



"""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    :	Optional[int]							,       __lowerCamelCase    :	Union[str, Any]							,       __lowerCamelCase    :	Tuple				):



     """simple docstring"""
     _snake_case   	=      jnp.ones((batch_size, length)				) / length
     return scores



   def    __UpperCAmelCase    (       self    :	Dict				):



     """simple docstring"""
     _snake_case   	=      None
     _snake_case   	=      2_0

     _snake_case   	=      self._get_uniform_logits(batch_size=2							,       length=lowerCamelCase__				)

     # tweak scores to not be uniform anymore
     _snake_case   	=      scores.at[1, 5].set((1 / length) + 0.1				)  # peak, 1st batch
     _snake_case   	=      scores.at[1, 1_0].set((1 / length) - 0.4				)  # valley, 1st batch

     # compute softmax
     _snake_case   	=      jax.nn.softmax(lowerCamelCase__							,       axis=-1				)

     _snake_case   	=      FlaxTemperatureLogitsWarper(temperature=0.5				)
     _snake_case   	=      FlaxTemperatureLogitsWarper(temperature=1.3				)

     _snake_case   	=      jax.nn.softmax(temp_dist_warper_sharper(lowerCamelCase__							,       scores.copy()							,       cur_len=lowerCamelCase__				)							,       axis=-1				)
     _snake_case   	=      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    :	str				):



     """simple docstring"""
     _snake_case   	=      None
     _snake_case   	=      1_0
     _snake_case   	=      2

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

     _snake_case   	=      FlaxTopKLogitsWarper(3				)

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

     _snake_case   	=      np.broadcast_to(np.arange(lowerCamelCase__				)[None, :]							,       (batch_size, length)				).copy()
     _snake_case   	=      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    :	Tuple				):



     """simple docstring"""
     _snake_case   	=      None
     _snake_case   	=      1_0
     _snake_case   	=      2

     # create distribution and take log (inverse to Softmax as taken in TopPLogitsWarper)
     _snake_case   	=      np.log(np.array([[0.3, 0.1, 0.1, 0.5], [0.1_5, 0.3, 0.3, 0.2_5]]				)				)

     _snake_case   	=      FlaxTopPLogitsWarper(0.8				)
     _snake_case   	=      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
     _snake_case   	=      np.array([[0.3, 0.0, 0.0, 0.5], [0.0, 0.3, 0.3, 0.2_5]]				)
     self.assertTrue(np.allclose(lowerCamelCase__							,       lowerCamelCase__							,       atol=1E-3				)				)

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

     # make ramp_logits more extreme
     _snake_case   	=      ramp_logits[1] * 1_0_0.0

     # make sure at least 2 tokens are kept
     _snake_case   	=      FlaxTopPLogitsWarper(0.9							,       min_tokens_to_keep=2							,       filter_value=0.0				)
     _snake_case   	=      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    :	List[str]				):



     """simple docstring"""
     _snake_case   	=      2_0
     _snake_case   	=      4
     _snake_case   	=      0

     _snake_case   	=      FlaxMinLengthLogitsProcessor(min_length=1_0							,       eos_token_id=lowerCamelCase__				)

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



   def    __UpperCAmelCase    (       self    :	str				):



     """simple docstring"""
     _snake_case   	=      2_0
     _snake_case   	=      4
     _snake_case   	=      0

     _snake_case   	=      FlaxForcedBOSTokenLogitsProcessor(bos_token_id=lowerCamelCase__				)

     # check that all scores are -inf except the bos_token_id score
     _snake_case   	=      ids_tensor((batch_size, 1)							,       vocab_size=2_0				)
     _snake_case   	=      1
     _snake_case   	=      self._get_uniform_logits(lowerCamelCase__							,       lowerCamelCase__				)
     _snake_case   	=      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
     _snake_case   	=      3
     _snake_case   	=      self._get_uniform_logits(lowerCamelCase__							,       lowerCamelCase__				)
     _snake_case   	=      logits_processor(lowerCamelCase__							,       lowerCamelCase__							,       cur_len=lowerCamelCase__				)
     self.assertFalse(jnp.isinf(lowerCamelCase__				).any()				)



   def    __UpperCAmelCase    (       self    :	int				):



     """simple docstring"""
     _snake_case   	=      2_0
     _snake_case   	=      4
     _snake_case   	=      0
     _snake_case   	=      5

     _snake_case   	=      FlaxForcedEOSTokenLogitsProcessor(max_length=lowerCamelCase__							,       eos_token_id=lowerCamelCase__				)

     # check that all scores are -inf except the eos_token_id when max_length is reached
     _snake_case   	=      ids_tensor((batch_size, 4)							,       vocab_size=2_0				)
     _snake_case   	=      4
     _snake_case   	=      self._get_uniform_logits(lowerCamelCase__							,       lowerCamelCase__				)
     _snake_case   	=      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
     _snake_case   	=      3
     _snake_case   	=      self._get_uniform_logits(lowerCamelCase__							,       lowerCamelCase__				)
     _snake_case   	=      logits_processor(lowerCamelCase__							,       lowerCamelCase__							,       cur_len=lowerCamelCase__				)
     self.assertFalse(jnp.isinf(lowerCamelCase__				).any()				)



   def    __UpperCAmelCase    (       self    :	Tuple				):



     """simple docstring"""
     _snake_case   	=      4
     _snake_case   	=      1_0
     _snake_case   	=      1_5
     _snake_case   	=      2
     _snake_case   	=      1
     _snake_case   	=      1_5

     # dummy input_ids and scores
     _snake_case   	=      ids_tensor((batch_size, sequence_length)							,       lowerCamelCase__				)
     _snake_case   	=      input_ids.copy()

     _snake_case   	=      self._get_uniform_logits(lowerCamelCase__							,       lowerCamelCase__				)
     _snake_case   	=      scores.copy()

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

     # instantiate all logits processors
     _snake_case   	=      FlaxMinLengthLogitsProcessor(min_length=1_0							,       eos_token_id=lowerCamelCase__				)
     _snake_case   	=      FlaxForcedBOSTokenLogitsProcessor(bos_token_id=lowerCamelCase__				)
     _snake_case   	=      FlaxForcedEOSTokenLogitsProcessor(max_length=lowerCamelCase__							,       eos_token_id=lowerCamelCase__				)

     _snake_case   	=      1_0

     # no processor list
     _snake_case   	=      temp_dist_warp(lowerCamelCase__							,       lowerCamelCase__							,       cur_len=lowerCamelCase__				)
     _snake_case   	=      top_k_warp(lowerCamelCase__							,       lowerCamelCase__							,       cur_len=lowerCamelCase__				)
     _snake_case   	=      top_p_warp(lowerCamelCase__							,       lowerCamelCase__							,       cur_len=lowerCamelCase__				)
     _snake_case   	=      min_dist_proc(lowerCamelCase__							,       lowerCamelCase__							,       cur_len=lowerCamelCase__				)
     _snake_case   	=      bos_dist_proc(lowerCamelCase__							,       lowerCamelCase__							,       cur_len=lowerCamelCase__				)
     _snake_case   	=      eos_dist_proc(lowerCamelCase__							,       lowerCamelCase__							,       cur_len=lowerCamelCase__				)

     # with processor list
     _snake_case   	=      FlaxLogitsProcessorList(
         [temp_dist_warp, top_k_warp, top_p_warp, min_dist_proc, bos_dist_proc, eos_dist_proc]				)
     _snake_case   	=      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    :	List[str]				):



     """simple docstring"""
     _snake_case   	=      4
     _snake_case   	=      1_0
     _snake_case   	=      1_5
     _snake_case   	=      2
     _snake_case   	=      1
     _snake_case   	=      1_5

     # dummy input_ids and scores
     _snake_case   	=      ids_tensor((batch_size, sequence_length)							,       lowerCamelCase__				)
     _snake_case   	=      input_ids.copy()

     _snake_case   	=      self._get_uniform_logits(lowerCamelCase__							,       lowerCamelCase__				)
     _snake_case   	=      scores.copy()

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

     # instantiate all logits processors
     _snake_case   	=      FlaxMinLengthLogitsProcessor(min_length=1_0							,       eos_token_id=lowerCamelCase__				)
     _snake_case   	=      FlaxForcedBOSTokenLogitsProcessor(bos_token_id=lowerCamelCase__				)
     _snake_case   	=      FlaxForcedEOSTokenLogitsProcessor(max_length=lowerCamelCase__							,       eos_token_id=lowerCamelCase__				)

     _snake_case   	=      1_0

     # no processor list
     def run_no_processor_list(__lowerCamelCase    :	Optional[Any]							,       __lowerCamelCase    :	Union[str, Any]							,       __lowerCamelCase    :	Optional[int]				):
       _snake_case   	=      temp_dist_warp(lowerCamelCase__							,       lowerCamelCase__							,       cur_len=lowerCamelCase__				)
       _snake_case   	=      top_k_warp(lowerCamelCase__							,       lowerCamelCase__							,       cur_len=lowerCamelCase__				)
       _snake_case   	=      top_p_warp(lowerCamelCase__							,       lowerCamelCase__							,       cur_len=lowerCamelCase__				)
       _snake_case   	=      min_dist_proc(lowerCamelCase__							,       lowerCamelCase__							,       cur_len=lowerCamelCase__				)
       _snake_case   	=      bos_dist_proc(lowerCamelCase__							,       lowerCamelCase__							,       cur_len=lowerCamelCase__				)
       _snake_case   	=      eos_dist_proc(lowerCamelCase__							,       lowerCamelCase__							,       cur_len=lowerCamelCase__				)
       return scores

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

     _snake_case   	=      jax.jit(lowerCamelCase__				)
     _snake_case   	=      jax.jit(lowerCamelCase__				)

     _snake_case   	=      jitted_run_no_processor_list(lowerCamelCase__							,       lowerCamelCase__							,       lowerCamelCase__				)
     _snake_case   	=      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()				)








import fire

from utils import calculate_rouge, save_json



def 			_A	(      SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE=None	,**SCREAMING_SNAKE_CASE      ):
	UpperCAmelCase__:	Tuple									= [x.strip() for x in open(SCREAMING_SNAKE_CASE      ).readlines()]
	UpperCAmelCase__:	Dict									= [x.strip() for x in open(SCREAMING_SNAKE_CASE      ).readlines()][: len(SCREAMING_SNAKE_CASE      )]
	UpperCAmelCase__:	Any									= calculate_rouge(SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE	,**SCREAMING_SNAKE_CASE      )
	if save_path is not None:
		save_json(SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE	,indent=SCREAMING_SNAKE_CASE      )
	return metrics  # these print nicely


if __name__ == "__main__":
					fire.Fire(calculate_rouge_path)