






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 	UpperCAmelCase      (      self					:			Tuple		,      __lowercase					:			int		,      __lowercase					:			int					)							->      Any:
        __UpperCAmelCase							:	Any           =  jnp.ones((batch_size, length)					) / length
        return scores
      def 	UpperCAmelCase      (      self					:			str					)							->      int:
        __UpperCAmelCase							:	int           =  None
        __UpperCAmelCase							:	Union[str, Any]           =  20

        __UpperCAmelCase							:	Dict           =  self._get_uniform_logits(batch_size=2		,      length=__lowercase					)

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

        # compute softmax
        __UpperCAmelCase							:	Any           =  jax.nn.softmax(__lowercase		,      axis=-1					)

        __UpperCAmelCase							:	Dict           =  FlaxTemperatureLogitsWarper(temperature=0.5					)
        __UpperCAmelCase							:	Optional[Any]           =  FlaxTemperatureLogitsWarper(temperature=1.3					)

        __UpperCAmelCase							:	Optional[Any]           =  jax.nn.softmax(temp_dist_warper_sharper(__lowercase		,      scores.copy()		,      cur_len=__lowercase					)		,      axis=-1					)
        __UpperCAmelCase							:	Optional[int]           =  jax.nn.softmax(temp_dist_warper_smoother(__lowercase		,      scores.copy()		,      cur_len=__lowercase					)		,      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					:			Tuple					)							->      Tuple:
        __UpperCAmelCase							:	int           =  None
        __UpperCAmelCase							:	int           =  10
        __UpperCAmelCase							:	Optional[Any]           =  2

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

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

        __UpperCAmelCase							:	Optional[int]           =  top_k_warp(__lowercase		,      __lowercase		,      cur_len=__lowercase					)

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

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

        # 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					:			int					)							->      Union[str, Any]:
        __UpperCAmelCase							:	Any           =  None
        __UpperCAmelCase							:	List[Any]           =  10
        __UpperCAmelCase							:	str           =  2

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

        __UpperCAmelCase							:	str           =  FlaxTopPLogitsWarper(0.8					)
        __UpperCAmelCase							:	Tuple           =  np.exp(top_p_warp(__lowercase		,      __lowercase		,      cur_len=__lowercase					)					)

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

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

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

        # make sure at least 2 tokens are kept
        __UpperCAmelCase							:	Dict           =  FlaxTopPLogitsWarper(0.9		,      min_tokens_to_keep=2		,      filter_value=0.0					)
        __UpperCAmelCase							:	Dict           =  top_p_warp(__lowercase		,      __lowercase		,      cur_len=__lowercase					)

        # 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					:			Dict					)							->      Optional[Any]:
        __UpperCAmelCase							:	int           =  20
        __UpperCAmelCase							:	Optional[Any]           =  4
        __UpperCAmelCase							:	Optional[Any]           =  0

        __UpperCAmelCase							:	Optional[int]           =  FlaxMinLengthLogitsProcessor(min_length=10		,      eos_token_id=__lowercase					)

        # check that min length is applied at length 5
        __UpperCAmelCase							:	Tuple           =  ids_tensor((batch_size, 20)		,      vocab_size=20					)
        __UpperCAmelCase							:	Dict           =  5
        __UpperCAmelCase							:	List[str]           =  self._get_uniform_logits(__lowercase		,      __lowercase					)
        __UpperCAmelCase							:	Union[str, Any]           =  min_dist_processor(__lowercase		,      __lowercase		,      cur_len=__lowercase					)
        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							:	Union[str, Any]           =  self._get_uniform_logits(__lowercase		,      __lowercase					)
        __UpperCAmelCase							:	int           =  15
        __UpperCAmelCase							:	int           =  min_dist_processor(__lowercase		,      __lowercase		,      cur_len=__lowercase					)
        self.assertFalse(jnp.isinf(__lowercase					).any()					)
      def 	UpperCAmelCase      (      self					:			Optional[int]					)							->      Optional[int]:
        __UpperCAmelCase							:	Optional[int]           =  20
        __UpperCAmelCase							:	Union[str, Any]           =  4
        __UpperCAmelCase							:	Tuple           =  0

        __UpperCAmelCase							:	Optional[int]           =  FlaxForcedBOSTokenLogitsProcessor(bos_token_id=__lowercase					)

        # check that all scores are -inf except the bos_token_id score
        __UpperCAmelCase							:	List[str]           =  ids_tensor((batch_size, 1)		,      vocab_size=20					)
        __UpperCAmelCase							:	Optional[Any]           =  1
        __UpperCAmelCase							:	str           =  self._get_uniform_logits(__lowercase		,      __lowercase					)
        __UpperCAmelCase							:	Dict           =  logits_processor(__lowercase		,      __lowercase		,      cur_len=__lowercase					)
        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							:	Dict           =  3
        __UpperCAmelCase							:	Optional[int]           =  self._get_uniform_logits(__lowercase		,      __lowercase					)
        __UpperCAmelCase							:	int           =  logits_processor(__lowercase		,      __lowercase		,      cur_len=__lowercase					)
        self.assertFalse(jnp.isinf(__lowercase					).any()					)
      def 	UpperCAmelCase      (      self					:			Optional[Any]					)							->      Dict:
        __UpperCAmelCase							:	Union[str, Any]           =  20
        __UpperCAmelCase							:	List[str]           =  4
        __UpperCAmelCase							:	Union[str, Any]           =  0
        __UpperCAmelCase							:	List[str]           =  5

        __UpperCAmelCase							:	Union[str, Any]           =  FlaxForcedEOSTokenLogitsProcessor(max_length=__lowercase		,      eos_token_id=__lowercase					)

        # check that all scores are -inf except the eos_token_id when max_length is reached
        __UpperCAmelCase							:	int           =  ids_tensor((batch_size, 4)		,      vocab_size=20					)
        __UpperCAmelCase							:	List[str]           =  4
        __UpperCAmelCase							:	Optional[int]           =  self._get_uniform_logits(__lowercase		,      __lowercase					)
        __UpperCAmelCase							:	int           =  logits_processor(__lowercase		,      __lowercase		,      cur_len=__lowercase					)
        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							:	Union[str, Any]           =  3
        __UpperCAmelCase							:	List[str]           =  self._get_uniform_logits(__lowercase		,      __lowercase					)
        __UpperCAmelCase							:	Dict           =  logits_processor(__lowercase		,      __lowercase		,      cur_len=__lowercase					)
        self.assertFalse(jnp.isinf(__lowercase					).any()					)
      def 	UpperCAmelCase      (      self					:			Optional[int]					)							->      int:
        __UpperCAmelCase							:	Tuple           =  4
        __UpperCAmelCase							:	Optional[int]           =  10
        __UpperCAmelCase							:	Union[str, Any]           =  15
        __UpperCAmelCase							:	Optional[int]           =  2
        __UpperCAmelCase							:	int           =  1
        __UpperCAmelCase							:	Optional[Any]           =  15

        # dummy input_ids and scores
        __UpperCAmelCase							:	Dict           =  ids_tensor((batch_size, sequence_length)		,      __lowercase					)
        __UpperCAmelCase							:	Optional[Any]           =  input_ids.copy()

        __UpperCAmelCase							:	str           =  self._get_uniform_logits(__lowercase		,      __lowercase					)
        __UpperCAmelCase							:	Union[str, Any]           =  scores.copy()

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

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

        __UpperCAmelCase							:	str           =  10

        # no processor list
        __UpperCAmelCase							:	Any           =  temp_dist_warp(__lowercase		,      __lowercase		,      cur_len=__lowercase					)
        __UpperCAmelCase							:	int           =  top_k_warp(__lowercase		,      __lowercase		,      cur_len=__lowercase					)
        __UpperCAmelCase							:	Any           =  top_p_warp(__lowercase		,      __lowercase		,      cur_len=__lowercase					)
        __UpperCAmelCase							:	Any           =  min_dist_proc(__lowercase		,      __lowercase		,      cur_len=__lowercase					)
        __UpperCAmelCase							:	Any           =  bos_dist_proc(__lowercase		,      __lowercase		,      cur_len=__lowercase					)
        __UpperCAmelCase							:	Dict           =  eos_dist_proc(__lowercase		,      __lowercase		,      cur_len=__lowercase					)

        # with processor list
        __UpperCAmelCase							:	Any           =  FlaxLogitsProcessorList(
            [temp_dist_warp, top_k_warp, top_p_warp, min_dist_proc, bos_dist_proc, eos_dist_proc]					)
        __UpperCAmelCase							:	Union[str, Any]           =  processor(__lowercase		,      __lowercase		,      cur_len=__lowercase					)

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

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




      def 	UpperCAmelCase      (      self					:			Dict					)							->      int:
        __UpperCAmelCase							:	str           =  4
        __UpperCAmelCase							:	Any           =  10
        __UpperCAmelCase							:	List[str]           =  15
        __UpperCAmelCase							:	int           =  2
        __UpperCAmelCase							:	Union[str, Any]           =  1
        __UpperCAmelCase							:	Union[str, Any]           =  15

        # dummy input_ids and scores
        __UpperCAmelCase							:	int           =  ids_tensor((batch_size, sequence_length)		,      __lowercase					)
        __UpperCAmelCase							:	Optional[int]           =  input_ids.copy()

        __UpperCAmelCase							:	Dict           =  self._get_uniform_logits(__lowercase		,      __lowercase					)
        __UpperCAmelCase							:	int           =  scores.copy()

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

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

        __UpperCAmelCase							:	Union[str, Any]           =  10

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

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

        __UpperCAmelCase							:	List[Any]           =  jax.jit(__lowercase					)
        __UpperCAmelCase							:	Union[str, Any]           =  jax.jit(__lowercase					)

        __UpperCAmelCase							:	List[str]           =  jitted_run_no_processor_list(__lowercase		,      __lowercase		,      __lowercase					)
        __UpperCAmelCase							:	Dict           =  jitted_run_processor_list(__lowercase		,      __lowercase		,      __lowercase					)

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

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










from math import log

from scipy.constants import Boltzmann, physical_constants

a		:       Any			     = 300  # TEMPERATURE (unit = K)






def 				lowerCamelCase__      (    __lowerCamelCase			:     float  ,		__lowerCamelCase			:     float  ,		__lowerCamelCase			:     float  ,		):

  if donor_conc <= 0:
    raise ValueError("""Donor concentration should be positive"""		)
  elif acceptor_conc <= 0:
    raise ValueError("""Acceptor concentration should be positive"""		)
  elif intrinsic_conc <= 0:
    raise ValueError("""Intrinsic concentration should be positive"""		)
  elif donor_conc <= intrinsic_conc:
    raise ValueError(
        """Donor concentration should be greater than intrinsic concentration"""		)
  elif acceptor_conc <= intrinsic_conc:
    raise ValueError(
        """Acceptor concentration should be greater than intrinsic concentration"""		)
  else:
    return (
        Boltzmann
        * T
        * log((donor_conc * acceptor_conc) / intrinsic_conc**2		)
        / physical_constants["electron volt"][0]
    )


if __name__ == "__main__":
       import doctest

       doctest.testmod()


