'''simple docstring'''
import random
import unittest

import numpy as np

import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax


if is_flax_available():
  import os

  import jax.numpy as jnp
  from jax import jit

  from transformers import AutoTokenizer, FlaxAutoModelForCausalLM
  from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pytorch_model

  a=  '''0.12'''  # assumed parallelism: 8


if is_torch_available():
  import torch







def  _UpperCamelCase (     _a	:	int				,     _a	:	List[str]				,     _a	:	List[str]=None			):




    """simple docstring"""



    if rng is None:
        __UpperCamelCase	:	Optional[int]		    =  random.Random()

    __UpperCamelCase	:	List[str]		    =  1
    for dim in shape:
        total_dims *= dim

    __UpperCamelCase	:	Optional[Any]		    =  []
    for _ in range(_a			):
        values.append(rng.randint(0				,     vocab_size - 1			)			)

    __UpperCamelCase	:	Dict		    =  np.array(_a				,     dtype=jnp.intaa			).reshape(_a			)

    return output







def  _UpperCamelCase (     _a	:	int				,     _a	:	Tuple=None			):




    """simple docstring"""



    __UpperCamelCase	:	int		    =  ids_tensor(_a				,     vocab_size=2				,     rng=_a			)
    # make sure that at least one token is attended to for each batch
    __UpperCamelCase	:	Dict		    =  1
    return attn_mask






@require_flax
class 			__lowercase		:







     """simple docstring"""






     SCREAMING_SNAKE_CASE__		   =						None
     SCREAMING_SNAKE_CASE__		   =						()







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase    ,					__UpperCamelCase	:	Optional[Any]		    =  self.model_tester.prepare_config_and_inputs_for_common()

         # cut to half length & take max batch_size 3
         __UpperCamelCase	:	int		    =  2
         __UpperCamelCase	:	Optional[Any]		    =  inputs['input_ids'].shape[-1] // 2
         __UpperCamelCase	:	Optional[Any]		    =  inputs['input_ids'][:max_batch_size, :sequence_length]

         __UpperCamelCase	:	int		    =  jnp.ones_like(_lowerCamelCase    )
         __UpperCamelCase	:	Optional[int]		    =  attention_mask[:max_batch_size, :sequence_length]

         # generate max 5 tokens
         __UpperCamelCase	:	List[Any]		    =  input_ids.shape[-1] + 5
         if config.eos_token_id is not None and config.pad_token_id is None:
             # hack to allow generate for models such as GPT2 as is done in `generate()`
             __UpperCamelCase	:	Dict		    =  config.eos_token_id
         return config, input_ids, attention_mask, max_length







     @is_pt_flax_cross_test
     def lowerCAmelCase     (		self    ):
         __UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase	:	Optional[Any]		    =  self._get_input_ids_and_config()
         __UpperCamelCase	:	Any		    =  False
         __UpperCamelCase	:	Optional[Any]		    =  max_length
         __UpperCamelCase	:	Tuple		    =  0

         for model_class in self.all_generative_model_classes:
             __UpperCamelCase	:	Tuple		    =  model_class(_lowerCamelCase    )

             __UpperCamelCase	:	Optional[Any]		    =  model_class.__name__[4:]  # Skip the "Flax" at the beginning
             __UpperCamelCase	:	List[Any]		    =  getattr(_lowerCamelCase     ,			_lowerCamelCase    )
             __UpperCamelCase	:	int		    =  pt_model_class(_lowerCamelCase    ).eval()
             __UpperCamelCase	:	int		    =  load_flax_weights_in_pytorch_model(_lowerCamelCase     ,			flax_model.params    )

             __UpperCamelCase	:	Tuple		    =  flax_model.generate(_lowerCamelCase    ).sequences
             __UpperCamelCase	:	Any		    =  pt_model.generate(torch.tensor(_lowerCamelCase     ,			dtype=torch.long    )    )

             if flax_generation_outputs.shape[-1] > pt_generation_outputs.shape[-1]:
                 __UpperCamelCase	:	Optional[Any]		    =  flax_generation_outputs[:, : pt_generation_outputs.shape[-1]]

             self.assertListEqual(pt_generation_outputs.numpy().tolist()     ,			flax_generation_outputs.tolist()    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase	:	List[Any]		    =  self._get_input_ids_and_config()
         __UpperCamelCase	:	Dict		    =  False
         __UpperCamelCase	:	Union[str, Any]		    =  max_length

         for model_class in self.all_generative_model_classes:
             __UpperCamelCase	:	Any		    =  model_class(_lowerCamelCase    )

             __UpperCamelCase	:	List[str]		    =  model.generate(_lowerCamelCase    ).sequences
             self.assertEqual(generation_outputs.shape[-1]     ,			_lowerCamelCase    )

             __UpperCamelCase	:	List[str]		    =  jit(model.generate    )
             __UpperCamelCase	:	Union[str, Any]		    =  jit_generate(_lowerCamelCase    ).sequences

             self.assertListEqual(generation_outputs.tolist()     ,			jit_generation_outputs.tolist()    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase	:	Tuple		    =  self._get_input_ids_and_config()
         __UpperCamelCase	:	Dict		    =  True
         __UpperCamelCase	:	List[str]		    =  max_length

         for model_class in self.all_generative_model_classes:
             __UpperCamelCase	:	List[Any]		    =  model_class(_lowerCamelCase    )

             __UpperCamelCase	:	Dict		    =  model.generate(_lowerCamelCase    ).sequences
             self.assertEqual(generation_outputs.shape[-1]     ,			_lowerCamelCase    )

             __UpperCamelCase	:	Tuple		    =  jit(model.generate    )
             __UpperCamelCase	:	List[Any]		    =  jit_generate(_lowerCamelCase    ).sequences

             self.assertListEqual(generation_outputs.tolist()     ,			jit_generation_outputs.tolist()    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase	:	Any		    =  self._get_input_ids_and_config()
         __UpperCamelCase	:	Any		    =  False
         __UpperCamelCase	:	List[Any]		    =  max_length
         __UpperCamelCase	:	Union[str, Any]		    =  2

         for model_class in self.all_generative_model_classes:
             __UpperCamelCase	:	Any		    =  model_class(_lowerCamelCase    )

             __UpperCamelCase	:	str		    =  model.generate(_lowerCamelCase    ).sequences
             self.assertEqual(generation_outputs.shape[-1]     ,			_lowerCamelCase    )

             __UpperCamelCase	:	List[Any]		    =  jit(model.generate    )
             __UpperCamelCase	:	Union[str, Any]		    =  jit_generate(_lowerCamelCase    ).sequences

             self.assertListEqual(generation_outputs.tolist()     ,			jit_generation_outputs.tolist()    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase	:	str		    =  self._get_input_ids_and_config()
         __UpperCamelCase	:	List[Any]		    =  False
         __UpperCamelCase	:	List[Any]		    =  max_length
         __UpperCamelCase	:	Tuple		    =  2
         __UpperCamelCase	:	List[Any]		    =  2

         for model_class in self.all_generative_model_classes:
             __UpperCamelCase	:	List[str]		    =  model_class(_lowerCamelCase    )

             __UpperCamelCase	:	int		    =  model.generate(_lowerCamelCase    ).sequences
             self.assertEqual(generation_outputs.shape[0]     ,			input_ids.shape[0] * config.num_return_sequences    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase	:	Any		    =  self._get_input_ids_and_config()
         __UpperCamelCase	:	List[str]		    =  True
         __UpperCamelCase	:	int		    =  max_length
         __UpperCamelCase	:	str		    =  0.8
         __UpperCamelCase	:	List[Any]		    =  1_0
         __UpperCamelCase	:	Tuple		    =  0.3
         __UpperCamelCase	:	Any		    =  1
         __UpperCamelCase	:	Tuple		    =  8
         __UpperCamelCase	:	str		    =  9

         for model_class in self.all_generative_model_classes:
             __UpperCamelCase	:	str		    =  model_class(_lowerCamelCase    )

             __UpperCamelCase	:	int		    =  model.generate(_lowerCamelCase    ).sequences
             self.assertEqual(generation_outputs.shape[-1]     ,			_lowerCamelCase    )

             __UpperCamelCase	:	str		    =  jit(model.generate    )
             __UpperCamelCase	:	List[str]		    =  jit_generate(_lowerCamelCase    ).sequences

             self.assertListEqual(generation_outputs.tolist()     ,			jit_generation_outputs.tolist()    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase	:	Tuple		    =  self._get_input_ids_and_config()
         __UpperCamelCase	:	Union[str, Any]		    =  max_length
         __UpperCamelCase	:	Union[str, Any]		    =  1
         __UpperCamelCase	:	List[str]		    =  8
         __UpperCamelCase	:	Optional[Any]		    =  9

         for model_class in self.all_generative_model_classes:
             __UpperCamelCase	:	Optional[Any]		    =  model_class(_lowerCamelCase    )

             __UpperCamelCase	:	str		    =  model.generate(_lowerCamelCase    ).sequences
             self.assertEqual(generation_outputs.shape[-1]     ,			_lowerCamelCase    )

             __UpperCamelCase	:	int		    =  jit(model.generate    )
             __UpperCamelCase	:	List[Any]		    =  jit_generate(_lowerCamelCase    ).sequences

             self.assertListEqual(generation_outputs.tolist()     ,			jit_generation_outputs.tolist()    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase	:	Optional[int]		    =  self._get_input_ids_and_config()
         __UpperCamelCase	:	int		    =  max_length
         __UpperCamelCase	:	List[Any]		    =  2
         __UpperCamelCase	:	Dict		    =  1
         __UpperCamelCase	:	str		    =  8
         __UpperCamelCase	:	Dict		    =  9

         for model_class in self.all_generative_model_classes:
             __UpperCamelCase	:	int		    =  model_class(_lowerCamelCase    )

             __UpperCamelCase	:	str		    =  model.generate(_lowerCamelCase    ).sequences
             self.assertEqual(generation_outputs.shape[-1]     ,			_lowerCamelCase    )

             __UpperCamelCase	:	Union[str, Any]		    =  jit(model.generate    )
             __UpperCamelCase	:	str		    =  jit_generate(_lowerCamelCase    ).sequences

             self.assertListEqual(generation_outputs.tolist()     ,			jit_generation_outputs.tolist()    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase	:	Any		    =  self._get_input_ids_and_config()

         # pad attention mask on the left
         __UpperCamelCase	:	int		    =  attention_mask.at[(0, 0)].set(0    )

         __UpperCamelCase	:	List[Any]		    =  False
         __UpperCamelCase	:	List[Any]		    =  max_length

         for model_class in self.all_generative_model_classes:
             __UpperCamelCase	:	Optional[Any]		    =  model_class(_lowerCamelCase    )

             __UpperCamelCase	:	Dict		    =  model.generate(_lowerCamelCase     ,			attention_mask=_lowerCamelCase    ).sequences
             self.assertEqual(generation_outputs.shape[-1]     ,			_lowerCamelCase    )

             __UpperCamelCase	:	List[Any]		    =  jit(model.generate    )
             __UpperCamelCase	:	Optional[Any]		    =  jit_generate(_lowerCamelCase     ,			attention_mask=_lowerCamelCase    ).sequences

             self.assertListEqual(generation_outputs.tolist()     ,			jit_generation_outputs.tolist()    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase	:	List[Any]		    =  self._get_input_ids_and_config()

         # pad attention mask on the left
         __UpperCamelCase	:	Tuple		    =  attention_mask.at[(0, 0)].set(0    )

         __UpperCamelCase	:	List[Any]		    =  True
         __UpperCamelCase	:	Optional[int]		    =  max_length

         for model_class in self.all_generative_model_classes:
             __UpperCamelCase	:	Optional[int]		    =  model_class(_lowerCamelCase    )

             __UpperCamelCase	:	str		    =  model.generate(_lowerCamelCase     ,			attention_mask=_lowerCamelCase    ).sequences
             self.assertEqual(generation_outputs.shape[-1]     ,			_lowerCamelCase    )

             __UpperCamelCase	:	int		    =  jit(model.generate    )
             __UpperCamelCase	:	Optional[int]		    =  jit_generate(_lowerCamelCase     ,			attention_mask=_lowerCamelCase    ).sequences

             self.assertListEqual(generation_outputs.tolist()     ,			jit_generation_outputs.tolist()    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase	:	Dict		    =  self._get_input_ids_and_config()

         # pad attention mask on the left
         __UpperCamelCase	:	Dict		    =  attention_mask.at[(0, 0)].set(0    )

         __UpperCamelCase	:	List[str]		    =  2
         __UpperCamelCase	:	Optional[int]		    =  max_length

         for model_class in self.all_generative_model_classes:
             __UpperCamelCase	:	int		    =  model_class(_lowerCamelCase    )

             __UpperCamelCase	:	Tuple		    =  model.generate(_lowerCamelCase     ,			attention_mask=_lowerCamelCase    ).sequences
             self.assertEqual(generation_outputs.shape[-1]     ,			_lowerCamelCase    )

             __UpperCamelCase	:	Optional[Any]		    =  jit(model.generate    )
             __UpperCamelCase	:	List[str]		    =  jit_generate(_lowerCamelCase     ,			attention_mask=_lowerCamelCase    ).sequences

             self.assertListEqual(generation_outputs.tolist()     ,			jit_generation_outputs.tolist()    )






@require_flax
class 			__lowercase		(						unittest.TestCase						):







     """simple docstring"""






     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Union[str, Any]		    =  AutoTokenizer.from_pretrained('hf-internal-testing/tiny-bert'    )
         __UpperCamelCase	:	Union[str, Any]		    =  FlaxAutoModelForCausalLM.from_pretrained('hf-internal-testing/tiny-bert-flax-only'    )

         __UpperCamelCase	:	List[Any]		    =  'Hello world'
         __UpperCamelCase	:	Optional[int]		    =  tokenizer(_lowerCamelCase     ,			return_tensors='np'    ).input_ids

         # typos are quickly detected (the correct argument is `do_sample`)
         with self.assertRaisesRegex(_lowerCamelCase     ,			'do_samples'    ):
             model.generate(_lowerCamelCase     ,			do_samples=_lowerCamelCase    )

         # arbitrary arguments that will not be used anywhere are also not accepted
         with self.assertRaisesRegex(_lowerCamelCase     ,			'foo'    ):
             __UpperCamelCase	:	int		    =  {'foo': 'bar'}
             model.generate(_lowerCamelCase     ,			**_lowerCamelCase    )




'''simple docstring'''
class 			__lowercase		:







     """simple docstring"""






     def __init__(		self    ):
         __UpperCamelCase	:	Any		    =  0
         __UpperCamelCase	:	Any		    =  0
         __UpperCamelCase	:	Any		    =  {}







     def lowerCAmelCase     (		self     ,			_lowerCamelCase    ):
         if vertex not in self.adjacency:
             __UpperCamelCase	:	Tuple		    =  {}
             self.num_vertices += 1







     def lowerCAmelCase     (		self     ,			_lowerCamelCase     ,			_lowerCamelCase     ,			_lowerCamelCase    ):
         self.add_vertex(_lowerCamelCase    )
         self.add_vertex(_lowerCamelCase    )

         if head == tail:
             return

         __UpperCamelCase	:	List[Any]		    =  weight
         __UpperCamelCase	:	Optional[int]		    =  weight







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	List[str]		    =  self.get_edges()
         for edge in edges:
             __UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase	:	Optional[int]		    =  edge
             edges.remove((tail, head, weight)    )
         for i in range(len(_lowerCamelCase    )    ):
             __UpperCamelCase	:	Union[str, Any]		    =  list(edges[i]    )

         edges.sort(key=lambda _lowerCamelCase    : e[2]    )
         for i in range(len(_lowerCamelCase    ) - 1    ):
             if edges[i][2] >= edges[i + 1][2]:
                 __UpperCamelCase	:	Optional[int]		    =  edges[i][2] + 1
         for edge in edges:
             __UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase	:	Optional[int]		    =  edge
             __UpperCamelCase	:	Tuple		    =  weight
             __UpperCamelCase	:	Optional[Any]		    =  weight







     def __str__(		self    ):
         __UpperCamelCase	:	Optional[Any]		    =  ''
         for tail in self.adjacency:
             for head in self.adjacency[tail]:
                 __UpperCamelCase	:	Tuple		    =  self.adjacency[head][tail]
                 string += f"""{head} -> {tail} == {weight}\n"""
         return string.rstrip('\n'    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Any		    =  []
         for tail in self.adjacency:
             for head in self.adjacency[tail]:
                 output.append((tail, head, self.adjacency[head][tail])    )
         return output







     def lowerCAmelCase     (		self    ):
         return self.adjacency.keys()







     @staticmethod
     def lowerCAmelCase     (		_lowerCamelCase=None     ,			_lowerCamelCase=None    ):
         __UpperCamelCase	:	Tuple		    =  Graph()
         if vertices is None:
             __UpperCamelCase	:	List[Any]		    =  []
         if edges is None:
             __UpperCamelCase	:	Optional[int]		    =  []
         for vertex in vertices:
             g.add_vertex(_lowerCamelCase    )
         for edge in edges:
             g.add_edge(*_lowerCamelCase    )
         return g






     class 			__lowercase		:







          """simple docstring"""






          def __init__(		self    ):
              __UpperCamelCase	:	Union[str, Any]		    =  {}
              __UpperCamelCase	:	int		    =  {}







          def __len__(		self    ):
              return len(self.parent    )







          def lowerCAmelCase     (		self     ,			_lowerCamelCase    ):
              if item in self.parent:
                  return self.find(_lowerCamelCase    )

              __UpperCamelCase	:	Optional[Any]		    =  item
              __UpperCamelCase	:	List[str]		    =  0
              return item







          def lowerCAmelCase     (		self     ,			_lowerCamelCase    ):
              if item not in self.parent:
                  return self.make_set(_lowerCamelCase    )
              if item != self.parent[item]:
                  __UpperCamelCase	:	int		    =  self.find(self.parent[item]    )
              return self.parent[item]







          def lowerCAmelCase     (		self     ,			_lowerCamelCase     ,			_lowerCamelCase    ):
              __UpperCamelCase	:	Tuple		    =  self.find(_lowerCamelCase    )
              __UpperCamelCase	:	Any		    =  self.find(_lowerCamelCase    )

              if roota == roota:
                  return roota

              if self.rank[roota] > self.rank[roota]:
                  __UpperCamelCase	:	Dict		    =  roota
                  return roota

              if self.rank[roota] < self.rank[roota]:
                  __UpperCamelCase	:	Optional[Any]		    =  roota
                  return roota

              if self.rank[roota] == self.rank[roota]:
                  self.rank[roota] += 1
                  __UpperCamelCase	:	Dict		    =  roota
                  return roota
              return None







     @staticmethod
     def lowerCAmelCase     (		_lowerCamelCase    ):
         __UpperCamelCase	:	int		    =  graph.num_vertices

         __UpperCamelCase	:	str		    =  Graph.UnionFind()
         __UpperCamelCase	:	Tuple		    =  []
         while num_components > 1:
             __UpperCamelCase	:	Dict		    =  {}
             for vertex in graph.get_vertices():
                 __UpperCamelCase	:	str		    =  -1

             __UpperCamelCase	:	int		    =  graph.get_edges()
             for edge in edges:
                 __UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase	:	List[str]		    =  edge
                 edges.remove((tail, head, weight)    )
             for edge in edges:
                 __UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase	:	Dict		    =  edge
                 __UpperCamelCase	:	List[Any]		    =  union_find.find(_lowerCamelCase    )
                 __UpperCamelCase	:	str		    =  union_find.find(_lowerCamelCase    )
                 if seta != seta:
                     if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
                         __UpperCamelCase	:	str		    =  [head, tail, weight]

                     if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
                         __UpperCamelCase	:	str		    =  [head, tail, weight]
             for vertex in cheap_edge:
                 if cheap_edge[vertex] != -1:
                     __UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase	:	List[str]		    =  cheap_edge[vertex]
                     if union_find.find(_lowerCamelCase    ) != union_find.find(_lowerCamelCase    ):
                         union_find.union(_lowerCamelCase     ,			_lowerCamelCase    )
                         mst_edges.append(cheap_edge[vertex]    )
                         __UpperCamelCase	:	int		    =  num_components - 1
         __UpperCamelCase	:	Union[str, Any]		    =  Graph.build(edges=_lowerCamelCase    )
         return mst



