




"""simple docstring"""

import argparse
import os


UpperCamelCase__			:     Tuple			       =				{
    "pytorch": {
        "1.13": {
            "torch": "1.13.1",
            "torchvision": "0.14.1",
            "torchaudio": "0.13.1",
            "python": 3.9,
            "cuda": "cu116",
            "install": (
                "python3 -m pip install --no-cache-dir -U torch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1"
                " --extra-index-url https://download.pytorch.org/whl/cu116"
            ),
            "base_image": "nvidia/cuda:11.6.2-cudnn8-devel-ubuntu20.04",
        },
        "1.12": {
            "torch": "1.12.1",
            "torchvision": "0.13.1",
            "torchaudio": "0.12.1",
            "python": 3.9,
            "cuda": "cu113",
            "install": (
                "python3 -m pip install --no-cache-dir -U torch==1.12.1 torchvision==0.13.1 torchaudio==0.12.1"
                " --extra-index-url https://download.pytorch.org/whl/cu113"
            ),
            "base_image": "nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04",
        },
        "1.11": {
            "torch": "1.11.0",
            "torchvision": "0.12.0",
            "torchaudio": "0.11.0",
            "python": 3.9,
            "cuda": "cu113",
            "install": (
                "python3 -m pip install --no-cache-dir -U torch==1.11.0 torchvision==0.12.0 torchaudio==0.11.0"
                " --extra-index-url https://download.pytorch.org/whl/cu113"
            ),
            "base_image": "nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04",
        },
        "1.10": {
            "torch": "1.10.2",
            "torchvision": "0.11.3",
            "torchaudio": "0.10.2",
            "python": 3.9,
            "cuda": "cu113",
            "install": (
                "python3 -m pip install --no-cache-dir -U torch==1.10.2 torchvision==0.11.3 torchaudio==0.10.2"
                " --extra-index-url https://download.pytorch.org/whl/cu113"
            ),
            "base_image": "nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04",
        },
        # torchaudio < 0.10 has no CUDA-enabled binary distributions
        "1.9": {
            "torch": "1.9.1",
            "torchvision": "0.10.1",
            "torchaudio": "0.9.1",
            "python": 3.9,
            "cuda": "cu111",
            "install": (
                "python3 -m pip install --no-cache-dir -U torch==1.9.1 torchvision==0.10.1 torchaudio==0.9.1"
                " --extra-index-url https://download.pytorch.org/whl/cu111"
            ),
            "base_image": "nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04",
        },
    },
    "tensorflow": {
        "2.11": {
            "tensorflow": "2.11.1",
            "install": "python3 -m pip install --no-cache-dir -U tensorflow==2.11.1",
            "base_image": "nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04",
        },
        "2.10": {
            "tensorflow": "2.10.1",
            "install": "python3 -m pip install --no-cache-dir -U tensorflow==2.10.1",
            "base_image": "nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04",
        },
        "2.9": {
            "tensorflow": "2.9.3",
            "install": "python3 -m pip install --no-cache-dir -U tensorflow==2.9.3",
            "base_image": "nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04",
        },
        "2.8": {
            "tensorflow": "2.8.2",
            "install": "python3 -m pip install --no-cache-dir -U tensorflow==2.8.2",
            "base_image": "nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04",
        },
        "2.7": {
            "tensorflow": "2.7.3",
            "install": "python3 -m pip install --no-cache-dir -U tensorflow==2.7.3",
            "base_image": "nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04",
        },
        "2.6": {
            "tensorflow": "2.6.5",
            "install": "python3 -m pip install --no-cache-dir -U tensorflow==2.6.5",
            "base_image": "nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04",
        },
        "2.5": {
            "tensorflow": "2.5.3",
            "install": "python3 -m pip install --no-cache-dir -U tensorflow==2.5.3",
            "base_image": "nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04",
        },
    },
}


if __name__ == "__main__":
		UpperCamelCase__			:     Optional[Any]			       =				argparse.ArgumentParser("Choose the framework and version to install")
		parser.add_argument(
		    "--framework", help="The framework to install. Should be `torch` or `tensorflow`", type=str, required=True
		)
		parser.add_argument("--version", help="The version of the framework to install.", type=str, required=True)
		UpperCamelCase__			:     Dict			       =				parser.parse_args()

		UpperCamelCase__			:     Any			       =				past_versions_testing[args.framework][args.version]

		os.system(f'echo "export INSTALL_CMD=\'{info["install"]}\'" >> ~/.profile')
		print(f'echo "export INSTALL_CMD=\'{info["install"]}\'" >> ~/.profile')

		UpperCamelCase__			:     List[str]			       =				""
		if args.framework == "pytorch":
				UpperCamelCase__			:     Dict			       =				info["cuda"]
		os.system(f'echo \"export CUDA=\'{cuda}\'\" >> ~/.profile')
		print(f'echo \"export CUDA=\'{cuda}\'\" >> ~/.profile')








"""simple docstring"""

import torch
import trajectory.utils as utils

from transformers import TrajectoryTransformerModel
class      A__   (   utils.Parser  ):
	A_				:					str      =   "halfcheetah-medium-expert-v2"
	A_				:					str      =   "config.offline"




def    snake_case__						(							lowerCAmelCase :		Optional[int]					,       lowerCAmelCase :		List[Any]					,       lowerCAmelCase :		List[str]					,       lowerCAmelCase :		Optional[int]					,       lowerCAmelCase :		List[Any]		):
					__snake_case   ,   __snake_case        =						utils.load_model(lowerCAmelCase					,       lowerCAmelCase					,       lowerCAmelCase					,       epoch=lowerCAmelCase					,       device=lowerCAmelCase		)
					__snake_case        =						TrajectoryTransformerModel(gpt.config		)

					trajectory_transformer.tok_emb.load_state_dict(gpt.tok_emb.state_dict()		)
					__snake_case        =						gpt.pos_emb
					trajectory_transformer.drop.load_state_dict(gpt.drop.state_dict()		)
					trajectory_transformer.ln_f.load_state_dict(gpt.ln_f.state_dict()		)
					trajectory_transformer.head.load_state_dict(gpt.head.state_dict()		)

					for i, block in enumerate(gpt.blocks		):
										trajectory_transformer.blocks[i].lna.load_state_dict(gpt.blocks[i].lna.state_dict()		)
										trajectory_transformer.blocks[i].lna.load_state_dict(gpt.blocks[i].lna.state_dict()		)
										trajectory_transformer.blocks[i].attn.load_state_dict(gpt.blocks[i].attn.state_dict()		)

										trajectory_transformer.blocks[i].la.load_state_dict(gpt.blocks[i].mlp[0].state_dict()		)
										trajectory_transformer.blocks[i].act.load_state_dict(gpt.blocks[i].mlp[1].state_dict()		)
										trajectory_transformer.blocks[i].la.load_state_dict(gpt.blocks[i].mlp[2].state_dict()		)
										trajectory_transformer.blocks[i].drop.load_state_dict(gpt.blocks[i].mlp[3].state_dict()		)

					torch.save(trajectory_transformer.state_dict()					,       """pytorch_model.bin"""		)


if __name__ == "__main__":
		UpperCamelCase__			:     int			       =				Parser().parse_args("plan")
		convert_trajectory_transformer_original_pytorch_checkpoint_to_pytorch(
		    args.logbase, args.dataset, args.gpt_loadpath, args.gpt_epoch, args.device
		)


