
from abc import ABC, abstractmethod
from typing import List, Optional





class     lowerCamelCase      (       __lowerCamelCase					):







	def __init__(     self      :Optional[int]			)		->      Optional[int]:







				"""simple docstring"""






				self.test()







	def  snake_case__     (     self      :Tuple			)		->      Optional[Any]:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE     						= 0
				SCREAMING_SNAKE_CASE     						= False
				while not completed:
							if counter == 1:
										self.reset()
							SCREAMING_SNAKE_CASE     						= self.advance()
							if not self.does_advance(lowercase			):
										raise Exception(
										    '''Custom Constraint is not defined correctly. self.does_advance(self.advance()) must be true.'''			)

							SCREAMING_SNAKE_CASE						,							SCREAMING_SNAKE_CASE						,							SCREAMING_SNAKE_CASE     						= self.update(lowercase			)
							counter += 1

							if counter > 1_0_0_0_0:
										raise Exception('''update() does not fulfill the constraint.'''			)

				if self.remaining() != 0:
							raise Exception('''Custom Constraint is not defined correctly.'''			)







	@abstractmethod
	def  snake_case__     (     self      :str			)		->      Any:







				"""simple docstring"""






				raise NotImplementedError(
				    f"""{self.__class__} is an abstract class. Only classes inheriting this class can be called."""			)







	@abstractmethod
	def  snake_case__     (     self      :str   ,     lowercase      :int			)		->      Tuple:







				"""simple docstring"""






				raise NotImplementedError(
				    f"""{self.__class__} is an abstract class. Only classes inheriting this class can be called."""			)







	@abstractmethod
	def  snake_case__     (     self      :List[Any]   ,     lowercase      :int			)		->      Tuple:







				"""simple docstring"""






				raise NotImplementedError(
				    f"""{self.__class__} is an abstract class. Only classes inheriting this class can be called."""			)







	@abstractmethod
	def  snake_case__     (     self      :Any			)		->      List[str]:







				"""simple docstring"""






				raise NotImplementedError(
				    f"""{self.__class__} is an abstract class. Only classes inheriting this class can be called."""			)







	@abstractmethod
	def  snake_case__     (     self      :Dict			)		->      Optional[int]:







				"""simple docstring"""






				raise NotImplementedError(
				    f"""{self.__class__} is an abstract class. Only classes inheriting this class can be called."""			)







	@abstractmethod
	def  snake_case__     (     self      :Dict   ,     lowercase      :Union[str, Any]=False			)		->      Any:







				"""simple docstring"""






				raise NotImplementedError(
				    f"""{self.__class__} is an abstract class. Only classes inheriting this class can be called."""			)





class     lowerCamelCase      (       __lowerCamelCase					):







	def __init__(     self      :Any   ,     lowercase      :List[int]			)		->      int:







				"""simple docstring"""






				super(lowercase   ,     self			).__init__()

				if not isinstance(lowercase   ,     lowercase			) or len(lowercase			) == 0:
							raise ValueError(f"""`token_ids` has to be a non-empty list, but is {token_ids}."""			)
				if any((not isinstance(lowercase   ,     lowercase			) or token_id < 0) for token_id in token_ids			):
							raise ValueError(f"""Each list in `token_ids` has to be a list of positive integers, but is {token_ids}."""			)

				SCREAMING_SNAKE_CASE     						= token_ids

				SCREAMING_SNAKE_CASE     						= len(self.token_ids			)
				SCREAMING_SNAKE_CASE     						= -1  # the index of the currently fulfilled step
				SCREAMING_SNAKE_CASE     						= False







	def  snake_case__     (     self      :Union[str, Any]			)		->      Union[str, Any]:







				"""simple docstring"""






				if self.completed:
							return None
				return self.token_ids[self.fulfilled_idx + 1]







	def  snake_case__     (     self      :Union[str, Any]   ,     lowercase      :int			)		->      Union[str, Any]:







				"""simple docstring"""






				if not isinstance(lowercase   ,     lowercase			):
							raise ValueError(f"""`token_id` has to be an `int`, but is {token_id} of type {type(lowercase			)}"""			)

				if self.completed:
							return False

				return token_id == self.token_ids[self.fulfilled_idx + 1]







	def  snake_case__     (     self      :int   ,     lowercase      :int			)		->      Optional[Any]:







				"""simple docstring"""






				if not isinstance(lowercase   ,     lowercase			):
							raise ValueError(f"""`token_id` has to be an `int`, but is {token_id} of type {type(lowercase			)}"""			)

				SCREAMING_SNAKE_CASE     						= False
				SCREAMING_SNAKE_CASE     						= False
				SCREAMING_SNAKE_CASE     						= False

				if self.does_advance(lowercase			):
							self.fulfilled_idx += 1
							SCREAMING_SNAKE_CASE     						= True
							if self.fulfilled_idx == (self.seqlen - 1):
										SCREAMING_SNAKE_CASE     						= True
							SCREAMING_SNAKE_CASE     						= completed
				else:
							# failed to make progress.
							SCREAMING_SNAKE_CASE     						= True
							self.reset()
				return stepped, completed, reset







	def  snake_case__     (     self      :Tuple			)		->      Optional[int]:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE     						= False
				SCREAMING_SNAKE_CASE     						= 0







	def  snake_case__     (     self      :List[Any]			)		->      Union[str, Any]:







				"""simple docstring"""






				return self.seqlen - (self.fulfilled_idx + 1)







	def  snake_case__     (     self      :Union[str, Any]   ,     lowercase      :Any=False			)		->      Dict:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE     						= PhrasalConstraint(self.token_ids			)

				if stateful:
							SCREAMING_SNAKE_CASE     						= self.seqlen
							SCREAMING_SNAKE_CASE     						= self.fulfilled_idx
							SCREAMING_SNAKE_CASE     						= self.completed

				return new_constraint





class     lowerCamelCase      :







	def __init__(     self      :List[Any]   ,     lowercase      :List[List[int]]   ,     lowercase      :Optional[int]=True			)		->      Any:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE     						= max([len(lowercase			) for one in nested_token_ids]			)

				SCREAMING_SNAKE_CASE     						= {}
				for token_ids in nested_token_ids:
							SCREAMING_SNAKE_CASE     						= root
							for tidx, token_id in enumerate(lowercase			):
										if token_id not in level:
													SCREAMING_SNAKE_CASE     						= {}

										SCREAMING_SNAKE_CASE     						= level[token_id]

				if no_subsets and self.has_subsets(lowercase   ,     lowercase			):
							raise ValueError(
							    '''Each list in `nested_token_ids` can\'t be a complete subset of another list, but is'''
							    f""" {nested_token_ids}."""			)

				SCREAMING_SNAKE_CASE     						= root







	def  snake_case__     (     self      :Optional[Any]   ,     lowercase      :Union[str, Any]			)		->      Tuple:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE     						= self.trie

				for current_token in current_seq:
							SCREAMING_SNAKE_CASE     						= start[current_token]

				SCREAMING_SNAKE_CASE     						= list(start.keys()			)

				return next_tokens







	def  snake_case__     (     self      :Dict   ,     lowercase      :List[Any]			)		->      Dict:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE     						= self.next_tokens(lowercase			)

				return len(lowercase			) == 0







	def  snake_case__     (     self      :str   ,     lowercase      :str			)		->      Dict:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE     						= list(root.values()			)
				if len(lowercase			) == 0:
							return 1
				else:
							return sum([self.count_leaves(lowercase			) for nn in next_nodes]			)







	def  snake_case__     (     self      :str   ,     lowercase      :Optional[int]   ,     lowercase      :List[Any]			)		->      Optional[Any]:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE     						= self.count_leaves(lowercase			)
				return len(lowercase			) != leaf_count





class     lowerCamelCase      (       __lowerCamelCase					):







	def __init__(     self      :Optional[int]   ,     lowercase      :List[List[int]]			)		->      Optional[Any]:







				"""simple docstring"""






				super(lowercase   ,     self			).__init__()

				if not isinstance(lowercase   ,     lowercase			) or len(lowercase			) == 0:
							raise ValueError(f"""`nested_token_ids` has to be a non-empty list, but is {nested_token_ids}."""			)
				if any(not isinstance(lowercase   ,     lowercase			) for token_ids in nested_token_ids			):
							raise ValueError(f"""`nested_token_ids` has to be a list of lists, but is {nested_token_ids}."""			)
				if any(
				    any((not isinstance(lowercase   ,     lowercase			) or token_id < 0) for token_id in token_ids			)
				    for token_ids in nested_token_ids			):
							raise ValueError(
							    f"""Each list in `nested_token_ids` has to be a list of positive integers, but is {nested_token_ids}."""			)

				SCREAMING_SNAKE_CASE     						= DisjunctiveTrie(lowercase			)
				SCREAMING_SNAKE_CASE     						= nested_token_ids

				SCREAMING_SNAKE_CASE     						= self.trie.max_height
				SCREAMING_SNAKE_CASE     						= []
				SCREAMING_SNAKE_CASE     						= False







	def  snake_case__     (     self      :List[str]			)		->      Optional[int]:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE     						= self.trie.next_tokens(self.current_seq			)

				if len(lowercase			) == 0:
							return None
				else:
							return token_list







	def  snake_case__     (     self      :Union[str, Any]   ,     lowercase      :int			)		->      Tuple:







				"""simple docstring"""






				if not isinstance(lowercase   ,     lowercase			):
							raise ValueError(f"""`token_id` is supposed to be type `int`, but is {token_id} of type {type(lowercase			)}"""			)

				SCREAMING_SNAKE_CASE     						= self.trie.next_tokens(self.current_seq			)

				return token_id in next_tokens







	def  snake_case__     (     self      :List[str]   ,     lowercase      :int			)		->      Any:







				"""simple docstring"""






				if not isinstance(lowercase   ,     lowercase			):
							raise ValueError(f"""`token_id` is supposed to be type `int`, but is {token_id} of type {type(lowercase			)}"""			)

				SCREAMING_SNAKE_CASE     						= False
				SCREAMING_SNAKE_CASE     						= False
				SCREAMING_SNAKE_CASE     						= False

				if self.does_advance(lowercase			):
							self.current_seq.append(lowercase			)
							SCREAMING_SNAKE_CASE     						= True
				else:
							SCREAMING_SNAKE_CASE     						= True
							self.reset()

				SCREAMING_SNAKE_CASE     						= self.trie.reached_leaf(self.current_seq			)
				SCREAMING_SNAKE_CASE     						= completed

				return stepped, completed, reset







	def  snake_case__     (     self      :str			)		->      str:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE     						= False
				SCREAMING_SNAKE_CASE     						= []







	def  snake_case__     (     self      :str			)		->      str:







				"""simple docstring"""






				if self.completed:
							# since this can be completed without reaching max height
							return 0
				else:
							return self.seqlen - len(self.current_seq			)







	def  snake_case__     (     self      :int   ,     lowercase      :Optional[int]=False			)		->      int:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE     						= DisjunctiveConstraint(self.token_ids			)

				if stateful:
							SCREAMING_SNAKE_CASE     						= self.seqlen
							SCREAMING_SNAKE_CASE     						= self.current_seq
							SCREAMING_SNAKE_CASE     						= self.completed

				return new_constraint





class     lowerCamelCase      :







	def __init__(     self      :int   ,     lowercase      :List[Constraint]			)		->      str:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE     						= constraints

				# max # of steps required to fulfill a given constraint
				SCREAMING_SNAKE_CASE     						= max([c.seqlen for c in constraints]			)
				SCREAMING_SNAKE_CASE     						= len(lowercase			)
				SCREAMING_SNAKE_CASE     						= False

				self.init_state()







	def  snake_case__     (     self      :Optional[int]			)		->      int:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE     						= []
				SCREAMING_SNAKE_CASE     						= None
				SCREAMING_SNAKE_CASE     						= [constraint.copy(stateful=lowercase			) for constraint in self.constraints]







	def  snake_case__     (     self      :Dict			)		->      Optional[int]:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE     						= 0
				if self.inprogress_constraint:
							# extra points for having a constraint mid-fulfilled
							add += self.max_seqlen - self.inprogress_constraint.remaining()

				return (len(self.complete_constraints			) * self.max_seqlen) + add







	def  snake_case__     (     self      :int			)		->      int:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE     						= []
				if self.inprogress_constraint is None:
							for constraint in self.pending_constraints:  # "pending" == "unfulfilled yet"
										SCREAMING_SNAKE_CASE     						= constraint.advance()
										if isinstance(lowercase   ,     lowercase			):
													token_list.append(lowercase			)
										elif isinstance(lowercase   ,     lowercase			):
													token_list.extend(lowercase			)
				else:
							SCREAMING_SNAKE_CASE     						= self.inprogress_constraint.advance()
							if isinstance(lowercase   ,     lowercase			):
										token_list.append(lowercase			)
							elif isinstance(lowercase   ,     lowercase			):
										token_list.extend(lowercase			)

				if len(lowercase			) == 0:
							return None
				else:
							return token_list







	def  snake_case__     (     self      :Tuple   ,     lowercase      :Optional[List[int]]			)		->      List[str]:







				"""simple docstring"""






				self.init_state()

				if token_ids is not None:
							for token in token_ids:
										# completes or steps **one** constraint
										SCREAMING_SNAKE_CASE						,							SCREAMING_SNAKE_CASE     						= self.add(lowercase			)

										# the entire list of constraints are fulfilled
										if self.completed:
													break







	def  snake_case__     (     self      :Dict   ,     lowercase      :int			)		->      Optional[int]:







				"""simple docstring"""






				if not isinstance(lowercase   ,     lowercase			):
							raise ValueError(f"""`token_id` should be an `int`, but is `{token_id}`."""			)

				SCREAMING_SNAKE_CASE						,							SCREAMING_SNAKE_CASE     						= False, False

				if self.completed:
							SCREAMING_SNAKE_CASE     						= True
							SCREAMING_SNAKE_CASE     						= False
							return complete, stepped

				if self.inprogress_constraint is not None:
							# In the middle of fulfilling a constraint. If the `token_id` *does* makes an incremental progress to current
							# job, simply update the state

							SCREAMING_SNAKE_CASE						,							SCREAMING_SNAKE_CASE						,							SCREAMING_SNAKE_CASE     						= self.inprogress_constraint.update(lowercase			)
							if reset:
										# 1. If the next token breaks the progress, then we must restart.
										#     e.g. constraint = "I love pies" and sequence so far is "I love" but `token_id` == "books".

										#     But that doesn't mean we self.init_state(), since we only reset the state for this particular
										#     constraint, not the full list of constraints.

										self.pending_constraints.append(self.inprogress_constraint.copy(stateful=lowercase			)			)
										SCREAMING_SNAKE_CASE     						= None

							if complete:
										# 2. If the next token completes the constraint, move it to completed list, set
										#     inprogress to None. If there are no pending constraints either, then this full list of constraints
										#     is complete.

										self.complete_constraints.append(self.inprogress_constraint			)
										SCREAMING_SNAKE_CASE     						= None

										if len(self.pending_constraints			) == 0:
													# we're done!
													SCREAMING_SNAKE_CASE     						= True

				else:
							# Not in the middle of fulfilling a constraint. So does this `token_id` helps us step towards any of our list
							# of constraints?

							for cidx, pending_constraint in enumerate(self.pending_constraints			):
										if pending_constraint.does_advance(lowercase			):
													SCREAMING_SNAKE_CASE						,							SCREAMING_SNAKE_CASE						,							SCREAMING_SNAKE_CASE     						= pending_constraint.update(lowercase			)

													if not stepped:
																raise Exception(
																    '''`constraint.update(token_id)` is not yielding incremental progress, '''
																    '''even though `constraint.does_advance(token_id)` is true.'''			)

													if complete:
																self.complete_constraints.append(lowercase			)
																SCREAMING_SNAKE_CASE     						= None

													if not complete and stepped:
																SCREAMING_SNAKE_CASE     						= pending_constraint

													if complete or stepped:
																# If we made any progress at all, then it's at least not a "pending constraint".

																SCREAMING_SNAKE_CASE     						= (
																    self.pending_constraints[:cidx] + self.pending_constraints[cidx + 1 :]
																)

																if len(self.pending_constraints			) == 0 and self.inprogress_constraint is None:
																			# If there's no longer any pending after this and no inprogress either, then we must be
																			# complete.

																			SCREAMING_SNAKE_CASE     						= True

																break  # prevent accidentally stepping through multiple constraints with just one token.

				return complete, stepped







	def  snake_case__     (     self      :Optional[int]   ,     lowercase      :List[Any]=True			)		->      Tuple:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE     						= ConstraintListState(self.constraints			)  # we actually never though self.constraints objects
				# throughout this process. So it's at initialization state.

				if stateful:
							SCREAMING_SNAKE_CASE     						= [
							    constraint.copy(stateful=lowercase			) for constraint in self.complete_constraints
							]
							if self.inprogress_constraint is not None:
										SCREAMING_SNAKE_CASE     						= self.inprogress_constraint.copy(stateful=lowercase			)
							SCREAMING_SNAKE_CASE     						= [constraint.copy() for constraint in self.pending_constraints]

				return new_state

import json
import os

import torch

from diffusers import UNetaDModel


os.makedirs('hub/hopper-medium-v2/unet/hor32', exist_ok=True)
os.makedirs('hub/hopper-medium-v2/unet/hor128', exist_ok=True)

os.makedirs('hub/hopper-medium-v2/value_function', exist_ok=True)


def    a      ( a	)     ->List[Any]:




			'''simple docstring'''


			if hor == 128:
						SCREAMING_SNAKE_CASE     						= ('''DownResnetBlock1D''', '''DownResnetBlock1D''', '''DownResnetBlock1D''')
						SCREAMING_SNAKE_CASE     						= (32, 128, 256)
						SCREAMING_SNAKE_CASE     						= ('''UpResnetBlock1D''', '''UpResnetBlock1D''')

			elif hor == 32:
						SCREAMING_SNAKE_CASE     						= ('''DownResnetBlock1D''', '''DownResnetBlock1D''', '''DownResnetBlock1D''', '''DownResnetBlock1D''')
						SCREAMING_SNAKE_CASE     						= (32, 64, 128, 256)
						SCREAMING_SNAKE_CASE     						= ('''UpResnetBlock1D''', '''UpResnetBlock1D''', '''UpResnetBlock1D''')
			SCREAMING_SNAKE_CASE     						= torch.load(F"""/Users/bglickenhaus/Documents/diffuser/temporal_unet-hopper-mediumv2-hor{hor}.torch"""	)
			SCREAMING_SNAKE_CASE     						= model.state_dict()
			SCREAMING_SNAKE_CASE     						= {
			    '''down_block_types''': down_block_types,
			    '''block_out_channels''': block_out_channels,
			    '''up_block_types''': up_block_types,
			    '''layers_per_block''': 1,
			    '''use_timestep_embedding''': True,
			    '''out_block_type''': '''OutConv1DBlock''',
			    '''norm_num_groups''': 8,
			    '''downsample_each_block''': False,
			    '''in_channels''': 14,
			    '''out_channels''': 14,
			    '''extra_in_channels''': 0,
			    '''time_embedding_type''': '''positional''',
			    '''flip_sin_to_cos''': False,
			    '''freq_shift''': 1,
			    '''sample_size''': 6_5536,
			    '''mid_block_type''': '''MidResTemporalBlock1D''',
			    '''act_fn''': '''mish''',
			}
			SCREAMING_SNAKE_CASE     						= UNetaDModel(**a	)
			print(F"""length of state dict: {len(state_dict.keys()	)}"""	)
			print(F"""length of value function dict: {len(hf_value_function.state_dict().keys()	)}"""	)
			SCREAMING_SNAKE_CASE     						= dict(zip(model.state_dict().keys()		,						hf_value_function.state_dict().keys()	)	)
			for k, v in mapping.items():
						SCREAMING_SNAKE_CASE     						= state_dict.pop(a	)
			hf_value_function.load_state_dict(a	)

			torch.save(hf_value_function.state_dict()		,						F"""hub/hopper-medium-v2/unet/hor{hor}/diffusion_pytorch_model.bin"""	)
			with open(F"""hub/hopper-medium-v2/unet/hor{hor}/config.json"""		,						'''w'''	) as f:
						json.dump(a		,						a	)


def    a      ( )     ->Optional[Any]:




			'''simple docstring'''


			SCREAMING_SNAKE_CASE     						= {
			    '''in_channels''': 14,
			    '''down_block_types''': ('''DownResnetBlock1D''', '''DownResnetBlock1D''', '''DownResnetBlock1D''', '''DownResnetBlock1D'''),
			    '''up_block_types''': (),
			    '''out_block_type''': '''ValueFunction''',
			    '''mid_block_type''': '''ValueFunctionMidBlock1D''',
			    '''block_out_channels''': (32, 64, 128, 256),
			    '''layers_per_block''': 1,
			    '''downsample_each_block''': True,
			    '''sample_size''': 6_5536,
			    '''out_channels''': 14,
			    '''extra_in_channels''': 0,
			    '''time_embedding_type''': '''positional''',
			    '''use_timestep_embedding''': True,
			    '''flip_sin_to_cos''': False,
			    '''freq_shift''': 1,
			    '''norm_num_groups''': 8,
			    '''act_fn''': '''mish''',
			}

			SCREAMING_SNAKE_CASE     						= torch.load('''/Users/bglickenhaus/Documents/diffuser/value_function-hopper-mediumv2-hor32.torch'''	)
			SCREAMING_SNAKE_CASE     						= model
			SCREAMING_SNAKE_CASE     						= UNetaDModel(**a	)
			print(F"""length of state dict: {len(state_dict.keys()	)}"""	)
			print(F"""length of value function dict: {len(hf_value_function.state_dict().keys()	)}"""	)

			SCREAMING_SNAKE_CASE     						= dict(zip(state_dict.keys()		,						hf_value_function.state_dict().keys()	)	)
			for k, v in mapping.items():
						SCREAMING_SNAKE_CASE     						= state_dict.pop(a	)

			hf_value_function.load_state_dict(a	)

			torch.save(hf_value_function.state_dict()		,						'''hub/hopper-medium-v2/value_function/diffusion_pytorch_model.bin'''	)
			with open('''hub/hopper-medium-v2/value_function/config.json'''		,						'''w'''	) as f:
						json.dump(a		,						a	)


if __name__ == "__main__":
							unet(3_2)
							# unet(128)
							value_function()