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https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
synced 2024-06-07 21:20:49 +00:00
Refactored Metal/mps fixes.
This commit is contained in:
Elias Oenal
parent
5dc05c0d0d
commit
b7f95869b4
@ -1,6 +1,3 @@
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# Metal backend fixes written and placed
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# into the public domain by Elias Oenal <sd@eliasoenal.com>
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import os
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import sys
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import traceback
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@ -50,25 +47,21 @@ def setup_codeformer():
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def __init__(self):
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self.net = None
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self.face_helper = None
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if shared.device.type == 'mps': # CodeFormer currently does not support mps backend
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shared.device_codeformer = torch.device('cpu')
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def create_models(self):
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if self.net is not None and self.face_helper is not None:
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return self.net, self.face_helper
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if shared.device.type == 'mps': # CodeFormer currently does not support mps backend
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net = net_class(dim_embd=512, codebook_size=1024, n_head=8, n_layers=9, connect_list=['32', '64', '128', '256']).to(torch.device('cpu'))
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else:
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net = net_class(dim_embd=512, codebook_size=1024, n_head=8, n_layers=9, connect_list=['32', '64', '128', '256']).to(shared.device)
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net = net_class(dim_embd=512, codebook_size=1024, n_head=8, n_layers=9, connect_list=['32', '64', '128', '256']).to(shared.device_codeformer)
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ckpt_path = load_file_from_url(url=pretrain_model_url, model_dir=os.path.join(path, 'weights/CodeFormer'), progress=True)
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checkpoint = torch.load(ckpt_path)['params_ema']
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net.load_state_dict(checkpoint)
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net.eval()
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if shared.device.type == 'mps': # CodeFormer currently does not support mps backend
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face_helper = FaceRestoreHelper(1, face_size=512, crop_ratio=(1, 1), det_model='retinaface_resnet50', save_ext='png', use_parse=True, device=torch.device('cpu'))
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else:
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face_helper = FaceRestoreHelper(1, face_size=512, crop_ratio=(1, 1), det_model='retinaface_resnet50', save_ext='png', use_parse=True, device=shared.device)
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face_helper = FaceRestoreHelper(1, face_size=512, crop_ratio=(1, 1), det_model='retinaface_resnet50', save_ext='png', use_parse=True, device=shared.device_codeformer)
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if not cmd_opts.unload_gfpgan:
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self.net = net
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@ -90,10 +83,8 @@ def setup_codeformer():
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for idx, cropped_face in enumerate(face_helper.cropped_faces):
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cropped_face_t = img2tensor(cropped_face / 255., bgr2rgb=True, float32=True)
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normalize(cropped_face_t, (0.5, 0.5, 0.5), (0.5, 0.5, 0.5), inplace=True)
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if shared.device.type == 'mps': # CodeFormer currently does not support mps backend
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cropped_face_t = cropped_face_t.unsqueeze(0).to(torch.device('cpu'))
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else:
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cropped_face_t = cropped_face_t.unsqueeze(0).to(shared.device)
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cropped_face_t = cropped_face_t.unsqueeze(0).to(shared.device_codeformer)
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try:
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with torch.no_grad():
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output = net(cropped_face_t, w=w if w is not None else shared.opts.code_former_weight, adain=True)[0]
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@ -1,6 +1,3 @@
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# Metal backend fixes written and placed
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# into the public domain by Elias Oenal <sd@eliasoenal.com>
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import contextlib
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import json
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import math
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@ -109,17 +106,19 @@ def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, see
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noise_shape = shape if seed_resize_from_h <= 0 or seed_resize_from_w <= 0 else (shape[0], seed_resize_from_h//8, seed_resize_from_w//8)
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# Pytorch currently doesn't handle seeting randomness correctly when the metal backend is used.
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generator = torch
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if shared.device.type == 'mps':
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g = torch.Generator(device='cpu')
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shared.device_seed_type = 'cpu'
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generator = torch.Generator(device=shared.device_seed_type)
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subnoise = None
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if subseeds is not None:
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subseed = 0 if i >= len(subseeds) else subseeds[i]
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if shared.device.type == 'mps':
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g.manual_seed(subseed)
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subnoise = torch.randn(noise_shape, generator=g, device='cpu').to('mps')
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else: # cpu or cuda
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torch.manual_seed(subseed)
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generator.manual_seed(subseed)
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if shared.device.type != shared.device_seed_type:
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subnoise = torch.randn(noise_shape, generator=generator, device=shared.device_seed_type).to(shared.device)
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else:
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subnoise = torch.randn(noise_shape, device=shared.device)
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# randn results depend on device; gpu and cpu get different results for same seed;
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@ -128,12 +127,11 @@ def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, see
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# it will break everyone's seeds.
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# When using the mps backend falling back to the cpu device is needed, since mps currently
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# does not implement seeding properly.
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if shared.device.type == 'mps':
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g.manual_seed(seed)
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noise = torch.randn(noise_shape, generator=g, device='cpu').to('mps')
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else: # cpu or cuda
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torch.manual_seed(seed)
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x = torch.randn(shape, device=shared.device)
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generator.manual_seed(seed)
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if shared.device.type != shared.device_seed_type:
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noise = torch.randn(noise_shape, generator=generator, device=shared.device_seed_type).to(shared.device)
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else:
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noise = torch.randn(noise_shape, device=shared.device)
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if subnoise is not None:
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#noise = subnoise * subseed_strength + noise * (1 - subseed_strength)
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@ -143,12 +141,10 @@ def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, see
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#noise = torch.nn.functional.interpolate(noise.unsqueeze(1), size=shape[1:], mode="bilinear").squeeze()
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# noise_shape = (64, 80)
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# shape = (64, 72)
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if shared.device.type == 'mps':
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g.manual_seed(seed)
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x = torch.randn(shape, generator=g, device='cpu').to('mps')
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generator.manual_seed(seed)
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if shared.device.type != shared.device_seed_type:
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x = torch.randn(shape, generator=generator, device=shared.device_seed_type).to(shared.device)
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else:
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torch.manual_seed(seed)
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x = torch.randn(shape, device=shared.device)
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dx = (shape[2] - noise_shape[2]) // 2 # -4
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dy = (shape[1] - noise_shape[1]) // 2
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@ -484,10 +480,10 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
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if self.image_mask is not None:
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init_mask = latent_mask
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latmask = init_mask.convert('RGB').resize((self.init_latent.shape[3], self.init_latent.shape[2]))
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precision = np.float64
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if shared.device.type == 'mps': # mps backend does not support float64
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latmask = np.moveaxis(np.array(latmask, dtype=np.float32), 2, 0) / 255
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else:
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latmask = np.moveaxis(np.array(latmask, dtype=np.float64), 2, 0) / 255
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precision = np.float32
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latmask = np.moveaxis(np.array(latmask, dtype=precision), 2, 0) / 255
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latmask = latmask[0]
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latmask = np.around(latmask)
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latmask = np.tile(latmask[None], (4, 1, 1))
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@ -46,6 +46,8 @@ parser.add_argument("--ui-config-file", type=str, help="filename to use for ui c
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cmd_opts = parser.parse_args()
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device = get_optimal_device()
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device_codeformer = device
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device_seed_type = device
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batch_cond_uncond = cmd_opts.always_batch_cond_uncond or not (cmd_opts.lowvram or cmd_opts.medvram)
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parallel_processing_allowed = not cmd_opts.lowvram and not cmd_opts.medvram
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