374 lines
13 KiB
Python
374 lines
13 KiB
Python
import os
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import sys
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import copy
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import json
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import threading
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import queue
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import traceback
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if '--dont-upcast-attention' in sys.argv:
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print("disabling upcasting of attention")
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os.environ['ATTN_PRECISION'] = "fp16"
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import torch
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import nodes
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def get_input_data(inputs, class_def, outputs={}, prompt={}, extra_data={}):
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valid_inputs = class_def.INPUT_TYPES()
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input_data_all = {}
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for x in inputs:
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input_data = inputs[x]
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if isinstance(input_data, list):
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input_unique_id = input_data[0]
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output_index = input_data[1]
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obj = outputs[input_unique_id][output_index]
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input_data_all[x] = obj
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else:
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if ("required" in valid_inputs and x in valid_inputs["required"]) or ("optional" in valid_inputs and x in valid_inputs["optional"]):
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input_data_all[x] = input_data
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if "hidden" in valid_inputs:
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h = valid_inputs["hidden"]
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for x in h:
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if h[x] == "PROMPT":
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input_data_all[x] = prompt
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if h[x] == "EXTRA_PNGINFO":
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if "extra_pnginfo" in extra_data:
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input_data_all[x] = extra_data['extra_pnginfo']
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return input_data_all
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def recursive_execute(prompt, outputs, current_item, extra_data={}):
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unique_id = current_item
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inputs = prompt[unique_id]['inputs']
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class_type = prompt[unique_id]['class_type']
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class_def = nodes.NODE_CLASS_MAPPINGS[class_type]
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if unique_id in outputs:
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return []
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executed = []
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for x in inputs:
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input_data = inputs[x]
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if isinstance(input_data, list):
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input_unique_id = input_data[0]
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output_index = input_data[1]
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if input_unique_id not in outputs:
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executed += recursive_execute(prompt, outputs, input_unique_id, extra_data)
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input_data_all = get_input_data(inputs, class_def, outputs, prompt, extra_data)
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obj = class_def()
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outputs[unique_id] = getattr(obj, obj.FUNCTION)(**input_data_all)
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return executed + [unique_id]
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def recursive_will_execute(prompt, outputs, current_item):
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unique_id = current_item
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inputs = prompt[unique_id]['inputs']
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will_execute = []
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if unique_id in outputs:
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return []
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for x in inputs:
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input_data = inputs[x]
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if isinstance(input_data, list):
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input_unique_id = input_data[0]
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output_index = input_data[1]
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if input_unique_id not in outputs:
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will_execute += recursive_will_execute(prompt, outputs, input_unique_id)
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return will_execute + [unique_id]
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def recursive_output_delete_if_changed(prompt, old_prompt, outputs, current_item):
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unique_id = current_item
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inputs = prompt[unique_id]['inputs']
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class_type = prompt[unique_id]['class_type']
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class_def = nodes.NODE_CLASS_MAPPINGS[class_type]
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is_changed_old = ''
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is_changed = ''
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if hasattr(class_def, 'IS_CHANGED'):
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if 'is_changed' not in prompt[unique_id]:
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if unique_id in old_prompt and 'is_changed' in old_prompt[unique_id]:
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is_changed_old = old_prompt[unique_id]['is_changed']
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input_data_all = get_input_data(inputs, class_def)
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is_changed = class_def.IS_CHANGED(**input_data_all)
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prompt[unique_id]['is_changed'] = is_changed
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else:
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is_changed = prompt[unique_id]['is_changed']
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if unique_id not in outputs:
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return True
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to_delete = False
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if is_changed != is_changed_old:
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to_delete = True
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elif unique_id not in old_prompt:
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to_delete = True
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elif inputs == old_prompt[unique_id]['inputs']:
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for x in inputs:
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input_data = inputs[x]
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if isinstance(input_data, list):
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input_unique_id = input_data[0]
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output_index = input_data[1]
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if input_unique_id in outputs:
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to_delete = recursive_output_delete_if_changed(prompt, old_prompt, outputs, input_unique_id)
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else:
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to_delete = True
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if to_delete:
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break
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else:
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to_delete = True
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if to_delete:
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print("deleted", unique_id)
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d = outputs.pop(unique_id)
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del d
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return to_delete
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class PromptExecutor:
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def __init__(self):
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self.outputs = {}
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self.old_prompt = {}
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def execute(self, prompt, extra_data={}):
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with torch.no_grad():
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for x in prompt:
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recursive_output_delete_if_changed(prompt, self.old_prompt, self.outputs, x)
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current_outputs = set(self.outputs.keys())
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executed = []
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try:
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to_execute = []
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for x in prompt:
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class_ = nodes.NODE_CLASS_MAPPINGS[prompt[x]['class_type']]
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if hasattr(class_, 'OUTPUT_NODE'):
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to_execute += [(0, x)]
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while len(to_execute) > 0:
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to_execute = sorted(list(map(lambda a: (len(recursive_will_execute(prompt, self.outputs, a[-1])), a[-1]), to_execute)))
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x = to_execute.pop(0)[-1]
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class_ = nodes.NODE_CLASS_MAPPINGS[prompt[x]['class_type']]
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if hasattr(class_, 'OUTPUT_NODE'):
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if class_.OUTPUT_NODE == True:
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valid = False
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try:
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m = validate_inputs(prompt, x)
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valid = m[0]
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except:
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valid = False
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if valid:
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executed += recursive_execute(prompt, self.outputs, x, extra_data)
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except Exception as e:
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print(traceback.format_exc())
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to_delete = []
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for o in self.outputs:
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if o not in current_outputs:
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to_delete += [o]
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if o in self.old_prompt:
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d = self.old_prompt.pop(o)
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del d
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for o in to_delete:
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d = self.outputs.pop(o)
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del d
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else:
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executed = set(executed)
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for x in executed:
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self.old_prompt[x] = copy.deepcopy(prompt[x])
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def validate_inputs(prompt, item):
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unique_id = item
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inputs = prompt[unique_id]['inputs']
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class_type = prompt[unique_id]['class_type']
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obj_class = nodes.NODE_CLASS_MAPPINGS[class_type]
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class_inputs = obj_class.INPUT_TYPES()
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required_inputs = class_inputs['required']
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for x in required_inputs:
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if x not in inputs:
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return (False, "Required input is missing. {}, {}".format(class_type, x))
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val = inputs[x]
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info = required_inputs[x]
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type_input = info[0]
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if isinstance(val, list):
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if len(val) != 2:
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return (False, "Bad Input. {}, {}".format(class_type, x))
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o_id = val[0]
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o_class_type = prompt[o_id]['class_type']
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r = nodes.NODE_CLASS_MAPPINGS[o_class_type].RETURN_TYPES
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if r[val[1]] != type_input:
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return (False, "Return type mismatch. {}, {}".format(class_type, x))
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r = validate_inputs(prompt, o_id)
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if r[0] == False:
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return r
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else:
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if type_input == "INT":
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val = int(val)
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inputs[x] = val
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if type_input == "FLOAT":
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val = float(val)
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inputs[x] = val
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if type_input == "STRING":
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val = str(val)
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inputs[x] = val
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if len(info) > 1:
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if "min" in info[1] and val < info[1]["min"]:
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return (False, "Value smaller than min. {}, {}".format(class_type, x))
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if "max" in info[1] and val > info[1]["max"]:
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return (False, "Value bigger than max. {}, {}".format(class_type, x))
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if isinstance(type_input, list):
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if val not in type_input:
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return (False, "Value not in list. {}, {}: {} not in {}".format(class_type, x, val, type_input))
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return (True, "")
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def validate_prompt(prompt):
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outputs = set()
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for x in prompt:
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class_ = nodes.NODE_CLASS_MAPPINGS[prompt[x]['class_type']]
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if hasattr(class_, 'OUTPUT_NODE') and class_.OUTPUT_NODE == True:
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outputs.add(x)
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if len(outputs) == 0:
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return (False, "Prompt has no outputs")
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good_outputs = set()
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errors = []
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for o in outputs:
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valid = False
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reason = ""
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try:
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m = validate_inputs(prompt, o)
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valid = m[0]
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reason = m[1]
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except:
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valid = False
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reason = "Parsing error"
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if valid == True:
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good_outputs.add(x)
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else:
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print("Failed to validate prompt for output {} {}".format(o, reason))
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print("output will be ignored")
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errors += [(o, reason)]
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if len(good_outputs) == 0:
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errors_list = "\n".join(map(lambda a: "{}".format(a[1]), errors))
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return (False, "Prompt has no properly connected outputs\n {}".format(errors_list))
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return (True, "")
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def prompt_worker(q):
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e = PromptExecutor()
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while True:
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item = q.get()
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e.execute(item[-2], item[-1])
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q.task_done()
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from http.server import BaseHTTPRequestHandler, HTTPServer
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class PromptServer(BaseHTTPRequestHandler):
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def _set_headers(self, code=200, ct='text/html'):
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self.send_response(code)
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self.send_header('Content-type', ct)
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self.end_headers()
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def log_message(self, format, *args):
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pass
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def do_GET(self):
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if self.path == "/prompt":
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self._set_headers(ct='application/json')
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prompt_info = {}
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exec_info = {}
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exec_info['queue_remaining'] = self.server.prompt_queue.unfinished_tasks
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prompt_info['exec_info'] = exec_info
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self.wfile.write(json.dumps(prompt_info).encode('utf-8'))
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elif self.path == "/object_info":
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self._set_headers(ct='application/json')
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out = {}
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for x in nodes.NODE_CLASS_MAPPINGS:
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obj_class = nodes.NODE_CLASS_MAPPINGS[x]
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info = {}
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info['input'] = obj_class.INPUT_TYPES()
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info['output'] = obj_class.RETURN_TYPES
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info['name'] = x #TODO
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info['description'] = ''
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info['category'] = 'sd'
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if hasattr(obj_class, 'CATEGORY'):
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info['category'] = obj_class.CATEGORY
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out[x] = info
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self.wfile.write(json.dumps(out).encode('utf-8'))
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elif self.path[1:] in os.listdir(self.server.server_dir):
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if self.path[1:].endswith('.css'):
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self._set_headers(ct='text/css')
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elif self.path[1:].endswith('.js'):
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self._set_headers(ct='text/javascript')
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else:
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self._set_headers()
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with open(os.path.join(self.server.server_dir, self.path[1:]), "rb") as f:
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self.wfile.write(f.read())
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else:
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self._set_headers()
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with open(os.path.join(self.server.server_dir, "index.html"), "rb") as f:
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self.wfile.write(f.read())
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def do_HEAD(self):
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self._set_headers()
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def do_POST(self):
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resp_code = 200
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out_string = ""
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if self.path == "/prompt":
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print("got prompt")
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self.data_string = self.rfile.read(int(self.headers['Content-Length']))
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json_data = json.loads(self.data_string)
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if "number" in json_data:
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number = float(json_data['number'])
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else:
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number = self.server.number
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self.server.number += 1
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if "prompt" in json_data:
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prompt = json_data["prompt"]
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valid = validate_prompt(prompt)
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extra_data = {}
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if "extra_data" in json_data:
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extra_data = json_data["extra_data"]
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if valid[0]:
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self.server.prompt_queue.put((number, id(prompt), prompt, extra_data))
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else:
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resp_code = 400
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out_string = valid[1]
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print("invalid prompt:", valid[1])
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self._set_headers(code=resp_code)
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self.end_headers()
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self.wfile.write(out_string.encode('utf8'))
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return
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def run(prompt_queue, address='', port=8188):
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server_address = (address, port)
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httpd = HTTPServer(server_address, PromptServer)
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httpd.server_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), "webshit")
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httpd.prompt_queue = prompt_queue
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httpd.number = 0
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if server_address[0] == '':
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addr = '0.0.0.0'
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else:
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addr = server_address[0]
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print("Starting server\n")
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print("To see the GUI go to: http://{}:{}".format(addr, server_address[1]))
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httpd.serve_forever()
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if __name__ == "__main__":
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q = queue.PriorityQueue()
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threading.Thread(target=prompt_worker, daemon=True, args=(q,)).start()
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run(q, address='127.0.0.1', port=8188)
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