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https://github.com/comfyanonymous/ComfyUI.git
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moved autoregressive nodes into an extra file
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Yousef Rafat
parent
907ed37fac
commit
90e7674f29
60
comfy_extras/nodes_autoregressive.py
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60
comfy_extras/nodes_autoregressive.py
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@ -0,0 +1,60 @@
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from comfy.autoregressive_sampling import auto_sample
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from comfy.comfy_types import IO
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class AutoRegressiveGeneration:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"model": ("MODEL", {"tooltip": "The model used for generation."}),
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"input_ids": ("TOKENS", ),
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"seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff, "control_after_generate": True, "tooltip": "The random seed used for controling the generation."}),
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"max_new_length": ("INT", {"default": 1024, "min": 1, "max": 10_000, "tooltip": "The max length for generation."}),
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"min_new_length": ("INT", {"default": 1, "min": 1, "max": 10_000, "tooltip": "The min length for generation."}),
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"top_k": ("INT", {"default": 50, "min": 1, "max": 30_000, "tooltip": "Takes the top k of the most probable tokens."}),
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"top_p": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "Percentage of tokens to leave after generation (top most probable tokens)."}),
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"temperature": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 50, "step": 0.01, "tooltip": "Temperature controls randomess by decreasing or increasing the probability of lesser likely tokens. Higher Temperature -> More Randomness"}),
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"do_sample": ("BOOLEAN", {"default": False, "tooltip": "Add randomness in decoding the tokens."}),
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}
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}
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RETURN_TYPES = ("TOKENS",)
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FUNCTION = "generate"
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CATEGORY = "sampling"
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# for cuda graphs
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_cached_autoregressive_sampler = None
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def generate(self, model, input_ids, seed, max_new_length, min_new_length, top_k, top_p, temperature, do_sample):
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return (auto_sample(self, model, input_ids, max_new_length, min_new_length, top_k, top_p, temperature, do_sample, seed = seed),)
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class DecodeTokens:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"clip": (IO.CLIP, {"tooltip": "The model used for generation."}),
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"tokens": ("TOKENS", ),}
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}
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FUNCTION = "decode"
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CATEGORY = "conditioning"
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RETURN_TYPES = ("TEXT", "AUDIO")
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def decode(self, clip, tokens):
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clip.load_model()
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if hasattr(clip.cond_stage_model, "decode_tokens"): # for special tokenizers
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return clip.cond_stage_model.decode_tokens(tokens)
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else:
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return (clip.tokenizer.decode(tokens, skip_special_tokens=True), None)
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NODE_CLASS_MAPPINGS = {
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"DecodeTokens": DecodeTokens,
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"AutoRegressiveGeneration": AutoRegressiveGeneration,
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"AutoRegressiveGeneration": "Autoregressive Generation",
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"DecodeTokens": "Decode Tokens",
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}
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54
nodes.py
54
nodes.py
@ -27,7 +27,6 @@ import comfy.sample
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import comfy.sd
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import comfy.utils
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import comfy.controlnet
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from comfy.autoregressive_sampling import auto_sample
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from comfy.comfy_types import IO, ComfyNodeABC, InputTypeDict, FileLocator
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from comfy_api.internal import register_versions, ComfyAPIWithVersion
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from comfy_api.version_list import supported_versions
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@ -1559,54 +1558,6 @@ class KSamplerAdvanced:
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disable_noise = True
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return common_ksampler(model, noise_seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise, disable_noise=disable_noise, start_step=start_at_step, last_step=end_at_step, force_full_denoise=force_full_denoise)
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class AutoRegressiveGeneration:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"model": ("MODEL", {"tooltip": "The model used for generation."}),
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"input_ids": ("TOKENS", ),
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"seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff, "control_after_generate": True, "tooltip": "The random seed used for controling the generation."}),
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"max_new_length": ("INT", {"default": 1024, "min": 1, "max": 10_000, "tooltip": "The max length for generation."}),
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"min_new_length": ("INT", {"default": 1, "min": 1, "max": 10_000, "tooltip": "The min length for generation."}),
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"top_k": ("INT", {"default": 50, "min": 1, "max": 30_000, "tooltip": "Takes the top k of the most probable tokens."}),
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"top_p": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "Percentage of tokens to leave after generation (top most probable tokens)."}),
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"temperature": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 50, "step": 0.01, "tooltip": "Temperature controls randomess by decreasing or increasing the probability of lesser likely tokens. Higher Temperature -> More Randomness"}),
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"do_sample": ("BOOLEAN", {"default": False, "tooltip": "Add randomness in decoding the tokens."}),
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}
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}
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RETURN_TYPES = ("TOKENS",)
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FUNCTION = "generate"
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CATEGORY = "sampling"
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# for cuda graphs
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_cached_autoregressive_sampler = None
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def generate(self, model, input_ids, seed, max_new_length, min_new_length, top_k, top_p, temperature, do_sample):
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return (auto_sample(self, model, input_ids, max_new_length, min_new_length, top_k, top_p, temperature, do_sample, seed = seed),)
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class DecodeTokens:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"clip": (IO.CLIP, {"tooltip": "The model used for generation."}),
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"tokens": ("TOKENS", ),}
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}
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FUNCTION = "decode"
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CATEGORY = "conditioning"
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RETURN_TYPES = ("TEXT", "AUDIO")
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def decode(self, clip, tokens):
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clip.load_model()
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if hasattr(clip.cond_stage_model, "decode_tokens"): # for special tokenizers
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return clip.cond_stage_model.decode_tokens(tokens)
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else:
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return (clip.tokenizer.decode(tokens, skip_special_tokens=True), None)
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class SaveImage:
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def __init__(self):
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self.output_dir = folder_paths.get_output_directory()
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@ -1994,11 +1945,9 @@ class ImagePadForOutpaint:
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NODE_CLASS_MAPPINGS = {
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"KSampler": KSampler,
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"AutoRegressiveGeneration": AutoRegressiveGeneration,
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"CheckpointLoaderSimple": CheckpointLoaderSimple,
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"CLIPTextEncode": CLIPTextEncode,
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"CLIPSetLastLayer": CLIPSetLastLayer,
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"DecodeTokens": DecodeTokens,
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"VAEDecode": VAEDecode,
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"VAEEncode": VAEEncode,
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"VAEEncodeForInpaint": VAEEncodeForInpaint,
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@ -2068,7 +2017,6 @@ NODE_DISPLAY_NAME_MAPPINGS = {
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# Sampling
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"KSampler": "KSampler",
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"KSamplerAdvanced": "KSampler (Advanced)",
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"AutoRegressiveGeneration": "Autoregressive Generation",
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# Loaders
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"CheckpointLoader": "Load Checkpoint With Config (DEPRECATED)",
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"CheckpointLoaderSimple": "Load Checkpoint",
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@ -2086,7 +2034,6 @@ NODE_DISPLAY_NAME_MAPPINGS = {
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"StyleModelApply": "Apply Style Model",
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"CLIPTextEncode": "CLIP Text Encode (Prompt)",
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"CLIPSetLastLayer": "CLIP Set Last Layer",
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"DecodeTokens": "Decode Tokens",
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"ConditioningCombine": "Conditioning (Combine)",
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"ConditioningAverage ": "Conditioning (Average)",
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"ConditioningConcat": "Conditioning (Concat)",
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@ -2384,6 +2331,7 @@ async def init_builtin_extra_nodes():
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"nodes_model_patch.py",
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"nodes_easycache.py",
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"nodes_audio_encoder.py",
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"nodes_autoregressive.py"
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]
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import_failed = []
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