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Merge branch 'main' into refactor/model-manager-2

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psychedelicious
2023-11-14 07:51:57 +11:00
committed by GitHub
parent 8c71ff37ae 7fcb8959fb
commit 4465f97cdf
253 changed files with 1712 additions and 3981 deletions
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8
invokeai/backend/util/hotfixes.py
View File

@ -732,7 +732,9 @@ class ControlNetModel(ModelMixin, ConfigMixin, FromOriginalControlnetMixin):
controlnet_down_block_res_samples = ()
for down_block_res_sample, controlnet_block in zip(down_block_res_samples, self.controlnet_down_blocks):
for down_block_res_sample, controlnet_block in zip(
down_block_res_samples, self.controlnet_down_blocks, strict=True
):
down_block_res_sample = controlnet_block(down_block_res_sample)
controlnet_down_block_res_samples = controlnet_down_block_res_samples + (down_block_res_sample,)
@ -745,7 +747,9 @@ class ControlNetModel(ModelMixin, ConfigMixin, FromOriginalControlnetMixin):
scales = torch.logspace(-1, 0, len(down_block_res_samples) + 1, device=sample.device) # 0.1 to 1.0
scales = scales * conditioning_scale
down_block_res_samples = [sample * scale for sample, scale in zip(down_block_res_samples, scales)]
down_block_res_samples = [
sample * scale for sample, scale in zip(down_block_res_samples, scales, strict=False)
]
mid_block_res_sample = mid_block_res_sample * scales[-1] # last one
else:
down_block_res_samples = [sample * conditioning_scale for sample in down_block_res_samples]

58
invokeai/backend/util/logging.py
View File

@ -225,34 +225,34 @@ def basicConfig(**kwargs):
_FACILITY_MAP = (
dict(
LOG_KERN=syslog.LOG_KERN,
LOG_USER=syslog.LOG_USER,
LOG_MAIL=syslog.LOG_MAIL,
LOG_DAEMON=syslog.LOG_DAEMON,
LOG_AUTH=syslog.LOG_AUTH,
LOG_LPR=syslog.LOG_LPR,
LOG_NEWS=syslog.LOG_NEWS,
LOG_UUCP=syslog.LOG_UUCP,
LOG_CRON=syslog.LOG_CRON,
LOG_SYSLOG=syslog.LOG_SYSLOG,
LOG_LOCAL0=syslog.LOG_LOCAL0,
LOG_LOCAL1=syslog.LOG_LOCAL1,
LOG_LOCAL2=syslog.LOG_LOCAL2,
LOG_LOCAL3=syslog.LOG_LOCAL3,
LOG_LOCAL4=syslog.LOG_LOCAL4,
LOG_LOCAL5=syslog.LOG_LOCAL5,
LOG_LOCAL6=syslog.LOG_LOCAL6,
LOG_LOCAL7=syslog.LOG_LOCAL7,
)
{
"LOG_KERN": syslog.LOG_KERN,
"LOG_USER": syslog.LOG_USER,
"LOG_MAIL": syslog.LOG_MAIL,
"LOG_DAEMON": syslog.LOG_DAEMON,
"LOG_AUTH": syslog.LOG_AUTH,
"LOG_LPR": syslog.LOG_LPR,
"LOG_NEWS": syslog.LOG_NEWS,
"LOG_UUCP": syslog.LOG_UUCP,
"LOG_CRON": syslog.LOG_CRON,
"LOG_SYSLOG": syslog.LOG_SYSLOG,
"LOG_LOCAL0": syslog.LOG_LOCAL0,
"LOG_LOCAL1": syslog.LOG_LOCAL1,
"LOG_LOCAL2": syslog.LOG_LOCAL2,
"LOG_LOCAL3": syslog.LOG_LOCAL3,
"LOG_LOCAL4": syslog.LOG_LOCAL4,
"LOG_LOCAL5": syslog.LOG_LOCAL5,
"LOG_LOCAL6": syslog.LOG_LOCAL6,
"LOG_LOCAL7": syslog.LOG_LOCAL7,
}
if SYSLOG_AVAILABLE
else dict()
else {}
)
_SOCK_MAP = dict(
SOCK_STREAM=socket.SOCK_STREAM,
SOCK_DGRAM=socket.SOCK_DGRAM,
)
_SOCK_MAP = {
"SOCK_STREAM": socket.SOCK_STREAM,
"SOCK_DGRAM": socket.SOCK_DGRAM,
}
class InvokeAIFormatter(logging.Formatter):
@ -344,7 +344,7 @@ LOG_FORMATTERS = {
class InvokeAILogger(object):
loggers = dict()
loggers = {}
@classmethod
def get_logger(
@ -364,7 +364,7 @@ class InvokeAILogger(object):
@classmethod
def get_loggers(cls, config: InvokeAIAppConfig) -> list[logging.Handler]:
handler_strs = config.log_handlers
handlers = list()
handlers = []
for handler in handler_strs:
handler_name, *args = handler.split("=", 2)
args = args[0] if len(args) > 0 else None
@ -398,7 +398,7 @@ class InvokeAILogger(object):
raise ValueError("syslog is not available on this system")
if not args:
args = "/dev/log" if Path("/dev/log").exists() else "address:localhost:514"
syslog_args = dict()
syslog_args = {}
try:
for a in args.split(","):
arg_name, *arg_value = a.split(":", 2)
@ -434,7 +434,7 @@ class InvokeAILogger(object):
path = url.path
port = url.port or 80
syslog_args = dict()
syslog_args = {}
for a in arg_list:
arg_name, *arg_value = a.split(":", 2)
if arg_name == "method":

15
invokeai/backend/util/util.py
View File

@ -29,7 +29,7 @@ def log_txt_as_img(wh, xc, size=10):
# wh a tuple of (width, height)
# xc a list of captions to plot
b = len(xc)
txts = list()
txts = []
for bi in range(b):
txt = Image.new("RGB", wh, color="white")
draw = ImageDraw.Draw(txt)
@ -93,7 +93,7 @@ def instantiate_from_config(config, **kwargs):
elif config == "__is_unconditional__":
return None
raise KeyError("Expected key `target` to instantiate.")
return get_obj_from_str(config["target"])(**config.get("params", dict()), **kwargs)
return get_obj_from_str(config["target"])(**config.get("params", {}), **kwargs)
def get_obj_from_str(string, reload=False):
@ -231,11 +231,12 @@ def rand_perlin_2d(shape, res, device, fade=lambda t: 6 * t**5 - 15 * t**4 + 10
angles = 2 * math.pi * rand_val
gradients = torch.stack((torch.cos(angles), torch.sin(angles)), dim=-1).to(device)
tile_grads = (
lambda slice1, slice2: gradients[slice1[0] : slice1[1], slice2[0] : slice2[1]]
.repeat_interleave(d[0], 0)
.repeat_interleave(d[1], 1)
)
def tile_grads(slice1, slice2):
return (
gradients[slice1[0] : slice1[1], slice2[0] : slice2[1]]
.repeat_interleave(d[0], 0)
.repeat_interleave(d[1], 1)
)
def dot(grad, shift):
return (