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safe check scripts type

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This commit is contained in:
Vladimir Mandic
2023-11-10 08:46:26 -05:00
parent 653d253bfe
commit 9778af1bc6
1 changed files with 8 additions and 8 deletions
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modules/processing.py
+8 -8
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@@ -677,7 +677,7 @@ def print_profile(profile, msg: str):
def process_images(p: StableDiffusionProcessing) -> Processed:
if not hasattr(p.sd_model, 'sd_checkpoint_info'):
return None
if p.scripts is not None:
if p.scripts is not None and isinstance(p.scripts, modules.scripts.ScriptRunner):
p.scripts.before_process(p)
stored_opts = {}
for k, v in p.override_settings.copy().items():
@@ -803,7 +803,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
p.all_subseeds = [int(subseed) + x for x in range(len(p.all_prompts))]
if os.path.exists(shared.opts.embeddings_dir) and not p.do_not_reload_embeddings and shared.backend == shared.Backend.ORIGINAL:
modules.sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings(force_reload=False)
if p.scripts is not None:
if p.scripts is not None and isinstance(p.scripts, modules.scripts.ScriptRunner):
p.scripts.process(p)
infotexts = []
output_images = []
@@ -841,7 +841,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
p.negative_prompts = p.all_negative_prompts[n * p.batch_size:(n + 1) * p.batch_size]
p.seeds = p.all_seeds[n * p.batch_size:(n + 1) * p.batch_size]
p.subseeds = p.all_subseeds[n * p.batch_size:(n + 1) * p.batch_size]
if p.scripts is not None:
if p.scripts is not None and isinstance(p.scripts, modules.scripts.ScriptRunner):
p.scripts.before_process_batch(p, batch_number=n, prompts=p.prompts, seeds=p.seeds, subseeds=p.subseeds)
if len(p.prompts) == 0:
break
@@ -849,7 +849,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
if not p.disable_extra_networks:
with devices.autocast():
modules.extra_networks.activate(p, extra_network_data)
if p.scripts is not None:
if p.scripts is not None and isinstance(p.scripts, modules.scripts.ScriptRunner):
p.scripts.process_batch(p, batch_number=n, prompts=p.prompts, seeds=p.seeds, subseeds=p.subseeds)
if n == 0:
with open(os.path.join(modules.paths.data_path, "params.txt"), "w", encoding="utf8") as file:
@@ -898,9 +898,9 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
if shared.cmd_opts.lowvram or shared.cmd_opts.medvram and shared.backend == shared.Backend.ORIGINAL:
modules.lowvram.send_everything_to_cpu()
devices.torch_gc()
if p.scripts is not None:
if p.scripts is not None and isinstance(p.scripts, modules.scripts.ScriptRunner):
p.scripts.postprocess_batch(p, x_samples_ddim, batch_number=n)
if p.scripts is not None:
if p.scripts is not None and isinstance(p.scripts, modules.scripts.ScriptRunner):
p.prompts = p.all_prompts[n * p.batch_size:(n + 1) * p.batch_size]
p.negative_prompts = p.all_negative_prompts[n * p.batch_size:(n + 1) * p.batch_size]
batch_params = modules.scripts.PostprocessBatchListArgs(list(x_samples_ddim))
@@ -928,7 +928,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
p.ops.append('face')
x_sample = modules.face_restoration.restore_faces(x_sample)
image = Image.fromarray(x_sample)
if p.scripts is not None:
if p.scripts is not None and isinstance(p.scripts, modules.scripts.ScriptRunner):
pp = modules.scripts.PostprocessImageArgs(image)
p.scripts.postprocess_image(p, pp)
image = pp.image
@@ -993,7 +993,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
index_of_first_image=index_of_first_image,
infotexts=infotexts,
)
if p.scripts is not None and not (shared.state.interrupted or shared.state.skipped):
if p.scripts is not None and isinstance(p.scripts, modules.scripts.ScriptRunner) and not (shared.state.interrupted or shared.state.skipped):
p.scripts.postprocess(p, res)
return res