


'''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						,    __a						,    __a							):

						'''simple docstring'''





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




	def 				__UpperCAmelCase							(       self							):

						'''simple docstring'''





						__a      :	Optional[Any]    =  None
						__a      :	List[Any]    =  20

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

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

						# compute softmax
						__a      :	Optional[Any]    =  jax.nn.softmax(__lowerCAmelCase						,    axis=-1							)

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

						__a      :	Optional[int]    =  jax.nn.softmax(temp_dist_warper_sharper(__lowerCAmelCase						,    scores.copy()						,    cur_len=__lowerCAmelCase							)						,    axis=-1							)
						__a      :	Optional[int]    =  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							):

						'''simple docstring'''





						__a      :	Any    =  None
						__a      :	Union[str, Any]    =  10
						__a      :	int    =  2

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

						__a      :	Dict    =  FlaxTopKLogitsWarper(3							)

						__a      :	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
						__a      :	List[Any]    =  5
						__a      :	int    =  FlaxTopKLogitsWarper(top_k=1						,    filter_value=0.0						,    min_tokens_to_keep=3							)

						__a      :	Union[str, Any]    =  np.broadcast_to(np.arange(__lowerCAmelCase							)[None, :]						,    (batch_size, length)							).copy()
						__a      :	Optional[int]    =  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							):

						'''simple docstring'''





						__a      :	Dict    =  None
						__a      :	Tuple    =  10
						__a      :	List[str]    =  2

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

						__a      :	List[Any]    =  FlaxTopPLogitsWarper(0.8							)
						__a      :	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
						__a      :	Tuple    =  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
						__a      :	Optional[Any]    =  np.broadcast_to(np.arange(__lowerCAmelCase							)[None, :]						,    (batch_size, vocab_size)							).copy() - (
						    vocab_size // 2
						)

						# make ramp_logits more extreme
						__a      :	Optional[Any]    =  ramp_logits[1] * 100.0

						# make sure at least 2 tokens are kept
						__a      :	Tuple    =  FlaxTopPLogitsWarper(0.9						,    min_tokens_to_keep=2						,    filter_value=0.0							)
						__a      :	Optional[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 				__UpperCAmelCase							(       self							):

						'''simple docstring'''





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

						__a      :	str    =  FlaxMinLengthLogitsProcessor(min_length=10						,    eos_token_id=__lowerCAmelCase							)

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




	def 				__UpperCAmelCase							(       self							):

						'''simple docstring'''





						__a      :	Dict    =  20
						__a      :	List[str]    =  4
						__a      :	Tuple    =  0

						__a      :	Tuple    =  FlaxForcedBOSTokenLogitsProcessor(bos_token_id=__lowerCAmelCase							)

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




	def 				__UpperCAmelCase							(       self							):

						'''simple docstring'''





						__a      :	Any    =  20
						__a      :	str    =  4
						__a      :	Any    =  0
						__a      :	Tuple    =  5

						__a      :	Optional[int]    =  FlaxForcedEOSTokenLogitsProcessor(max_length=__lowerCAmelCase						,    eos_token_id=__lowerCAmelCase							)

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




	def 				__UpperCAmelCase							(       self							):

						'''simple docstring'''





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

						# dummy input_ids and scores
						__a      :	List[Any]    =  ids_tensor((batch_size, sequence_length)						,    __lowerCAmelCase							)
						__a      :	List[Any]    =  input_ids.copy()

						__a      :	str    =  self._get_uniform_logits(__lowerCAmelCase						,    __lowerCAmelCase							)
						__a      :	int    =  scores.copy()

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

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

						__a      :	int    =  10

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

						# with processor list
						__a      :	Tuple    =  FlaxLogitsProcessorList(
						    [temp_dist_warp, top_k_warp, top_p_warp, min_dist_proc, bos_dist_proc, eos_dist_proc]							)
						__a      :	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 				__UpperCAmelCase							(       self							):

						'''simple docstring'''





						__a      :	int    =  4
						__a      :	Dict    =  10
						__a      :	str    =  15
						__a      :	str    =  2
						__a      :	List[Any]    =  1
						__a      :	Union[str, Any]    =  15

						# dummy input_ids and scores
						__a      :	Union[str, Any]    =  ids_tensor((batch_size, sequence_length)						,    __lowerCAmelCase							)
						__a      :	List[Any]    =  input_ids.copy()

						__a      :	str    =  self._get_uniform_logits(__lowerCAmelCase						,    __lowerCAmelCase							)
						__a      :	Tuple    =  scores.copy()

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

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

						__a      :	Any    =  10

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

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

						__a      :	Union[str, Any]    =  jax.jit(__lowerCAmelCase							)
						__a      :	Dict    =  jax.jit(__lowerCAmelCase							)

						__a      :	List[Any]    =  jitted_run_no_processor_list(__lowerCAmelCase						,    __lowerCAmelCase						,    __lowerCAmelCase							)
						__a      :	List[Any]    =  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'''



def   lowerCamelCase							(_SCREAMING_SNAKE_CASE				:       int       ):
					return number & 1 == 0


if __name__ == "__main__":
	import doctest

	doctest.testmod()



