






'''simple docstring'''







import time
from contextlib import contextmanager
from pathlib import Path

import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder


UpperCamelCase    :      Dict  			=		'__DUMMY_TRANSFORMERS_USER__'
UpperCamelCase    :      Tuple  			=		'Dummy User'
UpperCamelCase    :      Tuple  			=		'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'

UpperCamelCase    :      List[Any]  			=		'https://hub-ci.huggingface.co'
UpperCamelCase    :      Optional[int]  			=		CI_HUB_ENDPOINT + '/datasets/{repo_id}/resolve/{revision}/{path}'
UpperCamelCase    :      List[Any]  			=		CI_HUB_ENDPOINT + '/{repo_id}/resolve/{revision}/{filename}'
UpperCamelCase    :      int  			=		Path('~/.huggingface/hub_ci_token').expanduser()
@pytest.fixture
def 						A__			(				__lowerCAmelCase		:			Any						):
						monkeypatch.setattr(
						    """huggingface_hub.file_download.HUGGINGFACE_CO_URL_TEMPLATE"""   ,    __lowerCAmelCase						)
@pytest.fixture
def 						A__			(				__lowerCAmelCase		:			List[str]						):
						monkeypatch.setattr("""datasets.config.HF_ENDPOINT"""   ,    __lowerCAmelCase						)
						monkeypatch.setattr("""datasets.config.HUB_DATASETS_URL"""   ,    __lowerCAmelCase						)
@pytest.fixture
def 						A__			(				__lowerCAmelCase		:			List[str]						):
						monkeypatch.setattr("""huggingface_hub.hf_api.HfFolder.path_token"""   ,    __lowerCAmelCase						)
@pytest.fixture
def 						A__			(				__lowerCAmelCase		:			str   ,    __lowerCAmelCase		:			str						):
						HfFolder.save_token(__lowerCAmelCase						)
						yield
						HfFolder.delete_token()
@pytest.fixture(scope="""session"""						)
def 						A__			(				):
						return HfApi(endpoint=__lowerCAmelCase						)
@pytest.fixture(scope="""session"""						)
def 						A__			(				__lowerCAmelCase		:			HfApi						):
						lowerCamelCase__         =  HfFolder.get_token()
						HfFolder.save_token(__lowerCAmelCase						)
						yield CI_HUB_USER_TOKEN
						if previous_token is not None:
												HfFolder.save_token(__lowerCAmelCase						)
@pytest.fixture
def 						A__			(				__lowerCAmelCase		:			Tuple						):
						def _cleanup_repo(__lowerCAmelCase		:			Optional[int]						):
												hf_api.delete_repo(__lowerCAmelCase   ,    token=__lowerCAmelCase   ,    repo_type="""dataset"""						)

						return _cleanup_repo
@pytest.fixture
def 						A__			(				__lowerCAmelCase		:			Any						):
						@contextmanager
						def _temporary_repo(__lowerCAmelCase		:			Optional[int]						):
												try:
																		yield repo_id
												finally:
																		cleanup_repo(__lowerCAmelCase						)

						return _temporary_repo
@pytest.fixture(scope="""session"""						)
def 						A__			(				__lowerCAmelCase		:			HfApi   ,    __lowerCAmelCase		:			int   ,    __lowerCAmelCase		:			str						):
						lowerCamelCase__         =  F'''repo_txt_data-{int(time.time() * 10e3						)}'''
						lowerCamelCase__         =  F'''{CI_HUB_USER}/{repo_name}'''
						hf_api.create_repo(__lowerCAmelCase   ,    token=__lowerCAmelCase   ,    repo_type="""dataset"""   ,    private=__lowerCAmelCase						)
						hf_api.upload_file(
						    token=__lowerCAmelCase   ,    path_or_fileobj=str(__lowerCAmelCase						)   ,    path_in_repo="""data/text_data.txt"""   ,    repo_id=__lowerCAmelCase   ,    repo_type="""dataset"""   ,    )
						yield repo_id
						try:
												hf_api.delete_repo(__lowerCAmelCase   ,    token=__lowerCAmelCase   ,    repo_type="""dataset"""						)
						except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
												pass
@pytest.fixture()
def 						A__			(				__lowerCAmelCase		:			Optional[int]   ,    __lowerCAmelCase		:			List[str]   ,    __lowerCAmelCase		:			str						):
						return hf_private_dataset_repo_txt_data_
@pytest.fixture(scope="""session"""						)
def 						A__			(				__lowerCAmelCase		:			HfApi   ,    __lowerCAmelCase		:			Dict   ,    __lowerCAmelCase		:			int						):
						lowerCamelCase__         =  F'''repo_zipped_txt_data-{int(time.time() * 10e3						)}'''
						lowerCamelCase__         =  F'''{CI_HUB_USER}/{repo_name}'''
						hf_api.create_repo(__lowerCAmelCase   ,    token=__lowerCAmelCase   ,    repo_type="""dataset"""   ,    private=__lowerCAmelCase						)
						hf_api.upload_file(
						    token=__lowerCAmelCase   ,    path_or_fileobj=str(__lowerCAmelCase						)   ,    path_in_repo="""data.zip"""   ,    repo_id=__lowerCAmelCase   ,    repo_type="""dataset"""   ,    )
						yield repo_id
						try:
												hf_api.delete_repo(__lowerCAmelCase   ,    token=__lowerCAmelCase   ,    repo_type="""dataset"""						)
						except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
												pass
@pytest.fixture()
def 						A__			(				__lowerCAmelCase		:			str   ,    __lowerCAmelCase		:			Union[str, Any]   ,    __lowerCAmelCase		:			List[str]						):
						return hf_private_dataset_repo_zipped_txt_data_
@pytest.fixture(scope="""session"""						)
def 						A__			(				__lowerCAmelCase		:			HfApi   ,    __lowerCAmelCase		:			str   ,    __lowerCAmelCase		:			Any						):
						lowerCamelCase__         =  F'''repo_zipped_img_data-{int(time.time() * 10e3						)}'''
						lowerCamelCase__         =  F'''{CI_HUB_USER}/{repo_name}'''
						hf_api.create_repo(__lowerCAmelCase   ,    token=__lowerCAmelCase   ,    repo_type="""dataset"""   ,    private=__lowerCAmelCase						)
						hf_api.upload_file(
						    token=__lowerCAmelCase   ,    path_or_fileobj=str(__lowerCAmelCase						)   ,    path_in_repo="""data.zip"""   ,    repo_id=__lowerCAmelCase   ,    repo_type="""dataset"""   ,    )
						yield repo_id
						try:
												hf_api.delete_repo(__lowerCAmelCase   ,    token=__lowerCAmelCase   ,    repo_type="""dataset"""						)
						except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
												pass





@pytest.fixture()
def 						A__			(				__lowerCAmelCase		:			Tuple   ,    __lowerCAmelCase		:			int   ,    __lowerCAmelCase		:			Optional[int]						):
						return hf_private_dataset_repo_zipped_img_data_









'''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()

