != 0: - rem_tokens = [x[75:] for x in remade_batch_tokens] - rem_multipliers = [x[75:] for x in batch_multipliers] - - self.hijack.fixes = [] - for unfiltered in hijack_fixes: - fixes = [] - for fix in unfiltered: - if fix[0] == i: - fixes.append(fix[1]) - self.hijack.fixes.append(fixes) - - tokens = [] - multipliers = [] - for j in range(len(remade_batch_tokens)): - if len(remade_batch_tokens[j]) > 0: - tokens.append(remade_batch_tokens[j][:75]) - multipliers.append(batch_multipliers[j][:75]) - else: - tokens.append([self.wrapped.tokenizer.eos_token_id] * 75) - multipliers.append([1.0] * 75) - - z1 = self.process_tokens(tokens, multipliers) - z = z1 if z is None else torch.cat((z, z1), axis=-2) - - remade_batch_tokens = rem_tokens - batch_multipliers = rem_multipliers - i += 1 - - return z - - def process_tokens(self, remade_batch_tokens, batch_multipliers): - if not opts.use_old_emphasis_implementation: - remade_batch_tokens = [[self.wrapped.tokenizer.bos_token_id] + x[:75] + [self.wrapped.tokenizer.eos_token_id] for x in remade_batch_tokens] - batch_multipliers = [[1.0] + x[:75] + [1.0] for x in batch_multipliers] - - tokens = torch.asarray(remade_batch_tokens).to(device) - outputs = self.wrapped.transformer(input_ids=tokens, output_hidden_states=-opts.CLIP_stop_at_last_layers) - - if opts.CLIP_stop_at_last_layers > 1: - z = outputs.hidden_states[-opts.CLIP_stop_at_last_layers] - z = self.wrapped.transformer.text_model.final_layer_norm(z) - else: - z = outputs.last_hidden_state - - # restoring original mean is likely not correct, but it seems to work well to prevent artifacts that happen otherwise - batch_multipliers_of_same_length = [x + [1.0] * (75 - len(x)) for x in batch_multipliers] - batch_multipliers = torch.asarray(batch_multipliers_of_same_length).to(device) - original_mean = z.mean() - z *= batch_multipliers.reshape(batch_multipliers.shape + (1,)).expand(z.shape) - new_mean = z.mean() - z *= original_mean / new_mean + return remade_batch_tokens[0], token_count, sd_hijack_clip.get_target_prompt_token_count(token_count) - return z class EmbeddingsWithFixes(torch.nn.Module): diff --git a/modules/sd_hijack_clip.py b/modules/sd_hijack_clip.py new file mode 100644 index 00000000..b451d1cf --- /dev/null +++ b/modules/sd_hijack_clip.py @@ -0,0 +1,301 @@ +import math + +import torch + +from modules import prompt_parser, devices +from modules.shared import opts + + +def get_target_prompt_token_count(token_count): + return math.ceil(max(token_count, 1) / 75) * 75 + + +class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module): + def __init__(self, wrapped, hijack): + super().__init__() + self.wrapped = wrapped + self.hijack = hijack + + def tokenize(self, texts): + raise NotImplementedError + + def encode_with_transformers(self, tokens): + raise NotImplementedError + + def encode_embedding_init_text(self, init_text, nvpt): + raise NotImplementedError + + def tokenize_line(self, line, used_custom_terms, hijack_comments): + if opts.enable_emphasis: + parsed = prompt_parser.parse_prompt_attention(line) + else: + parsed = [[line, 1.0]] + + tokenized = self.tokenize([text for text, _ in parsed]) + + fixes = [] + remade_tokens = [] + multipliers = [] + last_comma = -1 + + for tokens, (text, weight) in zip(tokenized, parsed): + i = 0 + while i < len(tokens): + token = tokens[i] + + embedding, embedding_length_in_tokens = self.hijack.embedding_db.find_embedding_at_position(tokens, i) + + if token == self.comma_token: + last_comma = len(remade_tokens) + elif opts.comma_padding_backtrack != 0 and max(len(remade_tokens), 1) % 75 == 0 and last_comma != -1 and len(remade_tokens) - last_comma <= opts.comma_padding_backtrack: + last_comma += 1 + reloc_tokens = remade_tokens[last_comma:] + reloc_mults = multipliers[last_comma:] + + remade_tokens = remade_tokens[:last_comma] + length = len(remade_tokens) + + rem = int(math.ceil(length / 75)) * 75 - length + remade_tokens += [self.id_end] * rem + reloc_tokens + multipliers = multipliers[:last_comma] + [1.0] * rem + reloc_mults + + if embedding is None: + remade_tokens.append(token) + multipliers.append(weight) + i += 1 + else: + emb_len = int(embedding.vec.shape[0]) + iteration = len(remade_tokens) // 75 + if (len(remade_tokens) + emb_len) // 75 != iteration: + rem = (75 * (iteration + 1) - len(remade_tokens)) + remade_tokens += [self.id_end] * rem + multipliers += [1.0] * rem + iteration += 1 + fixes.append((iteration, (len(remade_tokens) % 75, embedding))) + remade_tokens += [0] * emb_len + multipliers += [weight] * emb_len + used_custom_terms.append((embedding.name, embedding.checksum())) + i += embedding_length_in_tokens + + token_count = len(remade_tokens) + prompt_target_length = get_target_prompt_token_count(token_count) + tokens_to_add = prompt_target_length - len(remade_tokens) + + remade_tokens = remade_tokens + [self.id_end] * tokens_to_add + multipliers = multipliers + [1.0] * tokens_to_add + + return remade_tokens, fixes, multipliers, token_count + + def process_text(self, texts): + used_custom_terms = [] + remade_batch_tokens = [] + hijack_comments = [] + hijack_fixes = [] + token_count = 0 + + cache = {} + batch_multipliers = [] + for line in texts: + if line in cache: + remade_tokens, fixes, multipliers = cache[line] + else: + remade_tokens, fixes, multipliers, current_token_count = self.tokenize_line(line, used_custom_terms, hijack_comments) + token_count = max(current_token_count, token_count) + + cache[line] = (remade_tokens, fixes, multipliers) + + remade_batch_tokens.append(remade_tokens) + hijack_fixes.append(fixes) + batch_multipliers.append(multipliers) + + return batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count + + def process_text_old(self, texts): + id_start = self.id_start + id_end = self.id_end + maxlen = self.wrapped.max_length # you get to stay at 77 + used_custom_terms = [] + remade_batch_tokens = [] + hijack_comments = [] + hijack_fixes = [] + token_count = 0 + + cache = {} + batch_tokens = self.tokenize(texts) + batch_multipliers = [] + for tokens in batch_tokens: + tuple_tokens = tuple(tokens) + + if tuple_tokens in cache: + remade_tokens, fixes, multipliers = cache[tuple_tokens] + else: + fixes = [] + remade_tokens = [] + multipliers = [] + mult = 1.0 + + i = 0 + while i < len(tokens): + token = tokens[i] + + embedding, embedding_length_in_tokens = self.hijack.embedding_db.find_embedding_at_position(tokens, i) + + mult_change = self.token_mults.get(token) if opts.enable_emphasis else None + if mult_change is not None: + mult *= mult_change + i += 1 + elif embedding is None: + remade_tokens.append(token) + multipliers.append(mult) + i += 1 + else: + emb_len = int(embedding.vec.shape[0]) + fixes.append((len(remade_tokens), embedding)) + remade_tokens += [0] * emb_len + multipliers += [mult] * emb_len + used_custom_terms.append((embedding.name, embedding.checksum())) + i += embedding_length_in_tokens + + if len(remade_tokens) > maxlen - 2: + vocab = {v: k for k, v in self.wrapped.tokenizer.get_vocab().items()} + ovf = remade_tokens[maxlen - 2:] + overflowing_words = [vocab.get(int(x), "") for x in ovf] + overflowing_text = self.wrapped.tokenizer.convert_tokens_to_string(''.join(overflowing_words)) + hijack_comments.append(f"Warning: too many input tokens; some ({len(overflowing_words)}) have been truncated:\n{overflowing_text}\n") + + token_count = len(remade_tokens) + remade_tokens = remade_tokens + [id_end] * (maxlen - 2 - len(remade_tokens)) + remade_tokens = [id_start] + remade_tokens[0:maxlen - 2] + [id_end] + cache[tuple_tokens] = (remade_tokens, fixes, multipliers) + + multipliers = multipliers + [1.0] * (maxlen - 2 - len(multipliers)) + multipliers = [1.0] + multipliers[0:maxlen - 2] + [1.0] + + remade_batch_tokens.append(remade_tokens) + hijack_fixes.append(fixes) + batch_multipliers.append(multipliers) + return batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count + + def forward(self, text): + use_old = opts.use_old_emphasis_implementation + if use_old: + batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count = self.process_text_old(text) + else: + batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count = self.process_text(text) + + self.hijack.comments += hijack_comments + + if len(used_custom_terms) > 0: + self.hijack.comments.append("Used embeddings: " + ", ".join([f'{word} [{checksum}]' for word, checksum in used_custom_terms])) + + if use_old: + self.hijack.fixes = hijack_fixes + return self.process_tokens(remade_batch_tokens, batch_multipliers) + + z = None + i = 0 + while max(map(len, remade_batch_tokens)) != 0: + rem_tokens = [x[75:] for x in remade_batch_tokens] + rem_multipliers = [x[75:] for x in batch_multipliers] + + self.hijack.fixes = [] + for unfiltered in hijack_fixes: + fixes = [] + for fix in unfiltered: + if fix[0] == i: + fixes.append(fix[1]) + self.hijack.fixes.append(fixes) + + tokens = [] + multipliers = [] + for j in range(len(remade_batch_tokens)): + if len(remade_batch_tokens[j]) > 0: + tokens.append(remade_batch_tokens[j][:75]) + multipliers.append(batch_multipliers[j][:75]) + else: + tokens.append([self.id_end] * 75) + multipliers.append([1.0] * 75) + + z1 = self.process_tokens(tokens, multipliers) + z = z1 if z is None else torch.cat((z, z1), axis=-2) + + remade_batch_tokens = rem_tokens + batch_multipliers = rem_multipliers + i += 1 + + return z + + def process_tokens(self, remade_batch_tokens, batch_multipliers): + if not opts.use_old_emphasis_implementation: + remade_batch_tokens = [[self.id_start] + x[:75] + [self.id_end] for x in remade_batch_tokens] + batch_multipliers = [[1.0] + x[:75] + [1.0] for x in batch_multipliers] + + tokens = torch.asarray(remade_batch_tokens).to(devices.device) + + if self.id_end != self.id_pad: + for batch_pos in range(len(remade_batch_tokens)): + index = remade_batch_tokens[batch_pos].index(self.id_end) + tokens[batch_pos, index+1:tokens.shape[1]] = self.id_pad + + z = self.encode_with_transformers(tokens) + + # restoring original mean is likely not correct, but it seems to work well to prevent artifacts that happen otherwise + batch_multipliers_of_same_length = [x + [1.0] * (75 - len(x)) for x in batch_multipliers] + batch_multipliers = torch.asarray(batch_multipliers_of_same_length).to(devices.device) + original_mean = z.mean() + z *= batch_multipliers.reshape(batch_multipliers.shape + (1,)).expand(z.shape) + new_mean = z.mean() + z *= original_mean / new_mean + + return z + + +class FrozenCLIPEmbedderWithCustomWords(FrozenCLIPEmbedderWithCustomWordsBase): + def __init__(self, wrapped, hijack): + super().__init__(wrapped, hijack) + self.tokenizer = wrapped.tokenizer + self.comma_token = [v for k, v in self.tokenizer.get_vocab().items() if k == ','][0] + + self.token_mults = {} + tokens_with_parens = [(k, v) for k, v in self.tokenizer.get_vocab().items() if '(' in k or ')' in k or '[' in k or ']' in k] + for text, ident in tokens_with_parens: + mult = 1.0 + for c in text: + if c == '[': + mult /= 1.1 + if c == ']': + mult *= 1.1 + if c == '(': + mult *= 1.1 + if c == ')': + mult /= 1.1 + + if mult != 1.0: + self.token_mults[ident] = mult + + self.id_start = self.wrapped.tokenizer.bos_token_id + self.id_end = self.wrapped.tokenizer.eos_token_id + self.id_pad = self.id_end + + def tokenize(self, texts): + tokenized = self.wrapped.tokenizer(texts, truncation=False, add_special_tokens=False)["input_ids"] + + return tokenized + + def encode_with_transformers(self, tokens): + outputs = self.wrapped.transformer(input_ids=tokens, output_hidden_states=-opts.CLIP_stop_at_last_layers) + + if opts.CLIP_stop_at_last_layers > 1: + z = outputs.hidden_states[-opts.CLIP_stop_at_last_layers] + z = self.wrapped.transformer.text_model.final_layer_norm(z) + else: + z = outputs.last_hidden_state + + return z + + def encode_embedding_init_text(self, init_text, nvpt): + embedding_layer = self.wrapped.transformer.text_model.embeddings + ids = self.wrapped.tokenizer(init_text, max_length=nvpt, return_tensors="pt", add_special_tokens=False)["input_ids"] + embedded = embedding_layer.token_embedding.wrapped(ids.to(devices.device)).squeeze(0) + + return embedded diff --git a/modules/sd_hijack_inpainting.py b/modules/sd_hijack_inpainting.py index 46714a4f..938f9a58 100644 --- a/modules/sd_hijack_inpainting.py +++ b/modules/sd_hijack_inpainting.py @@ -199,8 +199,8 @@ def sample_plms(self, @torch.no_grad() def p_sample_plms(self, x, c, t, index, repeat_noise=False, use_original_steps=False, quantize_denoised=False, - temperature=1., noise_dropout=0., score_corrector=None, corrector_kwargs=None, - unconditional_guidance_scale=1., unconditional_conditioning=None, old_eps=None, t_next=None): + temperature=1., noise_dropout=0., score_corrector=None, corrector_kwargs=None, + unconditional_guidance_scale=1., unconditional_conditioning=None, old_eps=None, t_next=None, dynamic_threshold=None): b, *_, device = *x.shape, x.device def get_model_output(x, t): @@ -249,6 +249,8 @@ def p_sample_plms(self, x, c, t, index, repeat_noise=False, use_original_steps=F pred_x0 = (x - sqrt_one_minus_at * e_t) / a_t.sqrt() if quantize_denoised: pred_x0, _, *_ = self.model.first_stage_model.quantize(pred_x0) + if dynamic_threshold is not None: + pred_x0 = norm_thresholding(pred_x0, dynamic_threshold) # direction pointing to x_t dir_xt = (1. - a_prev - sigma_t**2).sqrt() * e_t noise = sigma_t * noise_like(x.shape, device, repeat_noise) * temperature @@ -321,12 +323,16 @@ def should_hijack_inpainting(checkpoint_info): def do_inpainting_hijack(): - ldm.models.diffusion.ddpm.get_unconditional_conditioning = get_unconditional_conditioning + # most of this stuff seems to no longer be needed because it is already included into SD2.0 + # LatentInpaintDiffusion remains because SD2.0's LatentInpaintDiffusion can't be loaded without specifying a checkpoint + # p_sample_plms is needed because PLMS can't work with dicts as conditionings + # this file should be cleaned up later if weverything tuens out to work fine + + # ldm.models.diffusion.ddpm.get_unconditional_conditioning = get_unconditional_conditioning ldm.models.diffusion.ddpm.LatentInpaintDiffusion = LatentInpaintDiffusion - ldm.models.diffusion.ddim.DDIMSampler.p_sample_ddim = p_sample_ddim - ldm.models.diffusion.ddim.DDIMSampler.sample = sample_ddim + # ldm.models.diffusion.ddim.DDIMSampler.p_sample_ddim = p_sample_ddim + # ldm.models.diffusion.ddim.DDIMSampler.sample = sample_ddim ldm.models.diffusion.plms.PLMSSampler.p_sample_plms = p_sample_plms - ldm.models.diffusion.plms.PLMSSampler.sample = sample_plms - + # ldm.models.diffusion.plms.PLMSSampler.sample = sample_plms diff --git a/modules/sd_hijack_open_clip.py b/modules/sd_hijack_open_clip.py new file mode 100644 index 00000000..f733e852 --- /dev/null +++ b/modules/sd_hijack_open_clip.py @@ -0,0 +1,37 @@ +import open_clip.tokenizer +import torch + +from modules import sd_hijack_clip, devices +from modules.shared import opts + +tokenizer = open_clip.tokenizer._tokenizer + + +class FrozenOpenCLIPEmbedderWithCustomWords(sd_hijack_clip.FrozenCLIPEmbedderWithCustomWordsBase): + def __init__(self, wrapped, hijack): + super().__init__(wrapped, hijack) + + self.comma_token = [v for k, v in tokenizer.encoder.items() if k == ','][0] + self.id_start = tokenizer.encoder[""] + self.id_end = tokenizer.encoder[""] + self.id_pad = 0 + + def tokenize(self, texts): + assert not opts.use_old_emphasis_implementation, 'Old emphasis implementation not supported for Open Clip' + + tokenized = [tokenizer.encode(text) for text in texts] + + return tokenized + + def encode_with_transformers(self, tokens): + # set self.wrapped.layer_idx here according to opts.CLIP_stop_at_last_layers + z = self.wrapped.encode_with_transformer(tokens) + + return z + + def encode_embedding_init_text(self, init_text, nvpt): + ids = tokenizer.encode(init_text) + ids = torch.asarray([ids], device=devices.device, dtype=torch.int) + embedded = self.wrapped.model.token_embedding.wrapped(ids).squeeze(0) + + return embedded diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py index 4fe67854..4edd8c60 100644 --- a/modules/sd_samplers.py +++ b/modules/sd_samplers.py @@ -127,7 +127,8 @@ class InterruptedException(BaseException): class VanillaStableDiffusionSampler: def __init__(self, constructor, sd_model): self.sampler = constructor(sd_model) - self.orig_p_sample_ddim = self.sampler.p_sample_ddim if hasattr(self.sampler, 'p_sample_ddim') else self.sampler.p_sample_plms + self.is_plms = hasattr(self.sampler, 'p_sample_plms') + self.orig_p_sample_ddim = self.sampler.p_sample_plms if self.is_plms else self.sampler.p_sample_ddim self.mask = None self.nmask = None self.init_latent = None @@ -218,7 +219,6 @@ class VanillaStableDiffusionSampler: self.mask = p.mask if hasattr(p, 'mask') else None self.nmask = p.nmask if hasattr(p, 'nmask') else None - def adjust_steps_if_invalid(self, p, num_steps): if (self.config.name == 'DDIM' and p.ddim_discretize == 'uniform') or (self.config.name == 'PLMS'): valid_step = 999 / (1000 // num_steps) @@ -227,7 +227,6 @@ class VanillaStableDiffusionSampler: return num_steps - def sample_img2img(self, p, x, noise, conditioning, unconditional_conditioning, steps=None, image_conditioning=None): steps, t_enc = setup_img2img_steps(p, steps) steps = self.adjust_steps_if_invalid(p, steps) @@ -260,9 +259,10 @@ class VanillaStableDiffusionSampler: steps = self.adjust_steps_if_invalid(p, steps or p.steps) # Wrap the conditioning models with additional image conditioning for inpainting model + # dummy_for_plms is needed because PLMS code checks the first item in the dict to have the right shape if image_conditioning is not None: - conditioning = {"c_concat": [image_conditioning], "c_crossattn": [conditioning]} - unconditional_conditioning = {"c_concat": [image_conditioning], "c_crossattn": [unconditional_conditioning]} + conditioning = {"dummy_for_plms": np.zeros((conditioning.shape[0],)), "c_crossattn": [conditioning], "c_concat": [image_conditioning]} + unconditional_conditioning = {"c_crossattn": [unconditional_conditioning], "c_concat": [image_conditioning]} samples_ddim = self.launch_sampling(steps, lambda: self.sampler.sample(S=steps, conditioning=conditioning, batch_size=int(x.shape[0]), shape=x[0].shape, verbose=False, unconditional_guidance_scale=p.cfg_scale, unconditional_conditioning=unconditional_conditioning, x_T=x, eta=self.eta)[0]) @@ -350,7 +350,9 @@ class TorchHijack: class KDiffusionSampler: def __init__(self, funcname, sd_model): - self.model_wrap = k_diffusion.external.CompVisDenoiser(sd_model, quantize=shared.opts.enable_quantization) + denoiser = k_diffusion.external.CompVisVDenoiser if sd_model.parameterization == "v" else k_diffusion.external.CompVisDenoiser + + self.model_wrap = denoiser(sd_model, quantize=shared.opts.enable_quantization) self.funcname = funcname self.func = getattr(k_diffusion.sampling, self.funcname) self.extra_params = sampler_extra_params.get(funcname, []) diff --git a/modules/shared.py b/modules/shared.py index c93ae2a3..8fb1387a 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -11,17 +11,15 @@ import tqdm import modules.artists import modules.interrogate import modules.memmon -import modules.sd_models import modules.styles import modules.devices as devices -from modules import sd_samplers, sd_models, localization, sd_vae, extensions, script_loading -from modules.hypernetworks import hypernetwork +from modules import localization, sd_vae, extensions, script_loading from modules.paths import models_path, script_path, sd_path sd_model_file = os.path.join(script_path, 'model.ckpt') default_sd_model_file = sd_model_file parser = argparse.ArgumentParser() -parser.add_argument("--config", type=str, default=os.path.join(sd_path, "configs/stable-diffusion/v1-inference.yaml"), help="path to config which constructs model",) +parser.add_argument("--config", type=str, default=os.path.join(script_path, "v1-inference.yaml"), help="path to config which constructs model",) parser.add_argument("--ckpt", type=str, default=sd_model_file, help="path to checkpoint of stable diffusion model; if specified, this checkpoint will be added to the list of checkpoints and loaded",) parser.add_argument("--ckpt-dir", type=str, default=None, help="Path to directory with stable diffusion checkpoints") parser.add_argument("--gfpgan-dir", type=str, help="GFPGAN directory", default=('./src/gfpgan' if os.path.exists('./src/gfpgan') else './GFPGAN')) @@ -121,10 +119,12 @@ xformers_available = False config_filename = cmd_opts.ui_settings_file os.makedirs(cmd_opts.hypernetwork_dir, exist_ok=True) -hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir) +hypernetworks = {} loaded_hypernetwork = None + def reload_hypernetworks(): + from modules.hypernetworks import hypernetwork global hypernetworks hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir) @@ -206,10 +206,11 @@ class State: if self.current_latent is None: return + import modules.sd_samplers if opts.show_progress_grid: - self.current_image = sd_samplers.samples_to_image_grid(self.current_latent) + self.current_image = modules.sd_samplers.samples_to_image_grid(self.current_latent) else: - self.current_image = sd_samplers.sample_to_image(self.current_latent) + self.current_image = modules.sd_samplers.sample_to_image(self.current_latent) self.current_image_sampling_step = self.sampling_step @@ -248,6 +249,21 @@ def options_section(section_identifier, options_dict): return options_dict +def list_checkpoint_tiles(): + import modules.sd_models + return modules.sd_models.checkpoint_tiles() + + +def refresh_checkpoints(): + import modules.sd_models + return modules.sd_models.list_models() + + +def list_samplers(): + import modules.sd_samplers + return modules.sd_samplers.all_samplers + + hide_dirs = {"visible": not cmd_opts.hide_ui_dir_config} options_templates = {} @@ -333,7 +349,7 @@ options_templates.update(options_section(('training', "Training"), { })) options_templates.update(options_section(('sd', "Stable Diffusion"), { - "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, refresh=sd_models.list_models), + "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": list_checkpoint_tiles()}, refresh=refresh_checkpoints), "sd_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}), "sd_vae": OptionInfo("auto", "SD VAE", gr.Dropdown, lambda: {"choices": sd_vae.vae_list}, refresh=sd_vae.refresh_vae_list), "sd_vae_as_default": OptionInfo(False, "Ignore selected VAE for stable diffusion checkpoints that have their own .vae.pt next to them"), @@ -385,7 +401,7 @@ options_templates.update(options_section(('ui', "User interface"), { })) options_templates.update(options_section(('sampler-params', "Sampler parameters"), { - "hide_samplers": OptionInfo([], "Hide samplers in user interface (requires restart)", gr.CheckboxGroup, lambda: {"choices": [x.name for x in sd_samplers.all_samplers]}), + "hide_samplers": OptionInfo([], "Hide samplers in user interface (requires restart)", gr.CheckboxGroup, lambda: {"choices": [x.name for x in list_samplers()]}), "eta_ddim": OptionInfo(0.0, "eta (noise multiplier) for DDIM", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), "eta_ancestral": OptionInfo(1.0, "eta (noise multiplier) for ancestral samplers", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), "ddim_discretize": OptionInfo('uniform', "img2img DDIM discretize", gr.Radio, {"choices": ['uniform', 'quad']}), diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 5e4d8688..a273e663 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -64,7 +64,8 @@ class EmbeddingDatabase: self.word_embeddings[embedding.name] = embedding - ids = model.cond_stage_model.tokenizer([embedding.name], add_special_tokens=False)['input_ids'][0] + # TODO changing between clip and open clip changes tokenization, which will cause embeddings to stop working + ids = model.cond_stage_model.tokenize([embedding.name])[0] first_id = ids[0] if first_id not in self.ids_lookup: @@ -155,13 +156,11 @@ class EmbeddingDatabase: def create_embedding(name, num_vectors_per_token, overwrite_old, init_text='*'): cond_model = shared.sd_model.cond_stage_model - embedding_layer = cond_model.wrapped.transformer.text_model.embeddings with devices.autocast(): cond_model([""]) # will send cond model to GPU if lowvram/medvram is active - ids = cond_model.tokenizer(init_text, max_length=num_vectors_per_token, return_tensors="pt", add_special_tokens=False)["input_ids"] - embedded = embedding_layer.token_embedding.wrapped(ids.to(devices.device)).squeeze(0) + embedded = cond_model.encode_embedding_init_text(init_text, num_vectors_per_token) vec = torch.zeros((num_vectors_per_token, embedded.shape[1]), device=devices.device) for i in range(num_vectors_per_token): diff --git a/modules/ui.py b/modules/ui.py index e6da1b2a..e5cb69d0 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -478,9 +478,7 @@ def create_toprow(is_img2img): if is_img2img: with gr.Column(scale=1, elem_id="interrogate_col"): button_interrogate = gr.Button('Interrogate\nCLIP', elem_id="interrogate") - - if cmd_opts.deepdanbooru: - button_deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru") + button_deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru") with gr.Column(scale=1): with gr.Row(): @@ -1004,11 +1002,10 @@ def create_ui(wrap_gradio_gpu_call): outputs=[img2img_prompt], ) - if cmd_opts.deepdanbooru: - img2img_deepbooru.click( - fn=interrogate_deepbooru, - inputs=[init_img], - outputs=[img2img_prompt], + img2img_deepbooru.click( + fn=interrogate_deepbooru, + inputs=[init_img], + outputs=[img2img_prompt], ) diff --git a/requirements.txt b/requirements.txt index 762db4f3..e4e5ec64 100644 --- a/requirements.txt +++ b/requirements.txt @@ -28,3 +28,4 @@ kornia lark inflection GitPython +torchsde diff --git a/requirements_versions.txt b/requirements_versions.txt index 662ca684..8d557fe3 100644 --- a/requirements_versions.txt +++ b/requirements_versions.txt @@ -25,3 +25,4 @@ kornia==0.6.7 lark==1.1.2 inflection==0.5.1 GitPython==3.1.27 +torchsde==0.2.5 diff --git a/v1-inference.yaml b/v1-inference.yaml new file mode 100644 index 00000000..d4effe56 --- /dev/null +++ b/v1-inference.yaml @@ -0,0 +1,70 @@ +model: + base_learning_rate: 1.0e-04 + target: ldm.models.diffusion.ddpm.LatentDiffusion + params: + linear_start: 0.00085 + linear_end: 0.0120 + num_timesteps_cond: 1 + log_every_t: 200 + timesteps: 1000 + first_stage_key: "jpg" + cond_stage_key: "txt" + image_size: 64 + channels: 4 + cond_stage_trainable: false # Note: different from the one we trained before + conditioning_key: crossattn + monitor: val/loss_simple_ema + scale_factor: 0.18215 + use_ema: False + + scheduler_config: # 10000 warmup steps + target: ldm.lr_scheduler.LambdaLinearScheduler + params: + warm_up_steps: [ 10000 ] + cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases + f_start: [ 1.e-6 ] + f_max: [ 1. ] + f_min: [ 1. ] + + unet_config: + target: ldm.modules.diffusionmodules.openaimodel.UNetModel + params: + image_size: 32 # unused + in_channels: 4 + out_channels: 4 + model_channels: 320 + attention_resolutions: [ 4, 2, 1 ] + num_res_blocks: 2 + channel_mult: [ 1, 2, 4, 4 ] + num_heads: 8 + use_spatial_transformer: True + transformer_depth: 1 + context_dim: 768 + use_checkpoint: True + legacy: False + + first_stage_config: + target: ldm.models.autoencoder.AutoencoderKL + params: + embed_dim: 4 + monitor: val/rec_loss + ddconfig: + double_z: true + z_channels: 4 + resolution: 256 + in_channels: 3 + out_ch: 3 + ch: 128 + ch_mult: + - 1 + - 2 + - 4 + - 4 + num_res_blocks: 2 + attn_resolutions: [] + dropout: 0.0 + lossconfig: + target: torch.nn.Identity + + cond_stage_config: + target: ldm.modules.encoders.modules.FrozenCLIPEmbedder diff --git a/webui.py b/webui.py index c5e5fe75..23215d1e 100644 --- a/webui.py +++ b/webui.py @@ -10,7 +10,7 @@ from fastapi.middleware.gzip import GZipMiddleware from modules.paths import script_path -from modules import devices, sd_samplers, upscaler, extensions, localization +from modules import shared, devices, sd_samplers, upscaler, extensions, localization import modules.codeformer_model as codeformer import modules.extras import modules.face_restoration @@ -23,7 +23,6 @@ import modules.scripts import modules.sd_hijack import modules.sd_models import modules.sd_vae -import modules.shared as shared import modules.txt2img import modules.script_callbacks @@ -86,7 +85,7 @@ def initialize(): shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights())) shared.opts.onchange("sd_vae", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False) shared.opts.onchange("sd_vae_as_default", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False) - shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetworks.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork))) + shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: shared.reload_hypernetworks())) shared.opts.onchange("sd_hypernetwork_strength", modules.hypernetworks.hypernetwork.apply_strength) if cmd_opts.tls_keyfile is not None and cmd_opts.tls_keyfile is not None: -- cgit v1.2.3 From 89d8804768d4479d72d24ebbbd2bd00650ef5dc7 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 27 Nov 2022 18:48:08 +0300 Subject: only run install.py for enabled extensions --- launch.py | 27 ++++++++++++++++++++++++--- 1 file changed, 24 insertions(+), 3 deletions(-) (limited to 'launch.py') diff --git a/launch.py b/launch.py index c426e673..ad9ddd5a 100644 --- a/launch.py +++ b/launch.py @@ -5,6 +5,8 @@ import sys import importlib.util import shlex import platform +import argparse +import json dir_repos = "repositories" dir_extensions = "extensions" @@ -132,11 +134,26 @@ def run_extension_installer(extension_dir): print(e, file=sys.stderr) -def run_extensions_installers(): +def list_extensions(settings_file): + settings = {} + + try: + if os.path.isfile(settings_file): + with open(settings_file, "r", encoding="utf8") as file: + settings = json.load(file) + except Exception as e: + print(e, file=sys.stderr) + + disabled_extensions = set(settings.get('disabled_extensions', [])) + + return [x for x in os.listdir(dir_extensions) if x not in disabled_extensions] + + +def run_extensions_installers(settings_file): if not os.path.isdir(dir_extensions): return - for dirname_extension in os.listdir(dir_extensions): + for dirname_extension in list_extensions(settings_file): run_extension_installer(os.path.join(dir_extensions, dirname_extension)) @@ -165,6 +182,10 @@ def prepare_enviroment(): sys.argv += shlex.split(commandline_args) + parser = argparse.ArgumentParser() + parser.add_argument("--ui-settings-file", type=str, help="filename to use for ui settings", default='config.json') + args, _ = parser.parse_known_args(sys.argv) + sys.argv, skip_torch_cuda_test = extract_arg(sys.argv, '--skip-torch-cuda-test') sys.argv, reinstall_xformers = extract_arg(sys.argv, '--reinstall-xformers') sys.argv, update_check = extract_arg(sys.argv, '--update-check') @@ -223,7 +244,7 @@ def prepare_enviroment(): run_pip(f"install -r {requirements_file}", "requirements for Web UI") - run_extensions_installers() + run_extensions_installers(settings_file=args.ui_settings_file) if update_check: version_check(commit) -- cgit v1.2.3