





import dataclasses
import re
import string
from typing import Any, Dict, Iterator, List, Mapping, Optional, Sequence, Tuple

import numpy as np

from . import residue_constants


lowercase_          =		Mapping[str, np.ndarray]
lowercase_          =		Mapping[str, Any]  # Is a nested dict.
lowercase_          =		0.01
@dataclasses.dataclass(frozen=UpperCAmelCase				)
class     SCREAMING_SNAKE_CASE       :
   _UpperCamelCase   :		np.ndarray  # [num_res, num_atom_type, 3]

   # Amino-acid type for each residue represented as an integer between 0 and
   # 20, where 20 is 'X'.
   _UpperCamelCase   :		np.ndarray  # [num_res]

   # Binary float mask to indicate presence of a particular atom. 1.0 if an atom
   # is present and 0.0 if not. This should be used for loss masking.
   _UpperCamelCase   :		np.ndarray  # [num_res, num_atom_type]

   # Residue index as used in PDB. It is not necessarily continuous or 0-indexed.
   _UpperCamelCase   :		np.ndarray  # [num_res]

   # B-factors, or temperature factors, of each residue (in sq. angstroms units),
   # representing the displacement of the residue from its ground truth mean
   # value.
   _UpperCamelCase   :		np.ndarray  # [num_res, num_atom_type]

   # Chain indices for multi-chain predictions
   _UpperCamelCase   :		Optional[np.ndarray]			 =	None

   # Optional remark about the protein. Included as a comment in output PDB
   # files
   _UpperCamelCase   :		Optional[str]			 =	None

   # Templates used to generate this protein (prediction-only)
   _UpperCamelCase   :		Optional[Sequence[str]]			 =	None

   # Chain corresponding to each parent
   _UpperCamelCase   :		Optional[Sequence[int]]			 =	None






def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		)    ->       Protein:
  lowercase__           =  R'(\[[A-Z]+\]\n)'
  lowercase__           =  [tag.strip() for tag in re.split(_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		) if len(_SCREAMING_SNAKE_CASE		) > 0]
  lowercase__           =  zip(tags[0::2]		,						[l.split('\n'		) for l in tags[1::2]]		)

  lowercase__           =  ["N", "CA", "C"]
  lowercase__           =  None
  lowercase__           =  None
  lowercase__           =  None
  for g in groups:
    if "[PRIMARY]" == g[0]:
      lowercase__           =  g[1][0].strip()
      for i in range(len(_SCREAMING_SNAKE_CASE		)		):
        if seq[i] not in residue_constants.restypes:
          lowercase__           =  'X'  # FIXME: strings are immutable
      lowercase__           =  np.array(
          [residue_constants.restype_order.get(_SCREAMING_SNAKE_CASE		,						residue_constants.restype_num		) for res_symbol in seq]		)
    elif "[TERTIARY]" == g[0]:
      lowercase__           =  []
      for axis in range(3		):
        tertiary.append(list(map(_SCREAMING_SNAKE_CASE		,						g[1][axis].split()		)		)		)
      lowercase__           =  np.array(_SCREAMING_SNAKE_CASE		)
      lowercase__           =  np.zeros((len(tertiary[0]		) // 3, residue_constants.atom_type_num, 3)		).astype(np.floataa		)
      for i, atom in enumerate(_SCREAMING_SNAKE_CASE		):
        lowercase__           =  np.transpose(tertiary_np[:, i::3]		)
      atom_positions *= PICO_TO_ANGSTROM
    elif "[MASK]" == g[0]:
      lowercase__           =  np.array(list(map({'-': 0, '+': 1}.get		,						g[1][0].strip()		)		)		)
      lowercase__           =  np.zeros(
          (
              len(_SCREAMING_SNAKE_CASE		),
              residue_constants.atom_type_num,
          )		).astype(np.floataa		)
      for i, atom in enumerate(_SCREAMING_SNAKE_CASE		):
        lowercase__           =  1
      atom_mask *= mask[..., None]

  assert aatype is not None

  return Protein(
      atom_positions=_SCREAMING_SNAKE_CASE		,						atom_mask=_SCREAMING_SNAKE_CASE		,						aatype=_SCREAMING_SNAKE_CASE		,						residue_index=np.arange(len(_SCREAMING_SNAKE_CASE		)		)		,						b_factors=_SCREAMING_SNAKE_CASE		,						)




def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE = 0		)    ->       List[str]:
  lowercase__           =  []

  lowercase__           =  prot.remark
  if remark is not None:
    pdb_headers.append(F"""REMARK {remark}"""		)

  lowercase__           =  prot.parents
  lowercase__           =  prot.parents_chain_index
  if parents is not None and parents_chain_index is not None:
    lowercase__           =  [p for i, p in zip(_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		) if i == chain_id]

  if parents is None or len(_SCREAMING_SNAKE_CASE		) == 0:
    lowercase__           =  ['N/A']

  pdb_headers.append(F"""PARENT {" ".join(_SCREAMING_SNAKE_CASE		)}"""		)

  return pdb_headers




def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		)    ->       str:
  lowercase__           =  []
  lowercase__           =  pdb_str.split('\n'		)

  lowercase__           =  prot.remark
  if remark is not None:
    out_pdb_lines.append(F"""REMARK {remark}"""		)

  lowercase__           =  42
  if prot.parents is not None and len(prot.parents		) > 0:
    lowercase__           =  []
    if prot.parents_chain_index is not None:
      lowercase__           =  {}
      for p, i in zip(prot.parents		,						prot.parents_chain_index		):
        parent_dict.setdefault(str(_SCREAMING_SNAKE_CASE		)		,						[]		)
        parent_dict[str(_SCREAMING_SNAKE_CASE		)].append(_SCREAMING_SNAKE_CASE		)

      lowercase__           =  max([int(_SCREAMING_SNAKE_CASE		) for chain_idx in parent_dict]		)
      for i in range(max_idx + 1		):
        lowercase__           =  parent_dict.get(str(_SCREAMING_SNAKE_CASE		)		,						['N/A']		)
        parents_per_chain.append(_SCREAMING_SNAKE_CASE		)
    else:
      parents_per_chain.append(list(prot.parents		)		)
  else:
    lowercase__           =  [['N/A']]

  def make_parent_line(_SCREAMING_SNAKE_CASE		) -> str:
    return F"""PARENT {" ".join(_SCREAMING_SNAKE_CASE		)}"""

  out_pdb_lines.append(make_parent_line(parents_per_chain[0]		)		)

  lowercase__           =  0
  for i, l in enumerate(_SCREAMING_SNAKE_CASE		):
    if "PARENT" not in l and "REMARK" not in l:
      out_pdb_lines.append(_SCREAMING_SNAKE_CASE		)
    if "TER" in l and "END" not in lines[i + 1]:
      chain_counter += 1
      if not chain_counter >= len(_SCREAMING_SNAKE_CASE		):
        lowercase__           =  parents_per_chain[chain_counter]
      else:
        lowercase__           =  ['N/A']

      out_pdb_lines.append(make_parent_line(_SCREAMING_SNAKE_CASE		)		)

  return "\n".join(_SCREAMING_SNAKE_CASE		)




def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		)    ->       str:
  lowercase__           =  residue_constants.restypes + ['X']

  def res_atoa(_SCREAMING_SNAKE_CASE		) -> str:
    return residue_constants.restype_atoa.get(restypes[r]		,						'UNK'		)

  lowercase__           =  residue_constants.atom_types

  lowercase__           =  []

  lowercase__           =  prot.atom_mask
  lowercase__           =  prot.aatype
  lowercase__           =  prot.atom_positions
  lowercase__           =  prot.residue_index.astype(np.intaa		)
  lowercase__           =  prot.b_factors
  lowercase__           =  prot.chain_index

  if np.any(aatype > residue_constants.restype_num		):
    raise ValueError('Invalid aatypes.'		)

  lowercase__           =  get_pdb_headers(_SCREAMING_SNAKE_CASE		)
  if len(_SCREAMING_SNAKE_CASE		) > 0:
    pdb_lines.extend(_SCREAMING_SNAKE_CASE		)

  lowercase__           =  aatype.shape[0]
  lowercase__           =  1
  lowercase__           =  0
  lowercase__           =  string.ascii_uppercase
  lowercase__           =  None
  # Add all atom sites.
  for i in range(_SCREAMING_SNAKE_CASE		):
    lowercase__           =  res_atoa(aatype[i]		)
    for atom_name, pos, mask, b_factor in zip(_SCREAMING_SNAKE_CASE		,						atom_positions[i]		,						atom_mask[i]		,						b_factors[i]		):
      if mask < 0.5:
        continue

      lowercase__           =  'ATOM'
      lowercase__           =  atom_name if len(_SCREAMING_SNAKE_CASE		) == 4 else F""" {atom_name}"""
      lowercase__           =  ''
      lowercase__           =  ''
      lowercase__           =  1.0_0
      lowercase__           =  atom_name[0]  # Protein supports only C, N, O, S, this works.
      lowercase__           =  ''

      lowercase__           =  'A'
      if chain_index is not None:
        lowercase__           =  chain_tags[chain_index[i]]

      # PDB is a columnar format, every space matters here!
      lowercase__           =  (
          F"""{record_type:<6}{atom_index:>5} {name:<4}{alt_loc:>1}"""
          F"""{res_name_a:>3} {chain_tag:>1}"""
          F"""{residue_index[i]:>4}{insertion_code:>1}   """
          F"""{pos[0]:>8.3f}{pos[1]:>8.3f}{pos[2]:>8.3f}"""
          F"""{occupancy:>6.2f}{b_factor:>6.2f}          """
          F"""{element:>2}{charge:>2}"""
      )
      pdb_lines.append(_SCREAMING_SNAKE_CASE		)
      atom_index += 1

    lowercase__           =  i == n - 1
    if chain_index is not None:
      if i != n - 1 and chain_index[i + 1] != prev_chain_index:
        lowercase__           =  True
        lowercase__           =  chain_index[i + 1]

    if should_terminate:
      # Close the chain.
      lowercase__           =  'TER'
      lowercase__           =  (
          F"""{chain_end:<6}{atom_index:>5}      {res_atoa(aatype[i]		):>3} {chain_tag:>1}{residue_index[i]:>4}"""
      )
      pdb_lines.append(_SCREAMING_SNAKE_CASE		)
      atom_index += 1

      if i != n - 1:
        # "prev" is a misnomer here. This happens at the beginning of
        # each new chain.
        pdb_lines.extend(get_pdb_headers(_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		)		)

  pdb_lines.append('END'		)
  pdb_lines.append(''		)
  return "\n".join(_SCREAMING_SNAKE_CASE		)




def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		)    ->       np.ndarray:
  return residue_constants.STANDARD_ATOM_MASK[prot.aatype]




def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE = None		,						_SCREAMING_SNAKE_CASE = None		,						_SCREAMING_SNAKE_CASE = None		,						_SCREAMING_SNAKE_CASE = None		,						_SCREAMING_SNAKE_CASE = None		,						)    ->       Protein:
  return Protein(
      aatype=features['aatype']		,						atom_positions=result['final_atom_positions']		,						atom_mask=result['final_atom_mask']		,						residue_index=features['residue_index'] + 1		,						b_factors=b_factors if b_factors is not None else np.zeros_like(result['final_atom_mask']		)		,						chain_index=_SCREAMING_SNAKE_CASE		,						remark=_SCREAMING_SNAKE_CASE		,						parents=_SCREAMING_SNAKE_CASE		,						parents_chain_index=_SCREAMING_SNAKE_CASE		,						)









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


lowercase_          =		logging.get_logger(__name__)

lowercase_          =		{
    """transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""",
}
class     SCREAMING_SNAKE_CASE       (UpperCAmelCase				):
   _UpperCamelCase   :		Optional[Any]			 =	'transfo-xl'
   _UpperCamelCase   :		Any			 =	['mems']
   _UpperCamelCase   :		Any			 =	{
       'n_token': 'vocab_size',
       'hidden_size': 'd_model',
       'num_attention_heads': 'n_head',
       'num_hidden_layers': 'n_layer',
   }


   def __init__(   self      :    Optional[Any]      ,					a      :    Optional[int]=267_735      ,					a      :    str=[20_000, 40_000, 200_000]      ,					a      :    str=1_024      ,					a      :    str=1_024      ,					a      :    int=16      ,					a      :    Optional[int]=64      ,					a      :    Optional[int]=4_096      ,					a      :    int=4      ,					a      :    Tuple=False      ,					a      :    Any=18      ,					a      :    Tuple=1_600      ,					a      :    Union[str, Any]=1_000      ,					a      :    str=True      ,					a      :    Dict=True      ,					a      :    Any=0      ,					a      :    List[Any]=-1      ,					a      :    List[Any]=True      ,					a      :    Tuple=0.1      ,					a      :    List[Any]=0.0      ,					a      :    Optional[Any]=True      ,					a      :    int="normal"      ,					a      :    Optional[Any]=0.01      ,					a      :    str=0.01      ,					a      :    List[Any]=0.02      ,					a      :    List[Any]=1E-5      ,					a      :    Optional[Any]=0      ,					**a      :    Optional[int]      ,					)->       Optional[int]:





     """simple docstring"""







     lowercase__           =  vocab_size
     lowercase__           =  []
     self.cutoffs.extend(a	)
     if proj_share_all_but_first:
       lowercase__           =  [False] + [True] * len(self.cutoffs	)
     else:
       lowercase__           =  [False] + [False] * len(self.cutoffs	)
     lowercase__           =  d_model
     lowercase__           =  d_embed
     lowercase__           =  d_head
     lowercase__           =  d_inner
     lowercase__           =  div_val
     lowercase__           =  pre_lnorm
     lowercase__           =  n_layer
     lowercase__           =  n_head
     lowercase__           =  mem_len
     lowercase__           =  same_length
     lowercase__           =  attn_type
     lowercase__           =  clamp_len
     lowercase__           =  sample_softmax
     lowercase__           =  adaptive
     lowercase__           =  dropout
     lowercase__           =  dropatt
     lowercase__           =  untie_r
     lowercase__           =  init
     lowercase__           =  init_range
     lowercase__           =  proj_init_std
     lowercase__           =  init_std
     lowercase__           =  layer_norm_epsilon
     super().__init__(eos_token_id=a      ,					**a	)


   @property
   def 	SCREAMING_SNAKE_CASE_							(   self      :    Optional[Any]	)->       Union[str, Any]:





     """simple docstring"""







     logger.info(f"""The model {self.model_type} is one of the few models that has no sequence length limit."""	)
     return -1


   @max_position_embeddings.setter
   def 	SCREAMING_SNAKE_CASE_							(   self      :    Any      ,					a      :    Optional[int]	)->       Optional[int]:





     """simple docstring"""







     raise NotImplementedError(
         f"""The model {self.model_type} is one of the few models that has no sequence length limit."""	)


