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

from packaging import version


if TYPE_CHECKING:
  from ... import PreTrainedTokenizer, TensorType

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


a=  logging.get_logger(__name__)

a=  {
    "bigscience/bloom": "https://huggingface.co/bigscience/bloom/resolve/main/config.json",
    "bigscience/bloom-560m": "https://huggingface.co/bigscience/bloom-560m/blob/main/config.json",
    "bigscience/bloom-1b1": "https://huggingface.co/bigscience/bloom-1b1/blob/main/config.json",
    "bigscience/bloom-1b7": "https://huggingface.co/bigscience/bloom-1b7/blob/main/config.json",
    "bigscience/bloom-3b": "https://huggingface.co/bigscience/bloom-3b/blob/main/config.json",
    "bigscience/bloom-7b1": "https://huggingface.co/bigscience/bloom-7b1/blob/main/config.json",
}






class 			__lowercase		(						lowercase__						):







     """simple docstring"""






     SCREAMING_SNAKE_CASE__		   =						'''bloom'''
     SCREAMING_SNAKE_CASE__		   =						['''past_key_values''']
     SCREAMING_SNAKE_CASE__		   =						{
         '''num_hidden_layers''': '''n_layer''',
         '''num_attention_heads''': '''n_head''',
     }







     def __init__(		self     ,			_lowerCamelCase=2_5_0_8_8_0     ,			_lowerCamelCase=6_4     ,			_lowerCamelCase=2     ,			_lowerCamelCase=8     ,			_lowerCamelCase=1E-5     ,			_lowerCamelCase=0.0_2     ,			_lowerCamelCase=True     ,			_lowerCamelCase=1     ,			_lowerCamelCase=2     ,			_lowerCamelCase=False     ,			_lowerCamelCase=0.0     ,			_lowerCamelCase=0.0     ,			_lowerCamelCase=1     ,			_lowerCamelCase=False     ,			**_lowerCamelCase     ,			):
         __UpperCamelCase	:	Any		    =  vocab_size
         # Backward compatibility with n_embed kwarg
         __UpperCamelCase	:	List[str]		    =  kwargs.pop('n_embed'     ,			_lowerCamelCase    )
         __UpperCamelCase	:	int		    =  hidden_size if n_embed is None else n_embed
         __UpperCamelCase	:	Optional[Any]		    =  n_layer
         __UpperCamelCase	:	Union[str, Any]		    =  n_head
         __UpperCamelCase	:	int		    =  layer_norm_epsilon
         __UpperCamelCase	:	Union[str, Any]		    =  initializer_range
         __UpperCamelCase	:	Union[str, Any]		    =  use_cache
         __UpperCamelCase	:	List[str]		    =  pretraining_tp
         __UpperCamelCase	:	str		    =  apply_residual_connection_post_layernorm
         __UpperCamelCase	:	Optional[Any]		    =  hidden_dropout
         __UpperCamelCase	:	Tuple		    =  attention_dropout

         __UpperCamelCase	:	List[str]		    =  bos_token_id
         __UpperCamelCase	:	Any		    =  eos_token_id
         __UpperCamelCase	:	Optional[int]		    =  slow_but_exact

         super().__init__(bos_token_id=_lowerCamelCase     ,			eos_token_id=_lowerCamelCase     ,			**_lowerCamelCase    )






class 			__lowercase		(						lowercase__						):







     """simple docstring"""






     SCREAMING_SNAKE_CASE__		   =						version.parse('''1.12'''						)







     def __init__(		self     ,			_lowerCamelCase     ,			_lowerCamelCase = "default"     ,			_lowerCamelCase = None     ,			_lowerCamelCase = False     ,			):
         super().__init__(_lowerCamelCase     ,			task=_lowerCamelCase     ,			patching_specs=_lowerCamelCase     ,			use_past=_lowerCamelCase    )
         if not getattr(self._config     ,			'pad_token_id'     ,			_lowerCamelCase    ):
             # TODO: how to do that better?
             __UpperCamelCase	:	int		    =  0







     @property
     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Tuple		    =  OrderedDict({'input_ids': {0: 'batch', 1: 'sequence'}}    )
         if self.use_past:
             # BLOOM stores values on dynamic axis 2. For more details see: https://github.com/huggingface/transformers/pull/18344
             self.fill_with_past_key_values_(_lowerCamelCase     ,			direction='inputs'     ,			inverted_values_shape=_lowerCamelCase    )
             __UpperCamelCase	:	Tuple		    =  {0: "batch", 1: "past_sequence + sequence"}
         else:
             __UpperCamelCase	:	str		    =  {0: "batch", 1: "sequence"}

         return common_inputs







     @property
     def lowerCAmelCase     (		self    ):
         return self._config.n_layer







     @property
     def lowerCAmelCase     (		self    ):
         return self._config.n_head







     @property
     def lowerCAmelCase     (		self    ):
         return 1E-3







     def lowerCAmelCase     (		self     ,			_lowerCamelCase     ,			_lowerCamelCase = -1     ,			_lowerCamelCase = -1     ,			_lowerCamelCase = False     ,			_lowerCamelCase = None     ,			):
         __UpperCamelCase	:	Optional[int]		    =  super(_lowerCamelCase     ,			self    ).generate_dummy_inputs(
             _lowerCamelCase     ,			batch_size=_lowerCamelCase     ,			seq_length=_lowerCamelCase     ,			is_pair=_lowerCamelCase     ,			framework=_lowerCamelCase    )

         # We need to order the input in the way they appears in the forward()
         __UpperCamelCase	:	Union[str, Any]		    =  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

                 __UpperCamelCase	:	Tuple		    =  common_inputs["input_ids"].shape
                 # Not using the same length for past_key_values
                 __UpperCamelCase	:	str		    =  seqlen + 2
                 __UpperCamelCase	:	int		    =  self._config.hidden_size // self.num_attention_heads
                 __UpperCamelCase	:	List[str]		    =  (
                     batch * self.num_attention_heads,
                     head_dim,
                     past_key_values_length,
                 )
                 __UpperCamelCase	:	List[str]		    =  (
                     batch * self.num_attention_heads,
                     past_key_values_length,
                     head_dim,
                 )
                 __UpperCamelCase	:	List[str]		    =  [
                     (torch.zeros(_lowerCamelCase    ), torch.zeros(_lowerCamelCase    )) for _ in range(self.num_layers    )
                 ]

         __UpperCamelCase	:	Optional[int]		    =  common_inputs["attention_mask"]
         if self.use_past:
             __UpperCamelCase	:	Tuple		    =  ordered_inputs["attention_mask"].dtype
             __UpperCamelCase	:	Optional[int]		    =  torch.cat(
                 [ordered_inputs['attention_mask'], torch.ones(_lowerCamelCase     ,			_lowerCamelCase     ,			dtype=_lowerCamelCase    )]     ,			dim=1    )

         return ordered_inputs







     @property
     def lowerCAmelCase     (		self    ):
         return 1_3




'''simple docstring'''
import unittest

from .lib import (
    Matrix,
    Vector,
    axpy,
    square_zero_matrix,
    unit_basis_vector,
    zero_vector,
)






class 			__lowercase		(						unittest.TestCase						):







     """simple docstring"""






     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Dict		    =  Vector([1, 2, 3]    )
         self.assertEqual(x.component(0    )     ,			1    )
         self.assertEqual(x.component(2    )     ,			3    )
         __UpperCamelCase	:	Dict		    =  Vector()







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	str		    =  Vector([0, 0, 0, 0, 0, 1]    )
         self.assertEqual(str(_lowerCamelCase    )     ,			'(0,0,0,0,0,1)'    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Dict		    =  Vector([1, 2, 3, 4]    )
         self.assertEqual(len(_lowerCamelCase    )     ,			4    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Any		    =  Vector([1, 2]    )
         __UpperCamelCase	:	Optional[int]		    =  Vector([1, 2, 3, 4, 5]    )
         __UpperCamelCase	:	Optional[Any]		    =  Vector([0, 0, 0, 0, 0, 0, 0, 0, 0, 0]    )
         __UpperCamelCase	:	List[str]		    =  Vector([1, -1, 1, -1, 2, -3, 4, -5]    )
         self.assertAlmostEqual(x.euclidean_length()     ,			2.2_3_6     ,			3    )
         self.assertAlmostEqual(y.euclidean_length()     ,			7.4_1_6     ,			3    )
         self.assertEqual(z.euclidean_length()     ,			0    )
         self.assertAlmostEqual(w.euclidean_length()     ,			7.6_1_6     ,			3    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	int		    =  Vector([1, 2, 3]    )
         __UpperCamelCase	:	List[str]		    =  Vector([1, 1, 1]    )
         self.assertEqual((x + y).component(0    )     ,			2    )
         self.assertEqual((x + y).component(1    )     ,			3    )
         self.assertEqual((x + y).component(2    )     ,			4    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Optional[Any]		    =  Vector([1, 2, 3]    )
         __UpperCamelCase	:	Dict		    =  Vector([1, 1, 1]    )
         self.assertEqual((x - y).component(0    )     ,			0    )
         self.assertEqual((x - y).component(1    )     ,			1    )
         self.assertEqual((x - y).component(2    )     ,			2    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Dict		    =  Vector([1, 2, 3]    )
         __UpperCamelCase	:	int		    =  Vector([2, -1, 4]    )  # for test of dot product
         __UpperCamelCase	:	int		    =  Vector([1, -2, -1]    )
         self.assertEqual(str(x * 3.0    )     ,			'(3.0,6.0,9.0)'    )
         self.assertEqual((a * b)     ,			0    )







     def lowerCAmelCase     (		self    ):
         self.assertEqual(str(zero_vector(1_0    )    ).count('0'    )     ,			1_0    )







     def lowerCAmelCase     (		self    ):
         self.assertEqual(str(unit_basis_vector(3     ,			1    )    )     ,			'(0,1,0)'    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Optional[int]		    =  Vector([1, 2, 3]    )
         __UpperCamelCase	:	Union[str, Any]		    =  Vector([1, 0, 1]    )
         self.assertEqual(str(axpy(2     ,			_lowerCamelCase     ,			_lowerCamelCase    )    )     ,			'(3,4,7)'    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	List[str]		    =  Vector([1, 0, 0, 0, 0, 0]    )
         __UpperCamelCase	:	Optional[Any]		    =  x.copy()
         self.assertEqual(str(_lowerCamelCase    )     ,			str(_lowerCamelCase    )    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	List[str]		    =  Vector([1, 0, 0]    )
         x.change_component(0     ,			0    )
         x.change_component(1     ,			1    )
         self.assertEqual(str(_lowerCamelCase    )     ,			'(0,1,0)'    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Tuple		    =  Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]     ,			3     ,			3    )
         self.assertEqual('|1,2,3|\n|2,4,5|\n|6,7,8|\n'     ,			str(_lowerCamelCase    )    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Optional[int]		    =  Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]     ,			3     ,			3    )
         __UpperCamelCase	:	List[str]		    =  [[-3, -1_4, -1_0], [-5, -1_0, -5], [-2, -1, 0]]
         for x in range(a.height()    ):
             for y in range(a.width()    ):
                 self.assertEqual(minors[x][y]     ,			a.minor(_lowerCamelCase     ,			_lowerCamelCase    )    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	int		    =  Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]     ,			3     ,			3    )
         __UpperCamelCase	:	List[str]		    =  [[-3, 1_4, -1_0], [5, -1_0, 5], [-2, 1, 0]]
         for x in range(a.height()    ):
             for y in range(a.width()    ):
                 self.assertEqual(cofactors[x][y]     ,			a.cofactor(_lowerCamelCase     ,			_lowerCamelCase    )    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Any		    =  Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]     ,			3     ,			3    )
         self.assertEqual(-5     ,			a.determinant()    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	int		    =  Matrix([[1, 2, 3], [4, 5, 6], [7, 8, 9]]     ,			3     ,			3    )
         __UpperCamelCase	:	Union[str, Any]		    =  Vector([1, 2, 3]    )
         self.assertEqual('(14,32,50)'     ,			str(a * x    )    )
         self.assertEqual('|2,4,6|\n|8,10,12|\n|14,16,18|\n'     ,			str(a * 2    )    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Union[str, Any]		    =  Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]     ,			3     ,			3    )
         a.change_component(0     ,			2     ,			5    )
         self.assertEqual('|1,2,5|\n|2,4,5|\n|6,7,8|\n'     ,			str(_lowerCamelCase    )    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	int		    =  Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]     ,			3     ,			3    )
         self.assertEqual(7     ,			a.component(2     ,			1    )     ,			0.0_1    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	List[str]		    =  Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]     ,			3     ,			3    )
         __UpperCamelCase	:	Optional[Any]		    =  Matrix([[1, 2, 7], [2, 4, 5], [6, 7, 1_0]]     ,			3     ,			3    )
         self.assertEqual('|2,4,10|\n|4,8,10|\n|12,14,18|\n'     ,			str(a + b    )    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Optional[int]		    =  Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]     ,			3     ,			3    )
         __UpperCamelCase	:	Optional[int]		    =  Matrix([[1, 2, 7], [2, 4, 5], [6, 7, 1_0]]     ,			3     ,			3    )
         self.assertEqual('|0,0,-4|\n|0,0,0|\n|0,0,-2|\n'     ,			str(a - b    )    )







     def lowerCAmelCase     (		self    ):
         self.assertEqual(
             '|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n'     ,			str(square_zero_matrix(5    )    )     ,			)


if __name__ == "__main__":
  unittest.main()



