



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  lowerCamelCase__    (							unittest.TestCase):




		'''simple docstring'''



		def 	lowerCAmelCase__   (self	,__lowerCamelCase	,__lowerCamelCase				)  ->    Any:

						"""simple docstring"""






						lowerCAmelCase__  :       Tuple				=  jnp.ones((batch_size, length)				) / length
						return scores



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

						"""simple docstring"""






						lowerCAmelCase__  :       List[str]				=  None
						lowerCAmelCase__  :       Optional[Any]				=  20

						lowerCAmelCase__  :       List[Any]				=  self._get_uniform_logits(batch_size=2	,length=__lowerCamelCase				)

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

						# compute softmax
						lowerCAmelCase__  :       int				=  jax.nn.softmax(__lowerCamelCase	,axis=-1				)

						lowerCAmelCase__  :       Optional[int]				=  FlaxTemperatureLogitsWarper(temperature=0.5				)
						lowerCAmelCase__  :       Tuple				=  FlaxTemperatureLogitsWarper(temperature=1.3				)

						lowerCAmelCase__  :       Dict				=  jax.nn.softmax(temp_dist_warper_sharper(__lowerCamelCase	,scores.copy()	,cur_len=__lowerCamelCase				)	,axis=-1				)
						lowerCAmelCase__  :       Any				=  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 	lowerCAmelCase__   (self				)  ->    List[Any]:

						"""simple docstring"""






						lowerCAmelCase__  :       Optional[int]				=  None
						lowerCAmelCase__  :       Optional[int]				=  10
						lowerCAmelCase__  :       str				=  2

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

						lowerCAmelCase__  :       Union[str, Any]				=  FlaxTopKLogitsWarper(3				)

						lowerCAmelCase__  :       Optional[int]				=  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__  :       str				=  5
						lowerCAmelCase__  :       str				=  FlaxTopKLogitsWarper(top_k=1	,filter_value=0.0	,min_tokens_to_keep=3				)

						lowerCAmelCase__  :       Dict				=  np.broadcast_to(np.arange(__lowerCamelCase				)[None, :]	,(batch_size, length)				).copy()
						lowerCAmelCase__  :       Any				=  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 	lowerCAmelCase__   (self				)  ->    Any:

						"""simple docstring"""






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

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

						lowerCAmelCase__  :       Union[str, Any]				=  FlaxTopPLogitsWarper(0.8				)
						lowerCAmelCase__  :       Union[str, Any]				=  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__  :       List[Any]				=  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__  :       List[Any]				=  np.broadcast_to(np.arange(__lowerCamelCase				)[None, :]	,(batch_size, vocab_size)				).copy() - (
						    vocab_size // 2
						)

						# make ramp_logits more extreme
						lowerCAmelCase__  :       int				=  ramp_logits[1] * 100.0

						# make sure at least 2 tokens are kept
						lowerCAmelCase__  :       Any				=  FlaxTopPLogitsWarper(0.9	,min_tokens_to_keep=2	,filter_value=0.0				)
						lowerCAmelCase__  :       List[Any]				=  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 	lowerCAmelCase__   (self				)  ->    Union[str, Any]:

						"""simple docstring"""






						lowerCAmelCase__  :       Union[str, Any]				=  20
						lowerCAmelCase__  :       Any				=  4
						lowerCAmelCase__  :       Tuple				=  0

						lowerCAmelCase__  :       Dict				=  FlaxMinLengthLogitsProcessor(min_length=10	,eos_token_id=__lowerCamelCase				)

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



		def 	lowerCAmelCase__   (self				)  ->    List[str]:

						"""simple docstring"""






						lowerCAmelCase__  :       List[str]				=  20
						lowerCAmelCase__  :       Tuple				=  4
						lowerCAmelCase__  :       Optional[int]				=  0

						lowerCAmelCase__  :       List[str]				=  FlaxForcedBOSTokenLogitsProcessor(bos_token_id=__lowerCamelCase				)

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



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

						"""simple docstring"""






						lowerCAmelCase__  :       int				=  20
						lowerCAmelCase__  :       List[str]				=  4
						lowerCAmelCase__  :       Optional[int]				=  0
						lowerCAmelCase__  :       Dict				=  5

						lowerCAmelCase__  :       str				=  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__  :       Any				=  ids_tensor((batch_size, 4)	,vocab_size=20				)
						lowerCAmelCase__  :       List[Any]				=  4
						lowerCAmelCase__  :       List[Any]				=  self._get_uniform_logits(__lowerCamelCase	,__lowerCamelCase				)
						lowerCAmelCase__  :       List[Any]				=  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__  :       Any				=  3
						lowerCAmelCase__  :       int				=  self._get_uniform_logits(__lowerCamelCase	,__lowerCamelCase				)
						lowerCAmelCase__  :       Dict				=  logits_processor(__lowerCamelCase	,__lowerCamelCase	,cur_len=__lowerCamelCase				)
						self.assertFalse(jnp.isinf(__lowerCamelCase				).any()				)



		def 	lowerCAmelCase__   (self				)  ->    Tuple:

						"""simple docstring"""






						lowerCAmelCase__  :       List[str]				=  4
						lowerCAmelCase__  :       Optional[Any]				=  10
						lowerCAmelCase__  :       Optional[int]				=  15
						lowerCAmelCase__  :       Tuple				=  2
						lowerCAmelCase__  :       Union[str, Any]				=  1
						lowerCAmelCase__  :       Optional[Any]				=  15

						# dummy input_ids and scores
						lowerCAmelCase__  :       Tuple				=  ids_tensor((batch_size, sequence_length)	,__lowerCamelCase				)
						lowerCAmelCase__  :       Any				=  input_ids.copy()

						lowerCAmelCase__  :       Tuple				=  self._get_uniform_logits(__lowerCamelCase	,__lowerCamelCase				)
						lowerCAmelCase__  :       List[str]				=  scores.copy()

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

						# instantiate all logits processors
						lowerCAmelCase__  :       str				=  FlaxMinLengthLogitsProcessor(min_length=10	,eos_token_id=__lowerCamelCase				)
						lowerCAmelCase__  :       str				=  FlaxForcedBOSTokenLogitsProcessor(bos_token_id=__lowerCamelCase				)
						lowerCAmelCase__  :       int				=  FlaxForcedEOSTokenLogitsProcessor(max_length=__lowerCamelCase	,eos_token_id=__lowerCamelCase				)

						lowerCAmelCase__  :       Any				=  10

						# no processor list
						lowerCAmelCase__  :       Union[str, Any]				=  temp_dist_warp(__lowerCamelCase	,__lowerCamelCase	,cur_len=__lowerCamelCase				)
						lowerCAmelCase__  :       Any				=  top_k_warp(__lowerCamelCase	,__lowerCamelCase	,cur_len=__lowerCamelCase				)
						lowerCAmelCase__  :       List[str]				=  top_p_warp(__lowerCamelCase	,__lowerCamelCase	,cur_len=__lowerCamelCase				)
						lowerCAmelCase__  :       Optional[int]				=  min_dist_proc(__lowerCamelCase	,__lowerCamelCase	,cur_len=__lowerCamelCase				)
						lowerCAmelCase__  :       Optional[int]				=  bos_dist_proc(__lowerCamelCase	,__lowerCamelCase	,cur_len=__lowerCamelCase				)
						lowerCAmelCase__  :       Optional[int]				=  eos_dist_proc(__lowerCamelCase	,__lowerCamelCase	,cur_len=__lowerCamelCase				)

						# with processor list
						lowerCAmelCase__  :       List[str]				=  FlaxLogitsProcessorList(
						    [temp_dist_warp, top_k_warp, top_p_warp, min_dist_proc, bos_dist_proc, eos_dist_proc]				)
						lowerCAmelCase__  :       Optional[int]				=  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 	lowerCAmelCase__   (self				)  ->    Any:

						"""simple docstring"""






						lowerCAmelCase__  :       Tuple				=  4
						lowerCAmelCase__  :       List[Any]				=  10
						lowerCAmelCase__  :       str				=  15
						lowerCAmelCase__  :       List[Any]				=  2
						lowerCAmelCase__  :       Union[str, Any]				=  1
						lowerCAmelCase__  :       Optional[Any]				=  15

						# dummy input_ids and scores
						lowerCAmelCase__  :       Dict				=  ids_tensor((batch_size, sequence_length)	,__lowerCamelCase				)
						lowerCAmelCase__  :       Union[str, Any]				=  input_ids.copy()

						lowerCAmelCase__  :       Union[str, Any]				=  self._get_uniform_logits(__lowerCamelCase	,__lowerCamelCase				)
						lowerCAmelCase__  :       Optional[int]				=  scores.copy()

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

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

						lowerCAmelCase__  :       int				=  10

						# no processor list
						def run_no_processor_list(__lowerCamelCase	,__lowerCamelCase	,__lowerCamelCase				):
										lowerCAmelCase__  :       List[str]				=  temp_dist_warp(__lowerCamelCase	,__lowerCamelCase	,cur_len=__lowerCamelCase				)
										lowerCAmelCase__  :       str				=  top_k_warp(__lowerCamelCase	,__lowerCamelCase	,cur_len=__lowerCamelCase				)
										lowerCAmelCase__  :       Union[str, Any]				=  top_p_warp(__lowerCamelCase	,__lowerCamelCase	,cur_len=__lowerCamelCase				)
										lowerCAmelCase__  :       List[Any]				=  min_dist_proc(__lowerCamelCase	,__lowerCamelCase	,cur_len=__lowerCamelCase				)
										lowerCAmelCase__  :       Tuple				=  bos_dist_proc(__lowerCamelCase	,__lowerCamelCase	,cur_len=__lowerCamelCase				)
										lowerCAmelCase__  :       Any				=  eos_dist_proc(__lowerCamelCase	,__lowerCamelCase	,cur_len=__lowerCamelCase				)
										return scores

						# with processor list
						def run_processor_list(__lowerCamelCase	,__lowerCamelCase	,__lowerCamelCase				):
										lowerCAmelCase__  :       Tuple				=  FlaxLogitsProcessorList(
										    [temp_dist_warp, top_k_warp, top_p_warp, min_dist_proc, bos_dist_proc, eos_dist_proc]				)
										lowerCAmelCase__  :       int				=  processor(__lowerCamelCase	,__lowerCamelCase	,cur_len=__lowerCamelCase				)
										return scores

						lowerCAmelCase__  :       Any				=  jax.jit(__lowerCamelCase				)
						lowerCAmelCase__  :       Any				=  jax.jit(__lowerCamelCase				)

						lowerCAmelCase__  :       str				=  jitted_run_no_processor_list(__lowerCamelCase	,__lowerCamelCase	,__lowerCamelCase				)
						lowerCAmelCase__  :       int				=  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()				)






def 			lowerCAmelCase__	(					lowerCamelCase_	:	Any ,lowerCamelCase_	:	Optional[Any]):





				'''simple docstring'''

				lowerCAmelCase__  :       str				=  [0 for i in range(r + 1)]
				# nc0 = 1
				lowerCAmelCase__  :       Tuple				=  1
				for i in range(1 ,n + 1):
								# to compute current row from previous row.
								lowerCAmelCase__  :       Optional[int]				=  min(lowerCamelCase_ ,lowerCamelCase_)
								while j > 0:
												c[j] += c[j - 1]
												j -= 1
				return c[r]

print(binomial_coefficient(n=1_0, r=5))

