


"""simple docstring"""







from collections import OrderedDict
from typing import Any, List, Mapping, Optional

from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging


lowerCAmelCase__				    =       logging.get_logger(__name__)


lowerCAmelCase__				    =       {
    '''Salesforce/codegen-350M-nl''': '''https://huggingface.co/Salesforce/codegen-350M-nl/resolve/main/config.json''',
    '''Salesforce/codegen-350M-multi''': '''https://huggingface.co/Salesforce/codegen-350M-multi/resolve/main/config.json''',
    '''Salesforce/codegen-350M-mono''': '''https://huggingface.co/Salesforce/codegen-350M-mono/resolve/main/config.json''',
    '''Salesforce/codegen-2B-nl''': '''https://huggingface.co/Salesforce/codegen-2B-nl/resolve/main/config.json''',
    '''Salesforce/codegen-2B-multi''': '''https://huggingface.co/Salesforce/codegen-2B-multi/resolve/main/config.json''',
    '''Salesforce/codegen-2B-mono''': '''https://huggingface.co/Salesforce/codegen-2B-mono/resolve/main/config.json''',
    '''Salesforce/codegen-6B-nl''': '''https://huggingface.co/Salesforce/codegen-6B-nl/resolve/main/config.json''',
    '''Salesforce/codegen-6B-multi''': '''https://huggingface.co/Salesforce/codegen-6B-multi/resolve/main/config.json''',
    '''Salesforce/codegen-6B-mono''': '''https://huggingface.co/Salesforce/codegen-6B-mono/resolve/main/config.json''',
    '''Salesforce/codegen-16B-nl''': '''https://huggingface.co/Salesforce/codegen-16B-nl/resolve/main/config.json''',
    '''Salesforce/codegen-16B-multi''': '''https://huggingface.co/Salesforce/codegen-16B-multi/resolve/main/config.json''',
    '''Salesforce/codegen-16B-mono''': '''https://huggingface.co/Salesforce/codegen-16B-mono/resolve/main/config.json''',
}


class 				SCREAMING_SNAKE_CASE__    (		lowercase    ):
       """simple docstring"""


       a  :    List[Any]       ="codegen"
       a  :    Union[str, Any]       ={
           "max_position_embeddings": "n_positions",
           "hidden_size": "n_embd",
           "num_attention_heads": "n_head",
           "num_hidden_layers": "n_layer",
       }

       def __init__(						self		,					snake_case__=50_400		,					snake_case__=2_048		,					snake_case__=2_048		,					snake_case__=4_096		,					snake_case__=28		,					snake_case__=16		,					snake_case__=64		,					snake_case__=None		,					snake_case__="gelu_new"		,					snake_case__=0.0		,					snake_case__=0.0		,					snake_case__=0.0		,					snake_case__=1e-5		,					snake_case__=0.02		,					snake_case__=True		,					snake_case__=50_256		,					snake_case__=50_256		,					snake_case__=False		,					**snake_case__		,					):






         """simple docstring"""





         lowerCAmelCase					:					Any								=							vocab_size
         lowerCAmelCase					:					Optional[int]								=							n_ctx
         lowerCAmelCase					:					str								=							n_positions
         lowerCAmelCase					:					Optional[int]								=							n_embd
         lowerCAmelCase					:					Optional[int]								=							n_layer
         lowerCAmelCase					:					Optional[int]								=							n_head
         lowerCAmelCase					:					List[Any]								=							n_inner
         lowerCAmelCase					:					Optional[Any]								=							rotary_dim
         lowerCAmelCase					:					str								=							activation_function
         lowerCAmelCase					:					Tuple								=							resid_pdrop
         lowerCAmelCase					:					List[str]								=							embd_pdrop
         lowerCAmelCase					:					Tuple								=							attn_pdrop
         lowerCAmelCase					:					Dict								=							layer_norm_epsilon
         lowerCAmelCase					:					List[Any]								=							initializer_range
         lowerCAmelCase					:					Union[str, Any]								=							use_cache

         lowerCAmelCase					:					Union[str, Any]								=							bos_token_id
         lowerCAmelCase					:					Optional[Any]								=							eos_token_id

         super().__init__(
             bos_token_id=snake_case__		,					eos_token_id=snake_case__		,					tie_word_embeddings=snake_case__		,					**snake_case__						)


class 				SCREAMING_SNAKE_CASE__    (		lowercase    ):
       """simple docstring"""


       def __init__(						self		,					snake_case__		,					snake_case__ = "default"		,					snake_case__ = None		,					snake_case__ = False		,					):






         """simple docstring"""





         super().__init__(snake_case__		,					task=snake_case__		,					patching_specs=snake_case__		,					use_past=snake_case__						)
         if not getattr(self._config		,					"pad_token_id"		,					snake_case__						):
           # TODO: how to do that better?
           lowerCAmelCase					:					Tuple								=							0

       @property
       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					List[str]								=							OrderedDict({"input_ids": {0: "batch", 1: "sequence"}}						)
         if self.use_past:
           self.fill_with_past_key_values_(snake_case__		,					direction="inputs"						)
           lowerCAmelCase					:					Any								=							{0: "batch", 1: "past_sequence + sequence"}
         else:
           lowerCAmelCase					:					Optional[int]								=							{0: "batch", 1: "sequence"}

         return common_inputs

       @property
       def 	lowercase__							(						self						):






         """simple docstring"""





         return self._config.n_layer

       @property
       def 	lowercase__							(						self						):






         """simple docstring"""





         return self._config.n_head

       def 	lowercase__							(						self		,					snake_case__		,					snake_case__ = -1		,					snake_case__ = -1		,					snake_case__ = False		,					snake_case__ = None		,					):






         """simple docstring"""





         lowerCAmelCase					:					Optional[int]								=							super(snake_case__		,					self						).generate_dummy_inputs(
             snake_case__		,					batch_size=snake_case__		,					seq_length=snake_case__		,					is_pair=snake_case__		,					framework=snake_case__						)

         # We need to order the input in the way they appears in the forward()
         lowerCAmelCase					:					List[str]								=							OrderedDict({"input_ids": common_inputs["input_ids"]}						)

         # Need to add the past_keys
         if self.use_past:
           if not is_torch_available():
             raise ValueError("Cannot generate dummy past_keys inputs without PyTorch installed."						)
           else:
             import torch

             lowerCAmelCase						,  lowerCAmelCase					:					Union[str, Any]								=							common_inputs["input_ids"].shape
             # Not using the same length for past_key_values
             lowerCAmelCase					:					Dict								=							seqlen + 2
             lowerCAmelCase					:					int								=							(
                 batch,
                 self.num_attention_heads,
                 past_key_values_length,
                 self._config.hidden_size // self.num_attention_heads,
             )
             lowerCAmelCase					:					Any								=							[
                 (torch.zeros(snake_case__						), torch.zeros(snake_case__						)) for _ in range(self.num_layers						)
             ]

         lowerCAmelCase					:					str								=							common_inputs["attention_mask"]
         if self.use_past:
           lowerCAmelCase					:					List[str]								=							ordered_inputs["attention_mask"].dtype
           lowerCAmelCase					:					Tuple								=							torch.cat(
               [ordered_inputs["attention_mask"], torch.ones(snake_case__		,					snake_case__		,					dtype=snake_case__						)]		,					dim=1						)

         return ordered_inputs







       @property
       def 	lowercase__							(						self						):






         """simple docstring"""





         return 13









"""simple docstring"""







from typing import Any


class 				SCREAMING_SNAKE_CASE__    :
       """simple docstring"""


       def __init__(						self		,					snake_case__						):






         """simple docstring"""





         lowerCAmelCase					:					Optional[Any]								=							data
         lowerCAmelCase					:					Tuple								=							None


class 				SCREAMING_SNAKE_CASE__    :
       """simple docstring"""


       def __init__(						self						):






         """simple docstring"""





         lowerCAmelCase					:					Optional[int]								=							None

       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					Optional[Any]								=							self.head
         while temp is not None:
           print(temp.data		,					end=" "						)
           lowerCAmelCase					:					List[str]								=							temp.next
         print()

       def 	lowercase__							(						self		,					snake_case__						):






         """simple docstring"""





         lowerCAmelCase					:					int								=							Node(snake_case__						)
         lowerCAmelCase					:					Union[str, Any]								=							self.head
         lowerCAmelCase					:					Optional[Any]								=							new_node







       def 	lowercase__							(						self		,					snake_case__		,					snake_case__						):






         """simple docstring"""





         if node_data_a == node_data_a:
           return
         else:
           lowerCAmelCase					:					str								=							self.head
           while node_a is not None and node_a.data != node_data_a:
             lowerCAmelCase					:					Union[str, Any]								=							node_a.next

           lowerCAmelCase					:					Any								=							self.head
           while node_a is not None and node_a.data != node_data_a:
             lowerCAmelCase					:					List[Any]								=							node_a.next

           if node_a is None or node_a is None:
             return

           lowerCAmelCase						,  lowerCAmelCase					:					str								=							node_a.data, node_a.data


if __name__ == "__main__":
     lowerCAmelCase__				    =       LinkedList()
     for i in range(5, 0, -1):
          ll.push(i)

     ll.print_list()

     ll.swap_nodes(1, 4)
     print('''After swapping''')
     ll.print_list()





