




from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_lowerCAmelCase						:   List[Any]		=   logging.get_logger(__name__)

_lowerCAmelCase						:   Tuple		=   {
    "google/mobilenet_v2_1.4_224": "https://huggingface.co/google/mobilenet_v2_1.4_224/resolve/main/config.json",
    "google/mobilenet_v2_1.0_224": "https://huggingface.co/google/mobilenet_v2_1.0_224/resolve/main/config.json",
    "google/mobilenet_v2_0.75_160": "https://huggingface.co/google/mobilenet_v2_0.75_160/resolve/main/config.json",
    "google/mobilenet_v2_0.35_96": "https://huggingface.co/google/mobilenet_v2_0.35_96/resolve/main/config.json",
    # See all MobileNetV2 models at https://huggingface.co/models?filter=mobilenet_v2
}
class 			_UpperCamelCase      (				lowerCAmelCase		):
      UpperCAmelCase_        =		"""mobilenet_v2"""
      def __init__(			self   :List[Any] ,      lowerCamelCase   :List[str]=3 ,      lowerCamelCase   :Optional[Any]=224 ,      lowerCamelCase   :Any=1.0 ,      lowerCamelCase   :Optional[Any]=8 ,      lowerCamelCase   :str=8 ,      lowerCamelCase   :List[str]=6 ,      lowerCamelCase   :List[str]=32 ,      lowerCamelCase   :int=True ,      lowerCamelCase   :Optional[int]=True ,      lowerCamelCase   :int="relu6" ,      lowerCamelCase   :Optional[int]=True ,      lowerCamelCase   :int=0.8 ,      lowerCamelCase   :Dict=0.02 ,      lowerCamelCase   :Union[str, Any]=0.0_01 ,      lowerCamelCase   :Any=255 ,      **lowerCamelCase   :Tuple ,      )     ->			Tuple:
       super().__init__(**lowerCamelCase      )

       if depth_multiplier <= 0:
        raise ValueError("depth_multiplier must be greater than zero."      )

       UpperCAmelCase__							 =						num_channels
       UpperCAmelCase__							 =						image_size
       UpperCAmelCase__							 =						depth_multiplier
       UpperCAmelCase__							 =						depth_divisible_by
       UpperCAmelCase__							 =						min_depth
       UpperCAmelCase__							 =						expand_ratio
       UpperCAmelCase__							 =						output_stride
       UpperCAmelCase__							 =						first_layer_is_expansion
       UpperCAmelCase__							 =						finegrained_output
       UpperCAmelCase__							 =						hidden_act
       UpperCAmelCase__							 =						tf_padding
       UpperCAmelCase__							 =						classifier_dropout_prob
       UpperCAmelCase__							 =						initializer_range
       UpperCAmelCase__							 =						layer_norm_eps
       UpperCAmelCase__							 =						semantic_loss_ignore_index



class 			_UpperCamelCase      (				lowerCAmelCase		):
      UpperCAmelCase_        =		version.parse("""1.11"""		)
      @property
      def 	UpperCAmelCase_						(			self   :Optional[Any]      )     ->			Mapping[str, Mapping[int, str]]:
       return OrderedDict([("pixel_values", {0: "batch"})]      )
      @property
      def 	UpperCAmelCase_						(			self   :Union[str, Any]      )     ->			Mapping[str, Mapping[int, str]]:
       if self.task == "image-classification":
        return OrderedDict([("logits", {0: "batch"})]      )
       else:
        return OrderedDict([("last_hidden_state", {0: "batch"}), ("pooler_output", {0: "batch"})]      )







      @property
      def 	UpperCAmelCase_						(			self   :List[str]      )     ->			float:
       return 1e-4











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


_lowerCAmelCase						:   Union[str, Any]		=   logging.get_logger(__name__)

_lowerCAmelCase						:   Tuple		=   {
    "CarlCochet/trajectory-transformer-halfcheetah-medium-v2": (
        "https://huggingface.co/CarlCochet/trajectory-transformer-halfcheetah-medium-v2/resolve/main/config.json"
    ),
    # See all TrajectoryTransformer models at https://huggingface.co/models?filter=trajectory_transformer
}
class 			_UpperCamelCase      (				lowerCAmelCase		):
      UpperCAmelCase_        =		"""trajectory_transformer"""
      UpperCAmelCase_        =		["""past_key_values"""]
      UpperCAmelCase_        =		{
          """hidden_size""": """n_embd""",
          """num_attention_heads""": """n_head""",
          """num_hidden_layers""": """n_layer""",
      }
      def __init__(			self   :Union[str, Any] ,      lowerCamelCase   :Optional[int]=100 ,      lowerCamelCase   :Optional[int]=5 ,      lowerCamelCase   :Optional[Any]=1 ,      lowerCamelCase   :Any=1 ,      lowerCamelCase   :int=249 ,      lowerCamelCase   :Optional[Any]=6 ,      lowerCamelCase   :Optional[Any]=17 ,      lowerCamelCase   :Optional[int]=25 ,      lowerCamelCase   :Union[str, Any]=4 ,      lowerCamelCase   :Union[str, Any]=4 ,      lowerCamelCase   :Optional[int]=128 ,      lowerCamelCase   :List[Any]=0.1 ,      lowerCamelCase   :List[str]=0.1 ,      lowerCamelCase   :Tuple=0.1 ,      lowerCamelCase   :Dict=0.00_06 ,      lowerCamelCase   :Dict=512 ,      lowerCamelCase   :Optional[Any]=0.02 ,      lowerCamelCase   :Any=1e-12 ,      lowerCamelCase   :Optional[Any]=1 ,      lowerCamelCase   :List[Any]=True ,      lowerCamelCase   :int=1 ,      lowerCamelCase   :Dict=5_0256 ,      lowerCamelCase   :Union[str, Any]=5_0256 ,      **lowerCamelCase   :int ,      )     ->			Optional[Any]:
       UpperCAmelCase__							 =						vocab_size
       UpperCAmelCase__							 =						action_weight
       UpperCAmelCase__							 =						reward_weight
       UpperCAmelCase__							 =						value_weight
       UpperCAmelCase__							 =						max_position_embeddings
       UpperCAmelCase__							 =						block_size
       UpperCAmelCase__							 =						action_dim
       UpperCAmelCase__							 =						observation_dim
       UpperCAmelCase__							 =						transition_dim
       UpperCAmelCase__							 =						learning_rate
       UpperCAmelCase__							 =						n_layer
       UpperCAmelCase__							 =						n_head
       UpperCAmelCase__							 =						n_embd
       UpperCAmelCase__							 =						embd_pdrop
       UpperCAmelCase__							 =						attn_pdrop
       UpperCAmelCase__							 =						resid_pdrop
       UpperCAmelCase__							 =						initializer_range
       UpperCAmelCase__							 =						layer_norm_eps
       UpperCAmelCase__							 =						kaiming_initializer_range
       UpperCAmelCase__							 =						use_cache
       super().__init__(pad_token_id=lowerCamelCase ,      bos_token_id=lowerCamelCase ,      eos_token_id=lowerCamelCase ,      **lowerCamelCase      )





