






'''simple docstring'''







from collections import defaultdict
def 						A__			(				__lowerCAmelCase		:			str   ,    __lowerCAmelCase		:			str						):
						lowerCamelCase__         =  first_str.lower().strip()
						lowerCamelCase__         =  second_str.lower().strip()

						# Remove whitespace
						lowerCamelCase__         =  first_str.replace(""" """   ,    """"""						)
						lowerCamelCase__         =  second_str.replace(""" """   ,    """"""						)

						# Strings of different lengths are not anagrams
						if len(__lowerCAmelCase						) != len(__lowerCAmelCase						):
												return False

						# Default values for count should be 0
						lowerCamelCase__         =  defaultdict(__lowerCAmelCase						)

						# For each character in input strings,
						# increment count in the corresponding
						for i in range(len(__lowerCAmelCase						)						):
												count[first_str[i]] += 1
												count[second_str[i]] -= 1

						return all(_count == 0 for _count in count.values()						)


if __name__ == "__main__":
							from doctest import testmod

							testmod()
							UpperCamelCase    :      List[Any]  			=		input('Enter the first string ').strip()
							UpperCamelCase    :      List[str]  			=		input('Enter the second string ').strip()

							UpperCamelCase    :      Union[str, Any]  			=		check_anagrams(input_a, input_b)
							print(F'{input_a} and {input_b} are {"" if status else "not "}anagrams.')









'''simple docstring'''







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__			(				__lowerCAmelCase		:			Union[str, Any]						):
						if hor == 128:
												lowerCamelCase__         =  ("""DownResnetBlock1D""", """DownResnetBlock1D""", """DownResnetBlock1D""")
												lowerCamelCase__         =  (32, 128, 256)
												lowerCamelCase__         =  ("""UpResnetBlock1D""", """UpResnetBlock1D""")

						elif hor == 32:
												lowerCamelCase__         =  ("""DownResnetBlock1D""", """DownResnetBlock1D""", """DownResnetBlock1D""", """DownResnetBlock1D""")
												lowerCamelCase__         =  (32, 64, 128, 256)
												lowerCamelCase__         =  ("""UpResnetBlock1D""", """UpResnetBlock1D""", """UpResnetBlock1D""")
						lowerCamelCase__         =  torch.load(F'''/Users/bglickenhaus/Documents/diffuser/temporal_unet-hopper-mediumv2-hor{hor}.torch'''						)
						lowerCamelCase__         =  model.state_dict()
						lowerCamelCase__         =  {
						    """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""",
						}
						lowerCamelCase__         =  UNetaDModel(**__lowerCAmelCase						)
						print(F'''length of state dict: {len(state_dict.keys()						)}'''						)
						print(F'''length of value function dict: {len(hf_value_function.state_dict().keys()						)}'''						)
						lowerCamelCase__         =  dict(zip(model.state_dict().keys()   ,    hf_value_function.state_dict().keys()						)						)
						for k, v in mapping.items():
												lowerCamelCase__         =  state_dict.pop(__lowerCAmelCase						)
						hf_value_function.load_state_dict(__lowerCAmelCase						)

						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(__lowerCAmelCase   ,    __lowerCAmelCase						)
def 						A__			(				):
						lowerCamelCase__         =  {
						    """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""",
						}

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

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

						hf_value_function.load_state_dict(__lowerCAmelCase						)

						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(__lowerCAmelCase   ,    __lowerCAmelCase						)


if __name__ == "__main__":
							unet(32)
							# unet(128)
							value_function()

