



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


UpperCAmelCase								=   logging.get_logger(__name__)

UpperCAmelCase								=   {
    """openbmb/cpm-ant-10b""": """https://huggingface.co/openbmb/cpm-ant-10b/blob/main/config.json"""
    # See all CPMAnt models at https://huggingface.co/models?filter=cpmant
}

class 	__snake_case (				SCREAMING_SNAKE_CASE):







							'''simple docstring'''






							UpperCamelCase__			: str             =   """cpmant"""


							def __init__(							self					,					a_ = 30_720					,					a_ = 4_096					,					a_ = 32					,					a_ = 128					,					a_ = 10_240					,					a_ = 48					,					a_ = 0.0					,					a_ = 512					,					a_ = 2_048					,					a_ = 1E-6					,					a_ = 1.0					,					a_ = 32					,					a_ = 32					,					a_ = 32					,					a_ = True					,					**a_					,					):
											super().__init__(**a_						)
											a__			 =						prompt_types
											a__			 =						prompt_length
											a__			 =						segment_types
											a__			 =						hidden_size
											a__			 =						num_attention_heads
											a__			 =						dim_head
											a__			 =						dim_ff
											a__			 =						num_hidden_layers
											a__			 =						position_bias_num_buckets
											a__			 =						position_bias_max_distance
											a__			 =						dropout_p
											a__			 =						eps
											a__			 =						use_cache
											a__			 =						vocab_size
											a__			 =						init_std






import unittest

from transformers import BlenderbotTokenizer, BlenderbotTokenizerFast
from transformers.utils import cached_property

class 	__snake_case (				unittest.TestCase):







							'''simple docstring'''






							@cached_property
							def _a (							self						):
											return BlenderbotTokenizer.from_pretrained("""facebook/blenderbot-3B"""						)


							@cached_property
							def _a (							self						):
											return BlenderbotTokenizerFast.from_pretrained("""facebook/blenderbot-3B"""						)


							def _a (							self						):
											a__			 =						self.tokenizer_ab
											a__			 =						""" I am a small frog."""
											a__			 =						tok([src_text]					,					padding=a_					,					truncation=a_						)["""input_ids"""]
											a__			 =						tok.batch_decode(a_					,					skip_special_tokens=a_					,					clean_up_tokenization_spaces=a_						)[0]
											assert src_text == decoded


							def _a (							self						):
											a__			 =						self.rust_tokenizer_ab
											a__			 =						""" I am a small frog."""
											a__			 =						tok([src_text]					,					padding=a_					,					truncation=a_						)["""input_ids"""]
											a__			 =						tok.batch_decode(a_					,					skip_special_tokens=a_					,					clean_up_tokenization_spaces=a_						)[0]
											assert src_text == decoded


							def _a (							self						):
											assert self.tokenizer_ab.add_prefix_space
											assert self.tokenizer_ab([""" Sam""", """Sam"""]						).input_ids == [[5_502, 2], [5_502, 2]]







							def _a (							self						):
											assert self.rust_tokenizer_ab.add_prefix_space
											assert self.rust_tokenizer_ab([""" Sam""", """Sam"""]						).input_ids == [[5_502, 2], [5_502, 2]]

