




import unittest

from transformers import (
    MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
    TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
    SummarizationPipeline,
    TFPreTrainedModel,
    pipeline,
)
from transformers.testing_utils import get_gpu_count, is_pipeline_test, require_tf, require_torch, slow, torch_device
from transformers.tokenization_utils import TruncationStrategy

from .test_pipelines_common import ANY


__SCREAMING_SNAKE_CASE      :				Union[str, Any]				      =-1 if torch_device == """cpu""" else 0






@is_pipeline_test
class      A     (						unittest.TestCase						):
     """simple docstring"""

     _snake_case:		Tuple       =MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
     _snake_case:		int       =TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING




     def 	__snake_case				(      self					:				Any		,					A__					:				str		,					A__					:				int		,					A__					:				Dict     )			->    Any:
           lowerCamelCase__ 					=			SummarizationPipeline(model=A__		,					tokenizer=A__     )
           return summarizer, ["(CNN)The Palestinian Authority officially became", "Some other text"]




     def 	__snake_case				(      self					:				int		,					A__					:				int		,					A__					:				Tuple     )			->    Tuple:
           lowerCamelCase__ 					=			summarizer.model

           lowerCamelCase__ 					=			summarizer('(CNN)The Palestinian Authority officially became'     )
           self.assertEqual(A__		,					[{'summary_text': ANY(A__     )}]     )

           lowerCamelCase__ 					=			summarizer(
               '(CNN)The Palestinian Authority officially became '		,					num_beams=2		,					min_length=2		,					max_length=5		,					)
           self.assertEqual(A__		,					[{'summary_text': ANY(A__     )}]     )

           # Some models (Switch Transformers, LED, T5, LongT5, etc) can handle long sequences.
           lowerCamelCase__ 					=			[
               'SwitchTransformersConfig',
               'T5Config',
               'LongT5Config',
               'LEDConfig',
               'PegasusXConfig',
               'FSMTConfig',
               'M2M100Config',
               'ProphetNetConfig',  # positional embeddings up to a fixed maximum size (otherwise clamping the values)
           ]
           if model.config.__class__.__name__ not in model_can_handle_longer_seq:
                 # Too long and exception is expected.
                 # For TF models, if the weights are initialized in GPU context, we won't get expected index error from
                 # the embedding layer.
                 if not (
                     isinstance(A__		,					A__     )
                     and get_gpu_count() > 0
                     and len(summarizer.model.trainable_weights     ) > 0
                 ):
                       with self.assertRaises(A__     ):
                             lowerCamelCase__ 					=			summarizer('This ' * 1_0_0_0     )
           lowerCamelCase__ 					=			summarizer('This ' * 1_0_0_0		,					truncation=TruncationStrategy.ONLY_FIRST     )




     @require_torch
     def 	__snake_case				(      self					:				str     )			->    Union[str, Any]:
           lowerCamelCase__ 					=			pipeline(task='summarization'		,					model='sshleifer/tiny-mbart'		,					framework='pt'     )
           lowerCamelCase__ 					=			summarizer('This is a small test'     )
           self.assertEqual(
               A__		,					[
                   {
                       'summary_text': 'เข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไป'
                   }
               ]		,					)




     @require_tf
     def 	__snake_case				(      self					:				List[str]     )			->    List[str]:
           lowerCamelCase__ 					=			pipeline(task='summarization'		,					model='sshleifer/tiny-mbart'		,					framework='tf'     )
           lowerCamelCase__ 					=			summarizer('This is a small test'     )
           self.assertEqual(
               A__		,					[
                   {
                       'summary_text': 'เข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไป'
                   }
               ]		,					)




     @require_torch
     @slow
     def 	__snake_case				(      self					:				List[str]     )			->    Tuple:
           lowerCamelCase__ 					=			pipeline(task='summarization'		,					device=A__     )
           lowerCamelCase__ 					=			(
               ' (CNN)The Palestinian Authority officially became the 123rd member of the International Criminal Court on'
               ' Wednesday, a step that gives the court jurisdiction over alleged crimes in Palestinian territories. The'
               ' formal accession was marked with a ceremony at The Hague, in the Netherlands, where the court is based.'
               ' The Palestinians signed the ICC\'s founding Rome Statute in January, when they also accepted its'
               ' jurisdiction over alleged crimes committed "in the occupied Palestinian territory, including East'
               ' Jerusalem, since June 13, 2014." Later that month, the ICC opened a preliminary examination into the'
               ' situation in Palestinian territories, paving the way for possible war crimes investigations against'
               ' Israelis. As members of the court, Palestinians may be subject to counter-charges as well. Israel and'
               ' the United States, neither of which is an ICC member, opposed the Palestinians\' efforts to join the'
               ' body. But Palestinian Foreign Minister Riad al-Malki, speaking at Wednesday\'s ceremony, said it was a'
               ' move toward greater justice. "As Palestine formally becomes a State Party to the Rome Statute today, the'
               ' world is also a step closer to ending a long era of impunity and injustice," he said, according to an'
               ' ICC news release. "Indeed, today brings us closer to our shared goals of justice and peace." Judge'
               ' Kuniko Ozaki, a vice president of the ICC, said acceding to the treaty was just the first step for the'
               ' Palestinians. "As the Rome Statute today enters into force for the State of Palestine, Palestine'
               ' acquires all the rights as well as responsibilities that come with being a State Party to the Statute.'
               ' These are substantive commitments, which cannot be taken lightly," she said. Rights group Human Rights'
               ' Watch welcomed the development. "Governments seeking to penalize Palestine for joining the ICC should'
               ' immediately end their pressure, and countries that support universal acceptance of the court\'s treaty'
               ' should speak out to welcome its membership," said Balkees Jarrah, international justice counsel for the'
               ' group. \"What\'s objectionable is the attempts to undermine international justice, not Palestine\'s'
               ' decision to join a treaty to which over 100 countries around the world are members." In January, when'
               ' the preliminary ICC examination was opened, Israeli Prime Minister Benjamin Netanyahu described it as an'
               ' outrage, saying the court was overstepping its boundaries. The United States also said it "strongly"'
               ' disagreed with the court\'s decision. \"As we have said repeatedly, we do not believe that Palestine is a'
               ' state and therefore we do not believe that it is eligible to join the ICC," the State Department said in'
               ' a statement. It urged the warring sides to resolve their differences through direct negotiations. "We'
               ' will continue to oppose actions against Israel at the ICC as counterproductive to the cause of peace,"'
               ' it said. But the ICC begs to differ with the definition of a state for its purposes and refers to the'
               ' territories as "Palestine." While a preliminary examination is not a formal investigation, it allows the'
               ' court to review evidence and determine whether to investigate suspects on both sides. Prosecutor Fatou'
               ' Bensouda said her office would "conduct its analysis in full independence and impartiality." The war'
               ' between Israel and Hamas militants in Gaza last summer left more than 2,000 people dead. The inquiry'
               ' will include alleged war crimes committed since June. The International Criminal Court was set up in'
               ' 2002 to prosecute genocide, crimes against humanity and war crimes. CNN\'s Vasco Cotovio, Kareem Khadder'
               ' and Faith Karimi contributed to this report.'
           )
           lowerCamelCase__ 					=			(
               ' The Palestinian Authority becomes the 123rd member of the International Criminal Court . The move gives'
               ' the court jurisdiction over alleged crimes in Palestinian territories . Israel and the United States'
               ' opposed the Palestinians\' efforts to join the court . Rights group Human Rights Watch welcomes the move,'
               ' says governments seeking to penalize Palestine should end pressure .'
           )
           lowerCamelCase__ 					=			summarizer(A__     )
           self.assertEqual(result[0]['summary_text']		,					A__     )








from typing import Dict, Tuple, overload

import torch
import torch.types
from torch import nn

from . import residue_constants as rc
from .rigid_utils import Rigid, Rotation
from .tensor_utils import batched_gather

@overload
def      lowerCAmelCase_     (					lowerCamelCase:    torch.Tensor       ,			lowerCamelCase:    torch.Tensor       ,			lowerCamelCase:    None  )   ->     torch.Tensor:


      '''simple docstring'''




      ...

@overload
def      lowerCAmelCase_     (					lowerCamelCase:    torch.Tensor       ,			lowerCamelCase:    torch.Tensor       ,			lowerCamelCase:    torch.Tensor  )   ->     Tuple[torch.Tensor, torch.Tensor]:


      '''simple docstring'''




      ...

def      lowerCAmelCase_     (					lowerCamelCase:    Any       ,			lowerCamelCase:    Union[str, Any]       ,			lowerCamelCase:    Tuple  )   ->     int:


      '''simple docstring'''




      lowerCamelCase__ 					=			aatype == rc.restype_order['G']
      lowerCamelCase__ 					=			rc.atom_order['CA']
      lowerCamelCase__ 					=			rc.atom_order['CB']
      lowerCamelCase__ 					=			torch.where(
          is_gly[..., None].expand(*((-1,) * len(is_gly.shape  ))       ,			3  )       ,			all_atom_positions[..., ca_idx, :]       ,			all_atom_positions[..., cb_idx, :]       ,			)

      if all_atom_masks is not None:
            lowerCamelCase__ 					=			torch.where(
                lowerCamelCase       ,			all_atom_masks[..., ca_idx]       ,			all_atom_masks[..., cb_idx]       ,			)
            return pseudo_beta, pseudo_beta_mask
      else:
            return pseudo_beta

def      lowerCAmelCase_     (					lowerCamelCase:    torch.Tensor       ,			lowerCamelCase:    Dict[str, torch.Tensor]  )   ->     torch.Tensor:


      '''simple docstring'''




      lowerCamelCase__ 					=			batched_gather(
          lowerCamelCase       ,			batch['residx_atom37_to_atom14']       ,			dim=-2       ,			no_batch_dims=len(atomaa.shape[:-2]  )       ,			)

      lowerCamelCase__ 					=			atomaa_data * batch['atom37_atom_exists'][..., None]

      return atomaa_data

def      lowerCAmelCase_     (					lowerCamelCase:    Dict[str, torch.Tensor]  )   ->     torch.Tensor:


      '''simple docstring'''




      lowerCamelCase__ 					=			template_feats['template_aatype']
      lowerCamelCase__ 					=			template_feats['template_torsion_angles_sin_cos']
      lowerCamelCase__ 					=			template_feats['template_alt_torsion_angles_sin_cos']
      lowerCamelCase__ 					=			template_feats['template_torsion_angles_mask']
      lowerCamelCase__ 					=			torch.cat(
          [
              nn.functional.one_hot(lowerCamelCase       ,			22  ),
              torsion_angles_sin_cos.reshape(*torsion_angles_sin_cos.shape[:-2]       ,			14  ),
              alt_torsion_angles_sin_cos.reshape(*alt_torsion_angles_sin_cos.shape[:-2]       ,			14  ),
              torsion_angles_mask,
          ]       ,			dim=-1       ,			)

      return template_angle_feat

def      lowerCAmelCase_     (					lowerCamelCase:    Dict[str, torch.Tensor]       ,			lowerCamelCase:    torch.types.Number       ,			lowerCamelCase:    torch.types.Number       ,			lowerCamelCase:    int       ,			lowerCamelCase:    bool = False       ,			lowerCamelCase:    float = 1e-20       ,			lowerCamelCase:    float = 1e8       ,			)   ->     torch.Tensor:


      '''simple docstring'''




      lowerCamelCase__ 					=			batch['template_pseudo_beta_mask']
      lowerCamelCase__ 					=			template_mask[..., None] * template_mask[..., None, :]

      # Compute distogram (this seems to differ slightly from Alg. 5)
      lowerCamelCase__ 					=			batch['template_pseudo_beta']
      lowerCamelCase__ 					=			torch.sum((tpb[..., None, :] - tpb[..., None, :, :]) ** 2       ,			dim=-1       ,			keepdim=lowerCamelCase  )
      lowerCamelCase__ 					=			torch.linspace(lowerCamelCase       ,			lowerCamelCase       ,			lowerCamelCase       ,			device=tpb.device  ) ** 2
      lowerCamelCase__ 					=			torch.cat([lower[1:], lower.new_tensor([inf]  )]       ,			dim=-1  )
      lowerCamelCase__ 					=			((dgram > lower) * (dgram < upper)).type(dgram.dtype  )

      lowerCamelCase__ 					=			[dgram, template_mask_ad[..., None]]

      lowerCamelCase__ 					=			nn.functional.one_hot(
          batch['template_aatype']       ,			rc.restype_num + 2       ,			)

      lowerCamelCase__ 					=			batch['template_aatype'].shape[-1]
      to_concat.append(aatype_one_hot[..., None, :, :].expand(*aatype_one_hot.shape[:-2]       ,			lowerCamelCase       ,			-1       ,			-1  )  )
      to_concat.append(aatype_one_hot[..., None, :].expand(*aatype_one_hot.shape[:-2]       ,			-1       ,			lowerCamelCase       ,			-1  )  )

      lowerCamelCase__					,						lowerCamelCase__					,						lowerCamelCase__ 					=			[rc.atom_order[a] for a in ['N', 'CA', 'C']]
      lowerCamelCase__ 					=			Rigid.make_transform_from_reference(
          n_xyz=batch['template_all_atom_positions'][..., n, :]       ,			ca_xyz=batch['template_all_atom_positions'][..., ca, :]       ,			c_xyz=batch['template_all_atom_positions'][..., c, :]       ,			eps=lowerCamelCase       ,			)
      lowerCamelCase__ 					=			rigids.get_trans()[..., None, :, :]
      lowerCamelCase__ 					=			rigids[..., None].invert_apply(lowerCamelCase  )

      lowerCamelCase__ 					=			torch.rsqrt(eps + torch.sum(rigid_vec**2       ,			dim=-1  )  )

      lowerCamelCase__ 					=			batch['template_all_atom_mask']
      lowerCamelCase__ 					=			t_aa_masks[..., n] * t_aa_masks[..., ca] * t_aa_masks[..., c]
      lowerCamelCase__ 					=			template_mask[..., None] * template_mask[..., None, :]

      lowerCamelCase__ 					=			inv_distance_scalar * template_mask_ad
      lowerCamelCase__ 					=			rigid_vec * inv_distance_scalar[..., None]

      if not use_unit_vector:
            lowerCamelCase__ 					=			unit_vector * 0.0

      to_concat.extend(torch.unbind(unit_vector[..., None, :]       ,			dim=-1  )  )
      to_concat.append(template_mask_ad[..., None]  )

      lowerCamelCase__ 					=			torch.cat(lowerCamelCase       ,			dim=-1  )
      lowerCamelCase__ 					=			act * template_mask_ad[..., None]

      return act

def      lowerCAmelCase_     (					lowerCamelCase:    Dict[str, torch.Tensor]  )   ->     torch.Tensor:


      '''simple docstring'''




      lowerCamelCase__ 					=			nn.functional.one_hot(batch['extra_msa']       ,			23  )
      lowerCamelCase__ 					=			[
          msa_ahot,
          batch['extra_has_deletion'].unsqueeze(-1  ),
          batch['extra_deletion_value'].unsqueeze(-1  ),
      ]
      return torch.cat(lowerCamelCase       ,			dim=-1  )

def      lowerCAmelCase_     (					lowerCamelCase:    Rigid       ,			lowerCamelCase:    torch.Tensor       ,			lowerCamelCase:    torch.Tensor       ,			lowerCamelCase:    torch.Tensor       ,			)   ->     Rigid:


      '''simple docstring'''




      lowerCamelCase__ 					=			rrgdf[aatype, ...]

      # [*, N, 8] transformations, i.e.
      #   One [*, N, 8, 3, 3] rotation matrix and
      #   One [*, N, 8, 3]    translation matrix
      lowerCamelCase__ 					=			r.from_tensor_axa(lowerCamelCase  )

      lowerCamelCase__ 					=			alpha.new_zeros((*((1,) * len(alpha.shape[:-1]  )), 2)  )
      lowerCamelCase__ 					=			1

      # [*, N, 8, 2]
      lowerCamelCase__ 					=			torch.cat([bb_rot.expand(*alpha.shape[:-2]       ,			-1       ,			-1  ), alpha]       ,			dim=-2  )

      # [*, N, 8, 3, 3]
      # Produces rotation matrices of the form:
      # [
      #   [1, 0  , 0  ],
      #   [0, a_2,-a_1],
      #   [0, a_1, a_2]
      # ]
      # This follows the original code rather than the supplement, which uses
      # different indices.

      lowerCamelCase__ 					=			alpha.new_zeros(default_r.get_rots().get_rot_mats().shape  )
      lowerCamelCase__ 					=			1
      lowerCamelCase__ 					=			alpha[..., 1]
      lowerCamelCase__ 					=			-alpha[..., 0]
      lowerCamelCase__ 					=			alpha

      lowerCamelCase__ 					=			default_r.compose(Rigid(Rotation(rot_mats=lowerCamelCase  )       ,			lowerCamelCase  )  )

      lowerCamelCase__ 					=			all_frames[..., 5]
      lowerCamelCase__ 					=			all_frames[..., 6]
      lowerCamelCase__ 					=			all_frames[..., 7]

      lowerCamelCase__ 					=			all_frames[..., 4]
      lowerCamelCase__ 					=			chia_frame_to_bb.compose(lowerCamelCase  )
      lowerCamelCase__ 					=			chia_frame_to_bb.compose(lowerCamelCase  )
      lowerCamelCase__ 					=			chia_frame_to_bb.compose(lowerCamelCase  )

      lowerCamelCase__ 					=			Rigid.cat(
          [
              all_frames[..., :5],
              chia_frame_to_bb.unsqueeze(-1  ),
              chia_frame_to_bb.unsqueeze(-1  ),
              chia_frame_to_bb.unsqueeze(-1  ),
          ]       ,			dim=-1       ,			)

      lowerCamelCase__ 					=			r[..., None].compose(lowerCamelCase  )

      return all_frames_to_global


def      lowerCAmelCase_     (					lowerCamelCase:    Rigid       ,			lowerCamelCase:    torch.Tensor       ,			lowerCamelCase:    torch.Tensor       ,			lowerCamelCase:    torch.Tensor       ,			lowerCamelCase:    torch.Tensor       ,			lowerCamelCase:    torch.Tensor       ,			)   ->     torch.Tensor:


      '''simple docstring'''




      lowerCamelCase__ 					=			group_idx[aatype, ...]

      # [*, N, 14, 8]
      lowerCamelCase__ 					=			nn.functional.one_hot(
          lowerCamelCase       ,			num_classes=default_frames.shape[-3]       ,			)

      # [*, N, 14, 8]
      lowerCamelCase__ 					=			r[..., None, :] * group_mask_one_hot

      # [*, N, 14]
      lowerCamelCase__ 					=			t_atoms_to_global.map_tensor_fn(lambda lowerCamelCase  : torch.sum(lowerCamelCase       ,			dim=-1  )  )

      # [*, N, 14, 1]
      lowerCamelCase__ 					=			atom_mask[aatype, ...].unsqueeze(-1  )

      # [*, N, 14, 3]
      lowerCamelCase__ 					=			lit_positions[aatype, ...]
      lowerCamelCase__ 					=			t_atoms_to_global.apply(lowerCamelCase  )
      lowerCamelCase__ 					=			pred_positions * atom_mask

      return pred_positions