




import json
import os
import subprocess
import sys
import warnings
from argparse import ArgumentParser
from contextlib import AbstractContextManager
from typing import Dict, List, Optional

import requests

from ..utils import logging
from . import BaseTransformersCLICommand


__SCREAMING_SNAKE_CASE      :				int				      =logging.get_logger(__name__)  # pylint: disable=invalid-name


__SCREAMING_SNAKE_CASE      :				List[Any]				      ="""lfs-multipart-upload"""






class      A     (						_lowerCAmelCase						):
     """simple docstring"""

     @staticmethod
     def 	__snake_case				(      A__					:				ArgumentParser     )			->    str:
           lowerCamelCase__ 					=			parser.add_parser(
               'lfs-enable-largefiles'		,					help=(
                   'Deprecated: use `huggingface-cli` instead. Configure your repository to enable upload of files > 5GB.'
               )		,					)
           enable_parser.add_argument('path'		,					type=A__		,					help='Local path to repository you want to configure.'     )
           enable_parser.set_defaults(func=lambda A__     : LfsEnableCommand(A__     )     )

           lowerCamelCase__ 					=			parser.add_parser(
               A__		,					help=(
                   'Deprecated: use `huggingface-cli` instead. '
                   'Command will get called by git-lfs, do not call it directly.'
               )		,					)
           upload_parser.set_defaults(func=lambda A__     : LfsUploadCommand(A__     )     )






class      A     :
     """simple docstring"""

     def __init__(      self					:				List[Any]		,					A__					:				Tuple     )			->    Optional[int]:
           lowerCamelCase__ 					=			args




     def 	__snake_case				(      self					:				Dict     )			->    Dict:
           warnings.warn(
               'Managing repositories through transformers-cli is deprecated. Please use `huggingface-cli` instead.'     )
           lowerCamelCase__ 					=			os.path.abspath(self.args.path     )
           if not os.path.isdir(A__     ):
                 print('This does not look like a valid git repo.'     )
                 exit(1     )
           subprocess.run(
               'git config lfs.customtransfer.multipart.path transformers-cli'.split()		,					check=A__		,					cwd=A__     )
           subprocess.run(
               F"""git config lfs.customtransfer.multipart.args {LFS_MULTIPART_UPLOAD_COMMAND}""".split()		,					check=A__		,					cwd=A__		,					)
           print('Local repo set up for largefiles'     )

def      lowerCAmelCase_     (					lowerCamelCase:    Dict  )   ->     str:


      '''simple docstring'''




      lowerCamelCase__ 					=			json.dumps(lowerCamelCase  ) + '\n'
      sys.stdout.write(lowerCamelCase  )
      sys.stdout.flush()

def      lowerCAmelCase_     (					)   ->     Optional[Dict]:


      '''simple docstring'''




      lowerCamelCase__ 					=			json.loads(sys.stdin.readline().strip()  )

      if "terminate" in (msg.get('type'  ), msg.get('event'  )):
            # terminate message received
            return None

      if msg.get('event'  ) not in ("download", "upload"):
            logger.critical('Received unexpected message'  )
            sys.exit(1  )

      return msg






class      A     (						_lowerCAmelCase						):
     """simple docstring"""

     def __init__(      self					:				List[str]		,					A__					:				str		,					A__					:				int		,					A__					:				int     )			->    Optional[Any]:
           lowerCamelCase__ 					=			filepath
           lowerCamelCase__ 					=			seek_from
           lowerCamelCase__ 					=			read_limit
           lowerCamelCase__ 					=			0




     def __enter__(      self					:				Tuple     )			->    Optional[int]:
           lowerCamelCase__ 					=			open(self.filepath		,					'rb'     )
           self.f.seek(self.seek_from     )
           return self




     def __len__(      self					:				int     )			->    List[str]:
           lowerCamelCase__ 					=			os.fstat(self.f.fileno()     ).st_size
           return min(self.read_limit		,					total_length - self.seek_from     )




     def 	__snake_case				(      self					:				Union[str, Any]		,					A__					:				List[Any]=-1     )			->    List[Any]:
           if self.n_seen >= self.read_limit:
                 return b""
           lowerCamelCase__ 					=			self.read_limit - self.n_seen
           lowerCamelCase__ 					=			self.f.read(remaining_amount if n < 0 else min(A__		,					A__     )     )
           self.n_seen += len(A__     )
           return data




     def __iter__(      self					:				str     )			->    Optional[Any]:
           yield self.read(n=4 * 1_0_2_4 * 1_0_2_4     )




     def __exit__(      self					:				Tuple		,					*A__					:				int     )			->    str:
           self.f.close()






class      A     :
     """simple docstring"""

     def __init__(      self					:				List[Any]		,					A__					:				Optional[int]     )			->    Optional[int]:
           lowerCamelCase__ 					=			args




     def 	__snake_case				(      self					:				Any     )			->    List[Any]:
           # Immediately after invoking a custom transfer process, git-lfs
           # sends initiation data to the process over stdin.
           # This tells the process useful information about the configuration.
           lowerCamelCase__ 					=			json.loads(sys.stdin.readline().strip()     )
           if not (init_msg.get('event'     ) == "init" and init_msg.get('operation'     ) == "upload"):
                 write_msg({'error': {'code': 3_2, 'message': 'Wrong lfs init operation'}}     )
                 sys.exit(1     )

           # The transfer process should use the information it needs from the
           # initiation structure, and also perform any one-off setup tasks it
           # needs to do. It should then respond on stdout with a simple empty
           # confirmation structure, as follows:
           write_msg({}     )

           # After the initiation exchange, git-lfs will send any number of
           # transfer requests to the stdin of the transfer process, in a serial sequence.
           while True:
                 lowerCamelCase__ 					=			read_msg()
                 if msg is None:
                       # When all transfers have been processed, git-lfs will send
                       # a terminate event to the stdin of the transfer process.
                       # On receiving this message the transfer process should
                       # clean up and terminate. No response is expected.
                       sys.exit(0     )

                 lowerCamelCase__ 					=			msg['oid']
                 lowerCamelCase__ 					=			msg['path']
                 lowerCamelCase__ 					=			msg['action']['href']
                 lowerCamelCase__ 					=			msg['action']['header']
                 lowerCamelCase__ 					=			int(header.pop('chunk_size'     )     )
                 lowerCamelCase__ 					=			list(header.values()     )

                 lowerCamelCase__ 					=			[]
                 for i, presigned_url in enumerate(A__     ):
                       with FileSlice(A__		,					seek_from=i * chunk_size		,					read_limit=A__     ) as data:
                             lowerCamelCase__ 					=			requests.put(A__		,					data=A__     )
                             r.raise_for_status()
                             parts.append(
                                 {
                                     'etag': r.headers.get('etag'     ),
                                     'partNumber': i + 1,
                                 }     )
                             # In order to support progress reporting while data is uploading / downloading,
                             # the transfer process should post messages to stdout
                             write_msg(
                                 {
                                     'event': 'progress',
                                     'oid': oid,
                                     'bytesSoFar': (i + 1) * chunk_size,
                                     'bytesSinceLast': chunk_size,
                                 }     )
                             # Not precise but that's ok.

                 lowerCamelCase__ 					=			requests.post(
                     A__		,					json={
                         'oid': oid,
                         'parts': parts,
                     }		,					)
                 r.raise_for_status()

                 write_msg({'event': 'complete', 'oid': oid}     )





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