forked from comfyanonymous/ComfyUI
-
Notifications
You must be signed in to change notification settings - Fork 0
/
execution.py
363 lines (314 loc) · 12.7 KB
/
execution.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
import os
import sys
import copy
import json
import threading
import heapq
import traceback
import gc
import torch
import nodes
def get_input_data(inputs, class_def, outputs={}, prompt={}, extra_data={}):
valid_inputs = class_def.INPUT_TYPES()
input_data_all = {}
for x in inputs:
input_data = inputs[x]
if isinstance(input_data, list):
input_unique_id = input_data[0]
output_index = input_data[1]
obj = outputs[input_unique_id][output_index]
input_data_all[x] = obj
else:
if ("required" in valid_inputs and x in valid_inputs["required"]) or ("optional" in valid_inputs and x in valid_inputs["optional"]):
input_data_all[x] = input_data
if "hidden" in valid_inputs:
h = valid_inputs["hidden"]
for x in h:
if h[x] == "PROMPT":
input_data_all[x] = prompt
if h[x] == "EXTRA_PNGINFO":
if "extra_pnginfo" in extra_data:
input_data_all[x] = extra_data['extra_pnginfo']
return input_data_all
def recursive_execute(server, prompt, outputs, current_item, extra_data={}):
unique_id = current_item
inputs = prompt[unique_id]['inputs']
class_type = prompt[unique_id]['class_type']
class_def = nodes.NODE_CLASS_MAPPINGS[class_type]
if unique_id in outputs:
return []
executed = []
for x in inputs:
input_data = inputs[x]
if isinstance(input_data, list):
input_unique_id = input_data[0]
output_index = input_data[1]
if input_unique_id not in outputs:
executed += recursive_execute(server, prompt, outputs, input_unique_id, extra_data)
input_data_all = get_input_data(inputs, class_def, outputs, prompt, extra_data)
if server.client_id is not None:
server.last_node_id = unique_id
server.send_sync("executing", { "node": unique_id }, server.client_id)
obj = class_def()
nodes.before_node_execution()
outputs[unique_id] = getattr(obj, obj.FUNCTION)(**input_data_all)
if "ui" in outputs[unique_id] and server.client_id is not None:
server.send_sync("executed", { "node": unique_id, "output": outputs[unique_id]["ui"] }, server.client_id)
return executed + [unique_id]
def recursive_will_execute(prompt, outputs, current_item):
unique_id = current_item
inputs = prompt[unique_id]['inputs']
will_execute = []
if unique_id in outputs:
return []
for x in inputs:
input_data = inputs[x]
if isinstance(input_data, list):
input_unique_id = input_data[0]
output_index = input_data[1]
if input_unique_id not in outputs:
will_execute += recursive_will_execute(prompt, outputs, input_unique_id)
return will_execute + [unique_id]
def recursive_output_delete_if_changed(prompt, old_prompt, outputs, current_item):
unique_id = current_item
inputs = prompt[unique_id]['inputs']
class_type = prompt[unique_id]['class_type']
class_def = nodes.NODE_CLASS_MAPPINGS[class_type]
is_changed_old = ''
is_changed = ''
if hasattr(class_def, 'IS_CHANGED'):
if unique_id in old_prompt and 'is_changed' in old_prompt[unique_id]:
is_changed_old = old_prompt[unique_id]['is_changed']
if 'is_changed' not in prompt[unique_id]:
input_data_all = get_input_data(inputs, class_def)
is_changed = class_def.IS_CHANGED(**input_data_all)
prompt[unique_id]['is_changed'] = is_changed
else:
is_changed = prompt[unique_id]['is_changed']
if unique_id not in outputs:
return True
to_delete = False
if is_changed != is_changed_old:
to_delete = True
elif unique_id not in old_prompt:
to_delete = True
elif inputs == old_prompt[unique_id]['inputs']:
for x in inputs:
input_data = inputs[x]
if isinstance(input_data, list):
input_unique_id = input_data[0]
output_index = input_data[1]
if input_unique_id in outputs:
to_delete = recursive_output_delete_if_changed(prompt, old_prompt, outputs, input_unique_id)
else:
to_delete = True
if to_delete:
break
else:
to_delete = True
if to_delete:
d = outputs.pop(unique_id)
del d
return to_delete
class PromptExecutor:
def __init__(self, server):
self.outputs = {}
self.old_prompt = {}
self.server = server
def execute(self, prompt, extra_data={}):
nodes.interrupt_processing(False)
if "client_id" in extra_data:
self.server.client_id = extra_data["client_id"]
else:
self.server.client_id = None
with torch.inference_mode():
for x in prompt:
recursive_output_delete_if_changed(prompt, self.old_prompt, self.outputs, x)
current_outputs = set(self.outputs.keys())
executed = []
try:
to_execute = []
for x in prompt:
class_ = nodes.NODE_CLASS_MAPPINGS[prompt[x]['class_type']]
if hasattr(class_, 'OUTPUT_NODE'):
to_execute += [(0, x)]
while len(to_execute) > 0:
#always execute the output that depends on the least amount of unexecuted nodes first
to_execute = sorted(list(map(lambda a: (len(recursive_will_execute(prompt, self.outputs, a[-1])), a[-1]), to_execute)))
x = to_execute.pop(0)[-1]
class_ = nodes.NODE_CLASS_MAPPINGS[prompt[x]['class_type']]
if hasattr(class_, 'OUTPUT_NODE'):
if class_.OUTPUT_NODE == True:
valid = False
try:
m = validate_inputs(prompt, x)
valid = m[0]
except:
valid = False
if valid:
executed += recursive_execute(self.server, prompt, self.outputs, x, extra_data)
except Exception as e:
print(traceback.format_exc())
to_delete = []
for o in self.outputs:
if o not in current_outputs:
to_delete += [o]
if o in self.old_prompt:
d = self.old_prompt.pop(o)
del d
for o in to_delete:
d = self.outputs.pop(o)
del d
else:
executed = set(executed)
for x in executed:
self.old_prompt[x] = copy.deepcopy(prompt[x])
finally:
self.server.last_node_id = None
if self.server.client_id is not None:
self.server.send_sync("executing", { "node": None }, self.server.client_id)
gc.collect()
if torch.cuda.is_available():
if torch.version.cuda: #This seems to make things worse on ROCm so I only do it for cuda
torch.cuda.empty_cache()
torch.cuda.ipc_collect()
def validate_inputs(prompt, item):
unique_id = item
inputs = prompt[unique_id]['inputs']
class_type = prompt[unique_id]['class_type']
obj_class = nodes.NODE_CLASS_MAPPINGS[class_type]
class_inputs = obj_class.INPUT_TYPES()
required_inputs = class_inputs['required']
for x in required_inputs:
if x not in inputs:
return (False, "Required input is missing. {}, {}".format(class_type, x))
val = inputs[x]
info = required_inputs[x]
type_input = info[0]
if isinstance(val, list):
if len(val) != 2:
return (False, "Bad Input. {}, {}".format(class_type, x))
o_id = val[0]
o_class_type = prompt[o_id]['class_type']
r = nodes.NODE_CLASS_MAPPINGS[o_class_type].RETURN_TYPES
if r[val[1]] != type_input:
return (False, "Return type mismatch. {}, {}, {} != {}".format(class_type, x, r[val[1]], type_input))
r = validate_inputs(prompt, o_id)
if r[0] == False:
return r
else:
if type_input == "INT":
val = int(val)
inputs[x] = val
if type_input == "FLOAT":
val = float(val)
inputs[x] = val
if type_input == "STRING":
val = str(val)
inputs[x] = val
if len(info) > 1:
if "min" in info[1] and val < info[1]["min"]:
return (False, "Value smaller than min. {}, {}".format(class_type, x))
if "max" in info[1] and val > info[1]["max"]:
return (False, "Value bigger than max. {}, {}".format(class_type, x))
if isinstance(type_input, list):
if val not in type_input:
return (False, "Value not in list. {}, {}: {} not in {}".format(class_type, x, val, type_input))
return (True, "")
def validate_prompt(prompt):
outputs = set()
for x in prompt:
class_ = nodes.NODE_CLASS_MAPPINGS[prompt[x]['class_type']]
if hasattr(class_, 'OUTPUT_NODE') and class_.OUTPUT_NODE == True:
outputs.add(x)
if len(outputs) == 0:
return (False, "Prompt has no outputs")
good_outputs = set()
errors = []
for o in outputs:
valid = False
reason = ""
try:
m = validate_inputs(prompt, o)
valid = m[0]
reason = m[1]
except:
valid = False
reason = "Parsing error"
if valid == True:
good_outputs.add(x)
else:
print("Failed to validate prompt for output {} {}".format(o, reason))
print("output will be ignored")
errors += [(o, reason)]
if len(good_outputs) == 0:
errors_list = "\n".join(map(lambda a: "{}".format(a[1]), errors))
return (False, "Prompt has no properly connected outputs\n {}".format(errors_list))
return (True, "")
class PromptQueue:
def __init__(self, server):
self.server = server
self.mutex = threading.RLock()
self.not_empty = threading.Condition(self.mutex)
self.task_counter = 0
self.queue = []
self.currently_running = {}
self.history = {}
server.prompt_queue = self
def put(self, item):
with self.mutex:
heapq.heappush(self.queue, item)
self.server.queue_updated()
self.not_empty.notify()
def get(self):
with self.not_empty:
while len(self.queue) == 0:
self.not_empty.wait()
item = heapq.heappop(self.queue)
i = self.task_counter
self.currently_running[i] = copy.deepcopy(item)
self.task_counter += 1
self.server.queue_updated()
return (item, i)
def task_done(self, item_id, outputs):
with self.mutex:
prompt = self.currently_running.pop(item_id)
self.history[prompt[1]] = { "prompt": prompt, "outputs": {} }
for o in outputs:
if "ui" in outputs[o]:
self.history[prompt[1]]["outputs"][o] = outputs[o]["ui"]
self.server.queue_updated()
def get_current_queue(self):
with self.mutex:
out = []
for x in self.currently_running.values():
out += [x]
return (out, copy.deepcopy(self.queue))
def get_tasks_remaining(self):
with self.mutex:
return len(self.queue) + len(self.currently_running)
def wipe_queue(self):
with self.mutex:
self.queue = []
self.server.queue_updated()
def delete_queue_item(self, function):
with self.mutex:
for x in range(len(self.queue)):
if function(self.queue[x]):
if len(self.queue) == 1:
self.wipe_queue()
else:
self.queue.pop(x)
heapq.heapify(self.queue)
self.server.queue_updated()
return True
return False
def get_history(self):
with self.mutex:
return copy.deepcopy(self.history)
def wipe_history(self):
with self.mutex:
self.history = {}
def delete_history_item(self, id_to_delete):
with self.mutex:
self.history.pop(id_to_delete, None)