"""simple docstring"""




import time
from contextlib import contextmanager
from pathlib import Path

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


__lowerCAmelCase    :							Tuple													=						"""__DUMMY_TRANSFORMERS_USER__"""
__lowerCAmelCase    :							Dict													=						"""Dummy User"""
__lowerCAmelCase    :							Union[str, Any]													=						"""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"""

__lowerCAmelCase    :							Union[str, Any]													=						"""https://hub-ci.huggingface.co"""
__lowerCAmelCase    :							List[Any]													=						CI_HUB_ENDPOINT + """/datasets/{repo_id}/resolve/{revision}/{path}"""
__lowerCAmelCase    :							Union[str, Any]													=						CI_HUB_ENDPOINT + """/{repo_id}/resolve/{revision}/{filename}"""
__lowerCAmelCase    :							List[Any]													=						Path("~/.huggingface/hub_ci_token").expanduser()







@pytest.fixture
def 							_UpperCAmelCase		(       lowerCamelCase__     ):





		"""simple docstring"""




		monkeypatch.setattr(
		    """huggingface_hub.file_download.HUGGINGFACE_CO_URL_TEMPLATE"""			,  lowerCamelCase__     )







@pytest.fixture
def 							_UpperCAmelCase		(       lowerCamelCase__     ):





		"""simple docstring"""




		monkeypatch.setattr("""datasets.config.HF_ENDPOINT"""			,  lowerCamelCase__     )
		monkeypatch.setattr("""datasets.config.HUB_DATASETS_URL"""			,  lowerCamelCase__     )







@pytest.fixture
def 							_UpperCAmelCase		(       lowerCamelCase__     ):





		"""simple docstring"""




		monkeypatch.setattr("""huggingface_hub.hf_api.HfFolder.path_token"""			,  lowerCamelCase__     )







@pytest.fixture
def 							_UpperCAmelCase		(       lowerCamelCase__			,  lowerCamelCase__     ):





		"""simple docstring"""




		HfFolder.save_token(lowerCamelCase__     )
		yield
		HfFolder.delete_token()







@pytest.fixture(scope="""session"""     )
def 							_UpperCAmelCase		(       ):





		"""simple docstring"""




		return HfApi(endpoint=lowerCamelCase__     )







@pytest.fixture(scope="""session"""     )
def 							_UpperCAmelCase		(       lowerCamelCase__     ):





		"""simple docstring"""




		A        =   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 							_UpperCAmelCase		(       lowerCamelCase__     ):





		"""simple docstring"""




		def _cleanup_repo(lowerCamelCase__     ):
				hf_api.delete_repo(lowerCamelCase__			,  token=lowerCamelCase__			,  repo_type="""dataset"""     )

		return _cleanup_repo







@pytest.fixture
def 							_UpperCAmelCase		(       lowerCamelCase__     ):





		"""simple docstring"""




		@contextmanager
		def _temporary_repo(lowerCamelCase__     ):
				try:
						yield repo_id
				finally:
						cleanup_repo(lowerCamelCase__     )

		return _temporary_repo







@pytest.fixture(scope="""session"""     )
def 							_UpperCAmelCase		(       lowerCamelCase__			,  lowerCamelCase__			,  lowerCamelCase__     ):





		"""simple docstring"""




		A        =   f"""repo_txt_data-{int(time.time() * 10e3     )}"""
		A        =   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 							_UpperCAmelCase		(       lowerCamelCase__			,  lowerCamelCase__			,  lowerCamelCase__     ):





		"""simple docstring"""




		return hf_private_dataset_repo_txt_data_







@pytest.fixture(scope="""session"""     )
def 							_UpperCAmelCase		(       lowerCamelCase__			,  lowerCamelCase__			,  lowerCamelCase__     ):





		"""simple docstring"""




		A        =   f"""repo_zipped_txt_data-{int(time.time() * 10e3     )}"""
		A        =   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 							_UpperCAmelCase		(       lowerCamelCase__			,  lowerCamelCase__			,  lowerCamelCase__     ):





		"""simple docstring"""




		return hf_private_dataset_repo_zipped_txt_data_







@pytest.fixture(scope="""session"""     )
def 							_UpperCAmelCase		(       lowerCamelCase__			,  lowerCamelCase__			,  lowerCamelCase__     ):





		"""simple docstring"""




		A        =   f"""repo_zipped_img_data-{int(time.time() * 10e3     )}"""
		A        =   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 							_UpperCAmelCase		(       lowerCamelCase__			,  lowerCamelCase__			,  lowerCamelCase__     ):





		"""simple docstring"""




		return hf_private_dataset_repo_zipped_img_data_





"""simple docstring"""




import argparse

import torch

from transformers import MobileBertConfig, MobileBertForPreTraining, load_tf_weights_in_mobilebert
from transformers.utils import logging


logging.set_verbosity_info()







def 							_UpperCAmelCase		(       lowerCamelCase__			,  lowerCamelCase__			,  lowerCamelCase__     ):





		"""simple docstring"""




		lowerCAmelCase__        =   MobileBertConfig.from_json_file(lowerCamelCase__     )
		print(f"""Building PyTorch model from configuration: {config}"""     )
		lowerCAmelCase__        =   MobileBertForPreTraining(lowerCamelCase__     )
		# Load weights from tf checkpoint
		lowerCAmelCase__        =   load_tf_weights_in_mobilebert(lowerCamelCase__			,  lowerCamelCase__			,  lowerCamelCase__     )
		# Save pytorch-model
		print(f"""Save PyTorch model to {pytorch_dump_path}"""     )
		torch.save(model.state_dict()			,  lowerCamelCase__     )


if __name__ == "__main__":
			__lowerCAmelCase    :							List[str]													=						argparse.ArgumentParser()
			# Required parameters
			parser.add_argument(
			    "--tf_checkpoint_path", default=None, type=str, required=True, help="Path to the TensorFlow checkpoint path."
			)
			parser.add_argument(
			    "--mobilebert_config_file",
			    default=None,
			    type=str,
			    required=True,
			    help=(
			        "The config json file corresponding to the pre-trained MobileBERT model. \n"
			        "This specifies the model architecture."
			    ),
			)
			parser.add_argument(
			    "--pytorch_dump_path", default=None, type=str, required=True, help="Path to the output PyTorch model."
			)
			__lowerCAmelCase    :							Optional[int]													=						parser.parse_args()
			convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.mobilebert_config_file, args.pytorch_dump_path)




