






'''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 				lowercase       (							unittest.TestCase      ):


				'''simple docstring'''

				def    a__				(					self     :     str				,     __lowerCamelCase     :     int				,     __lowerCamelCase     :     int     )							->							int:

					'''simple docstring'''




					lowerCamelCase__  =     jnp.ones((batch_size, length)     ) / length
					return scores

				def    a__				(					self     :     Tuple     )							->							List[str]:

					'''simple docstring'''




					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    a__				(					self     :     List[str]     )							->							List[str]:

					'''simple docstring'''




					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    a__				(					self     :     Dict     )							->							Optional[Any]:

					'''simple docstring'''




					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], [0.1_5, 0.3, 0.3, 0.2_5]]     )     )

					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, 0.2_5]]     )
					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_0_0.0

					# 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    a__				(					self     :     int     )							->							Optional[int]:

					'''simple docstring'''




					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    a__				(					self     :     List[Any]     )							->							Tuple:

					'''simple docstring'''




					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    a__				(					self     :     Optional[int]     )							->							Tuple:

					'''simple docstring'''




					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    a__				(					self     :     List[str]     )							->							Tuple:

					'''simple docstring'''




					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    a__				(					self     :     Dict     )							->							str:

					'''simple docstring'''




					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     :     str				,     __lowerCamelCase     :     Optional[int]				,     __lowerCamelCase     :     Optional[Any]     ):
						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     :     str				,     __lowerCamelCase     :     str				,     __lowerCamelCase     :     List[Any]     ):
						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'''





class 				lowercase       :


    '''simple docstring'''

    def __init__(					self     :     Union[str, Any]     )							->							None:

     '''simple docstring'''




     lowerCamelCase__  =     {}  # Mapping from char to TrieNode
     lowerCamelCase__  =     False

    def    a__				(					self     :     List[Any]				,     __lowerCamelCase     :     list[str]     )							->							None:

     '''simple docstring'''




     for word in words:
      self.insert(__lowerCamelCase     )

    def    a__				(					self     :     int				,     __lowerCamelCase     :     str     )							->							None:

     '''simple docstring'''




     lowerCamelCase__  =     self
     for char in word:
      if char not in curr.nodes:
       lowerCamelCase__  =     TrieNode()
      lowerCamelCase__  =     curr.nodes[char]
     lowerCamelCase__  =     True

    def    a__				(					self     :     Optional[Any]				,     __lowerCamelCase     :     str     )							->							bool:

     '''simple docstring'''




     lowerCamelCase__  =     self
     for char in word:
      if char not in curr.nodes:
       return False
      lowerCamelCase__  =     curr.nodes[char]
     return curr.is_leaf




    def    a__				(					self     :     Optional[Any]				,     __lowerCamelCase     :     str     )							->							None:

     '''simple docstring'''




     def _delete(__lowerCamelCase     :     TrieNode				,     __lowerCamelCase     :     str				,     __lowerCamelCase     :     int     ) -> bool:
      if index == len(__lowerCamelCase     ):
       # If word does not exist
       if not curr.is_leaf:
        return False
       lowerCamelCase__  =     False
       return len(curr.nodes     ) == 0
      lowerCamelCase__  =     word[index]
      lowerCamelCase__  =     curr.nodes.get(__lowerCamelCase     )
      # If char not in current trie node
      if not char_node:
       return False
      # Flag to check if node can be deleted
      lowerCamelCase__  =     _delete(__lowerCamelCase				,     __lowerCamelCase				,     index + 1     )
      if delete_curr:
       del curr.nodes[char]
       return len(curr.nodes     ) == 0
      return delete_curr

     _delete(self				,     __lowerCamelCase				,     0     )






def    lowerCamelCase_     (    lowercase__				,     lowercase__):
 if node.is_leaf:
  print(lowercase__				,     end=" ")

 for key, value in node.nodes.items():
  print_words(lowercase__				,     word + key)






def    lowerCamelCase_     (    ):
 lowerCamelCase__  =     "banana bananas bandana band apple all beast".split()
 lowerCamelCase__  =     TrieNode()
 root.insert_many(lowercase__)
 # print_words(root, "")
 assert all(root.find(lowercase__) for word in words)
 assert root.find("banana")
 assert not root.find("bandanas")
 assert not root.find("apps")
 assert root.find("apple")
 assert root.find("all")
 root.delete("all")
 assert not root.find("all")
 root.delete("banana")
 assert not root.find("banana")
 assert root.find("bananas")
 return True






def    lowerCamelCase_     (    lowercase__				,     lowercase__):
 print(str(lowercase__)				,     "works!" if passes else "doesn't work :(")






def    lowerCamelCase_     (    ):
 assert test_trie()






def    lowerCamelCase_     (    ):
 print_results("Testing trie functionality"				,     test_trie())


if __name__ == "__main__":
 main()

