
"""simple docstring"""




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


_A			:       Any   		=       logging.get_logger(__name__)

_A			:       Union[str, Any]   		=       {
    """google/realm-cc-news-pretrained-embedder""": (
        """https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/config.json"""
    ),
    """google/realm-cc-news-pretrained-encoder""": (
        """https://huggingface.co/google/realm-cc-news-pretrained-encoder/resolve/main/config.json"""
    ),
    """google/realm-cc-news-pretrained-scorer""": (
        """https://huggingface.co/google/realm-cc-news-pretrained-scorer/resolve/main/config.json"""
    ),
    """google/realm-cc-news-pretrained-openqa""": (
        """https://huggingface.co/google/realm-cc-news-pretrained-openqa/aresolve/main/config.json"""
    ),
    """google/realm-orqa-nq-openqa""": """https://huggingface.co/google/realm-orqa-nq-openqa/resolve/main/config.json""",
    """google/realm-orqa-nq-reader""": """https://huggingface.co/google/realm-orqa-nq-reader/resolve/main/config.json""",
    """google/realm-orqa-wq-openqa""": """https://huggingface.co/google/realm-orqa-wq-openqa/resolve/main/config.json""",
    """google/realm-orqa-wq-reader""": """https://huggingface.co/google/realm-orqa-wq-reader/resolve/main/config.json""",
    # See all REALM models at https://huggingface.co/models?filter=realm
}

class 		a__						(      a_						):
   __lowerCAmelCase            =				"""realm"""
   def __init__(			self	,    _a=30_522	,    _a=768	,    _a=128	,    _a=12	,    _a=12	,    _a=8	,    _a=3_072	,    _a="gelu_new"	,    _a=0.1	,    _a=0.1	,    _a=512	,    _a=2	,    _a=0.0_2	,    _a=1E-12	,    _a=256	,    _a=10	,    _a=1E-3	,    _a=5	,    _a=320	,    _a=13_353_718	,    _a=5_000	,    _a=1	,    _a=0	,    _a=2	,    **_a	,    ):
          super().__init__(pad_token_id=_a	,    bos_token_id=_a	,    eos_token_id=_a	,    **_a				)

          # Common config
          lowercase    :				Optional[Any]       		=							vocab_size
          lowercase    :				Union[str, Any]       		=							max_position_embeddings
          lowercase    :				str       		=							hidden_size
          lowercase    :				Optional[int]       		=							retriever_proj_size
          lowercase    :				List[str]       		=							num_hidden_layers
          lowercase    :				Any       		=							num_attention_heads
          lowercase    :				Optional[int]       		=							num_candidates
          lowercase    :				Optional[int]       		=							intermediate_size
          lowercase    :				Tuple       		=							hidden_act
          lowercase    :				Any       		=							hidden_dropout_prob
          lowercase    :				str       		=							attention_probs_dropout_prob
          lowercase    :				Optional[int]       		=							initializer_range
          lowercase    :				Optional[int]       		=							type_vocab_size
          lowercase    :				str       		=							layer_norm_eps

          # Reader config
          lowercase    :				List[str]       		=							span_hidden_size
          lowercase    :				Tuple       		=							max_span_width
          lowercase    :				Union[str, Any]       		=							reader_layer_norm_eps
          lowercase    :				Tuple       		=							reader_beam_size
          lowercase    :				Tuple       		=							reader_seq_len

          # Retrieval config
          lowercase    :				Optional[Any]       		=							num_block_records
          lowercase    :				Optional[int]       		=							searcher_beam_size




"""simple docstring"""




import os
import unittest

from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow

from ...test_tokenization_common import TokenizerTesterMixin

@require_jieba
class 		a__						(      a_,			unittest.TestCase						):
   __lowerCAmelCase            =				CpmAntTokenizer
   __lowerCAmelCase            =				False
   def 			__magic_name__			(			self				):
          super().setUp()

          lowercase    :				List[str]       		=							[
              "<d>",
              "</d>",
              "<s>",
              "</s>",
              "</_>",
              "<unk>",
              "<pad>",
              "</n>",
              "我",
              "是",
              "C",
              "P",
              "M",
              "A",
              "n",
              "t",
          ]
          lowercase    :				Dict       		=							os.path.join(self.tmpdirname	,    VOCAB_FILES_NAMES["vocab_file"]				)
          with open(self.vocab_file	,    "w"	,    encoding="utf-8"				) as vocab_writer:
                 vocab_writer.write("".join([x + "\n" for x in vocab_tokens]				)				)

   @tooslow
   def 			__magic_name__			(			self				):
          lowercase    :				Tuple       		=							CpmAntTokenizer.from_pretrained("openbmb/cpm-ant-10b"				)
          lowercase    :				str       		=							"今天天气真好！"
          lowercase    :				Optional[int]       		=							["今天", "天气", "真", "好", "！"]
          lowercase    :				int       		=							tokenizer.tokenize(_a				)
          self.assertListEqual(_a	,    _a				)
          lowercase    :				Any       		=							"今天天气真好！"
          lowercase    :				int       		=							[tokenizer.bos_token] + tokens

          lowercase    :				List[str]       		=							[6, 9_802, 14_962, 2_082, 831, 244]
          self.assertListEqual(tokenizer.convert_tokens_to_ids(_a				)	,    _a				)

          lowercase    :				str       		=							tokenizer.decode(_a				)
          self.assertEqual(_a	,    _a				)


