mrq/stable-diffusion-webui
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pushed the lost --precision switch fr anon to test i

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AUTOMATIC 2022-08-29 09:45:31 +03:00
parent 036a0dde70
commit 808590654e
1 changed files with 8 additions and 4 deletions
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webui.py
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@ -54,6 +54,7 @@ parser.add_argument("--max-batch-count", type=int, default=16, help="maximum bat
parser.add_argument("--embeddings-dir", type=str, default='embeddings', help="embeddings dirtectory for textual inversion (default: embeddings)")
parser.add_argument("--allow-code", action='store_true', help="allow custom script execution from webui")
parser.add_argument("--lowvram", action='store_true', help="enamble optimizations for low vram")
parser.add_argument("--precision", type=str, help="evaluate at this precision", choices=["full", "autocast"], default="autocast")
cmd_opts = parser.parse_args()
@ -273,8 +274,9 @@ def create_random_tensors(shape, seeds):
def torch_gc():
torch.cuda.empty_cache()
torch.cuda.ipc_collect()
if torch.cuda.is_available():
torch.cuda.empty_cache()
torch.cuda.ipc_collect()
def save_image(image, path, basename, seed=None, prompt=None, extension='png', info=None, short_filename=False):
@ -528,6 +530,7 @@ def draw_xy_grid(xs, ys, x_label, y_label, cell):
return grid
def resize_image(resize_mode, im, width, height):
if resize_mode == 0:
res = im.resize((width, height), resample=LANCZOS)
@ -747,7 +750,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
if len(used_custom_terms) > 0:
self.hijack.comments.append("Used custom terms: " + ", ".join([f'{word} [{checksum}]' for word, checksum in used_custom_terms]))
tokens = torch.asarray(remade_batch_tokens).to(self.wrapped.device)
tokens = torch.asarray(remade_batch_tokens).to(device)
outputs = self.wrapped.transformer(input_ids=tokens)
z = outputs.last_hidden_state
@ -906,8 +909,9 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
model_hijack.load_textual_inversion_embeddings(cmd_opts.embeddings_dir, model)
output_images = []
precision_scope = autocast if cmd_opts.precision == "autocast" else nullcontext
ema_scope = (nullcontext if cmd_opts.lowvram else model.ema_scope)
with torch.no_grad(), autocast("cuda"), ema_scope():
with torch.no_grad(), precision_scope("cuda"), ema_scope():
p.init()
for n in range(p.n_iter):