from typing import Mapping

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


lowerCAmelCase__  	=      logging.get_logger(__name__)

lowerCAmelCase__  	=      {
    "google/long-t5-local-base": "https://huggingface.co/google/long-t5-local-base/blob/main/config.json",
    "google/long-t5-local-large": "https://huggingface.co/google/long-t5-local-large/blob/main/config.json",
    "google/long-t5-tglobal-base": "https://huggingface.co/google/long-t5-tglobal-base/blob/main/config.json",
    "google/long-t5-tglobal-large": "https://huggingface.co/google/long-t5-tglobal-large/blob/main/config.json",
}
class 	_a  (							lowerCamelCase_					):



	"""simple docstring"""



	__SCREAMING_SNAKE_CASE              =					'longt5'
	__SCREAMING_SNAKE_CASE              =					['past_key_values']
	__SCREAMING_SNAKE_CASE              =					{'hidden_size': 'd_model', 'num_attention_heads': 'num_heads', 'num_hidden_layers': 'num_layers'}


	def __init__(   self       ,  lowerCAmelCase_=32128       ,  lowerCAmelCase_=512       ,  lowerCAmelCase_=64       ,  lowerCAmelCase_=2048       ,  lowerCAmelCase_=6       ,  lowerCAmelCase_=None       ,  lowerCAmelCase_=8       ,  lowerCAmelCase_=127       ,  lowerCAmelCase_=16       ,  lowerCAmelCase_=32       ,  lowerCAmelCase_=128       ,  lowerCAmelCase_=0.1       ,  lowerCAmelCase_=1e-6       ,  lowerCAmelCase_=1.0       ,  lowerCAmelCase_="relu"       ,  lowerCAmelCase_=True       ,  lowerCAmelCase_="local"       ,  lowerCAmelCase_=True       ,  lowerCAmelCase_=0       ,  lowerCAmelCase_=1       ,  **lowerCAmelCase_       ,  ):
		_lowercase   =vocab_size
		_lowercase   =d_model
		_lowercase   =d_kv
		_lowercase   =d_ff
		_lowercase   =num_layers
		# default = symmetry
		_lowercase   =num_decoder_layers if num_decoder_layers is not None else self.num_layers
		_lowercase   =num_heads
		_lowercase   =local_radius
		_lowercase   =global_block_size
		_lowercase   =relative_attention_num_buckets
		_lowercase   =relative_attention_max_distance
		_lowercase   =dropout_rate
		_lowercase   =layer_norm_epsilon
		_lowercase   =initializer_factor
		_lowercase   =feed_forward_proj
		_lowercase   =encoder_attention_type
		_lowercase   =use_cache

		_lowercase   =self.feed_forward_proj.split("-"       )
		_lowercase   =act_info[-1]
		_lowercase   =act_info[0] == "gated"

		if len(lowerCAmelCase_       ) > 1 and act_info[0] != "gated" or len(lowerCAmelCase_       ) > 2:
			raise ValueError(
			    F'''`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer.'''
			    "Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. "
			    "'gated-gelu' or 'relu'"       )

		# for backwards compatibility
		if feed_forward_proj == "gated-gelu":
			_lowercase   ="gelu_new"

		super().__init__(
		    pad_token_id=lowerCAmelCase_       ,  eos_token_id=lowerCAmelCase_       ,  is_encoder_decoder=lowerCAmelCase_       ,  **lowerCAmelCase_       ,  )

class 	_a  (							lowerCamelCase_					):



	"""simple docstring"""



	@property
	def __lowerCAmelCase      (   self       ):
		_lowercase   ={
		    "input_ids": {0: "batch", 1: "encoder_sequence"},
		    "attention_mask": {0: "batch", 1: "encoder_sequence"},
		}
		if self.use_past:
			_lowercase   ="past_encoder_sequence + sequence"
			_lowercase   ={0: "batch"}
			_lowercase   ={0: "batch", 1: "past_decoder_sequence + sequence"}
		else:
			_lowercase   ={0: "batch", 1: "decoder_sequence"}
			_lowercase   ={0: "batch", 1: "decoder_sequence"}

		if self.use_past:
			self.fill_with_past_key_values_(lowerCAmelCase_       ,  direction="inputs"       )

		return common_inputs


	@property
	def __lowerCAmelCase      (   self       ):
		return 13






"""simple docstring"""






import json
import os
import unittest

from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import (
    VOCAB_FILES_NAMES,
    GPTNeoXJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class      _SCREAMING_SNAKE_CASE   (     A__      ,					unittest.TestCase				):
			UpperCAmelCase_    :List[str]												=		GPTNeoXJapaneseTokenizer
			UpperCAmelCase_    :List[str]												=		False
			UpperCAmelCase_    :int												=		{"do_clean_text": False, "add_prefix_space": False}






			def 					__lowerCAmelCase					(   self			)     ->	Optional[Any]:
						super().setUp()

						lowerCAmelCase_       :int     	=    [
						    """こん""",
						    """こんに""",
						    """にちは""",
						    """ばんは""",
						    """世界,㔺界""",
						    """、""",
						    """。""",
						    """<BR>""",
						    """<SP>""",
						    """<TAB>""",
						    """<URL>""",
						    """<EMAIL>""",
						    """<TEL>""",
						    """<DATE>""",
						    """<PRICE>""",
						    """<BLOCK>""",
						    """<KIGOU>""",
						    """<U2000U2BFF>""",
						    """<|emoji1|>""",
						    """<unk>""",
						    """<|startoftext|>""",
						    """<|endoftext|>""",
						]
						lowerCAmelCase_       :str     	=    {"""emoji""": {"""\ud83d\ude00""": """<|emoji1|>"""}, """emoji_inv""": {"""<|emoji1|>""": """\ud83d\ude00"""}}  # 😀
						lowerCAmelCase_       :Dict     	=    {"""unk_token""": """<unk>"""}

						lowerCAmelCase_       :Union[str, Any]     	=    os.path.join(self.tmpdirname			,  VOCAB_FILES_NAMES["""vocab_file"""]			)
						lowerCAmelCase_       :Union[str, Any]     	=    os.path.join(self.tmpdirname			,  VOCAB_FILES_NAMES["""emoji_file"""]			)
						with open(self.vocab_file			,  """w"""			,  encoding="""utf-8"""			) as vocab_writer:
									vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]			)			)
						with open(self.emoji_file			,  """w"""			) as emoji_writer:
									emoji_writer.write(json.dumps(__A			)			)






			def 					__lowerCAmelCase					(   self			,  **__A			)     ->	str:
						kwargs.update(self.special_tokens_map			)
						return GPTNeoXJapaneseTokenizer.from_pretrained(self.tmpdirname			,  **__A			)






			def 					__lowerCAmelCase					(   self			,  __A			)     ->	List[Any]:
						lowerCAmelCase_       :Optional[Any]     	=    """こんにちは、世界。 \nこんばんは、㔺界。😀"""
						lowerCAmelCase_       :List[Any]     	=    """こんにちは、世界。 \nこんばんは、世界。😀"""
						return input_text, output_text






			def 					__lowerCAmelCase					(   self			,  __A			)     ->	Optional[Any]:
						lowerCAmelCase_	,			lowerCAmelCase_       :Optional[int]     	=    self.get_input_output_texts(__A			)
						lowerCAmelCase_       :List[Any]     	=    tokenizer.encode(__A			,  add_special_tokens=__A			)
						lowerCAmelCase_       :Optional[Any]     	=    tokenizer.decode(__A			,  clean_up_tokenization_spaces=__A			)
						return text, ids






			def 					__lowerCAmelCase					(   self			)     ->	str:
						pass  # TODO add if relevant






			def 					__lowerCAmelCase					(   self			)     ->	Any:
						pass  # TODO add if relevant






			def 					__lowerCAmelCase					(   self			)     ->	Optional[int]:
						pass  # TODO add if relevant






			def 					__lowerCAmelCase					(   self			)     ->	Optional[Any]:
						lowerCAmelCase_       :int     	=    self.get_tokenizer()

						# Testing tokenization
						lowerCAmelCase_       :List[str]     	=    """こんにちは、世界。　こんばんは、㔺界。"""
						lowerCAmelCase_       :int     	=    ["""こん""", """にちは""", """、""", """世界""", """。""", """<SP>""", """こん""", """ばんは""", """、""", """㔺界""", """。"""]
						lowerCAmelCase_       :List[Any]     	=    tokenizer.tokenize(__A			)
						self.assertListEqual(__A			,  __A			)

						# Testing conversion to ids without special tokens
						lowerCAmelCase_       :List[str]     	=    [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6]
						lowerCAmelCase_       :Dict     	=    tokenizer.convert_tokens_to_ids(__A			)
						self.assertListEqual(__A			,  __A			)

						# Testing conversion to ids with special tokens
						lowerCAmelCase_       :Tuple     	=    tokens + [tokenizer.unk_token]
						lowerCAmelCase_       :str     	=    [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6, 19]
						lowerCAmelCase_       :Any     	=    tokenizer.convert_tokens_to_ids(__A			)
						self.assertListEqual(__A			,  __A			)






			@slow
			def 					__lowerCAmelCase					(   self			)     ->	Any:
						lowerCAmelCase_       :str     	=    self.tokenizer_class.from_pretrained("""abeja/gpt-neox-japanese-2.7b"""			)

						lowerCAmelCase_       :Union[str, Any]     	=    tokenizer.encode("""ありがとう。"""			,  add_special_tokens=__A			)
						lowerCAmelCase_       :Dict     	=    tokenizer.encode("""どういたしまして。"""			,  add_special_tokens=__A			)

						lowerCAmelCase_       :Union[str, Any]     	=    tokenizer.build_inputs_with_special_tokens(__A			)
						lowerCAmelCase_       :Optional[int]     	=    tokenizer.build_inputs_with_special_tokens(__A			,  __A			)

						assert encoded_sentence == ids_a
						assert encoded_pair == ids_a + ids_a






			def 					__lowerCAmelCase					(   self			)     ->	Dict:
						# Intentionally convert some words to accommodate character fluctuations unique to Japanese
						pass






			def 					__lowerCAmelCase					(   self			)     ->	List[str]:
						# tokenizer has no padding token
						pass






