353 lines
12 KiB
Python
353 lines
12 KiB
Python
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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 heapq
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import traceback
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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(server, 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(server, 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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if server.client_id is not None:
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server.send_sync("executing", { "node": unique_id }, server.client_id)
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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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if "ui" in outputs[unique_id] and server.client_id is not None:
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server.send_sync("executed", { "node": unique_id, "output": outputs[unique_id]["ui"] }, server.client_id)
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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 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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if 'is_changed' not in prompt[unique_id]:
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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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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, server):
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self.outputs = {}
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self.old_prompt = {}
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self.server = server
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def execute(self, prompt, extra_data={}):
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if "client_id" in extra_data:
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self.server.client_id = extra_data["client_id"]
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else:
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self.server.client_id = None
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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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#always execute the output that depends on the least amount of unexecuted nodes first
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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(self.server, 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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finally:
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if self.server.client_id is not None:
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self.server.send_sync("executing", { "node": None }, self.server.client_id)
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torch.cuda.empty_cache()
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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, r[val[1]], type_input))
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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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class PromptQueue:
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def __init__(self, server):
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self.server = server
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self.mutex = threading.RLock()
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self.not_empty = threading.Condition(self.mutex)
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self.task_counter = 0
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self.queue = []
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self.currently_running = {}
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self.history = {}
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server.prompt_queue = self
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def put(self, item):
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with self.mutex:
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heapq.heappush(self.queue, item)
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self.server.queue_updated()
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self.not_empty.notify()
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def get(self):
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with self.not_empty:
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while len(self.queue) == 0:
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self.not_empty.wait()
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item = heapq.heappop(self.queue)
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i = self.task_counter
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self.currently_running[i] = copy.deepcopy(item)
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self.task_counter += 1
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self.server.queue_updated()
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return (item, i)
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def task_done(self, item_id, outputs):
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with self.mutex:
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prompt = self.currently_running.pop(item_id)
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self.history[prompt[1]] = { "prompt": prompt, "outputs": {} }
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for o in outputs:
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if "ui" in outputs[o]:
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self.history[prompt[1]]["outputs"][o] = outputs[o]["ui"]
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self.server.queue_updated()
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def get_current_queue(self):
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with self.mutex:
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out = []
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for x in self.currently_running.values():
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out += [x]
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return (out, copy.deepcopy(self.queue))
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def get_tasks_remaining(self):
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with self.mutex:
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return len(self.queue) + len(self.currently_running)
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def wipe_queue(self):
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with self.mutex:
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self.queue = []
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self.server.queue_updated()
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def delete_queue_item(self, function):
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with self.mutex:
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for x in range(len(self.queue)):
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if function(self.queue[x]):
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if len(self.queue) == 1:
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self.wipe_queue()
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else:
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self.queue.pop(x)
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heapq.heapify(self.queue)
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self.server.queue_updated()
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return True
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return False
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def get_history(self):
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with self.mutex:
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return copy.deepcopy(self.history)
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def wipe_history(self):
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with self.mutex:
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self.history = {}
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def delete_history_item(self, id_to_delete):
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with self.mutex:
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self.history.pop(id_to_delete, None)
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