'''simple docstring'''

import unittest

import numpy as np

from transformers import is_flax_available
from transformers.testing_utils import require_flax

from ..test_modeling_flax_common import ids_tensor


if is_flax_available():
 import jax
 import jax.numpy as jnp

 from transformers.generation import (
     FlaxForcedBOSTokenLogitsProcessor,
     FlaxForcedEOSTokenLogitsProcessor,
     FlaxLogitsProcessorList,
     FlaxMinLengthLogitsProcessor,
     FlaxTemperatureLogitsWarper,
     FlaxTopKLogitsWarper,
     FlaxTopPLogitsWarper,
 )


@require_flax
class     __UpperCAmelCase       ( unittest.TestCase		):





  def 						UpperCAmelCase_	(	self    ,     _lowerCamelCase    ,     _lowerCamelCase ):
     lowerCAmelCase_			=      jnp.ones((batch_size, length) ) / length
     return scores





  def 						UpperCAmelCase_	(	self ):
     lowerCAmelCase_			=      None
     lowerCAmelCase_			=      20

     lowerCAmelCase_			=      self._get_uniform_logits(batch_size=2    ,     length=_lowerCamelCase )

     # tweak scores to not be uniform anymore
     lowerCAmelCase_			=      scores.at[1, 5].set((1 / length) + 0.1 )  # peak, 1st batch
     lowerCAmelCase_			=      scores.at[1, 10].set((1 / length) - 0.4 )  # valley, 1st batch

     # compute softmax
     lowerCAmelCase_			=      jax.nn.softmax(_lowerCamelCase    ,     axis=-1 )

     lowerCAmelCase_			=      FlaxTemperatureLogitsWarper(temperature=0.5 )
     lowerCAmelCase_			=      FlaxTemperatureLogitsWarper(temperature=1.3 )

     lowerCAmelCase_			=      jax.nn.softmax(temp_dist_warper_sharper(_lowerCamelCase    ,     scores.copy()    ,     cur_len=_lowerCamelCase )    ,     axis=-1 )
     lowerCAmelCase_			=      jax.nn.softmax(temp_dist_warper_smoother(_lowerCamelCase    ,     scores.copy()    ,     cur_len=_lowerCamelCase )    ,     axis=-1 )

     # uniform distribution stays uniform
     self.assertTrue(jnp.allclose(probs[0, :]    ,     warped_prob_sharp[0, :]    ,     atol=1E-3 ) )
     self.assertTrue(jnp.allclose(probs[0, :]    ,     warped_prob_smooth[0, :]    ,     atol=1E-3 ) )

     # sharp peaks get higher, valleys get lower
     self.assertLess(probs[1, :].max()    ,     warped_prob_sharp[1, :].max() )
     self.assertGreater(probs[1, :].min()    ,     warped_prob_sharp[1, :].min() )

     # smooth peaks get lower, valleys get higher
     self.assertGreater(probs[1, :].max()    ,     warped_prob_smooth[1, :].max() )
     self.assertLess(probs[1, :].min()    ,     warped_prob_smooth[1, :].min() )





  def 						UpperCAmelCase_	(	self ):
     lowerCAmelCase_			=      None
     lowerCAmelCase_			=      10
     lowerCAmelCase_			=      2

     # create ramp distribution
     lowerCAmelCase_			=      np.broadcast_to(np.arange(_lowerCamelCase )[None, :]    ,     (batch_size, vocab_size) ).copy()
     lowerCAmelCase_			=      ramp_logits[1:, : vocab_size // 2] + vocab_size

     lowerCAmelCase_			=      FlaxTopKLogitsWarper(3 )

     lowerCAmelCase_			=      top_k_warp(_lowerCamelCase    ,     _lowerCamelCase    ,     cur_len=_lowerCamelCase )

     # check that correct tokens are filtered
     self.assertListEqual(jnp.isinf(scores[0] ).tolist()    ,     7 * [True] + 3 * [False] )
     self.assertListEqual(jnp.isinf(scores[1] ).tolist()    ,     2 * [True] + 3 * [False] + 5 * [True] )

     # check special case
     lowerCAmelCase_			=      5
     lowerCAmelCase_			=      FlaxTopKLogitsWarper(top_k=1    ,     filter_value=0.0    ,     min_tokens_to_keep=3 )

     lowerCAmelCase_			=      np.broadcast_to(np.arange(_lowerCamelCase )[None, :]    ,     (batch_size, length) ).copy()
     lowerCAmelCase_			=      top_k_warp_safety_check(_lowerCamelCase    ,     _lowerCamelCase    ,     cur_len=_lowerCamelCase )

     # min_tokens overwrites k: 3 tokens are kept => 2 tokens are nullified
     self.assertListEqual((scores == 0.0).sum(axis=-1 ).tolist()    ,     [2, 2] )





  def 						UpperCAmelCase_	(	self ):
     lowerCAmelCase_			=      None
     lowerCAmelCase_			=      10
     lowerCAmelCase_			=      2

     # create distribution and take log (inverse to Softmax as taken in TopPLogitsWarper)
     lowerCAmelCase_			=      np.log(np.array([[0.3, 0.1, 0.1, 0.5], [0.15, 0.3, 0.3, 0.25]] ) )

     lowerCAmelCase_			=      FlaxTopPLogitsWarper(0.8 )
     lowerCAmelCase_			=      np.exp(top_p_warp(_lowerCamelCase    ,     _lowerCamelCase    ,     cur_len=_lowerCamelCase ) )

     # dist should be filtered to keep min num values so that sum is >= top_p
     # exp (-inf) => 0
     lowerCAmelCase_			=      np.array([[0.3, 0.0, 0.0, 0.5], [0.0, 0.3, 0.3, 0.25]] )
     self.assertTrue(np.allclose(_lowerCamelCase    ,     _lowerCamelCase    ,     atol=1E-3 ) )

     # check edge cases with negative and extreme logits
     lowerCAmelCase_			=      np.broadcast_to(np.arange(_lowerCamelCase )[None, :]    ,     (batch_size, vocab_size) ).copy() - (
         vocab_size // 2
     )

     # make ramp_logits more extreme
     lowerCAmelCase_			=      ramp_logits[1] * 1_00.0

     # make sure at least 2 tokens are kept
     lowerCAmelCase_			=      FlaxTopPLogitsWarper(0.9    ,     min_tokens_to_keep=2    ,     filter_value=0.0 )
     lowerCAmelCase_			=      top_p_warp(_lowerCamelCase    ,     _lowerCamelCase    ,     cur_len=_lowerCamelCase )

     # first batch should keep three tokens, second batch would keep only 1, but due to `min_tokens_to_keep=2` keeps 2.
     self.assertListEqual((filtered_dist != 0.0).sum(axis=-1 ).tolist()    ,     [3, 2] )





  def 						UpperCAmelCase_	(	self ):
     lowerCAmelCase_			=      20
     lowerCAmelCase_			=      4
     lowerCAmelCase_			=      0

     lowerCAmelCase_			=      FlaxMinLengthLogitsProcessor(min_length=10    ,     eos_token_id=_lowerCamelCase )

     # check that min length is applied at length 5
     lowerCAmelCase_			=      ids_tensor((batch_size, 20)    ,     vocab_size=20 )
     lowerCAmelCase_			=      5
     lowerCAmelCase_			=      self._get_uniform_logits(_lowerCamelCase    ,     _lowerCamelCase )
     lowerCAmelCase_			=      min_dist_processor(_lowerCamelCase    ,     _lowerCamelCase    ,     cur_len=_lowerCamelCase )
     self.assertListEqual(scores_before_min_length[:, eos_token_id].tolist()    ,     4 * [-float('''inf''' )] )

     # check that min length is not applied anymore at length 15
     lowerCAmelCase_			=      self._get_uniform_logits(_lowerCamelCase    ,     _lowerCamelCase )
     lowerCAmelCase_			=      15
     lowerCAmelCase_			=      min_dist_processor(_lowerCamelCase    ,     _lowerCamelCase    ,     cur_len=_lowerCamelCase )
     self.assertFalse(jnp.isinf(_lowerCamelCase ).any() )





  def 						UpperCAmelCase_	(	self ):
     lowerCAmelCase_			=      20
     lowerCAmelCase_			=      4
     lowerCAmelCase_			=      0

     lowerCAmelCase_			=      FlaxForcedBOSTokenLogitsProcessor(bos_token_id=_lowerCamelCase )

     # check that all scores are -inf except the bos_token_id score
     lowerCAmelCase_			=      ids_tensor((batch_size, 1)    ,     vocab_size=20 )
     lowerCAmelCase_			=      1
     lowerCAmelCase_			=      self._get_uniform_logits(_lowerCamelCase    ,     _lowerCamelCase )
     lowerCAmelCase_			=      logits_processor(_lowerCamelCase    ,     _lowerCamelCase    ,     cur_len=_lowerCamelCase )
     self.assertTrue(jnp.isneginf(scores[:, bos_token_id + 1 :] ).all() )
     self.assertListEqual(scores[:, bos_token_id].tolist()    ,     4 * [0] )  # score for bos_token_id shold be zero

     # check that bos_token_id is not forced if current length is greater than 1
     lowerCAmelCase_			=      3
     lowerCAmelCase_			=      self._get_uniform_logits(_lowerCamelCase    ,     _lowerCamelCase )
     lowerCAmelCase_			=      logits_processor(_lowerCamelCase    ,     _lowerCamelCase    ,     cur_len=_lowerCamelCase )
     self.assertFalse(jnp.isinf(_lowerCamelCase ).any() )





  def 						UpperCAmelCase_	(	self ):
     lowerCAmelCase_			=      20
     lowerCAmelCase_			=      4
     lowerCAmelCase_			=      0
     lowerCAmelCase_			=      5

     lowerCAmelCase_			=      FlaxForcedEOSTokenLogitsProcessor(max_length=_lowerCamelCase    ,     eos_token_id=_lowerCamelCase )

     # check that all scores are -inf except the eos_token_id when max_length is reached
     lowerCAmelCase_			=      ids_tensor((batch_size, 4)    ,     vocab_size=20 )
     lowerCAmelCase_			=      4
     lowerCAmelCase_			=      self._get_uniform_logits(_lowerCamelCase    ,     _lowerCamelCase )
     lowerCAmelCase_			=      logits_processor(_lowerCamelCase    ,     _lowerCamelCase    ,     cur_len=_lowerCamelCase )
     self.assertTrue(jnp.isneginf(scores[:, eos_token_id + 1 :] ).all() )
     self.assertListEqual(scores[:, eos_token_id].tolist()    ,     4 * [0] )  # score for eos_token_id should be zero

     # check that eos_token_id is not forced if max_length is not reached
     lowerCAmelCase_			=      3
     lowerCAmelCase_			=      self._get_uniform_logits(_lowerCamelCase    ,     _lowerCamelCase )
     lowerCAmelCase_			=      logits_processor(_lowerCamelCase    ,     _lowerCamelCase    ,     cur_len=_lowerCamelCase )
     self.assertFalse(jnp.isinf(_lowerCamelCase ).any() )





  def 						UpperCAmelCase_	(	self ):
     lowerCAmelCase_			=      4
     lowerCAmelCase_			=      10
     lowerCAmelCase_			=      15
     lowerCAmelCase_			=      2
     lowerCAmelCase_			=      1
     lowerCAmelCase_			=      15

     # dummy input_ids and scores
     lowerCAmelCase_			=      ids_tensor((batch_size, sequence_length)    ,     _lowerCamelCase )
     lowerCAmelCase_			=      input_ids.copy()

     lowerCAmelCase_			=      self._get_uniform_logits(_lowerCamelCase    ,     _lowerCamelCase )
     lowerCAmelCase_			=      scores.copy()

     # instantiate all dist processors
     lowerCAmelCase_			=      FlaxTemperatureLogitsWarper(temperature=0.5 )
     lowerCAmelCase_			=      FlaxTopKLogitsWarper(3 )
     lowerCAmelCase_			=      FlaxTopPLogitsWarper(0.8 )

     # instantiate all logits processors
     lowerCAmelCase_			=      FlaxMinLengthLogitsProcessor(min_length=10    ,     eos_token_id=_lowerCamelCase )
     lowerCAmelCase_			=      FlaxForcedBOSTokenLogitsProcessor(bos_token_id=_lowerCamelCase )
     lowerCAmelCase_			=      FlaxForcedEOSTokenLogitsProcessor(max_length=_lowerCamelCase    ,     eos_token_id=_lowerCamelCase )

     lowerCAmelCase_			=      10

     # no processor list
     lowerCAmelCase_			=      temp_dist_warp(_lowerCamelCase    ,     _lowerCamelCase    ,     cur_len=_lowerCamelCase )
     lowerCAmelCase_			=      top_k_warp(_lowerCamelCase    ,     _lowerCamelCase    ,     cur_len=_lowerCamelCase )
     lowerCAmelCase_			=      top_p_warp(_lowerCamelCase    ,     _lowerCamelCase    ,     cur_len=_lowerCamelCase )
     lowerCAmelCase_			=      min_dist_proc(_lowerCamelCase    ,     _lowerCamelCase    ,     cur_len=_lowerCamelCase )
     lowerCAmelCase_			=      bos_dist_proc(_lowerCamelCase    ,     _lowerCamelCase    ,     cur_len=_lowerCamelCase )
     lowerCAmelCase_			=      eos_dist_proc(_lowerCamelCase    ,     _lowerCamelCase    ,     cur_len=_lowerCamelCase )

     # with processor list
     lowerCAmelCase_			=      FlaxLogitsProcessorList(
         [temp_dist_warp, top_k_warp, top_p_warp, min_dist_proc, bos_dist_proc, eos_dist_proc] )
     lowerCAmelCase_			=      processor(_lowerCamelCase    ,     _lowerCamelCase    ,     cur_len=_lowerCamelCase )

     # scores should be equal
     self.assertTrue(jnp.allclose(_lowerCamelCase    ,     _lowerCamelCase    ,     atol=1E-3 ) )

     # input_ids should never be changed
     self.assertListEqual(input_ids.tolist()    ,     input_ids_comp.tolist() )







  def 						UpperCAmelCase_	(	self ):
     lowerCAmelCase_			=      4
     lowerCAmelCase_			=      10
     lowerCAmelCase_			=      15
     lowerCAmelCase_			=      2
     lowerCAmelCase_			=      1
     lowerCAmelCase_			=      15

     # dummy input_ids and scores
     lowerCAmelCase_			=      ids_tensor((batch_size, sequence_length)    ,     _lowerCamelCase )
     lowerCAmelCase_			=      input_ids.copy()

     lowerCAmelCase_			=      self._get_uniform_logits(_lowerCamelCase    ,     _lowerCamelCase )
     lowerCAmelCase_			=      scores.copy()

     # instantiate all dist processors
     lowerCAmelCase_			=      FlaxTemperatureLogitsWarper(temperature=0.5 )
     lowerCAmelCase_			=      FlaxTopKLogitsWarper(3 )
     lowerCAmelCase_			=      FlaxTopPLogitsWarper(0.8 )

     # instantiate all logits processors
     lowerCAmelCase_			=      FlaxMinLengthLogitsProcessor(min_length=10    ,     eos_token_id=_lowerCamelCase )
     lowerCAmelCase_			=      FlaxForcedBOSTokenLogitsProcessor(bos_token_id=_lowerCamelCase )
     lowerCAmelCase_			=      FlaxForcedEOSTokenLogitsProcessor(max_length=_lowerCamelCase    ,     eos_token_id=_lowerCamelCase )

     lowerCAmelCase_			=      10

     # no processor list
     def run_no_processor_list(_lowerCamelCase    ,     _lowerCamelCase    ,     _lowerCamelCase ):
        lowerCAmelCase_			=      temp_dist_warp(_lowerCamelCase    ,     _lowerCamelCase    ,     cur_len=_lowerCamelCase )
        lowerCAmelCase_			=      top_k_warp(_lowerCamelCase    ,     _lowerCamelCase    ,     cur_len=_lowerCamelCase )
        lowerCAmelCase_			=      top_p_warp(_lowerCamelCase    ,     _lowerCamelCase    ,     cur_len=_lowerCamelCase )
        lowerCAmelCase_			=      min_dist_proc(_lowerCamelCase    ,     _lowerCamelCase    ,     cur_len=_lowerCamelCase )
        lowerCAmelCase_			=      bos_dist_proc(_lowerCamelCase    ,     _lowerCamelCase    ,     cur_len=_lowerCamelCase )
        lowerCAmelCase_			=      eos_dist_proc(_lowerCamelCase    ,     _lowerCamelCase    ,     cur_len=_lowerCamelCase )
        return scores

     # with processor list
     def run_processor_list(_lowerCamelCase    ,     _lowerCamelCase    ,     _lowerCamelCase ):
        lowerCAmelCase_			=      FlaxLogitsProcessorList(
            [temp_dist_warp, top_k_warp, top_p_warp, min_dist_proc, bos_dist_proc, eos_dist_proc] )
        lowerCAmelCase_			=      processor(_lowerCamelCase    ,     _lowerCamelCase    ,     cur_len=_lowerCamelCase )
        return scores

     lowerCAmelCase_			=      jax.jit(_lowerCamelCase )
     lowerCAmelCase_			=      jax.jit(_lowerCamelCase )

     lowerCAmelCase_			=      jitted_run_no_processor_list(_lowerCamelCase    ,     _lowerCamelCase    ,     _lowerCamelCase )
     lowerCAmelCase_			=      jitted_run_processor_list(_lowerCamelCase    ,     _lowerCamelCase    ,     _lowerCamelCase )

     # scores should be equal
     self.assertTrue(jnp.allclose(_lowerCamelCase    ,     _lowerCamelCase    ,     atol=1E-3 ) )

     # input_ids should never be changed
     self.assertListEqual(input_ids.tolist()    ,     input_ids_comp.tolist() )






'''simple docstring'''

import contextlib
import importlib
import io
import unittest

import transformers

# Try to import everything from transformers to ensure every object can be loaded.
from transformers import *  # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, require_tf, require_torch
from transformers.utils import ContextManagers, find_labels, is_flax_available, is_tf_available, is_torch_available


if is_torch_available():
 from transformers import BertForPreTraining, BertForQuestionAnswering, BertForSequenceClassification

if is_tf_available():
 from transformers import TFBertForPreTraining, TFBertForQuestionAnswering, TFBertForSequenceClassification

if is_flax_available():
 from transformers import FlaxBertForPreTraining, FlaxBertForQuestionAnswering, FlaxBertForSequenceClassification


A_     :						Optional[Any]    							=DUMMY_UNKNOWN_IDENTIFIER
# An actual model hosted on huggingface.co

A_     :						Tuple    							='''main'''
# Default branch name
A_     :						Dict    							='''f2c752cfc5c0ab6f4bdec59acea69eefbee381c2'''
# One particular commit (not the top of `main`)
A_     :						int    							='''aaaaaaa'''
# This commit does not exist, so we should 404.

A_     :						List[str]    							='''d9e9f15bc825e4b2c9249e9578f884bbcb5e3684'''
# Sha-1 of config.json on the top of `main`, for checking purposes
A_     :						List[str]    							='''4b243c475af8d0a7754e87d7d096c92e5199ec2fe168a2ee7998e3b8e9bcb1d3'''



@contextlib.contextmanager
def snake_case_      (					)			->					Tuple:
   print('''Welcome!''')
   yield
   print('''Bye!''')



@contextlib.contextmanager
def snake_case_      (					)			->					str:
   print('''Bonjour!''')
   yield
   print('''Au revoir!''')


class     __UpperCAmelCase       ( unittest.TestCase		):





  def 						UpperCAmelCase_	(	self ):
     # If the spec is missing, importlib would not be able to import the module dynamically.
     assert transformers.__spec__ is not None
     assert importlib.util.find_spec('''transformers''' ) is not None






class     __UpperCAmelCase       ( unittest.TestCase		):





  @unittest.mock.patch('''sys.stdout'''    ,     new_callable=io.StringIO )
  def 						UpperCAmelCase_	(	self    ,     _lowerCamelCase ):
     with ContextManagers([] ):
        print('''Transformers are awesome!''' )
     # The print statement adds a new line at the end of the output
     self.assertEqual(mock_stdout.getvalue()    ,     '''Transformers are awesome!\n''' )





  @unittest.mock.patch('''sys.stdout'''    ,     new_callable=io.StringIO )
  def 						UpperCAmelCase_	(	self    ,     _lowerCamelCase ):
     with ContextManagers([context_en()] ):
        print('''Transformers are awesome!''' )
     # The output should be wrapped with an English welcome and goodbye
     self.assertEqual(mock_stdout.getvalue()    ,     '''Welcome!\nTransformers are awesome!\nBye!\n''' )





  @unittest.mock.patch('''sys.stdout'''    ,     new_callable=io.StringIO )
  def 						UpperCAmelCase_	(	self    ,     _lowerCamelCase ):
     with ContextManagers([context_fr(), context_en()] ):
        print('''Transformers are awesome!''' )
     # The output should be wrapped with an English and French welcome and goodbye
     self.assertEqual(mock_stdout.getvalue()    ,     '''Bonjour!\nWelcome!\nTransformers are awesome!\nBye!\nAu revoir!\n''' )





  @require_torch
  def 						UpperCAmelCase_	(	self ):
     self.assertEqual(find_labels(_lowerCamelCase )    ,     ['''labels'''] )
     self.assertEqual(find_labels(_lowerCamelCase )    ,     ['''labels''', '''next_sentence_label'''] )
     self.assertEqual(find_labels(_lowerCamelCase )    ,     ['''start_positions''', '''end_positions'''] )


     class     __UpperCAmelCase       ( __a		):
       pass






     self.assertEqual(find_labels(_lowerCamelCase )    ,     ['''labels'''] )





  @require_tf
  def 						UpperCAmelCase_	(	self ):
     self.assertEqual(find_labels(_lowerCamelCase )    ,     ['''labels'''] )
     self.assertEqual(find_labels(_lowerCamelCase )    ,     ['''labels''', '''next_sentence_label'''] )
     self.assertEqual(find_labels(_lowerCamelCase )    ,     ['''start_positions''', '''end_positions'''] )


     class     __UpperCAmelCase       ( __a		):
       pass






     self.assertEqual(find_labels(_lowerCamelCase )    ,     ['''labels'''] )







  @require_flax
  def 						UpperCAmelCase_	(	self ):
     # Flax models don't have labels
     self.assertEqual(find_labels(_lowerCamelCase )    ,     [] )
     self.assertEqual(find_labels(_lowerCamelCase )    ,     [] )
     self.assertEqual(find_labels(_lowerCamelCase )    ,     [] )


     class     __UpperCAmelCase       ( __a		):
       pass






     self.assertEqual(find_labels(_lowerCamelCase )    ,     [] )





