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Adding some suggests from the author

pull/10/head
Hacker 17082006 2 years ago
parent
commit
493671574e
  1. 87
      custom_nodes/example.py
  2. 87
      custom_nodes/example_folder/__init__.py
  3. 4
      custom_nodes/example_folder/utils.py
  4. 0
      custom_nodes/put_custom_nodes_here
  5. 13
      nodes.py

87
custom_nodes/example.py

@ -0,0 +1,87 @@
class Example:
"""
A example node
Class methods
-------------
INPUT_TYPES (dict):
Tell the main program input parameters of nodes.
Attributes
----------
RETURN_TYPES (`tuple`):
The type of each element in the output tulple.
FUNCTION (`str`):
The name of the entry-point method which will return a tuple. For example, if `FUNCTION = "execute"` then it will run Example().execute()
OUTPUT_NODE ([`bool`]):
WIP
CATEGORY (`str`):
WIP
execute(s) -> tuple || None:
The entry point method. The name of this method must be the same as the value of property `FUNCTION`.
For example, if `FUNCTION = "execute"` then this method's name must be `execute`, if `FUNCTION = "foo"` then it must be `foo`.
"""
def __init__(self):
pass
@classmethod
def INPUT_TYPES(s):
"""
Return a dictionary which contains config for all input fields.
The type can be a string indicate a type or a list indicate selection.
Prebuilt types (string): "MODEL", "VAE", "CLIP", "CONDITIONING", "LATENT", "IMAGE", "INT", "STRING", "FLOAT".
Input in type "INT", "STRING" or "FLOAT" will be converted automatically from a string to the corresponse Python type before passing and have special config
Argument: s (`None`): Useless ig
Returns: `dict`:
- Key input_fields_group (`string`): Can be either required, hidden or optional. A node class must have property `required`
- Value input_fields (`dict`): Contains input fields config:
* Key field_name (`string`): Name of a entry-point method's argument
* Value field_config (`tuple`):
+ First value is a string indicate the type of field or a list for selection.
+ Secound value is a config for type "INT", "STRING" or "FLOAT".
"""
return {
"required": {
"string_field": ("STRING", {
"multiline": True, #Allow the input to be multilined
"default": "Hello World!"
}),
"int_field": ("INT", {
"default": 0,
"min": 0, #Minimum value
"max": 4096, #Maximum value
"step": 64 #Slider's step
}),
#Like INT
"float_field": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}),
"print_to_screen": (["Enable", "Disable"], {"default": "Enable"})
},
#"hidden": {
# "prompt": "PROMPT",
# "extra_pnginfo": "EXTRA_PNGINFO"
#},
}
RETURN_TYPES = ("STRING", "INT", "FLOAT", "STRING")
FUNCTION = "test"
#OUTPUT_NODE = True
CATEGORY = "Example"
def test(self, string_field, int_field, float_field, print_to_screen):
if print_to_screen == "Enable":
print(f"""Your input contains:
string_field aka input text: {string_field}
int_field: {int_field}
float_field: {float_field}
""")
return (string_field, int_field, float_field, print_to_screen)
NODE_CLASS_MAPPINGS = {
"Example": Example
}
"""
NODE_CLASS_MAPPINGS (dict): A dictionary contains all nodes you want to export
"""

87
custom_nodes/example_folder/__init__.py

@ -0,0 +1,87 @@
from utils import waste_cpu_resource
class ExampleFolder:
"""
A example node
Class methods
-------------
INPUT_TYPES (dict):
Tell the main program input parameters of nodes.
Attributes
----------
RETURN_TYPES (`tuple`):
The type of each element in the output tulple.
FUNCTION (`str`):
The name of the entry-point method which will return a tuple. For example, if `FUNCTION = "execute"` then it will run Example().execute()
OUTPUT_NODE ([`bool`]):
WIP
CATEGORY (`str`):
WIP
execute(s) -> tuple || None:
The entry point method. The name of this method must be the same as the value of property `FUNCTION`.
For example, if `FUNCTION = "execute"` then this method's name must be `execute`, if `FUNCTION = "foo"` then it must be `foo`.
"""
def __init__(self):
pass
@classmethod
def INPUT_TYPES(s):
"""
Return a dictionary which contains config for all input fields.
The type can be a string indicate a type or a list indicate selection.
Prebuilt types (string): "MODEL", "VAE", "CLIP", "CONDITIONING", "LATENT", "IMAGE", "INT", "STRING", "FLOAT".
Input in type "INT", "STRING" or "FLOAT" will be converted automatically from a string to the corresponse Python type before passing and have special config
Argument: s (`None`): Useless ig
Returns: `dict`:
- Key input_fields_group (`string`): Can be either required, hidden or optional. A node class must have property `required`
- Value input_fields (`dict`): Contains input fields config:
* Key field_name (`string`): Name of a entry-point method's argument
* Value field_config (`tuple`):
+ First value is a string indicate the type of field or a list for selection.
+ Secound value is a config for type "INT", "STRING" or "FLOAT".
"""
return {
"required": {
"string_field": ("STRING", {
"multiline": True, #Allow the input to be multilined
"default": "Hello World!"
}),
"int_field": ("INT", {
"default": 0,
"min": 0, #Minimum value
"max": 4096, #Maximum value
"step": 64 #Slider's step
}),
#Like INT
"print_to_screen": (["Enable", "Disable"], {"default": "Enable"})
},
#"hidden": {
# "prompt": "PROMPT",
# "extra_pnginfo": "EXTRA_PNGINFO"
#},
}
RETURN_TYPES = ("STRING", "INT", "FLOAT", "STRING")
FUNCTION = "test"
#OUTPUT_NODE = True
CATEGORY = "Example"
def test(self, string_field, int_field, print_to_screen):
rand_float = waste_cpu_resource()
if print_to_screen == "Enable":
print(f"""Your input contains:
string_field aka input text: {string_field}
int_field: {int_field}
A random float number: {rand_float}
""")
return (string_field, int_field, rand_float, print_to_screen)
NODE_CLASS_MAPPINGS = {
"ExampleFolder": ExampleFolder
}
"""
NODE_CLASS_MAPPINGS (dict): A dictionary contains all nodes you want to export
"""

4
custom_nodes/example_folder/utils.py

@ -0,0 +1,4 @@
import torch
def waste_cpu_resource():
x = torch.rand(1, 1e6, dtype=torch.float64).cpu()
return x.numpy()[0, 1]

0
custom_nodes/put_custom_nodes_here

13
nodes.py

@ -598,12 +598,19 @@ NODE_CLASS_MAPPINGS = {
"CLIPLoader": CLIPLoader,
}
CUSTOM_NODE_PATH = os.path.join(os.path.dirname(os.path.realpath(__file__)), "custom_nodes")
def load_custom_nodes():
possible_modules = os.listdir("custom_nodes")
possible_modules.remove("put_custom_nodes_here")
possible_modules = os.listdir(CUSTOM_NODE_PATH)
try:
possible_modules.remove("example.py")
possible_modules.remove("example_folder")
except ValueError: pass
for possible_module in possible_modules:
module_path = os.path.join(CUSTOM_NODE_PATH, possible_module)
if os.path.isfile(module_path) and os.path.splitext(module_path)[1] != ".py": continue
try:
custom_nodes = import_module(possible_module, "custom_nodes")
custom_nodes = import_module(possible_module, CUSTOM_NODE_PATH)
if getattr(custom_nodes, "NODE_CLASS_MAPPINGS") is not None:
NODE_CLASS_MAPPINGS.update(custom_nodes.NODE_CLASS_MAPPINGS)
else:

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