




"""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 ):


			def    a_  (   self   :     Tuple   ,	UpperCamelCase_   :     int   ,	UpperCamelCase_   :     int):


						"""simple docstring"""




						__UpperCAmelCase						:			Union[str, Any]												=       jnp.ones((batch_size, length)) / length
						return scores


			def    a_  (   self   :     Optional[Any]):


						"""simple docstring"""




						__UpperCAmelCase						:			List[Any]												=       None
						__UpperCAmelCase						:			int												=       20

						__UpperCAmelCase						:			int												=       self._get_uniform_logits(batch_size=2   ,	length=UpperCamelCase_)

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

						# compute softmax
						__UpperCAmelCase						:			List[str]												=       jax.nn.softmax(UpperCamelCase_   ,	axis=-1)

						__UpperCAmelCase						:			str												=       FlaxTemperatureLogitsWarper(temperature=0.5)
						__UpperCAmelCase						:			Tuple												=       FlaxTemperatureLogitsWarper(temperature=1.3)

						__UpperCAmelCase						:			Union[str, Any]												=       jax.nn.softmax(temp_dist_warper_sharper(UpperCamelCase_   ,	scores.copy()   ,	cur_len=UpperCamelCase_)   ,	axis=-1)
						__UpperCAmelCase						:			List[Any]												=       jax.nn.softmax(temp_dist_warper_smoother(UpperCamelCase_   ,	scores.copy()   ,	cur_len=UpperCamelCase_)   ,	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   :     Dict):


						"""simple docstring"""




						__UpperCAmelCase						:			int												=       None
						__UpperCAmelCase						:			Tuple												=       10
						__UpperCAmelCase						:			Any												=       2

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

						__UpperCAmelCase						:			str												=       FlaxTopKLogitsWarper(3)

						__UpperCAmelCase						:			Union[str, Any]												=       top_k_warp(UpperCamelCase_   ,	UpperCamelCase_   ,	cur_len=UpperCamelCase_)

						# 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
						__UpperCAmelCase						:			Tuple												=       5
						__UpperCAmelCase						:			List[Any]												=       FlaxTopKLogitsWarper(top_k=1   ,	filter_value=0.0   ,	min_tokens_to_keep=3)

						__UpperCAmelCase						:			str												=       np.broadcast_to(np.arange(UpperCamelCase_)[None, :]   ,	(batch_size, length)).copy()
						__UpperCAmelCase						:			str												=       top_k_warp_safety_check(UpperCamelCase_   ,	UpperCamelCase_   ,	cur_len=UpperCamelCase_)

						# 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):


						"""simple docstring"""




						__UpperCAmelCase						:			Any												=       None
						__UpperCAmelCase						:			Optional[int]												=       10
						__UpperCAmelCase						:			Dict												=       2

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

						__UpperCAmelCase						:			Optional[Any]												=       FlaxTopPLogitsWarper(0.8)
						__UpperCAmelCase						:			int												=       np.exp(top_p_warp(UpperCamelCase_   ,	UpperCamelCase_   ,	cur_len=UpperCamelCase_))

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

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

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

						# make sure at least 2 tokens are kept
						__UpperCAmelCase						:			Optional[int]												=       FlaxTopPLogitsWarper(0.9   ,	min_tokens_to_keep=2   ,	filter_value=0.0)
						__UpperCAmelCase						:			int												=       top_p_warp(UpperCamelCase_   ,	UpperCamelCase_   ,	cur_len=UpperCamelCase_)

						# 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   :     Tuple):


						"""simple docstring"""




						__UpperCAmelCase						:			int												=       20
						__UpperCAmelCase						:			Optional[Any]												=       4
						__UpperCAmelCase						:			Union[str, Any]												=       0

						__UpperCAmelCase						:			int												=       FlaxMinLengthLogitsProcessor(min_length=10   ,	eos_token_id=UpperCamelCase_)

						# check that min length is applied at length 5
						__UpperCAmelCase						:			List[Any]												=       ids_tensor((batch_size, 20)   ,	vocab_size=20)
						__UpperCAmelCase						:			int												=       5
						__UpperCAmelCase						:			Any												=       self._get_uniform_logits(UpperCamelCase_   ,	UpperCamelCase_)
						__UpperCAmelCase						:			int												=       min_dist_processor(UpperCamelCase_   ,	UpperCamelCase_   ,	cur_len=UpperCamelCase_)
						self.assertListEqual(scores_before_min_length[:, eos_token_id].tolist()   ,	4 * [-float("inf")])

						# check that min length is not applied anymore at length 15
						__UpperCAmelCase						:			List[str]												=       self._get_uniform_logits(UpperCamelCase_   ,	UpperCamelCase_)
						__UpperCAmelCase						:			Dict												=       15
						__UpperCAmelCase						:			Optional[int]												=       min_dist_processor(UpperCamelCase_   ,	UpperCamelCase_   ,	cur_len=UpperCamelCase_)
						self.assertFalse(jnp.isinf(UpperCamelCase_).any())


			def    a_  (   self   :     Optional[int]):


						"""simple docstring"""




						__UpperCAmelCase						:			Optional[Any]												=       20
						__UpperCAmelCase						:			Optional[int]												=       4
						__UpperCAmelCase						:			Tuple												=       0

						__UpperCAmelCase						:			Any												=       FlaxForcedBOSTokenLogitsProcessor(bos_token_id=UpperCamelCase_)

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


			def    a_  (   self   :     Any):


						"""simple docstring"""




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

						__UpperCAmelCase						:			Optional[Any]												=       FlaxForcedEOSTokenLogitsProcessor(max_length=UpperCamelCase_   ,	eos_token_id=UpperCamelCase_)

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


			def    a_  (   self   :     Any):


						"""simple docstring"""




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

						# dummy input_ids and scores
						__UpperCAmelCase						:			Dict												=       ids_tensor((batch_size, sequence_length)   ,	UpperCamelCase_)
						__UpperCAmelCase						:			Tuple												=       input_ids.copy()

						__UpperCAmelCase						:			Dict												=       self._get_uniform_logits(UpperCamelCase_   ,	UpperCamelCase_)
						__UpperCAmelCase						:			Optional[Any]												=       scores.copy()

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

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

						__UpperCAmelCase						:			Any												=       10

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

						# with processor list
						__UpperCAmelCase						:			str												=       FlaxLogitsProcessorList(
						    [temp_dist_warp, top_k_warp, top_p_warp, min_dist_proc, bos_dist_proc, eos_dist_proc])
						__UpperCAmelCase						:			Optional[int]												=       processor(UpperCamelCase_   ,	UpperCamelCase_   ,	cur_len=UpperCamelCase_)

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

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


			def    a_  (   self   :     Optional[int]):


						"""simple docstring"""




						__UpperCAmelCase						:			Tuple												=       4
						__UpperCAmelCase						:			str												=       10
						__UpperCAmelCase						:			Optional[int]												=       15
						__UpperCAmelCase						:			int												=       2
						__UpperCAmelCase						:			List[str]												=       1
						__UpperCAmelCase						:			Dict												=       15

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

						__UpperCAmelCase						:			str												=       self._get_uniform_logits(UpperCamelCase_   ,	UpperCamelCase_)
						__UpperCAmelCase						:			int												=       scores.copy()

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

						# instantiate all logits processors
						__UpperCAmelCase						:			List[str]												=       FlaxMinLengthLogitsProcessor(min_length=10   ,	eos_token_id=UpperCamelCase_)
						__UpperCAmelCase						:			Optional[int]												=       FlaxForcedBOSTokenLogitsProcessor(bos_token_id=UpperCamelCase_)
						__UpperCAmelCase						:			Tuple												=       FlaxForcedEOSTokenLogitsProcessor(max_length=UpperCamelCase_   ,	eos_token_id=UpperCamelCase_)

						__UpperCAmelCase						:			Optional[Any]												=       10

						# no processor list
						def run_no_processor_list(UpperCamelCase_   :     Union[str, Any]   ,	UpperCamelCase_   :     Optional[Any]   ,	UpperCamelCase_   :     Dict):
									__UpperCAmelCase						:			Any												=       temp_dist_warp(UpperCamelCase_   ,	UpperCamelCase_   ,	cur_len=UpperCamelCase_)
									__UpperCAmelCase						:			List[str]												=       top_k_warp(UpperCamelCase_   ,	UpperCamelCase_   ,	cur_len=UpperCamelCase_)
									__UpperCAmelCase						:			int												=       top_p_warp(UpperCamelCase_   ,	UpperCamelCase_   ,	cur_len=UpperCamelCase_)
									__UpperCAmelCase						:			int												=       min_dist_proc(UpperCamelCase_   ,	UpperCamelCase_   ,	cur_len=UpperCamelCase_)
									__UpperCAmelCase						:			int												=       bos_dist_proc(UpperCamelCase_   ,	UpperCamelCase_   ,	cur_len=UpperCamelCase_)
									__UpperCAmelCase						:			Any												=       eos_dist_proc(UpperCamelCase_   ,	UpperCamelCase_   ,	cur_len=UpperCamelCase_)
									return scores

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

						__UpperCAmelCase						:			str												=       jax.jit(UpperCamelCase_)
						__UpperCAmelCase						:			List[str]												=       jax.jit(UpperCamelCase_)

						__UpperCAmelCase						:			List[Any]												=       jitted_run_no_processor_list(UpperCamelCase_   ,	UpperCamelCase_   ,	UpperCamelCase_)
						__UpperCAmelCase						:			Dict												=       jitted_run_processor_list(UpperCamelCase_   ,	UpperCamelCase_   ,	UpperCamelCase_)

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

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






'''simple docstring'''







import unittest

from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
class 						UpperCamelCase__       (			SCREAMING_SNAKE_CASE_     ,       unittest.TestCase						):



     """simple docstring"""






     __magic_name__           =     RoFormerTokenizer
     __magic_name__           =     RoFormerTokenizerFast
     __magic_name__           =     True
     __magic_name__           =     True







     def a						(			self ):

            '''simple docstring'''

            super().setUp()







     def a						(			self   ,						**snake_case__ ):

            '''simple docstring'''

            return self.tokenizer_class.from_pretrained('junnyu/roformer_chinese_base'   ,						**snake_case__ )







     def a						(			self   ,						**snake_case__ ):

            '''simple docstring'''

            return self.rust_tokenizer_class.from_pretrained('junnyu/roformer_chinese_base'   ,						**snake_case__ )







     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				List[Any]       =							'永和服装饰品有限公司,今天天气非常好'
            _lowerCAmelCase     :				str       =							'永和 服装 饰品 有限公司 , 今 天 天 气 非常 好'
            return input_text, output_text







     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				Optional[int]       =							self.get_tokenizer()
            _lowerCAmelCase      ,  _lowerCAmelCase     :				int       =							self.get_chinese_input_output_texts()
            _lowerCAmelCase     :				List[Any]       =							tokenizer.tokenize(snake_case__ )

            self.assertListEqual(snake_case__   ,						output_text.split() )

            _lowerCAmelCase     :				Optional[Any]       =							tokens + [tokenizer.unk_token]
            _lowerCAmelCase     :				List[str]       =							[2_2943, 2_1332, 3_4431, 4_5904, 117, 306, 1231, 1231, 2653, 3_3994, 1266, 100]
            self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case__ )   ,						snake_case__ )







     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				List[Any]       =							self.get_rust_tokenizer()
            _lowerCAmelCase      ,  _lowerCAmelCase     :				Any       =							self.get_chinese_input_output_texts()
            _lowerCAmelCase     :				Optional[int]       =							tokenizer.tokenize(snake_case__ )
            self.assertListEqual(snake_case__   ,						output_text.split() )
            _lowerCAmelCase     :				Tuple       =							tokens + [tokenizer.unk_token]
            _lowerCAmelCase     :				List[Any]       =							[2_2943, 2_1332, 3_4431, 4_5904, 117, 306, 1231, 1231, 2653, 3_3994, 1266, 100]
            self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case__ )   ,						snake_case__ )







     def a						(			self ):

            '''simple docstring'''

            pass







     def a						(			self ):

            '''simple docstring'''

            pass







     def a						(			self ):

            '''simple docstring'''

            pass

