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chore: fix typos
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Signed-off-by: snoppy <[email protected]>
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xiaoxianBoy committed Jun 21, 2024
1 parent feee37d commit 13f2297
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Showing 6 changed files with 6 additions and 6 deletions.
2 changes: 1 addition & 1 deletion extensions-builtin/LDSR/sd_hijack_ddpm_v1.py
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Expand Up @@ -572,7 +572,7 @@ def delta_border(self, h, w):
:param h: height
:param w: width
:return: normalized distance to image border,
wtith min distance = 0 at border and max dist = 0.5 at image center
with min distance = 0 at border and max dist = 0.5 at image center
"""
lower_right_corner = torch.tensor([h - 1, w - 1]).view(1, 1, 2)
arr = self.meshgrid(h, w) / lower_right_corner
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2 changes: 1 addition & 1 deletion modules/api/api.py
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Expand Up @@ -372,7 +372,7 @@ def apply_infotext(self, request, tabname, *, script_runner=None, mentioned_scri
return {}

possible_fields = infotext_utils.paste_fields[tabname]["fields"]
set_fields = request.model_dump(exclude_unset=True) if hasattr(request, "request") else request.dict(exclude_unset=True) # pydantic v1/v2 have differenrt names for this
set_fields = request.model_dump(exclude_unset=True) if hasattr(request, "request") else request.dict(exclude_unset=True) # pydantic v1/v2 have different names for this
params = infotext_utils.parse_generation_parameters(request.infotext)

def get_field_value(field, params):
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2 changes: 1 addition & 1 deletion modules/devices.py
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Expand Up @@ -258,7 +258,7 @@ def test_for_nans(x, where):
@lru_cache
def first_time_calculation():
"""
just do any calculation with pytorch layers - the first time this is done it allocaltes about 700MB of memory and
just do any calculation with pytorch layers - the first time this is done it allocates about 700MB of memory and
spends about 2.7 seconds doing that, at least with NVidia.
"""

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2 changes: 1 addition & 1 deletion modules/models/diffusion/uni_pc/uni_pc.py
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Expand Up @@ -323,7 +323,7 @@ def cond_grad_fn(x, t_input, condition):

def model_fn(x, t_continuous, condition, unconditional_condition):
"""
The noise predicition model function that is used for DPM-Solver.
The noise prediction model function that is used for DPM-Solver.
"""
if t_continuous.reshape((-1,)).shape[0] == 1:
t_continuous = t_continuous.expand((x.shape[0]))
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2 changes: 1 addition & 1 deletion modules/shared.py
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Expand Up @@ -47,7 +47,7 @@
sd_model: sd_models_types.WebuiSdModel = None

settings_components: dict = None
"""assigned from ui.py, a mapping on setting names to gradio components repsponsible for those settings"""
"""assigned from ui.py, a mapping on setting names to gradio components responsible for those settings"""

tab_names = []

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2 changes: 1 addition & 1 deletion modules/util.py
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Expand Up @@ -156,7 +156,7 @@ def update_file_entry(self, path):

def topological_sort(dependencies):
"""Accepts a dictionary mapping name to its dependencies, returns a list of names ordered according to dependencies.
Ignores errors relating to missing dependeencies or circular dependencies
Ignores errors relating to missing dependencies or circular dependencies
"""

visited = {}
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