'''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        SCREAMING_SNAKE_CASE__       (			self		:		List[str]  ,    a		:		int  ,    a		:		int   ):





         """simple docstring"""



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






     def        SCREAMING_SNAKE_CASE__       (			self		:		List[str]   ):





         """simple docstring"""



         __lowerCamelCase          =  None
         __lowerCamelCase          =  20

         __lowerCamelCase          =  self._get_uniform_logits(batch_size=2  ,    length=lowerCAmelCase__   )

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

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

         __lowerCamelCase          =  FlaxTemperatureLogitsWarper(temperature=0.5   )
         __lowerCamelCase          =  FlaxTemperatureLogitsWarper(temperature=1.3   )

         __lowerCamelCase          =  jax.nn.softmax(temp_dist_warper_sharper(lowerCAmelCase__  ,    scores.copy()  ,    cur_len=lowerCAmelCase__   )  ,    axis=-1   )
         __lowerCamelCase          =  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        SCREAMING_SNAKE_CASE__       (			self		:		Union[str, Any]   ):





         """simple docstring"""



         __lowerCamelCase          =  None
         __lowerCamelCase          =  10
         __lowerCamelCase          =  2

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

         __lowerCamelCase          =  FlaxTopKLogitsWarper(3   )

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

         __lowerCamelCase          =  np.broadcast_to(np.arange(lowerCAmelCase__   )[None, :]  ,    (batch_size, length)   ).copy()
         __lowerCamelCase          =  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        SCREAMING_SNAKE_CASE__       (			self		:		List[str]   ):





         """simple docstring"""



         __lowerCamelCase          =  None
         __lowerCamelCase          =  10
         __lowerCamelCase          =  2

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

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

         # make ramp_logits more extreme
         __lowerCamelCase          =  ramp_logits[1] * 1_00.0

         # make sure at least 2 tokens are kept
         __lowerCamelCase          =  FlaxTopPLogitsWarper(0.9  ,    min_tokens_to_keep=2  ,    filter_value=0.0   )
         __lowerCamelCase          =  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        SCREAMING_SNAKE_CASE__       (			self		:		Any   ):





         """simple docstring"""



         __lowerCamelCase          =  20
         __lowerCamelCase          =  4
         __lowerCamelCase          =  0

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

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






     def        SCREAMING_SNAKE_CASE__       (			self		:		List[Any]   ):





         """simple docstring"""



         __lowerCamelCase          =  20
         __lowerCamelCase          =  4
         __lowerCamelCase          =  0

         __lowerCamelCase          =  FlaxForcedBOSTokenLogitsProcessor(bos_token_id=lowerCAmelCase__   )

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






     def        SCREAMING_SNAKE_CASE__       (			self		:		int   ):





         """simple docstring"""



         __lowerCamelCase          =  20
         __lowerCamelCase          =  4
         __lowerCamelCase          =  0
         __lowerCamelCase          =  5

         __lowerCamelCase          =  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          =  ids_tensor((batch_size, 4)  ,    vocab_size=20   )
         __lowerCamelCase          =  4
         __lowerCamelCase          =  self._get_uniform_logits(lowerCAmelCase__  ,    lowerCAmelCase__   )
         __lowerCamelCase          =  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          =  3
         __lowerCamelCase          =  self._get_uniform_logits(lowerCAmelCase__  ,    lowerCAmelCase__   )
         __lowerCamelCase          =  logits_processor(lowerCAmelCase__  ,    lowerCAmelCase__  ,    cur_len=lowerCAmelCase__   )
         self.assertFalse(jnp.isinf(lowerCAmelCase__   ).any()   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		Dict   ):





         """simple docstring"""



         __lowerCamelCase          =  4
         __lowerCamelCase          =  10
         __lowerCamelCase          =  15
         __lowerCamelCase          =  2
         __lowerCamelCase          =  1
         __lowerCamelCase          =  15

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

         __lowerCamelCase          =  self._get_uniform_logits(lowerCAmelCase__  ,    lowerCAmelCase__   )
         __lowerCamelCase          =  scores.copy()

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

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

         __lowerCamelCase          =  10

         # no processor list
         __lowerCamelCase          =  temp_dist_warp(lowerCAmelCase__  ,    lowerCAmelCase__  ,    cur_len=lowerCAmelCase__   )
         __lowerCamelCase          =  top_k_warp(lowerCAmelCase__  ,    lowerCAmelCase__  ,    cur_len=lowerCAmelCase__   )
         __lowerCamelCase          =  top_p_warp(lowerCAmelCase__  ,    lowerCAmelCase__  ,    cur_len=lowerCAmelCase__   )
         __lowerCamelCase          =  min_dist_proc(lowerCAmelCase__  ,    lowerCAmelCase__  ,    cur_len=lowerCAmelCase__   )
         __lowerCamelCase          =  bos_dist_proc(lowerCAmelCase__  ,    lowerCAmelCase__  ,    cur_len=lowerCAmelCase__   )
         __lowerCamelCase          =  eos_dist_proc(lowerCAmelCase__  ,    lowerCAmelCase__  ,    cur_len=lowerCAmelCase__   )

         # with processor list
         __lowerCamelCase          =  FlaxLogitsProcessorList(
             [temp_dist_warp, top_k_warp, top_p_warp, min_dist_proc, bos_dist_proc, eos_dist_proc]   )
         __lowerCamelCase          =  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        SCREAMING_SNAKE_CASE__       (			self		:		Optional[Any]   ):





         """simple docstring"""



         __lowerCamelCase          =  4
         __lowerCamelCase          =  10
         __lowerCamelCase          =  15
         __lowerCamelCase          =  2
         __lowerCamelCase          =  1
         __lowerCamelCase          =  15

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

         __lowerCamelCase          =  self._get_uniform_logits(lowerCAmelCase__  ,    lowerCAmelCase__   )
         __lowerCamelCase          =  scores.copy()

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

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

         __lowerCamelCase          =  10

         # no processor list
         def run_no_processor_list(a		:		Dict  ,    a		:		int  ,    a		:		Optional[int]   ):
             __lowerCamelCase          =  temp_dist_warp(lowerCAmelCase__  ,    lowerCAmelCase__  ,    cur_len=lowerCAmelCase__   )
             __lowerCamelCase          =  top_k_warp(lowerCAmelCase__  ,    lowerCAmelCase__  ,    cur_len=lowerCAmelCase__   )
             __lowerCamelCase          =  top_p_warp(lowerCAmelCase__  ,    lowerCAmelCase__  ,    cur_len=lowerCAmelCase__   )
             __lowerCamelCase          =  min_dist_proc(lowerCAmelCase__  ,    lowerCAmelCase__  ,    cur_len=lowerCAmelCase__   )
             __lowerCamelCase          =  bos_dist_proc(lowerCAmelCase__  ,    lowerCAmelCase__  ,    cur_len=lowerCAmelCase__   )
             __lowerCamelCase          =  eos_dist_proc(lowerCAmelCase__  ,    lowerCAmelCase__  ,    cur_len=lowerCAmelCase__   )
             return scores

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

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

         __lowerCamelCase          =  jitted_run_no_processor_list(lowerCAmelCase__  ,    lowerCAmelCase__  ,    lowerCAmelCase__   )
         __lowerCamelCase          =  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'''




from __future__ import annotations

from typing import Any






def __lowerCAmelCase			(							UpperCamelCase__    )     ->   None:
    create_state_space_tree(UpperCamelCase__    ,  []    ,  0    )






def __lowerCAmelCase			(							UpperCamelCase__    ,  UpperCamelCase__    ,  UpperCamelCase__    )     ->   None:

    if index == len(UpperCamelCase__    ):
        print(UpperCamelCase__    )
        return

    create_state_space_tree(UpperCamelCase__    ,  UpperCamelCase__    ,  index + 1    )
    current_subsequence.append(sequence[index]    )
    create_state_space_tree(UpperCamelCase__    ,  UpperCamelCase__    ,  index + 1    )
    current_subsequence.pop()


if __name__ == "__main__":
  __UpperCAmelCase												=[3, 1, 2, 4]
  generate_all_subsequences(seq)

  seq.clear()
  seq.extend(["A", "B", "C"])
  generate_all_subsequences(seq)
