Tasha Upchurch
d2d16cadfe
This commit introduces significant enhancements and new features across multiple files in the project. Major changes include: 1. `pytorch_nodes.py`: Expanded PyTorch node functionalities with additional imports, device compatibility checks, optimizer state updates, and training enhancements. Introduced new methods like `optimizer_to` for transferring optimizer state to a specified device, `reset_optimizer_weights` to clear optimizer states, and `make_image_tensor` for converting outputs to image tensors. Also, improved the training process with device compatibility checks, optimizer updates, and the ability to save and load models during training for efficiency. 2. `server_endpoints.py`: Modified server endpoints for improved git integration and user management. Adjustments include dynamic handling of different git repositories, refined branch and user management in GitIO class, and the integration of user-specific git settings in user management functions. 3. `config.yaml`: Added new configurations for temporary directory and git repositories, providing more flexibility and control over file management and version control integration. 4. `torchvision_nodes.py`: Introduced a new file to integrate torchvision functionalities. It includes classes for transform composition, application of torchvision transforms, and handling of torchvision-specific data structures. 5. `hf_diffusers_nodes.py`: Integrated Hugging Face's diffusers library with new nodes for loading and utilizing DDPMPipelines, handling tensor to image conversions, and managing datasets from the Hugging Face ecosystem. 6. `image.py`, `video.py`, `functional.py`: Refactored and enhanced existing functionalities. Included minor tweaks and bug fixes to improve the overall efficiency and robustness of image and video processing capabilities. 7. `requirements.txt`: Updated dependencies, replacing `fastnoisesimd` with `diffusers` to align with the newly integrated Hugging Face diffusers functionalities. 8. `config.py`: Improved the configuration file loading mechanism with dynamic path handling and the ability to replace placeholders with actual paths, enhancing the flexibility of configuration management. This comprehensive update significantly enhances the project's capabilities in machine learning, especially in PyTorch and torchvision, and improves server endpoint functionalities for better user and version control management.
652 lines
18 KiB
Python
652 lines
18 KiB
Python
import hashlib
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NODE_CLASS_MAPPINGS = {}
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NODE_DISPLAY_NAME_MAPPINGS = {}
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_list = {"list": ("LIST",)}
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_func = {"func": ("FUNC", {"default": None})}
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_func_extra = {"func_extra": ("FUNC",)}
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_text = {"code": ("STRING", {"multiline": True, "default": "y mapped to output"})}
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_image = {"image": ("IMAGE",)}
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_string = {"string": ("STRING", {"default": None})}
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_any = {"any": ("*", {"default": None})}
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optional = lambda x: {"optional": {k: v for k, v in x.items()}}
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required = lambda x: {"required": {k: v for k, v in x.items()}}
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both = lambda a, b: {**a, **b}
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many = lambda *dicts: {k: v for d in dicts for k, v in d.items()} # non tested
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def ETK_functional_base(cls):
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cls.FUNCTION = "func"
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cls.CATEGORY = "ETK/functional"
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NODE_CLASS_MAPPINGS[cls.__name__] = cls
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return cls
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def new_exec(c, g, l):
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global old_exec
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import os
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# if GDE_SECURE_MODE is set to NO_EXEC then we will not execute any code
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# this is a security feature to prevent malicious code from being executed
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# this is set in the GDE settings
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GDE_SECURE_MODE = os.environ.get("GDE_SECURE_MODE", None)
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if GDE_SECURE_MODE == "NO_EXEC":
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raise Exception("GDE_SECURE_MODE is set to NO_EXEC, not executing code")
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old_exec(c, g, l)
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return locals
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old_exec = exec
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exec = new_exec
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@ETK_functional_base
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class FuncBase:
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"""
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Base class for func nodes
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Allows for a function to be passed in as a callable
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and
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for a string to be passed in as code to be executed
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also
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returns the function as a callable
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"""
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def __init__(self):
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from custom_nodes.EternalKernelLiteGraphNodes.image import common_ksampler, TinyTxtToImg
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self.locals = locals()
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self.globals = globals()
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@classmethod
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def INPUT_TYPES(cls):
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req = required(_text)
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opt = optional(
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both(
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both(
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_func,
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_func_extra
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),
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_list
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)
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)
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use = both(req, opt)
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return use
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RETURN_TYPES = ("FUNC",)
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FUNCTION = "func"
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CATEGORY = "ETK/func"
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def func(self, **kwargs):
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import inspect
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self.globals = globals()
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self.locals = locals()
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self.locals["x1"] = kwargs.get("func", None)
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self.locals["x2"] = kwargs.get("func_extra", None)
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self.locals["x_list"] = kwargs.get("list", None)
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self.IN_FUNC = kwargs.get("func", None)
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self.EXTRA_IN_FUNC = kwargs.get("func_extra", None)
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self.exec_code = kwargs.get("code", None)
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self.ARGS = kwargs
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self.CODE = inspect.getsource(self.func)
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exec(self.exec_code, self.globals, self.locals)
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return (self.func,)
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@ETK_functional_base
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class FuncRender:
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"""
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as input takes a function and a string of code
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optionally takes a list of arguments
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returns rendered results of types
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float, string, int, list
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"""
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def __init__(self):
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from custom_nodes.EternalKernelLiteGraphNodes.image import common_ksampler, TinyTxtToImg
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self.locals = locals()
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self.globals = globals()
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@classmethod
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def INPUT_TYPES(cls):
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use = both(
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required(
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_text),
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optional(both(_list, _func)
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)
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)
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return use
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RETURN_TYPES = ("FLOAT", "STRING", "INT", "LIST")
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FUNCTION = "func"
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CATEGORY = "ETK/func"
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def func(self, **kwargs):
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y_float = None
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y_string = None
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y_int = None
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func = kwargs.get("func", None)
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code = kwargs.get("code", None)
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globals = self.globals
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locals = self.locals
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locals["y_float"] = y_float
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locals["y_string"] = y_string
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locals["y_int"] = y_int
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locals["y_list"] = None
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locals["x"] = func
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locals["x_list"] = kwargs.get("list", None)
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# code should do something like:
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# func like : lambda x:["what"]*x
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# code like : 'f=[x for x in x(2)]'
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exec(code, globals, locals)
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self.globals = globals
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self.locals = locals
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return (locals["y_float"], locals["y_string"], locals["y_int"], locals["y_list"],)
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@ETK_functional_base
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class FuncRenderImage:
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def __init__(self):
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from custom_nodes.EternalKernelLiteGraphNodes.image import common_ksampler, TinyTxtToImg
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self.locals = locals()
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self.globals = globals()
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@classmethod
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def INPUT_TYPES(cls):
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use = both(
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required(
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both(_func, _text)),
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optional(_list)
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)
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return use
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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "func"
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CATEGORY = "ETK/func"
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OUTPUT_NODE = True
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def func(self, func, code, **kwargs):
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globals = self.globals
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locals = self.locals
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locals["x"] = func
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locals["x_list"] = kwargs.get("list", None)
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# code should do something like:
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# func like : lambda x:["what"]*x
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# code like : 'f=[x for x in x(2)]'
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exec(code, globals, locals)
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self.globals = globals
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self.locals = locals
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return (locals["y"],)
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@ETK_functional_base
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class ExecWidget:
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import torch
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"""runs eval on the given text"""
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@classmethod
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def INPUT_TYPES(cls):
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return {"optional":
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{
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"code_str_in": ("STRING", {"multiline": True,
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"default": ""
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}),
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"image1_in": ("IMAGE",),
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"float1_in": ("FLOAT", {"multiline": False}),
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"string1_in": ("STRING", {"multiline": False}),
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"int1_in": ("INT", {"multiline": False}),
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},
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"required": {
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"text_to_eval": ("STRING",
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{"multiline": True,
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"default": "int_out=int_out\n"
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"float_out=float_out\n"
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"string_out=string_out\n"
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"image_out=image_out\n"
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}),
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}
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}
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CATEGORY = "text"
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RETURN_TYPES = ("STRING", "IMAGE", "FLOAT", "INT", "TUPLE", "CODE")
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FUNCTION = "pre_exec_handler"
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INTERNAL_STATE_DISPLAY_CODE = True
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OUTPUT_NODE = True
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def pre_exec_handler(self, **kwargs):
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image1_in = kwargs.get("image1_in", None)
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float1_in = kwargs.get("float1_in", 0.0)
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string1_in = kwargs.get("string1_in", "")
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int1_in = kwargs.get("int1_in", 0)
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tuple1_in = kwargs.get("tuple1_in", None)
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name = kwargs.get("name", "exec_func")
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text_to_eval = kwargs.get("text_to_eval", "")
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code_str_in = kwargs.get("code_str_in", "")
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if code_str_in != "":
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text_to_eval = code_str_in
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else:
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code_str_in = None
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ret = self.exec_handler(text_to_eval, image1_in, float1_in, string1_in, int1_in, tuple1_in, name)
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ret_formatted = {"ui": {"text": [ret[-1]]}, "result": ret}
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return ret_formatted
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def exec_handler(self, text_to_eval, image_obj: torch.Tensor = None, float_obj: float = 0.0, string_obj: str = "",
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int_obj: int = 0, tuple_obj: tuple = None, name: str = "exec_func"):
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"""
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>>> ExecWidget().exec_handler("2 + 3")
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'5'
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"""
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new_locals = {"float_out": float_obj,
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"image_out": image_obj,
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"string_out": string_obj,
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"int_out": int_obj,
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"tuple_out": tuple_obj,
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}
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try:
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if isinstance(text_to_eval, list):
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text_to_eval = text_to_eval[0]
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# evaluate for code tag
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if "<code>" in text_to_eval and "</code>" in text_to_eval:
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start = text_to_eval.find("<code>")
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end = text_to_eval.find("</code>")
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text_to_eval = text_to_eval[start + 6:end]
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# also evaluate for ```python tag
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if "```python" in text_to_eval and "```" in text_to_eval:
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start = text_to_eval.find("```python")
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end = text_to_eval.find("```", start + 8)
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text_to_eval = text_to_eval[start + 9:end]
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if "```" in text_to_eval:
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start = text_to_eval.find("```")
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end = text_to_eval.find("```", start + 2)
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text_to_eval = text_to_eval[start + 3:end]
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exec(text_to_eval, globals(), new_locals)
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source_code = text_to_eval
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except Exception as e:
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string_obj = str(e)
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source_code = text_to_eval
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string_obj = new_locals.get("string_out", string_obj)
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image_obj = new_locals.get("image_out", image_obj)
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float_obj = new_locals.get("float_out", float_obj)
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int_obj = new_locals.get("int_out", int_obj)
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tuple_obj = new_locals.get("tuple_out", tuple_obj)
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return (string_obj, image_obj, float_obj, int_obj, tuple_obj, text_to_eval)
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@classmethod
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def IS_CHANGED_NOPE(s, text_to_eval, image1_in: torch.Tensor = None, float1_in: float = 0.0, string1_in: str = "",
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int1_in: int = 0, name: str = "exec_func"):
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m = hashlib.sha256()
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m.update(name.encode("utf-8"))
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return m.digest().hex()
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@ETK_functional_base
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class FuncListToList:
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"""runs eval on the given text, with a list as input and output"""
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(cls):
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req = required(
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both(_list,
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_text)
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)
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opt = optional(_func)
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use = both(req, opt)
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return use
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CATEGORY = "ETK/func"
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RETURN_TYPES = ("LIST",)
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FUNCTION = "func"
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def func(self, **kwargs):
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func = kwargs.get("func", None)
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code = kwargs.get("code", None)
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my_globals = globals()
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my_locals = locals()
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my_locals["x"] = func
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my_locals["x_list"] = kwargs.get("list", None)
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exec(code, my_globals, my_locals)
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return (my_locals["y_list"],)
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@ETK_functional_base
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class FuncStrToStr:
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"""runs eval on the given text, with a string as input and outputs a string"""
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(cls):
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req = required(both(_string, _text))
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return req
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CATEGORY = "ETK/func"
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RETURN_TYPES = ("STRING",)
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FUNCTION = "func"
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def func(self, **kwargs):
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text = kwargs.get("string", None)
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x = text
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code = kwargs.get("code", None)
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my_globals = globals()
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my_locals = locals()
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exec(code, my_globals, my_locals)
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return (my_locals["y"],)
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@ETK_functional_base
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class FuncStrToList:
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(cls):
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req = required(both(_string, _text))
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return req
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CATEGORY = "ETK/func"
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RETURN_TYPES = ("LIST",)
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FUNCTION = "func"
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def func(self, **kwargs):
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text = kwargs.get("string", None)
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code = kwargs.get("code", None)
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x = text
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my_globals = globals()
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my_locals = locals()
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exec(code, my_globals, my_locals)
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return (my_locals["y_list"],)
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@ETK_functional_base
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class FuncListToStr:
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(cls):
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req = required(both(_list, _text))
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return req
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CATEGORY = "ETK/func"
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RETURN_TYPES = ("STRING",)
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FUNCTION = "func"
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def func(self, **kwargs):
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lst = kwargs.get("list", None)
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code = kwargs.get("code", None)
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x = lst
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x_list = lst
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my_globals = globals()
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my_locals = locals()
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exec(code, my_globals, my_locals)
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return (my_locals["y"],)
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@ETK_functional_base
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class GetFirstCodeBlock():
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""" returns the first code block in the text which is surrounded with ``` or
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```python or
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<code> tags. If no code block is found, returns an empty string"""
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(cls):
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req = required(_text)
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return req
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CATEGORY = "ETK/func"
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RETURN_TYPES = ("STRING",)
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FUNCTION = "func"
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def func(self, **kwargs):
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text = kwargs.get("code", None)
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# find the code block
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if "```python" in text and "```" in text:
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start = text.find("```python")
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end = text.find("```", start + 8)
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text = text[start + 9:end]
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elif "```" in text:
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start = text.find("```")
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end = text.find("```", start + 2)
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text = text[start + 3:end]
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elif "<code>" in text and "</code>" in text:
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start = text.find("<code>")
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end = text.find("</code>")
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text = text[start + 6:end]
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else:
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text = ""
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return (text,)
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@ETK_functional_base
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class FuncAnysToImage:
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"""runs eval on the given text, with 5 anys as input and outputs an image"""
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(cls):
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req = optional(
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both(
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both({"any1": ("*", {"default": None})}, {"any2": ("*", {"default": None})}),
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both({"any3": ("*", {"default": None})}, {"any4": ("*", {"default": None})})
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),
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)
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req["required"] = {}
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req["required"].update(_text)
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return req
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CATEGORY = "ETK/func"
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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "func"
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def func(self, **kwargs):
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code = kwargs.get("code", None)
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any1 = kwargs.get("any1", None)
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any2 = kwargs.get("any2", None)
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any3 = kwargs.get("any3", None)
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any4 = kwargs.get("any4", None)
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my_globals = globals()
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my_locals = locals()
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my_locals["any1"] = any1
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my_locals["any2"] = any2
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my_locals["any3"] = any3
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my_locals["any4"] = any4
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exec(code, my_globals, my_locals)
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if "y" in my_locals.keys():
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return (my_locals["y"],)
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elif "y" in my_globals.keys():
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return (my_globals["y"],)
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else:
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return (None,)
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@ETK_functional_base
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class FuncAnysToLatent:
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"""runs eval on the given text, with 5 anys as input and outputs a latent"""
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def __init__(self):
|
|
pass
|
|
|
|
@classmethod
|
|
def INPUT_TYPES(cls):
|
|
req = optional(
|
|
both(
|
|
both({"any1": ("*", {"default": None})}, {"any2": ("*", {"default": None})}),
|
|
both({"any3": ("*", {"default": None})}, {"any4": ("*", {"default": None})})
|
|
),
|
|
)
|
|
req["required"] = {}
|
|
req["required"].update(_text)
|
|
|
|
return req
|
|
|
|
CATEGORY = "ETK/func"
|
|
RETURN_TYPES = ("LATENT",)
|
|
FUNCTION = "func"
|
|
|
|
def func(self, **kwargs):
|
|
code = kwargs.get("code", None)
|
|
any1 = kwargs.get("any1", None)
|
|
any2 = kwargs.get("any2", None)
|
|
any3 = kwargs.get("any3", None)
|
|
any4 = kwargs.get("any4", None)
|
|
|
|
my_globals = globals()
|
|
my_locals = locals()
|
|
|
|
my_locals["any1"] = any1
|
|
my_locals["any2"] = any2
|
|
my_locals["any3"] = any3
|
|
my_locals["any4"] = any4
|
|
|
|
exec(code, my_globals, my_locals)
|
|
if "y" in my_locals.keys():
|
|
return (my_locals["y"],)
|
|
elif "y" in my_globals.keys():
|
|
return (my_globals["y"],)
|
|
else:
|
|
return (None,)
|
|
|
|
@ETK_functional_base
|
|
class FuncAnysToString:
|
|
"""runs eval on the given text, with 5 anys as input and outputs a string"""
|
|
|
|
def __init__(self):
|
|
pass
|
|
|
|
@classmethod
|
|
def INPUT_TYPES(cls):
|
|
req = optional(
|
|
both(
|
|
both({"any1": ("*", {"default": None})}, {"any2": ("*", {"default": None})}),
|
|
both({"any3": ("*", {"default": None})}, {"any4": ("*", {"default": None})})
|
|
),
|
|
)
|
|
req["required"] = {}
|
|
req["required"].update(_text)
|
|
|
|
return req
|
|
|
|
CATEGORY = "ETK/func"
|
|
RETURN_TYPES = ("STRING",)
|
|
FUNCTION = "func"
|
|
|
|
def func(self, **kwargs):
|
|
code = kwargs.get("code", None)
|
|
any1 = kwargs.get("any1", None)
|
|
any2 = kwargs.get("any2", None)
|
|
any3 = kwargs.get("any3", None)
|
|
any4 = kwargs.get("any4", None)
|
|
|
|
my_globals = globals()
|
|
my_locals = locals()
|
|
|
|
my_locals["any1"] = any1
|
|
my_locals["any2"] = any2
|
|
my_locals["any3"] = any3
|
|
my_locals["any4"] = any4
|
|
|
|
exec(code, my_globals, my_locals)
|
|
if "y" in my_locals.keys():
|
|
return (my_locals["y"],)
|
|
elif "y" in my_globals.keys():
|
|
return (my_globals["y"],)
|
|
else:
|
|
return (None,)
|
|
|
|
@ETK_functional_base
|
|
class FuncAnysToList:
|
|
"""runs eval on the given text, with 5 anys as input and outputs a list"""
|
|
|
|
def __init__(self):
|
|
pass
|
|
|
|
@classmethod
|
|
def INPUT_TYPES(cls):
|
|
req = optional(
|
|
both(
|
|
both({"any1": ("*", {"default": None})}, {"any2": ("*", {"default": None})}),
|
|
both({"any3": ("*", {"default": None})}, {"any4": ("*", {"default": None})})
|
|
),
|
|
)
|
|
req["required"] = {}
|
|
req["required"].update(_text)
|
|
|
|
return req
|
|
|
|
CATEGORY = "ETK/func"
|
|
RETURN_TYPES = ("LIST",)
|
|
FUNCTION = "func"
|
|
|
|
def func(self, **kwargs):
|
|
code = kwargs.get("code", None)
|
|
any1 = kwargs.get("any1", None)
|
|
any2 = kwargs.get("any2", None)
|
|
any3 = kwargs.get("any3", None)
|
|
any4 = kwargs.get("any4", None)
|
|
|
|
my_globals = globals()
|
|
my_locals = locals()
|
|
|
|
my_locals["any1"] = any1
|
|
my_locals["any2"] = any2
|
|
my_locals["any3"] = any3
|
|
my_locals["any4"] = any4
|
|
|
|
exec(code, my_globals, my_locals)
|
|
if "y" in my_locals.keys():
|
|
return (my_locals["y"],)
|
|
elif "y" in my_globals.keys():
|
|
return (my_globals["y"],)
|
|
else:
|
|
return (None,)
|
|
if __name__ == "__main__":
|
|
test = {}
|
|
|
|
pass
|