

import argparse

import torch

from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging


logging.set_verbosity_info()





def a(lowercase__			, lowercase__			, lowercase__	):





	'''simple docstring'''
	# Initialise PyTorch model
	snake_case_      		= LxmertConfig.from_json_file(lowercase__	)
	print(f"""Building PyTorch model from configuration: {config}"""	)
	snake_case_      		= LxmertForPreTraining(lowercase__	)

	# Load weights from tf checkpoint
	load_tf_weights_in_lxmert(lowercase__			, lowercase__			, lowercase__	)

	# Save pytorch-model
	print(f"""Save PyTorch model to {pytorch_dump_path}"""	)
	torch.save(model.state_dict()			, lowercase__	)


if __name__ == "__main__":
		A											=     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(
		    '--config_file',
		    default=None,
		    type=str,
		    required=True,
		    help='The config json file corresponding to the pre-trained model. \nThis specifies the model architecture.',
		)
		parser.add_argument(
		    '--pytorch_dump_path', default=None, type=str, required=True, help='Path to the output PyTorch model.'
		)
		A											=     parser.parse_args()
		convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.config_file, args.pytorch_dump_path)



# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

# this script dumps information about the environment

import os
import platform
import sys


A											=     '3'

print('Python version:', sys.version)

print('OS platform:', platform.platform())
print('OS architecture:', platform.machine())

try:
		import torch

		print('Torch version:', torch.__version__)
		print('Cuda available:', torch.cuda.is_available())
		print('Cuda version:', torch.version.cuda)
		print('CuDNN version:', torch.backends.cudnn.version())
		print('Number of GPUs available:', torch.cuda.device_count())
except ImportError:
		print('Torch version:', None)

try:
		import transformers

		print('transformers version:', transformers.__version__)
except ImportError:
		print('transformers version:', None)
