




import platform
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand







def 	_a      (						SCREAMING_SNAKE_CASE_							:				List[Any]     ):
					return EnvironmentCommand()


class 			a__    (					snake_case__      ):






						@staticmethod
						def 				__SCREAMING_SNAKE_CASE(   _A			):




											"""simple docstring"""



											__lowerCAmelCase				   =       parser.add_parser("env"			)
											download_parser.set_defaults(func=_A			)






						def 				__SCREAMING_SNAKE_CASE(   self			):




											"""simple docstring"""



											__lowerCAmelCase				   =       huggingface_hub.__version__

											__lowerCAmelCase				   =       "not installed"
											__lowerCAmelCase				   =       "NA"
											if is_torch_available():
																import torch

																__lowerCAmelCase				   =       torch.__version__
																__lowerCAmelCase				   =       torch.cuda.is_available()

											__lowerCAmelCase				   =       "not installed"
											if is_transformers_available():
																import transformers

																__lowerCAmelCase				   =       transformers.__version__

											__lowerCAmelCase				   =       "not installed"
											if is_accelerate_available():
																import accelerate

																__lowerCAmelCase				   =       accelerate.__version__

											__lowerCAmelCase				   =       "not installed"
											if is_xformers_available():
																import xformers

																__lowerCAmelCase				   =       xformers.__version__

											__lowerCAmelCase				   =       {
											    "`diffusers` version": version,
											    "Platform": platform.platform(),
											    "Python version": platform.python_version(),
											    "PyTorch version (GPU?)": f"""{pt_version} ({pt_cuda_available})""",
											    "Huggingface_hub version": hub_version,
											    "Transformers version": transformers_version,
											    "Accelerate version": accelerate_version,
											    "xFormers version": xformers_version,
											    "Using GPU in script?": "<fill in>",
											    "Using distributed or parallel set-up in script?": "<fill in>",
											}

											print("\nCopy-and-paste the text below in your GitHub issue and FILL OUT the two last points.\n"			)
											print(self.format_dict(_A			)			)

											return info






						@staticmethod
						def 				__SCREAMING_SNAKE_CASE(   _A			):




											"""simple docstring"""



											return "\n".join([f"""- {prop}: {val}""" for prop, val in d.items()]			) + "\n"










from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCamelCase__    			=			logging.get_logger(__name__)

UpperCamelCase__    			=			{
    """edbeeching/decision-transformer-gym-hopper-medium""": (
        """https://huggingface.co/edbeeching/decision-transformer-gym-hopper-medium/resolve/main/config.json"""
    ),
    # See all DecisionTransformer models at https://huggingface.co/models?filter=decision_transformer
}
class 			a__    (					snake_case__      ):
						_a							:    Optional[int]					=    """decision_transformer"""
						_a							:    Optional[int]					=    ["""past_key_values"""]
						_a							:    Dict					=    {
						    """max_position_embeddings""": """n_positions""",
						    """num_attention_heads""": """n_head""",
						    """num_hidden_layers""": """n_layer""",
						}






						def __init__(   self		,			_A=1_7		,			_A=4		,			_A=1_2_8		,			_A=4_0_9_6		,			_A=True		,			_A=1		,			_A=1_0_2_4		,			_A=3		,			_A=1		,			_A=None		,			_A="relu"		,			_A=0.1		,			_A=0.1		,			_A=0.1		,			_A=1E-5		,			_A=0.02		,			_A=True		,			_A=True		,			_A=5_0_2_5_6		,			_A=5_0_2_5_6		,			_A=False		,			_A=False		,			**_A		,			):




											"""simple docstring"""



											__lowerCAmelCase				   =       state_dim
											__lowerCAmelCase				   =       act_dim
											__lowerCAmelCase				   =       hidden_size
											__lowerCAmelCase				   =       max_ep_len
											__lowerCAmelCase				   =       action_tanh
											__lowerCAmelCase				   =       vocab_size
											__lowerCAmelCase				   =       n_positions
											__lowerCAmelCase				   =       n_layer
											__lowerCAmelCase				   =       n_head
											__lowerCAmelCase				   =       n_inner
											__lowerCAmelCase				   =       activation_function
											__lowerCAmelCase				   =       resid_pdrop
											__lowerCAmelCase				   =       embd_pdrop
											__lowerCAmelCase				   =       attn_pdrop
											__lowerCAmelCase				   =       layer_norm_epsilon
											__lowerCAmelCase				   =       initializer_range
											__lowerCAmelCase				   =       scale_attn_weights
											__lowerCAmelCase				   =       use_cache
											__lowerCAmelCase				   =       scale_attn_by_inverse_layer_idx
											__lowerCAmelCase				   =       reorder_and_upcast_attn

											__lowerCAmelCase				   =       bos_token_id
											__lowerCAmelCase				   =       eos_token_id

											super().__init__(bos_token_id=_A		,			eos_token_id=_A		,			**_A			)




