nodes/cubiq-ComfyUI_IPAdapter_plus
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add composition weight type, small performance optimization

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matt3o
2024-04-01 12:42:08 +02:00
parent e736a64212
commit d20fb1fbbf
2 changed files with 26 additions and 23 deletions
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CrossAttentionPatch.py
+23 -20
View File
@@ -54,6 +54,29 @@ class CrossAttentionPatch:
for weight, cond, uncond, ipadapter, mask, weight_type, sigma_start, sigma_end, unfold_batch, embeds_scaling in zip(self.weights, self.conds, self.unconds, self.ipadapters, self.masks, self.weight_types, self.sigma_starts, self.sigma_ends, self.unfold_batch, self.embeds_scaling):
if sigma <= sigma_start and sigma >= sigma_end:
if weight_type == 'ease in':
weight = weight * (0.05 + 0.95 * (1 - t_idx / self.layers))
elif weight_type == 'ease out':
weight = weight * (0.05 + 0.95 * (t_idx / self.layers))
elif weight_type == 'ease in-out':
weight = weight * (0.05 + 0.95 * (1 - abs(t_idx - (self.layers/2)) / (self.layers/2)))
elif weight_type == 'reverse in-out':
weight = weight * (0.05 + 0.95 * (abs(t_idx - (self.layers/2)) / (self.layers/2)))
elif weight_type == 'weak input' and block_type == 'input':
weight = weight * 0.2
elif weight_type == 'weak middle' and block_type == 'middle':
weight = weight * 0.2
elif weight_type == 'weak output' and block_type == 'output':
weight = weight * 0.2
elif weight_type == 'strong middle' and (block_type == 'input' or block_type == 'output'):
weight = weight * 0.2
elif weight_type.startswith('style transfer'):
if t_idx != 6:
continue
elif weight_type.startswith('composition'):
if t_idx != 3:
continue
if unfold_batch and cond.shape[0] > 1:
# Check AnimateDiff context window
if ad_params is not None and ad_params["sub_idxs"] is not None:
@@ -81,26 +104,6 @@ class CrossAttentionPatch:
v_cond = ipadapter.ip_layers.to_kvs[self.v_key](cond).repeat(batch_prompt, 1, 1)
v_uncond = ipadapter.ip_layers.to_kvs[self.v_key](uncond).repeat(batch_prompt, 1, 1)
if weight_type == 'ease in':
weight = weight * (0.05 + 0.95 * (1 - t_idx / self.layers))
elif weight_type == 'ease out':
weight = weight * (0.05 + 0.95 * (t_idx / self.layers))
elif weight_type == 'ease in-out':
weight = weight * (0.05 + 0.95 * (1 - abs(t_idx - (self.layers/2)) / (self.layers/2)))
elif weight_type == 'reverse in-out':
weight = weight * (0.05 + 0.95 * (abs(t_idx - (self.layers/2)) / (self.layers/2)))
elif weight_type == 'weak input' and block_type == 'input':
weight = weight * 0.2
elif weight_type == 'weak middle' and block_type == 'middle':
weight = weight * 0.2
elif weight_type == 'weak output' and block_type == 'output':
weight = weight * 0.2
elif weight_type == 'strong middle' and (block_type == 'input' or block_type == 'output'):
weight = weight * 0.2
elif weight_type.startswith('style transfer'):
if t_idx != 6:
weight = 0.0
ip_k = torch.cat([(k_cond, k_uncond)[i] for i in cond_or_uncond], dim=0)
ip_v = torch.cat([(v_cond, v_uncond)[i] for i in cond_or_uncond], dim=0)
IPAdapterPlus.py
+3 -3
View File
@@ -37,7 +37,7 @@ else:
current_paths, _ = folder_paths.folder_names_and_paths["ipadapter"]
folder_paths.folder_names_and_paths["ipadapter"] = (current_paths, folder_paths.supported_pt_extensions)
WEIGHT_TYPES = ["linear", "ease in", "ease out", 'ease in-out', 'reverse in-out', 'weak input', 'weak output', 'weak middle', 'strong middle', 'style transfer (SDXL)']
WEIGHT_TYPES = ["linear", "ease in", "ease out", 'ease in-out', 'reverse in-out', 'weak input', 'weak output', 'weak middle', 'strong middle', 'style transfer (SDXL)', 'composition (SDXL)']
"""
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -171,8 +171,8 @@ def ipadapter_execute(model,
output_cross_attention_dim = ipadapter["ip_adapter"]["1.to_k_ip.weight"].shape[1]
is_sdxl = output_cross_attention_dim == 2048
if weight_type == "style transfer (SDXL)" and not is_sdxl:
raise Exception("Style Transfer weight type is only available for SDXL models")
if '(SDXL)' in weight_type and not is_sdxl:
raise Exception("Style Transfer and Composition weight types are available for SDXL models only")
#weight_type = "linear"
#print("\033[33mINFO: 'Style Transfer' weight type is only available for SDXL models, falling back to 'linear'.\033[0m")