


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 				lowerCamelCase_			(							self:     Dict   ,						UpperCamelCase_:     int   ,						UpperCamelCase_:     int							)      ->       Any:





									"""simple docstring"""







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

							def 				lowerCamelCase_			(							self:     str							)      ->       str:





									"""simple docstring"""







									lowercase__						=				None
									lowercase__						=				20

									lowercase__						=				self._get_uniform_logits(batch_size=2   ,						length=UpperCamelCase_							)

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

									# compute softmax
									lowercase__						=				jax.nn.softmax(UpperCamelCase_   ,						axis=-1							)

									lowercase__						=				FlaxTemperatureLogitsWarper(temperature=0.5							)
									lowercase__						=				FlaxTemperatureLogitsWarper(temperature=1.3							)

									lowercase__						=				jax.nn.softmax(temp_dist_warper_sharper(UpperCamelCase_   ,						scores.copy()   ,						cur_len=UpperCamelCase_							)   ,						axis=-1							)
									lowercase__						=				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 				lowerCamelCase_			(							self:     Optional[int]							)      ->       Optional[Any]:





									"""simple docstring"""







									lowercase__						=				None
									lowercase__						=				10
									lowercase__						=				2

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

									lowercase__						=				FlaxTopKLogitsWarper(3							)

									lowercase__						=				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
									lowercase__						=				5
									lowercase__						=				FlaxTopKLogitsWarper(top_k=1   ,						filter_value=0.0   ,						min_tokens_to_keep=3							)

									lowercase__						=				np.broadcast_to(np.arange(UpperCamelCase_							)[None, :]   ,						(batch_size, length)							).copy()
									lowercase__						=				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 				lowerCamelCase_			(							self:     Tuple							)      ->       Any:





									"""simple docstring"""







									lowercase__						=				None
									lowercase__						=				10
									lowercase__						=				2

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

									lowercase__						=				FlaxTopPLogitsWarper(0.8							)
									lowercase__						=				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
									lowercase__						=				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
									lowercase__						=				np.broadcast_to(np.arange(UpperCamelCase_							)[None, :]   ,						(batch_size, vocab_size)							).copy() - (
									    vocab_size // 2
									)

									# make ramp_logits more extreme
									lowercase__						=				ramp_logits[1] * 100.0

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





									"""simple docstring"""







									lowercase__						=				20
									lowercase__						=				4
									lowercase__						=				0

									lowercase__						=				FlaxMinLengthLogitsProcessor(min_length=10   ,						eos_token_id=UpperCamelCase_							)

									# check that min length is applied at length 5
									lowercase__						=				ids_tensor((batch_size, 20)   ,						vocab_size=20							)
									lowercase__						=				5
									lowercase__						=				self._get_uniform_logits(UpperCamelCase_   ,						UpperCamelCase_							)
									lowercase__						=				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
									lowercase__						=				self._get_uniform_logits(UpperCamelCase_   ,						UpperCamelCase_							)
									lowercase__						=				15
									lowercase__						=				min_dist_processor(UpperCamelCase_   ,						UpperCamelCase_   ,						cur_len=UpperCamelCase_							)
									self.assertFalse(jnp.isinf(UpperCamelCase_							).any()							)

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





									"""simple docstring"""







									lowercase__						=				20
									lowercase__						=				4
									lowercase__						=				0

									lowercase__						=				FlaxForcedBOSTokenLogitsProcessor(bos_token_id=UpperCamelCase_							)

									# check that all scores are -inf except the bos_token_id score
									lowercase__						=				ids_tensor((batch_size, 1)   ,						vocab_size=20							)
									lowercase__						=				1
									lowercase__						=				self._get_uniform_logits(UpperCamelCase_   ,						UpperCamelCase_							)
									lowercase__						=				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
									lowercase__						=				3
									lowercase__						=				self._get_uniform_logits(UpperCamelCase_   ,						UpperCamelCase_							)
									lowercase__						=				logits_processor(UpperCamelCase_   ,						UpperCamelCase_   ,						cur_len=UpperCamelCase_							)
									self.assertFalse(jnp.isinf(UpperCamelCase_							).any()							)

							def 				lowerCamelCase_			(							self:     List[Any]							)      ->       Tuple:





									"""simple docstring"""







									lowercase__						=				20
									lowercase__						=				4
									lowercase__						=				0
									lowercase__						=				5

									lowercase__						=				FlaxForcedEOSTokenLogitsProcessor(max_length=UpperCamelCase_   ,						eos_token_id=UpperCamelCase_							)

									# check that all scores are -inf except the eos_token_id when max_length is reached
									lowercase__						=				ids_tensor((batch_size, 4)   ,						vocab_size=20							)
									lowercase__						=				4
									lowercase__						=				self._get_uniform_logits(UpperCamelCase_   ,						UpperCamelCase_							)
									lowercase__						=				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
									lowercase__						=				3
									lowercase__						=				self._get_uniform_logits(UpperCamelCase_   ,						UpperCamelCase_							)
									lowercase__						=				logits_processor(UpperCamelCase_   ,						UpperCamelCase_   ,						cur_len=UpperCamelCase_							)
									self.assertFalse(jnp.isinf(UpperCamelCase_							).any()							)

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





									"""simple docstring"""







									lowercase__						=				4
									lowercase__						=				10
									lowercase__						=				15
									lowercase__						=				2
									lowercase__						=				1
									lowercase__						=				15

									# dummy input_ids and scores
									lowercase__						=				ids_tensor((batch_size, sequence_length)   ,						UpperCamelCase_							)
									lowercase__						=				input_ids.copy()

									lowercase__						=				self._get_uniform_logits(UpperCamelCase_   ,						UpperCamelCase_							)
									lowercase__						=				scores.copy()

									# instantiate all dist processors
									lowercase__						=				FlaxTemperatureLogitsWarper(temperature=0.5							)
									lowercase__						=				FlaxTopKLogitsWarper(3							)
									lowercase__						=				FlaxTopPLogitsWarper(0.8							)

									# instantiate all logits processors
									lowercase__						=				FlaxMinLengthLogitsProcessor(min_length=10   ,						eos_token_id=UpperCamelCase_							)
									lowercase__						=				FlaxForcedBOSTokenLogitsProcessor(bos_token_id=UpperCamelCase_							)
									lowercase__						=				FlaxForcedEOSTokenLogitsProcessor(max_length=UpperCamelCase_   ,						eos_token_id=UpperCamelCase_							)

									lowercase__						=				10

									# no processor list
									lowercase__						=				temp_dist_warp(UpperCamelCase_   ,						UpperCamelCase_   ,						cur_len=UpperCamelCase_							)
									lowercase__						=				top_k_warp(UpperCamelCase_   ,						UpperCamelCase_   ,						cur_len=UpperCamelCase_							)
									lowercase__						=				top_p_warp(UpperCamelCase_   ,						UpperCamelCase_   ,						cur_len=UpperCamelCase_							)
									lowercase__						=				min_dist_proc(UpperCamelCase_   ,						UpperCamelCase_   ,						cur_len=UpperCamelCase_							)
									lowercase__						=				bos_dist_proc(UpperCamelCase_   ,						UpperCamelCase_   ,						cur_len=UpperCamelCase_							)
									lowercase__						=				eos_dist_proc(UpperCamelCase_   ,						UpperCamelCase_   ,						cur_len=UpperCamelCase_							)

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





									"""simple docstring"""







									lowercase__						=				4
									lowercase__						=				10
									lowercase__						=				15
									lowercase__						=				2
									lowercase__						=				1
									lowercase__						=				15

									# dummy input_ids and scores
									lowercase__						=				ids_tensor((batch_size, sequence_length)   ,						UpperCamelCase_							)
									lowercase__						=				input_ids.copy()

									lowercase__						=				self._get_uniform_logits(UpperCamelCase_   ,						UpperCamelCase_							)
									lowercase__						=				scores.copy()

									# instantiate all dist processors
									lowercase__						=				FlaxTemperatureLogitsWarper(temperature=0.5							)
									lowercase__						=				FlaxTopKLogitsWarper(3							)
									lowercase__						=				FlaxTopPLogitsWarper(0.8							)

									# instantiate all logits processors
									lowercase__						=				FlaxMinLengthLogitsProcessor(min_length=10   ,						eos_token_id=UpperCamelCase_							)
									lowercase__						=				FlaxForcedBOSTokenLogitsProcessor(bos_token_id=UpperCamelCase_							)
									lowercase__						=				FlaxForcedEOSTokenLogitsProcessor(max_length=UpperCamelCase_   ,						eos_token_id=UpperCamelCase_							)

									lowercase__						=				10

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

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

									lowercase__						=				jax.jit(UpperCamelCase_							)
									lowercase__						=				jax.jit(UpperCamelCase_							)

									lowercase__						=				jitted_run_no_processor_list(UpperCamelCase_   ,						UpperCamelCase_   ,						UpperCamelCase_							)
									lowercase__						=				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()							)






lowerCAmelCase	=							[sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_0000)]
def       _a			(				SCREAMING_SNAKE_CASE					):


		"""simple docstring"""




		lowercase__						=				0
		while number:
				# Increased Speed Slightly by checking every 5 digits together.
				sum_of_digits_squared += DIGITS_SQUARED[number % 10_00_00]
				number //= 10_00_00

		return sum_of_digits_squared


# There are 2 Chains made,
# One ends with 89 with the chain member 58 being the one which when declared first,
# there will be the least number of iterations for all the members to be checked.

# The other one ends with 1 and has only one element 1.

# So 58 and 1 are chosen to be declared at the starting.

# Changed dictionary to an array to quicken the solution
lowerCAmelCase	=							[None] * 1000_0000
lowerCAmelCase	=							True
lowerCAmelCase	=							False
def       _a			(				SCREAMING_SNAKE_CASE					):


		"""simple docstring"""




		if CHAINS[number - 1] is not None:
				return CHAINS[number - 1]  # type: ignore

		lowercase__						=				chain(next_number(SCREAMING_SNAKE_CASE					)					)
		lowercase__						=				number_chain

		while number < 10_00_00_00:
				lowercase__						=				number_chain
				number *= 10

		return number_chain
def       _a			(				SCREAMING_SNAKE_CASE = 10_00_00_00					):


		"""simple docstring"""




		for i in range(1						,    SCREAMING_SNAKE_CASE					):
				if CHAINS[i] is None:
						chain(i + 1					)

		return CHAINS[:number].count(SCREAMING_SNAKE_CASE					)


if __name__ == "__main__":
			import doctest

			doctest.testmod()
			print(f"""{solution() = }""")


