Merge pull request #223 from Kosinkadink/multigpu

Get context-related info from ad_params in transformer_options

Author: Kosinkadink

adv_control/control_reference.py

@@ -162,7 +162,7 @@ def __init__(self, ref_opts: ReferenceOptions, timestep_keyframes: TimestepKeyfr
         self.extra_hooks = extra_hooks.clone() if extra_hooks else self.import_and_create_wrapper_hooks()
         # ContextRef stuff
         self.is_context_ref = False
-        self.contextref_cond_idx = -1
+        self.contextref_cond_idx = -1 # NOTE: does nothing ever since conds got uuids associated with them; can remove
         self.contextref_version = RETURNED_CONTEXTREF_VERSION
 
     @property

adv_control/sampling.py

@@ -18,9 +18,7 @@
                                 handle_context_ref_setup, handle_reference_injection,
                                 REF_CONTROL_LIST_ALL, CONTEXTREF_CLEAN_FUNC)
 from .dinklink import get_dinklink
-from .utils import torch_dfs, WrapperConsts
-
-CURRENT_WRAPPER_VERSION = 10001
+from .utils import torch_dfs, WrapperConsts, CURRENT_WRAPPER_VERSION
 
 def prepare_dinklink_acn_wrapper():
     # expose acn_sampler_sample_wrapper

adv_control/utils.py

@@ -35,6 +35,8 @@ def load_torch_file_with_dict(*args, **kwargs):
     return load_torch_file_with_dict
 
 
+CURRENT_WRAPPER_VERSION = 10002
+
 class WrapperConsts:
     ACN = "ACN"
     VERSION = "version"
@@ -480,6 +482,8 @@ class WeightTypeException(TypeError):
 
 
 class AdvancedControlBase:
+    ACN_VERSION = CURRENT_WRAPPER_VERSION
+    
     def __init__(self, base: ControlBase, timestep_keyframes: TimestepKeyframeGroup, weights_default: ControlWeights, require_vae=False, allow_condhint_latents=False):
         self.base = base
         self.compatible_weights = [ControlWeightType.UNIVERSAL, ControlWeightType.DEFAULT]
@@ -679,6 +683,11 @@ def get_control_inject(self, x_noisy, t, cond, batched_number, transformer_optio
         self.batched_number = batched_number
         self.batch_size = len(t)
         self.cond_or_uncond = transformer_options.get("cond_or_uncond", None)
+        # fill out ad_param-related fields, if present
+        if "ad_params" in transformer_options:
+            self.sub_idxs = transformer_options["ad_params"]["sub_idxs"]
+            self.full_latent_length = transformer_options["ad_params"]["full_length"]
+            self.context_length = transformer_options["ad_params"]["context_length"]
         # prepare timestep and everything related
         self.prepare_current_timestep(t=t, transformer_options=transformer_options)
         # if should not perform any actions for the controlnet, exit without doing any work

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-advanced-controlnet"
 description = "Nodes for scheduling ControlNet strength across timesteps and batched latents, as well as applying custom weights and attention masks."
-version = "1.5.3"
+version = "1.5.4"
 license = { file = "LICENSE" }
 dependencies = []