

"""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 					_lowerCAmelCase  (	unittest.TestCase   ):







 """simple docstring"""







 def 					_lowercase (			self							:			Dict,					UpperCAmelCase__							:			int,					UpperCAmelCase__							:			int	):
    __lowercase								=						jnp.ones((batch_size, length)	) / length
    return scores


 def 					_lowercase (			self							:			Union[str, Any]	):
    __lowercase								=						None
    __lowercase								=						2_0

    __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, 1_0].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 					_lowercase (			self							:			Union[str, Any]	):
    __lowercase								=						None
    __lowercase								=						1_0
    __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 					_lowercase (			self							:			Any	):
    __lowercase								=						None
    __lowercase								=						1_0
    __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 					_lowercase (			self							:			List[Any]	):
    __lowercase								=						2_0
    __lowercase								=						4
    __lowercase								=						0

    __lowercase								=						FlaxMinLengthLogitsProcessor(min_length=1_0,					eos_token_id=UpperCAmelCase__	)

    # check that min length is applied at length 5
    __lowercase								=						ids_tensor((batch_size, 2_0),					vocab_size=2_0	)
    __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								=						1_5
    __lowercase								=						min_dist_processor(UpperCAmelCase__,					UpperCAmelCase__,					cur_len=UpperCAmelCase__	)
    self.assertFalse(jnp.isinf(UpperCAmelCase__	).any()	)


 def 					_lowercase (			self							:			Tuple	):
    __lowercase								=						2_0
    __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=2_0	)
    __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 					_lowercase (			self							:			List[Any]	):
    __lowercase								=						2_0
    __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=2_0	)
    __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 					_lowercase (			self							:			Union[str, Any]	):
    __lowercase								=						4
    __lowercase								=						1_0
    __lowercase								=						1_5
    __lowercase								=						2
    __lowercase								=						1
    __lowercase								=						1_5

    # 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=1_0,					eos_token_id=UpperCAmelCase__	)
    __lowercase								=						FlaxForcedBOSTokenLogitsProcessor(bos_token_id=UpperCAmelCase__	)
    __lowercase								=						FlaxForcedEOSTokenLogitsProcessor(max_length=UpperCAmelCase__,					eos_token_id=UpperCAmelCase__	)

    __lowercase								=						1_0

    # 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 					_lowercase (			self							:			List[Any]	):
    __lowercase								=						4
    __lowercase								=						1_0
    __lowercase								=						1_5
    __lowercase								=						2
    __lowercase								=						1
    __lowercase								=						1_5

    # 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=1_0,					eos_token_id=UpperCAmelCase__	)
    __lowercase								=						FlaxForcedBOSTokenLogitsProcessor(bos_token_id=UpperCAmelCase__	)
    __lowercase								=						FlaxForcedEOSTokenLogitsProcessor(max_length=UpperCAmelCase__,					eos_token_id=UpperCAmelCase__	)

    __lowercase								=						1_0

    # no processor list
    def run_no_processor_list(UpperCAmelCase__							:			str,					UpperCAmelCase__							:			Optional[Any],					UpperCAmelCase__							:			Any	):
       __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__							:			List[str],					UpperCAmelCase__							:			List[str],					UpperCAmelCase__							:			Optional[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()	)







"""simple docstring"""





import baseaa




def   _A  (  UpperCamelCase_     :       str)	->						bytes:
   '''simple docstring'''


   return baseaa.baaencode(string.encode("utf-8"))




def   _A  (  UpperCamelCase_     :       bytes)	->						str:
   '''simple docstring'''


   return baseaa.baadecode(UpperCamelCase_).decode("utf-8")


if __name__ == "__main__":
   _a       =							'Hello World!'
   _a       =							baseaa_encode(test)
   print(encoded)

   _a       =							baseaa_decode(encoded)
   print(decoded)




