



"""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     A__     (						unittest.TestCase							):




	'''simple docstring'''





	def 							_SCREAMING_SNAKE_CASE     (  self:	Union[str, Any] ,    _SCREAMING_SNAKE_CASE:	int ,    _SCREAMING_SNAKE_CASE:	int)       -> List[Any]:

				"""simple docstring"""

				__lowerCAmelCase   :						int				= jnp.ones((batch_size, length)) / length
				return scores

	def 							_SCREAMING_SNAKE_CASE     (  self:	str)       -> Tuple:

				"""simple docstring"""

				__lowerCAmelCase   :						List[str]				= None
				__lowerCAmelCase   :						Dict				= 20

				__lowerCAmelCase   :						List[Any]				= self._get_uniform_logits(batch_size=2 ,    length=_SCREAMING_SNAKE_CASE)

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

				# compute softmax
				__lowerCAmelCase   :						Dict				= jax.nn.softmax(_SCREAMING_SNAKE_CASE ,    axis=-1)

				__lowerCAmelCase   :						Any				= FlaxTemperatureLogitsWarper(temperature=0.5)
				__lowerCAmelCase   :						Union[str, Any]				= FlaxTemperatureLogitsWarper(temperature=1.3)

				__lowerCAmelCase   :						List[Any]				= jax.nn.softmax(temp_dist_warper_sharper(_SCREAMING_SNAKE_CASE ,    scores.copy() ,    cur_len=_SCREAMING_SNAKE_CASE) ,    axis=-1)
				__lowerCAmelCase   :						Optional[Any]				= jax.nn.softmax(temp_dist_warper_smoother(_SCREAMING_SNAKE_CASE ,    scores.copy() ,    cur_len=_SCREAMING_SNAKE_CASE) ,    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 							_SCREAMING_SNAKE_CASE     (  self:	int)       -> List[Any]:

				"""simple docstring"""

				__lowerCAmelCase   :						List[str]				= None
				__lowerCAmelCase   :						Optional[int]				= 10
				__lowerCAmelCase   :						Union[str, Any]				= 2

				# create ramp distribution
				__lowerCAmelCase   :						List[str]				= np.broadcast_to(np.arange(_SCREAMING_SNAKE_CASE)[None, :] ,    (batch_size, vocab_size)).copy()
				__lowerCAmelCase   :						Optional[Any]				= ramp_logits[1:, : vocab_size // 2] + vocab_size

				__lowerCAmelCase   :						Dict				= FlaxTopKLogitsWarper(3)

				__lowerCAmelCase   :						List[str]				= top_k_warp(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)

				# 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   :						Union[str, Any]				= 5
				__lowerCAmelCase   :						Any				= FlaxTopKLogitsWarper(top_k=1 ,    filter_value=0.0 ,    min_tokens_to_keep=3)

				__lowerCAmelCase   :						List[Any]				= np.broadcast_to(np.arange(_SCREAMING_SNAKE_CASE)[None, :] ,    (batch_size, length)).copy()
				__lowerCAmelCase   :						List[str]				= top_k_warp_safety_check(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)

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

	def 							_SCREAMING_SNAKE_CASE     (  self:	List[Any])       -> Any:

				"""simple docstring"""

				__lowerCAmelCase   :						Dict				= None
				__lowerCAmelCase   :						Optional[int]				= 10
				__lowerCAmelCase   :						Optional[int]				= 2

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

				__lowerCAmelCase   :						Dict				= FlaxTopPLogitsWarper(0.8)
				__lowerCAmelCase   :						Dict				= np.exp(top_p_warp(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE))

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

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

				# make ramp_logits more extreme
				__lowerCAmelCase   :						List[str]				= ramp_logits[1] * 100.0

				# make sure at least 2 tokens are kept
				__lowerCAmelCase   :						Optional[Any]				= FlaxTopPLogitsWarper(0.9 ,    min_tokens_to_keep=2 ,    filter_value=0.0)
				__lowerCAmelCase   :						Tuple				= top_p_warp(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)

				# 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 							_SCREAMING_SNAKE_CASE     (  self:	List[Any])       -> int:

				"""simple docstring"""

				__lowerCAmelCase   :						str				= 20
				__lowerCAmelCase   :						Dict				= 4
				__lowerCAmelCase   :						Optional[int]				= 0

				__lowerCAmelCase   :						Tuple				= FlaxMinLengthLogitsProcessor(min_length=10 ,    eos_token_id=_SCREAMING_SNAKE_CASE)

				# check that min length is applied at length 5
				__lowerCAmelCase   :						Optional[int]				= ids_tensor((batch_size, 20) ,    vocab_size=20)
				__lowerCAmelCase   :						Any				= 5
				__lowerCAmelCase   :						Optional[Any]				= self._get_uniform_logits(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Optional[Any]				= min_dist_processor(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
				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   :						Optional[int]				= self._get_uniform_logits(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						List[str]				= 15
				__lowerCAmelCase   :						Tuple				= min_dist_processor(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
				self.assertFalse(jnp.isinf(_SCREAMING_SNAKE_CASE).any())

	def 							_SCREAMING_SNAKE_CASE     (  self:	Union[str, Any])       -> Dict:

				"""simple docstring"""

				__lowerCAmelCase   :						Optional[Any]				= 20
				__lowerCAmelCase   :						List[Any]				= 4
				__lowerCAmelCase   :						List[Any]				= 0

				__lowerCAmelCase   :						Optional[Any]				= FlaxForcedBOSTokenLogitsProcessor(bos_token_id=_SCREAMING_SNAKE_CASE)

				# check that all scores are -inf except the bos_token_id score
				__lowerCAmelCase   :						Any				= ids_tensor((batch_size, 1) ,    vocab_size=20)
				__lowerCAmelCase   :						int				= 1
				__lowerCAmelCase   :						str				= self._get_uniform_logits(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Optional[int]				= logits_processor(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
				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   :						Dict				= 3
				__lowerCAmelCase   :						List[str]				= self._get_uniform_logits(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Optional[int]				= logits_processor(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
				self.assertFalse(jnp.isinf(_SCREAMING_SNAKE_CASE).any())

	def 							_SCREAMING_SNAKE_CASE     (  self:	Optional[Any])       -> Optional[int]:

				"""simple docstring"""

				__lowerCAmelCase   :						List[str]				= 20
				__lowerCAmelCase   :						List[str]				= 4
				__lowerCAmelCase   :						Optional[Any]				= 0
				__lowerCAmelCase   :						List[str]				= 5

				__lowerCAmelCase   :						Any				= FlaxForcedEOSTokenLogitsProcessor(max_length=_SCREAMING_SNAKE_CASE ,    eos_token_id=_SCREAMING_SNAKE_CASE)

				# check that all scores are -inf except the eos_token_id when max_length is reached
				__lowerCAmelCase   :						int				= ids_tensor((batch_size, 4) ,    vocab_size=20)
				__lowerCAmelCase   :						Tuple				= 4
				__lowerCAmelCase   :						str				= self._get_uniform_logits(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Union[str, Any]				= logits_processor(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
				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   :						Dict				= 3
				__lowerCAmelCase   :						int				= self._get_uniform_logits(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Optional[Any]				= logits_processor(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
				self.assertFalse(jnp.isinf(_SCREAMING_SNAKE_CASE).any())

	def 							_SCREAMING_SNAKE_CASE     (  self:	Dict)       -> str:

				"""simple docstring"""

				__lowerCAmelCase   :						Any				= 4
				__lowerCAmelCase   :						List[str]				= 10
				__lowerCAmelCase   :						Tuple				= 15
				__lowerCAmelCase   :						List[Any]				= 2
				__lowerCAmelCase   :						List[str]				= 1
				__lowerCAmelCase   :						List[str]				= 15

				# dummy input_ids and scores
				__lowerCAmelCase   :						Any				= ids_tensor((batch_size, sequence_length) ,    _SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Dict				= input_ids.copy()

				__lowerCAmelCase   :						Any				= self._get_uniform_logits(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						str				= scores.copy()

				# instantiate all dist processors
				__lowerCAmelCase   :						List[str]				= FlaxTemperatureLogitsWarper(temperature=0.5)
				__lowerCAmelCase   :						Dict				= FlaxTopKLogitsWarper(3)
				__lowerCAmelCase   :						Any				= FlaxTopPLogitsWarper(0.8)

				# instantiate all logits processors
				__lowerCAmelCase   :						List[Any]				= FlaxMinLengthLogitsProcessor(min_length=10 ,    eos_token_id=_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						str				= FlaxForcedBOSTokenLogitsProcessor(bos_token_id=_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Union[str, Any]				= FlaxForcedEOSTokenLogitsProcessor(max_length=_SCREAMING_SNAKE_CASE ,    eos_token_id=_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase   :						str				= 10

				# no processor list
				__lowerCAmelCase   :						Tuple				= temp_dist_warp(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						List[Any]				= top_k_warp(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Tuple				= top_p_warp(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Optional[Any]				= min_dist_proc(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Dict				= bos_dist_proc(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Union[str, Any]				= eos_dist_proc(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)

				# with processor list
				__lowerCAmelCase   :						Optional[int]				= FlaxLogitsProcessorList(
				    [temp_dist_warp, top_k_warp, top_p_warp, min_dist_proc, bos_dist_proc, eos_dist_proc])
				__lowerCAmelCase   :						Dict				= processor(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)

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

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







	def 							_SCREAMING_SNAKE_CASE     (  self:	Tuple)       -> Optional[Any]:

				"""simple docstring"""

				__lowerCAmelCase   :						Optional[Any]				= 4
				__lowerCAmelCase   :						Optional[Any]				= 10
				__lowerCAmelCase   :						Optional[Any]				= 15
				__lowerCAmelCase   :						Dict				= 2
				__lowerCAmelCase   :						List[str]				= 1
				__lowerCAmelCase   :						Union[str, Any]				= 15

				# dummy input_ids and scores
				__lowerCAmelCase   :						Dict				= ids_tensor((batch_size, sequence_length) ,    _SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						str				= input_ids.copy()

				__lowerCAmelCase   :						Union[str, Any]				= self._get_uniform_logits(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						List[Any]				= scores.copy()

				# instantiate all dist processors
				__lowerCAmelCase   :						Optional[Any]				= FlaxTemperatureLogitsWarper(temperature=0.5)
				__lowerCAmelCase   :						Optional[int]				= FlaxTopKLogitsWarper(3)
				__lowerCAmelCase   :						Optional[int]				= FlaxTopPLogitsWarper(0.8)

				# instantiate all logits processors
				__lowerCAmelCase   :						List[str]				= FlaxMinLengthLogitsProcessor(min_length=10 ,    eos_token_id=_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Union[str, Any]				= FlaxForcedBOSTokenLogitsProcessor(bos_token_id=_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Any				= FlaxForcedEOSTokenLogitsProcessor(max_length=_SCREAMING_SNAKE_CASE ,    eos_token_id=_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase   :						Dict				= 10

				# no processor list
				def run_no_processor_list(_SCREAMING_SNAKE_CASE:	Optional[Any] ,    _SCREAMING_SNAKE_CASE:	Tuple ,    _SCREAMING_SNAKE_CASE:	int):
							__lowerCAmelCase   :						Dict				= temp_dist_warp(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
							__lowerCAmelCase   :						Any				= top_k_warp(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
							__lowerCAmelCase   :						Optional[int]				= top_p_warp(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
							__lowerCAmelCase   :						Tuple				= min_dist_proc(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
							__lowerCAmelCase   :						Tuple				= bos_dist_proc(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
							__lowerCAmelCase   :						Optional[Any]				= eos_dist_proc(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
							return scores

				# with processor list
				def run_processor_list(_SCREAMING_SNAKE_CASE:	Optional[Any] ,    _SCREAMING_SNAKE_CASE:	str ,    _SCREAMING_SNAKE_CASE:	List[Any]):
							__lowerCAmelCase   :						Optional[Any]				= FlaxLogitsProcessorList(
							    [temp_dist_warp, top_k_warp, top_p_warp, min_dist_proc, bos_dist_proc, eos_dist_proc])
							__lowerCAmelCase   :						Optional[int]				= processor(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    cur_len=_SCREAMING_SNAKE_CASE)
							return scores

				__lowerCAmelCase   :						List[Any]				= jax.jit(_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						List[Any]				= jax.jit(_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase   :						Optional[int]				= jitted_run_no_processor_list(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Any				= jitted_run_processor_list(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)

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

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




"""simple docstring"""






def     _lowercase       (						__snake_case = 3      ,__snake_case = 7      ,__snake_case = 1_000_000			)		->     int:
			__lowerCAmelCase   :						Optional[Any]				= 0
			__lowerCAmelCase   :						List[str]				= 1

			for current_denominator in range(1      ,limit + 1			):
						__lowerCAmelCase   :						Optional[int]				= current_denominator * numerator // denominator
						if current_denominator % denominator == 0:
									current_numerator -= 1
						if current_numerator * max_denominator > current_denominator * max_numerator:
									__lowerCAmelCase   :						Union[str, Any]				= current_numerator
									__lowerCAmelCase   :						int				= current_denominator
			return max_numerator


if __name__ == "__main__":
	print(solution(numerator=3, denominator=7, limit=1_000_000))