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feat(nodes): update all invocations to use new invocation context

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Update all invocations to use the new context. The changes are all fairly simple, but there are a lot of them.

Supporting minor changes:
- Patch bump for all nodes that use the context
- Update invocation processor to provide new context
- Minor change to `EventServiceBase` to accept a node's ID instead of the dict version of a node
- Minor change to `ModelManagerService` to support the new wrapped context
- Fanagling of imports to avoid circular dependencies
This commit is contained in:
psychedelicious
2024-01-13 23:23:16 +11:00
parent 9bc2d09889
commit 8637c40661
32 changed files with 716 additions and 1191 deletions
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44
invokeai/app/invocations/param_easing.py
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@ -41,7 +41,7 @@ from matplotlib.ticker import MaxNLocator
from invokeai.app.invocations.primitives import FloatCollectionOutput
from .baseinvocation import BaseInvocation, InvocationContext, invocation
from .baseinvocation import BaseInvocation, invocation
from .fields import InputField
@ -62,7 +62,7 @@ class FloatLinearRangeInvocation(BaseInvocation):
description="number of values to interpolate over (including start and stop)",
)
def invoke(self, context: InvocationContext) -> FloatCollectionOutput:
def invoke(self, context) -> FloatCollectionOutput:
param_list = list(np.linspace(self.start, self.stop, self.steps))
return FloatCollectionOutput(collection=param_list)
@ -110,7 +110,7 @@ EASING_FUNCTION_KEYS = Literal[tuple(EASING_FUNCTIONS_MAP.keys())]
title="Step Param Easing",
tags=["step", "easing"],
category="step",
version="1.0.0",
version="1.0.1",
)
class StepParamEasingInvocation(BaseInvocation):
"""Experimental per-step parameter easing for denoising steps"""
@ -130,7 +130,7 @@ class StepParamEasingInvocation(BaseInvocation):
# alt_mirror: bool = InputField(default=False, description="alternative mirroring by dual easing")
show_easing_plot: bool = InputField(default=False, description="show easing plot")
def invoke(self, context: InvocationContext) -> FloatCollectionOutput:
def invoke(self, context) -> FloatCollectionOutput:
log_diagnostics = False
# convert from start_step_percent to nearest step <= (steps * start_step_percent)
# start_step = int(np.floor(self.num_steps * self.start_step_percent))
@ -149,19 +149,19 @@ class StepParamEasingInvocation(BaseInvocation):
postlist = list(num_poststeps * [self.post_end_value])
if log_diagnostics:
context.services.logger.debug("start_step: " + str(start_step))
context.services.logger.debug("end_step: " + str(end_step))
context.services.logger.debug("num_easing_steps: " + str(num_easing_steps))
context.services.logger.debug("num_presteps: " + str(num_presteps))
context.services.logger.debug("num_poststeps: " + str(num_poststeps))
context.services.logger.debug("prelist size: " + str(len(prelist)))
context.services.logger.debug("postlist size: " + str(len(postlist)))
context.services.logger.debug("prelist: " + str(prelist))
context.services.logger.debug("postlist: " + str(postlist))
context.logger.debug("start_step: " + str(start_step))
context.logger.debug("end_step: " + str(end_step))
context.logger.debug("num_easing_steps: " + str(num_easing_steps))
context.logger.debug("num_presteps: " + str(num_presteps))
context.logger.debug("num_poststeps: " + str(num_poststeps))
context.logger.debug("prelist size: " + str(len(prelist)))
context.logger.debug("postlist size: " + str(len(postlist)))
context.logger.debug("prelist: " + str(prelist))
context.logger.debug("postlist: " + str(postlist))
easing_class = EASING_FUNCTIONS_MAP[self.easing]
if log_diagnostics:
context.services.logger.debug("easing class: " + str(easing_class))
context.logger.debug("easing class: " + str(easing_class))
easing_list = []
if self.mirror: # "expected" mirroring
# if number of steps is even, squeeze duration down to (number_of_steps)/2
@ -172,7 +172,7 @@ class StepParamEasingInvocation(BaseInvocation):
base_easing_duration = int(np.ceil(num_easing_steps / 2.0))
if log_diagnostics:
context.services.logger.debug("base easing duration: " + str(base_easing_duration))
context.logger.debug("base easing duration: " + str(base_easing_duration))
even_num_steps = num_easing_steps % 2 == 0 # even number of steps
easing_function = easing_class(
start=self.start_value,
@ -184,14 +184,14 @@ class StepParamEasingInvocation(BaseInvocation):
easing_val = easing_function.ease(step_index)
base_easing_vals.append(easing_val)
if log_diagnostics:
context.services.logger.debug("step_index: " + str(step_index) + ", easing_val: " + str(easing_val))
context.logger.debug("step_index: " + str(step_index) + ", easing_val: " + str(easing_val))
if even_num_steps:
mirror_easing_vals = list(reversed(base_easing_vals))
else:
mirror_easing_vals = list(reversed(base_easing_vals[0:-1]))
if log_diagnostics:
context.services.logger.debug("base easing vals: " + str(base_easing_vals))
context.services.logger.debug("mirror easing vals: " + str(mirror_easing_vals))
context.logger.debug("base easing vals: " + str(base_easing_vals))
context.logger.debug("mirror easing vals: " + str(mirror_easing_vals))
easing_list = base_easing_vals + mirror_easing_vals
# FIXME: add alt_mirror option (alternative to default or mirror), or remove entirely
@ -226,12 +226,12 @@ class StepParamEasingInvocation(BaseInvocation):
step_val = easing_function.ease(step_index)
easing_list.append(step_val)
if log_diagnostics:
context.services.logger.debug("step_index: " + str(step_index) + ", easing_val: " + str(step_val))
context.logger.debug("step_index: " + str(step_index) + ", easing_val: " + str(step_val))
if log_diagnostics:
context.services.logger.debug("prelist size: " + str(len(prelist)))
context.services.logger.debug("easing_list size: " + str(len(easing_list)))
context.services.logger.debug("postlist size: " + str(len(postlist)))
context.logger.debug("prelist size: " + str(len(prelist)))
context.logger.debug("easing_list size: " + str(len(easing_list)))
context.logger.debug("postlist size: " + str(len(postlist)))
param_list = prelist + easing_list + postlist