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-rw-r--r--modules/shared.py13
1 files changed, 10 insertions, 3 deletions
diff --git a/modules/shared.py b/modules/shared.py
index 9c9fd857..b7a3ce5c 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -153,6 +153,7 @@ class State:
job = ""
job_no = 0
job_count = 0
+ processing_has_refined_job_count = False
job_timestamp = '0'
sampling_step = 0
sampling_steps = 0
@@ -183,6 +184,7 @@ class State:
"interrupted": self.interrupted,
"job": self.job,
"job_count": self.job_count,
+ "job_timestamp": self.job_timestamp,
"job_no": self.job_no,
"sampling_step": self.sampling_step,
"sampling_steps": self.sampling_steps,
@@ -193,6 +195,7 @@ class State:
def begin(self):
self.sampling_step = 0
self.job_count = -1
+ self.processing_has_refined_job_count = False
self.job_no = 0
self.job_timestamp = datetime.datetime.now().strftime("%Y%m%d%H%M%S")
self.current_latent = None
@@ -213,12 +216,13 @@ class State:
"""sets self.current_image from self.current_latent if enough sampling steps have been made after the last call to this"""
def set_current_image(self):
+ if not parallel_processing_allowed:
+ return
+
if self.sampling_step - self.current_image_sampling_step >= opts.show_progress_every_n_steps and opts.show_progress_every_n_steps > 0:
self.do_set_current_image()
def do_set_current_image(self):
- if not parallel_processing_allowed:
- return
if self.current_latent is None:
return
@@ -230,6 +234,7 @@ class State:
self.current_image_sampling_step = self.sampling_step
+
state = State()
artist_db = modules.artists.ArtistsDatabase(os.path.join(script_path, 'artists.csv'))
@@ -437,6 +442,7 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters"
's_tmin': OptionInfo(0.0, "sigma tmin", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}),
+ 'always_discard_next_to_last_sigma': OptionInfo(False, "Always discard next-to-last sigma"),
}))
options_templates.update(options_section((None, "Hidden options"), {
@@ -570,6 +576,7 @@ latent_upscale_modes = {
"Latent (bicubic)": {"mode": "bicubic", "antialias": False},
"Latent (bicubic antialiased)": {"mode": "bicubic", "antialias": True},
"Latent (nearest)": {"mode": "nearest", "antialias": False},
+ "Latent (nearest-exact)": {"mode": "nearest-exact", "antialias": False},
}
sd_upscalers = []
@@ -605,7 +612,7 @@ class TotalTQDM:
return
if self._tqdm is None:
self.reset()
- self._tqdm.total=new_total
+ self._tqdm.total = new_total
def clear(self):
if self._tqdm is not None: