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Code Issues Actions 14 Packages Projects Releases Wiki Activity

Update _for_testing to experimental

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This commit is contained in:
Alexis Rolland 2026-05-08 08:16:28 +08:00
parent e6d9529575
commit 8cf7e08df8
17 changed files with 41 additions and 41 deletions
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2
comfy_extras/nodes_advanced_samplers.py
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@ -92,7 +92,7 @@ class SamplerEulerCFGpp(io.ComfyNode):
return io.Schema(
node_id="SamplerEulerCFGpp",
display_name="SamplerEulerCFG++",
category="_for_testing", # "sampling/custom_sampling/samplers"
category="experimental", # "sampling/custom_sampling/samplers"
inputs=[
io.Combo.Input("version", options=["regular", "alternative"], advanced=True),
],

8
comfy_extras/nodes_attention_multiply.py
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@ -25,7 +25,7 @@ class UNetSelfAttentionMultiply(io.ComfyNode):
def define_schema(cls) -> io.Schema:
return io.Schema(
node_id="UNetSelfAttentionMultiply",
category="_for_testing/attention_experiments",
category="experimental/attention_experiments",
inputs=[
io.Model.Input("model"),
io.Float.Input("q", default=1.0, min=0.0, max=10.0, step=0.01, advanced=True),
@ -48,7 +48,7 @@ class UNetCrossAttentionMultiply(io.ComfyNode):
def define_schema(cls) -> io.Schema:
return io.Schema(
node_id="UNetCrossAttentionMultiply",
category="_for_testing/attention_experiments",
category="experimental/attention_experiments",
inputs=[
io.Model.Input("model"),
io.Float.Input("q", default=1.0, min=0.0, max=10.0, step=0.01, advanced=True),
@ -72,7 +72,7 @@ class CLIPAttentionMultiply(io.ComfyNode):
return io.Schema(
node_id="CLIPAttentionMultiply",
search_aliases=["clip attention scale", "text encoder attention"],
category="_for_testing/attention_experiments",
category="experimental/attention_experiments",
inputs=[
io.Clip.Input("clip"),
io.Float.Input("q", default=1.0, min=0.0, max=10.0, step=0.01, advanced=True),
@ -106,7 +106,7 @@ class UNetTemporalAttentionMultiply(io.ComfyNode):
def define_schema(cls) -> io.Schema:
return io.Schema(
node_id="UNetTemporalAttentionMultiply",
category="_for_testing/attention_experiments",
category="experimental/attention_experiments",
inputs=[
io.Model.Input("model"),
io.Float.Input("self_structural", default=1.0, min=0.0, max=10.0, step=0.01, advanced=True),

4
comfy_extras/nodes_cond.py
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@ -8,7 +8,7 @@ class CLIPTextEncodeControlnet(io.ComfyNode):
def define_schema(cls) -> io.Schema:
return io.Schema(
node_id="CLIPTextEncodeControlnet",
category="_for_testing/conditioning",
category="experimental/conditioning",
inputs=[
io.Clip.Input("clip"),
io.Conditioning.Input("conditioning"),
@ -35,7 +35,7 @@ class T5TokenizerOptions(io.ComfyNode):
def define_schema(cls) -> io.Schema:
return io.Schema(
node_id="T5TokenizerOptions",
category="_for_testing/conditioning",
category="experimental/conditioning",
inputs=[
io.Clip.Input("clip"),
io.Int.Input("min_padding", default=0, min=0, max=10000, step=1, advanced=True),

4
comfy_extras/nodes_custom_sampler.py
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@ -984,7 +984,7 @@ class AddNoise(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="AddNoise",
category="_for_testing/custom_sampling/noise",
category="experimental/custom_sampling/noise",
is_experimental=True,
inputs=[
io.Model.Input("model"),
@ -1034,7 +1034,7 @@ class ManualSigmas(io.ComfyNode):
return io.Schema(
node_id="ManualSigmas",
search_aliases=["custom noise schedule", "define sigmas"],
category="_for_testing/custom_sampling",
category="experimental/custom_sampling",
is_experimental=True,
inputs=[
io.String.Input("sigmas", default="1, 0.5", multiline=False)

2
comfy_extras/nodes_differential_diffusion.py
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@ -13,7 +13,7 @@ class DifferentialDiffusion(io.ComfyNode):
node_id="DifferentialDiffusion",
search_aliases=["inpaint gradient", "variable denoise strength"],
display_name="Differential Diffusion",
category="_for_testing",
category="experimental",
inputs=[
io.Model.Input("model"),
io.Float.Input(

2
comfy_extras/nodes_fresca.py
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@ -60,7 +60,7 @@ class FreSca(io.ComfyNode):
node_id="FreSca",
search_aliases=["frequency guidance"],
display_name="FreSca",
category="_for_testing",
category="experimental",
description="Applies frequency-dependent scaling to the guidance",
inputs=[
io.Model.Input("model"),

2
comfy_extras/nodes_lora_extract.py
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@ -91,7 +91,7 @@ class LoraSave(io.ComfyNode):
node_id="LoraSave",
search_aliases=["export lora"],
display_name="Extract and Save Lora",
category="_for_testing",
category="experimental",
inputs=[
io.String.Input("filename_prefix", default="loras/ComfyUI_extracted_lora"),
io.Int.Input("rank", default=8, min=1, max=4096, step=1, advanced=True),

2
comfy_extras/nodes_mahiro.py
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@ -11,7 +11,7 @@ class Mahiro(io.ComfyNode):
return io.Schema(
node_id="Mahiro",
display_name="Positive-Biased Guidance",
category="_for_testing",
category="experimental",
description="Modify the guidance to scale more on the 'direction' of the positive prompt rather than the difference between the negative prompt.",
inputs=[
io.Model.Input("model"),

4
comfy_extras/nodes_perpneg.py
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@ -25,7 +25,7 @@ class PerpNeg(io.ComfyNode):
return io.Schema(
node_id="PerpNeg",
display_name="Perp-Neg (DEPRECATED)",
category="_for_testing",
category="experimental",
inputs=[
io.Model.Input("model"),
io.Conditioning.Input("empty_conditioning"),
@ -128,7 +128,7 @@ class PerpNegGuider(io.ComfyNode):
return io.Schema(
node_id="PerpNegGuider",
display_name="Perp-Neg Guider",
category="_for_testing",
category="experimental",
inputs=[
io.Model.Input("model"),
io.Conditioning.Input("positive"),

4
comfy_extras/nodes_photomaker.py
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@ -123,7 +123,7 @@ class PhotoMakerLoader(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="PhotoMakerLoader",
category="_for_testing/photomaker",
category="experimental/photomaker",
inputs=[
io.Combo.Input("photomaker_model_name", options=folder_paths.get_filename_list("photomaker")),
],
@ -149,7 +149,7 @@ class PhotoMakerEncode(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="PhotoMakerEncode",
category="_for_testing/photomaker",
category="experimental/photomaker",
inputs=[
io.Photomaker.Input("photomaker"),
io.Image.Input("image"),

2
comfy_extras/nodes_sag.py
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@ -113,7 +113,7 @@ class SelfAttentionGuidance(io.ComfyNode):
return io.Schema(
node_id="SelfAttentionGuidance",
display_name="Self-Attention Guidance",
category="_for_testing",
category="experimental",
inputs=[
io.Model.Input("model"),
io.Float.Input("scale", default=0.5, min=-2.0, max=5.0, step=0.01),

2
comfy_extras/nodes_stable_cascade.py
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@ -119,7 +119,7 @@ class StableCascade_SuperResolutionControlnet(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="StableCascade_SuperResolutionControlnet",
category="_for_testing/stable_cascade",
category="experimental/stable_cascade",
is_experimental=True,
inputs=[
io.Image.Input("image"),

2
comfy_extras/nodes_torch_compile.py
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@ -10,7 +10,7 @@ class TorchCompileModel(io.ComfyNode):
def define_schema(cls) -> io.Schema:
return io.Schema(
node_id="TorchCompileModel",
category="_for_testing",
category="experimental",
inputs=[
io.Model.Input("model"),
io.Combo.Input(

12
nodes.py
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@ -330,7 +330,7 @@ class VAEDecodeTiled:
RETURN_TYPES = ("IMAGE",)
FUNCTION = "decode"
CATEGORY = "_for_testing"
CATEGORY = "experimental"
def decode(self, vae, samples, tile_size, overlap=64, temporal_size=64, temporal_overlap=8):
if tile_size < overlap * 4:
@ -377,7 +377,7 @@ class VAEEncodeTiled:
RETURN_TYPES = ("LATENT",)
FUNCTION = "encode"
CATEGORY = "_for_testing"
CATEGORY = "experimental"
def encode(self, vae, pixels, tile_size, overlap, temporal_size=64, temporal_overlap=8):
t = vae.encode_tiled(pixels, tile_x=tile_size, tile_y=tile_size, overlap=overlap, tile_t=temporal_size, overlap_t=temporal_overlap)
@ -493,7 +493,7 @@ class SaveLatent:
OUTPUT_NODE = True
CATEGORY = "_for_testing"
CATEGORY = "experimental"
def save(self, samples, filename_prefix="ComfyUI", prompt=None, extra_pnginfo=None):
full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(filename_prefix, self.output_dir)
@ -538,7 +538,7 @@ class LoadLatent:
files = [f for f in os.listdir(input_dir) if os.path.isfile(os.path.join(input_dir, f)) and f.endswith(".latent")]
return {"required": {"latent": [sorted(files), ]}, }
CATEGORY = "_for_testing"
CATEGORY = "experimental"
RETURN_TYPES = ("LATENT", )
FUNCTION = "load"
@ -1443,7 +1443,7 @@ class LatentBlend:
RETURN_TYPES = ("LATENT",)
FUNCTION = "blend"
CATEGORY = "_for_testing"
CATEGORY = "experimental"
def blend(self, samples1, samples2, blend_factor:float, blend_mode: str="normal"):
@ -2142,7 +2142,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
"ImageSharpen": "Sharpen Image",
"ImageScaleToTotalPixels": "Scale Image to Total Pixels",
"GetImageSize": "Get Image Size",
# _for_testing
# experimental
"VAEDecodeTiled": "VAE Decode (Tiled)",
"VAEEncodeTiled": "VAE Encode (Tiled)",
}

4
tests/execution/testing_nodes/testing-pack/api_test_nodes.py
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@ -21,7 +21,7 @@ class TestAsyncProgressUpdate(ComfyNodeABC):
RETURN_TYPES = (IO.ANY,)
FUNCTION = "execute"
CATEGORY = "_for_testing/async"
CATEGORY = "experimental/async"
async def execute(self, value, sleep_seconds):
start = time.time()
@ -51,7 +51,7 @@ class TestSyncProgressUpdate(ComfyNodeABC):
RETURN_TYPES = (IO.ANY,)
FUNCTION = "execute"
CATEGORY = "_for_testing/async"
CATEGORY = "experimental/async"
def execute(self, value, sleep_seconds):
start = time.time()

20
tests/execution/testing_nodes/testing-pack/async_test_nodes.py
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@ -21,7 +21,7 @@ class TestAsyncValidation(ComfyNodeABC):
RETURN_TYPES = ("IMAGE",)
FUNCTION = "process"
CATEGORY = "_for_testing/async"
CATEGORY = "experimental/async"
@classmethod
async def VALIDATE_INPUTS(cls, value, threshold):
@ -53,7 +53,7 @@ class TestAsyncError(ComfyNodeABC):
RETURN_TYPES = (IO.ANY,)
FUNCTION = "error_execution"
CATEGORY = "_for_testing/async"
CATEGORY = "experimental/async"
async def error_execution(self, value, error_after):
await asyncio.sleep(error_after)
@ -74,7 +74,7 @@ class TestAsyncValidationError(ComfyNodeABC):
RETURN_TYPES = ("IMAGE",)
FUNCTION = "process"
CATEGORY = "_for_testing/async"
CATEGORY = "experimental/async"
@classmethod
async def VALIDATE_INPUTS(cls, value, max_value):
@ -105,7 +105,7 @@ class TestAsyncTimeout(ComfyNodeABC):
RETURN_TYPES = (IO.ANY,)
FUNCTION = "timeout_execution"
CATEGORY = "_for_testing/async"
CATEGORY = "experimental/async"
async def timeout_execution(self, value, timeout, operation_time):
try:
@ -129,7 +129,7 @@ class TestSyncError(ComfyNodeABC):
RETURN_TYPES = (IO.ANY,)
FUNCTION = "sync_error"
CATEGORY = "_for_testing/async"
CATEGORY = "experimental/async"
def sync_error(self, value):
raise RuntimeError("Intentional sync execution error for testing")
@ -150,7 +150,7 @@ class TestAsyncLazyCheck(ComfyNodeABC):
RETURN_TYPES = ("IMAGE",)
FUNCTION = "process"
CATEGORY = "_for_testing/async"
CATEGORY = "experimental/async"
async def check_lazy_status(self, condition, input1, input2):
# Simulate async checking (e.g., querying remote service)
@ -184,7 +184,7 @@ class TestDynamicAsyncGeneration(ComfyNodeABC):
RETURN_TYPES = ("IMAGE",)
FUNCTION = "generate_async_workflow"
CATEGORY = "_for_testing/async"
CATEGORY = "experimental/async"
def generate_async_workflow(self, image1, image2, num_async_nodes, sleep_duration):
g = GraphBuilder()
@ -229,7 +229,7 @@ class TestAsyncResourceUser(ComfyNodeABC):
RETURN_TYPES = (IO.ANY,)
FUNCTION = "use_resource"
CATEGORY = "_for_testing/async"
CATEGORY = "experimental/async"
async def use_resource(self, value, resource_id, duration):
# Check if resource is already in use
@ -265,7 +265,7 @@ class TestAsyncBatchProcessing(ComfyNodeABC):
RETURN_TYPES = ("IMAGE",)
FUNCTION = "process_batch"
CATEGORY = "_for_testing/async"
CATEGORY = "experimental/async"
async def process_batch(self, images, process_time_per_item, unique_id):
batch_size = images.shape[0]
@ -305,7 +305,7 @@ class TestAsyncConcurrentLimit(ComfyNodeABC):
RETURN_TYPES = (IO.ANY,)
FUNCTION = "limited_execution"
CATEGORY = "_for_testing/async"
CATEGORY = "experimental/async"
async def limited_execution(self, value, duration, node_id):
async with self._semaphore:

6
tests/execution/testing_nodes/testing-pack/specific_tests.py
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@ -409,7 +409,7 @@ class TestSleep(ComfyNodeABC):
RETURN_TYPES = (IO.ANY,)
FUNCTION = "sleep"
CATEGORY = "_for_testing"
CATEGORY = "experimental"
async def sleep(self, value, seconds, unique_id):
pbar = ProgressBar(seconds, node_id=unique_id)
@ -440,7 +440,7 @@ class TestParallelSleep(ComfyNodeABC):
}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "parallel_sleep"
CATEGORY = "_for_testing"
CATEGORY = "experimental"
OUTPUT_NODE = True
def parallel_sleep(self, image1, image2, image3, sleep1, sleep2, sleep3, unique_id):
@ -474,7 +474,7 @@ class TestOutputNodeWithSocketOutput:
}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "process"
CATEGORY = "_for_testing"
CATEGORY = "experimental"
OUTPUT_NODE = True
def process(self, image, value):