


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()							)






from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase	=							logging.get_logger(__name__)

lowerCAmelCase	=							{
    'unc-nlp/lxmert-base-uncased': 'https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json',
}


class 	_a							(      UpperCamelCase__      ):
							_lowercase     :      List[Any]  				=			'''lxmert'''
							_lowercase     :      Any  				=			{}

							def __init__(							self:     Any   ,						UpperCamelCase_:     List[Any]=30_522   ,						UpperCamelCase_:     int=768   ,						UpperCamelCase_:     Optional[Any]=12   ,						UpperCamelCase_:     Dict=9_500   ,						UpperCamelCase_:     List[Any]=1_600   ,						UpperCamelCase_:     List[Any]=400   ,						UpperCamelCase_:     List[str]=3_072   ,						UpperCamelCase_:     int="gelu"   ,						UpperCamelCase_:     Any=0.1   ,						UpperCamelCase_:     int=0.1   ,						UpperCamelCase_:     List[str]=512   ,						UpperCamelCase_:     Optional[int]=2   ,						UpperCamelCase_:     Union[str, Any]=0.02   ,						UpperCamelCase_:     Dict=1E-1_2   ,						UpperCamelCase_:     List[Any]=9   ,						UpperCamelCase_:     List[Any]=5   ,						UpperCamelCase_:     Optional[Any]=5   ,						UpperCamelCase_:     str=2_048   ,						UpperCamelCase_:     Dict=4   ,						UpperCamelCase_:     Any=6.67   ,						UpperCamelCase_:     Dict=True   ,						UpperCamelCase_:     List[str]=True   ,						UpperCamelCase_:     Dict=True   ,						UpperCamelCase_:     Any=True   ,						UpperCamelCase_:     Tuple=True   ,						UpperCamelCase_:     Optional[Any]=True   ,						UpperCamelCase_:     Any=True   ,						**UpperCamelCase_:     Union[str, Any]   ,						)      ->       Union[str, Any]:





									"""simple docstring"""







									lowercase__						=				vocab_size
									lowercase__						=				hidden_size
									lowercase__						=				num_attention_heads
									lowercase__						=				hidden_act
									lowercase__						=				intermediate_size
									lowercase__						=				hidden_dropout_prob
									lowercase__						=				attention_probs_dropout_prob
									lowercase__						=				max_position_embeddings
									lowercase__						=				type_vocab_size
									lowercase__						=				initializer_range
									lowercase__						=				layer_norm_eps
									lowercase__						=				num_qa_labels
									lowercase__						=				num_object_labels
									lowercase__						=				num_attr_labels
									lowercase__						=				l_layers
									lowercase__						=				x_layers
									lowercase__						=				r_layers
									lowercase__						=				visual_feat_dim
									lowercase__						=				visual_pos_dim
									lowercase__						=				visual_loss_normalizer
									lowercase__						=				task_matched
									lowercase__						=				task_mask_lm
									lowercase__						=				task_obj_predict
									lowercase__						=				task_qa
									lowercase__						=				visual_obj_loss
									lowercase__						=				visual_attr_loss
									lowercase__						=				visual_feat_loss
									lowercase__						=				{'''vision''': r_layers, '''cross_encoder''': x_layers, '''language''': l_layers}
									super().__init__(**UpperCamelCase_							)


