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https://github.com/comfyanonymous/ComfyUI.git
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Merge c6ad7a4d01
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04b50d6260
1
.github/workflows/stable-release.yml
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.github/workflows/stable-release.yml
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@ -1,4 +1,3 @@
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name: "Release Stable Version"
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name: "Release Stable Version"
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on:
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on:
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2
.github/workflows/test-unit.yml
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.github/workflows/test-unit.yml
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@ -15,7 +15,7 @@ jobs:
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continue-on-error: true
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continue-on-error: true
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steps:
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steps:
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- uses: actions/checkout@v4
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- uses: actions/checkout@v4
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- name: Set up Python
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- name: Set up Python
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uses: actions/setup-python@v4
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uses: actions/setup-python@v4
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with:
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with:
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python-version: '3.12'
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python-version: '3.12'
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@ -36,7 +36,7 @@ ComfyUI lets you design and execute advanced stable diffusion pipelines using a
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## Get Started
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## Get Started
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#### [Desktop Application](https://www.comfy.org/download)
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#### [Desktop Application](https://www.comfy.org/download)
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- The easiest way to get started.
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- The easiest way to get started.
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- Available on Windows & macOS.
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- Available on Windows & macOS.
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#### [Windows Portable Package](#installing)
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#### [Windows Portable Package](#installing)
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@ -190,7 +190,7 @@ This is the command to install the nightly with ROCm 6.3 which might have some p
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### Intel GPUs (Windows and Linux)
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### Intel GPUs (Windows and Linux)
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(Option 1) Intel Arc GPU users can install native PyTorch with torch.xpu support using pip (currently available in PyTorch nightly builds). More information can be found [here](https://pytorch.org/docs/main/notes/get_start_xpu.html)
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(Option 1) Intel Arc GPU users can install native PyTorch with torch.xpu support using pip (currently available in PyTorch nightly builds). More information can be found [here](https://pytorch.org/docs/main/notes/get_start_xpu.html)
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1. To install PyTorch nightly, use the following command:
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1. To install PyTorch nightly, use the following command:
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```pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/xpu```
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```pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/xpu```
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@ -321,7 +321,7 @@ Generate a self-signed certificate (not appropriate for shared/production use) a
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Use `--tls-keyfile key.pem --tls-certfile cert.pem` to enable TLS/SSL, the app will now be accessible with `https://...` instead of `http://...`.
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Use `--tls-keyfile key.pem --tls-certfile cert.pem` to enable TLS/SSL, the app will now be accessible with `https://...` instead of `http://...`.
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> Note: Windows users can use [alexisrolland/docker-openssl](https://github.com/alexisrolland/docker-openssl) or one of the [3rd party binary distributions](https://wiki.openssl.org/index.php/Binaries) to run the command example above.
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> Note: Windows users can use [alexisrolland/docker-openssl](https://github.com/alexisrolland/docker-openssl) or one of the [3rd party binary distributions](https://wiki.openssl.org/index.php/Binaries) to run the command example above.
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<br/><br/>If you use a container, note that the volume mount `-v` can be a relative path so `... -v ".\:/openssl-certs" ...` would create the key & cert files in the current directory of your command prompt or powershell terminal.
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<br/><br/>If you use a container, note that the volume mount `-v` can be a relative path so `... -v ".\:/openssl-certs" ...` would create the key & cert files in the current directory of your command prompt or powershell terminal.
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## Support and dev channel
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## Support and dev channel
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@ -587,7 +587,7 @@ def get_sorted_list_via_attr(objects: list, attr: str) -> list:
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sorted_list.extend(object_list)
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sorted_list.extend(object_list)
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return sorted_list
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return sorted_list
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def create_transformer_options_from_hooks(model: ModelPatcher, hooks: HookGroup, transformer_options: dict[str]=None):
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def create_transformer_options_from_hooks(model: ModelPatcher, hooks: HookGroup, transformer_options: dict[str]=None):
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# if no hooks or is not a ModelPatcher for sampling, return empty dict
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# if no hooks or is not a ModelPatcher for sampling, return empty dict
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if hooks is None or model.is_clip:
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if hooks is None or model.is_clip:
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return {}
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return {}
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@ -618,10 +618,10 @@ class PixArtAlpha(supported_models_base.BASE):
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}
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}
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sampling_settings = {
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sampling_settings = {
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"beta_schedule" : "sqrt_linear",
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"beta_schedule": "sqrt_linear",
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"linear_start" : 0.0001,
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"linear_start": 0.0001,
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"linear_end" : 0.02,
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"linear_end": 0.02,
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"timesteps" : 1000,
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"timesteps": 1000,
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}
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}
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unet_extra_config = {}
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unet_extra_config = {}
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@ -681,8 +681,8 @@ class HunyuanDiT1(HunyuanDiT):
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unet_extra_config = {}
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unet_extra_config = {}
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sampling_settings = {
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sampling_settings = {
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"linear_start" : 0.00085,
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"linear_start": 0.00085,
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"linear_end" : 0.03,
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"linear_end": 0.03,
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}
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}
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class Flux(supported_models_base.BASE):
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class Flux(supported_models_base.BASE):
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@ -449,8 +449,8 @@ PIXART_MAP_BLOCK = {
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("mlp.fc1.bias", "ff.net.0.proj.bias"),
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("mlp.fc1.bias", "ff.net.0.proj.bias"),
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("mlp.fc2.weight", "ff.net.2.weight"),
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("mlp.fc2.weight", "ff.net.2.weight"),
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("mlp.fc2.bias", "ff.net.2.bias"),
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("mlp.fc2.bias", "ff.net.2.bias"),
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("cross_attn.proj.weight" ,"attn2.to_out.0.weight"),
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("cross_attn.proj.weight", "attn2.to_out.0.weight"),
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("cross_attn.proj.bias" ,"attn2.to_out.0.bias"),
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("cross_attn.proj.bias", "attn2.to_out.0.bias"),
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}
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}
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def pixart_to_diffusers(mmdit_config, output_prefix=""):
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def pixart_to_diffusers(mmdit_config, output_prefix=""):
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@ -9,7 +9,7 @@ class Morphology:
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@classmethod
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@classmethod
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def INPUT_TYPES(s):
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def INPUT_TYPES(s):
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return {"required": {"image": ("IMAGE",),
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return {"required": {"image": ("IMAGE",),
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"operation": (["erode", "dilate", "open", "close", "gradient", "bottom_hat", "top_hat"],),
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"operation": (["erode", "dilate", "open", "close", "gradient", "bottom_hat", "top_hat"],),
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"kernel_size": ("INT", {"default": 3, "min": 3, "max": 999, "step": 1}),
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"kernel_size": ("INT", {"default": 3, "min": 3, "max": 999, "step": 1}),
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}}
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}}
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@ -84,7 +84,7 @@ class CacheHelper:
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cache_helper = CacheHelper()
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cache_helper = CacheHelper()
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extension_mimetypes_cache = {
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extension_mimetypes_cache = {
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"webp" : "image",
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"webp": "image",
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}
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}
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def map_legacy(folder_name: str) -> str:
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def map_legacy(folder_name: str) -> str:
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4
nodes.py
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nodes.py
@ -1989,7 +1989,7 @@ NODE_CLASS_MAPPINGS = {
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"ImageBatch": ImageBatch,
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"ImageBatch": ImageBatch,
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"ImagePadForOutpaint": ImagePadForOutpaint,
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"ImagePadForOutpaint": ImagePadForOutpaint,
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"EmptyImage": EmptyImage,
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"EmptyImage": EmptyImage,
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"ConditioningAverage": ConditioningAverage ,
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"ConditioningAverage": ConditioningAverage,
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"ConditioningCombine": ConditioningCombine,
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"ConditioningCombine": ConditioningCombine,
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"ConditioningConcat": ConditioningConcat,
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"ConditioningConcat": ConditioningConcat,
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"ConditioningSetArea": ConditioningSetArea,
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"ConditioningSetArea": ConditioningSetArea,
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"LatentUpscaleBy": "Upscale Latent By",
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"LatentUpscaleBy": "Upscale Latent By",
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"LatentComposite": "Latent Composite",
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"LatentComposite": "Latent Composite",
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"LatentBlend": "Latent Blend",
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"LatentBlend": "Latent Blend",
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"LatentFromBatch" : "Latent From Batch",
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"LatentFromBatch": "Latent From Batch",
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"RepeatLatentBatch": "Repeat Latent Batch",
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"RepeatLatentBatch": "Repeat Latent Batch",
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# Image
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# Image
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"SaveImage": "Save Image",
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"SaveImage": "Save Image",
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[pytest]
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[pytest]
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markers =
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markers =
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inference: mark as inference test (deselect with '-m "not inference"')
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inference: mark as inference test (deselect with '-m "not inference"')
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execution: mark as execution test (deselect with '-m "not execution"')
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execution: mark as execution test (deselect with '-m "not execution"')
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testpaths =
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testpaths =
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