ComfyUI/tests/inference/testing_nodes/testing-pack/stubs.py

130 lines
3.6 KiB
Python

import torch
class StubImage:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"content": (['WHITE', 'BLACK', 'NOISE'],),
"height": ("INT", {"default": 512, "min": 1, "max": 1024 ** 3, "step": 1}),
"width": ("INT", {"default": 512, "min": 1, "max": 4096 ** 3, "step": 1}),
"batch_size": ("INT", {"default": 1, "min": 1, "max": 1024 ** 3, "step": 1}),
},
}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "stub_image"
CATEGORY = "Testing/Stub Nodes"
def stub_image(self, content, height, width, batch_size):
if content == "WHITE":
return (torch.ones(batch_size, height, width, 3),)
elif content == "BLACK":
return (torch.zeros(batch_size, height, width, 3),)
elif content == "NOISE":
return (torch.rand(batch_size, height, width, 3),)
class StubConstantImage:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"value": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01}),
"height": ("INT", {"default": 512, "min": 1, "max": 1024 ** 3, "step": 1}),
"width": ("INT", {"default": 512, "min": 1, "max": 4096 ** 3, "step": 1}),
"batch_size": ("INT", {"default": 1, "min": 1, "max": 1024 ** 3, "step": 1}),
},
}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "stub_constant_image"
CATEGORY = "Testing/Stub Nodes"
def stub_constant_image(self, value, height, width, batch_size):
return (torch.ones(batch_size, height, width, 3) * value,)
class StubMask:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"value": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01}),
"height": ("INT", {"default": 512, "min": 1, "max": 1024 ** 3, "step": 1}),
"width": ("INT", {"default": 512, "min": 1, "max": 4096 ** 3, "step": 1}),
"batch_size": ("INT", {"default": 1, "min": 1, "max": 1024 ** 3, "step": 1}),
},
}
RETURN_TYPES = ("MASK",)
FUNCTION = "stub_mask"
CATEGORY = "Testing/Stub Nodes"
def stub_mask(self, value, height, width, batch_size):
return (torch.ones(batch_size, height, width) * value,)
class StubInt:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"value": ("INT", {"default": 0, "min": -0xffffffff, "max": 0xffffffff, "step": 1}),
},
}
RETURN_TYPES = ("INT",)
FUNCTION = "stub_int"
CATEGORY = "Testing/Stub Nodes"
def stub_int(self, value):
return (value,)
class StubFloat:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"value": ("FLOAT", {"default": 0.0, "min": -1.0e38, "max": 1.0e38, "step": 0.01}),
},
}
RETURN_TYPES = ("FLOAT",)
FUNCTION = "stub_float"
CATEGORY = "Testing/Stub Nodes"
def stub_float(self, value):
return (value,)
TEST_STUB_NODE_CLASS_MAPPINGS = {
"StubImage": StubImage,
"StubConstantImage": StubConstantImage,
"StubMask": StubMask,
"StubInt": StubInt,
"StubFloat": StubFloat,
}
TEST_STUB_NODE_DISPLAY_NAME_MAPPINGS = {
"StubImage": "Stub Image",
"StubConstantImage": "Stub Constant Image",
"StubMask": "Stub Mask",
"StubInt": "Stub Int",
"StubFloat": "Stub Float",
}