





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


lowerCAmelCase_						   =    Mapping[str, np.ndarray]
lowerCAmelCase_						   =    Mapping[str, Any]  # Is a nested dict.
lowerCAmelCase_						   =    0.01



@dataclasses.dataclass(frozen=UpperCAmelCase_							)
class        _lowerCAmelCase    :


  '''simple docstring'''
  a_							:       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'.
  a_							:       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.
  a_							:       np.ndarray  # [num_res, num_atom_type]

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

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

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

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

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




def     lowerCamelCase_	(      lowerCAmelCase:	str				)->		Protein:
  _snake_case   :				List[Any]														=      R'(\[[A-Z]+\]\n)'
  _snake_case   :				List[str]														=      [tag.strip() for tag in re.split(lowerCAmelCase    ,							lowerCAmelCase				) if len(lowerCAmelCase				) > 0]
  _snake_case   :				Iterator[Tuple[str, List[str]]]														=      zip(tags[0::2]    ,							[l.split('\n'				) for l in tags[1::2]]				)

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

  assert aatype is not None

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


def     lowerCamelCase_	(      lowerCAmelCase:	Protein    ,							lowerCAmelCase:	int = 0				)->		List[str]:
  _snake_case   :				List[str]														=      []

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

  _snake_case   :				str														=      prot.parents
  _snake_case   :				Optional[Any]														=      prot.parents_chain_index
  if parents is not None and parents_chain_index is not None:
    _snake_case   :				Union[str, Any]														=      [p for i, p in zip(lowerCAmelCase    ,							lowerCAmelCase				) if i == chain_id]

  if parents is None or len(lowerCAmelCase				) == 0:
    _snake_case   :				Optional[int]														=      ['N/A']

  pdb_headers.append(F"""PARENT {' '.join(lowerCAmelCase				)}"""				)

  return pdb_headers


def     lowerCamelCase_	(      lowerCAmelCase:	Protein    ,							lowerCAmelCase:	str				)->		str:
  _snake_case   :				List[str]														=      []
  _snake_case   :				Union[str, Any]														=      pdb_str.split('\n'				)

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

  _snake_case   :				List[List[str]]
  if prot.parents is not None and len(prot.parents				) > 0:
    _snake_case   :				Any														=      []
    if prot.parents_chain_index is not None:
      _snake_case   :				Dict[str, List[str]]														=      {}
      for p, i in zip(prot.parents    ,							prot.parents_chain_index				):
        parent_dict.setdefault(str(lowerCAmelCase				)    ,							[]				)
        parent_dict[str(lowerCAmelCase				)].append(lowerCAmelCase				)

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

  def make_parent_line(lowerCAmelCase:	Sequence[str]				) -> str:
    return F"""PARENT {' '.join(lowerCAmelCase				)}"""

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

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

      out_pdb_lines.append(make_parent_line(lowerCAmelCase				)				)

  return "\n".join(lowerCAmelCase				)


def     lowerCamelCase_	(      lowerCAmelCase:	Protein				)->		str:
  _snake_case   :				int														=      residue_constants.restypes + ['X']

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

  _snake_case   :				str														=      residue_constants.atom_types

  _snake_case   :				List[str]														=      []

  _snake_case   :				Any														=      prot.atom_mask
  _snake_case   :				Optional[int]														=      prot.aatype
  _snake_case   :				str														=      prot.atom_positions
  _snake_case   :				Tuple														=      prot.residue_index.astype(np.intaa				)
  _snake_case   :				List[str]														=      prot.b_factors
  _snake_case   :				Dict														=      prot.chain_index

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

  _snake_case   :				Any														=      get_pdb_headers(lowerCAmelCase				)
  if len(lowerCAmelCase				) > 0:
    pdb_lines.extend(lowerCAmelCase				)

  _snake_case   :				Optional[Any]														=      aatype.shape[0]
  _snake_case   :				Optional[Any]														=      1
  _snake_case   :				Union[str, Any]														=      0
  _snake_case   :				int														=      string.ascii_uppercase
  _snake_case   :				str														=      None
  # Add all atom sites.
  for i in range(lowerCAmelCase				):
    _snake_case   :				Dict														=      res_atoa(aatype[i]				)
    for atom_name, pos, mask, b_factor in zip(lowerCAmelCase    ,							atom_positions[i]    ,							atom_mask[i]    ,							b_factors[i]				):
      if mask < 0.5:
        continue

      _snake_case   :				Optional[Any]														=      'ATOM'
      _snake_case   :				Tuple														=      atom_name if len(lowerCAmelCase				) == 4 else F""" {atom_name}"""
      _snake_case   :				Dict														=      ''
      _snake_case   :				Any														=      ''
      _snake_case   :				int														=      1.0_0
      _snake_case   :				str														=      atom_name[0]  # Protein supports only C, N, O, S, this works.
      _snake_case   :				List[str]														=      ''

      _snake_case   :				List[Any]														=      'A'
      if chain_index is not None:
        _snake_case   :				List[Any]														=      chain_tags[chain_index[i]]

      # PDB is a columnar format, every space matters here!
      _snake_case   :				str														=      (
          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(lowerCAmelCase				)
      atom_index += 1

    _snake_case   :				Dict														=      i == n - 1
    if chain_index is not None:
      if i != n - 1 and chain_index[i + 1] != prev_chain_index:
        _snake_case   :				str														=      True
        _snake_case   :				Optional[Any]														=      chain_index[i + 1]

    if should_terminate:
      # Close the chain.
      _snake_case   :				int														=      'TER'
      _snake_case   :				List[str]														=      (
          F"""{chain_end:<6}{atom_index:>5}      {res_atoa(aatype[i]				):>3} {chain_tag:>1}{residue_index[i]:>4}"""
      )
      pdb_lines.append(lowerCAmelCase				)
      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(lowerCAmelCase    ,							lowerCAmelCase				)				)

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


def     lowerCamelCase_	(      lowerCAmelCase:	Protein				)->		np.ndarray:
  return residue_constants.STANDARD_ATOM_MASK[prot.aatype]







def     lowerCamelCase_	(      lowerCAmelCase:	FeatureDict    ,							lowerCAmelCase:	ModelOutput    ,							lowerCAmelCase:	Optional[np.ndarray] = None    ,							lowerCAmelCase:	Optional[np.ndarray] = None    ,							lowerCAmelCase:	Optional[str] = None    ,							lowerCAmelCase:	Optional[Sequence[str]] = None    ,							lowerCAmelCase:	Optional[Sequence[int]] = 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=lowerCAmelCase    ,							remark=lowerCAmelCase    ,							parents=lowerCAmelCase    ,							parents_chain_index=lowerCAmelCase    ,							)











from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowerCAmelCase_						   =    logging.get_logger(__name__)

lowerCAmelCase_						   =    {
    """roberta-base""": """https://huggingface.co/roberta-base/resolve/main/config.json""",
    """roberta-large""": """https://huggingface.co/roberta-large/resolve/main/config.json""",
    """roberta-large-mnli""": """https://huggingface.co/roberta-large-mnli/resolve/main/config.json""",
    """distilroberta-base""": """https://huggingface.co/distilroberta-base/resolve/main/config.json""",
    """roberta-base-openai-detector""": """https://huggingface.co/roberta-base-openai-detector/resolve/main/config.json""",
    """roberta-large-openai-detector""": """https://huggingface.co/roberta-large-openai-detector/resolve/main/config.json""",
}



class        _lowerCAmelCase    (			UpperCAmelCase_							):


  '''simple docstring'''
  a_							:       int      					="""roberta"""







  def __init__(      self      :					int      ,				UpperCamelCase      :					Tuple=5_02_65      ,				UpperCamelCase      :					Any=7_68      ,				UpperCamelCase      :					List[Any]=12      ,				UpperCamelCase      :					str=12      ,				UpperCamelCase      :					Dict=30_72      ,				UpperCamelCase      :					Any="gelu"      ,				UpperCamelCase      :					List[Any]=0.1      ,				UpperCamelCase      :					Optional[Any]=0.1      ,				UpperCamelCase      :					Optional[Any]=5_12      ,				UpperCamelCase      :					List[str]=2      ,				UpperCamelCase      :					Optional[Any]=0.02      ,				UpperCamelCase      :					Tuple=1e-1_2      ,				UpperCamelCase      :					str=1      ,				UpperCamelCase      :					int=0      ,				UpperCamelCase      :					Any=2      ,				UpperCamelCase      :					int="absolute"      ,				UpperCamelCase      :					int=True      ,				UpperCamelCase      :					List[Any]=None      ,				**UpperCamelCase      :					Any      ,				):


    '''simple docstring'''





    super().__init__(pad_token_id=UpperCamelCase      ,				bos_token_id=UpperCamelCase      ,				eos_token_id=UpperCamelCase      ,				**UpperCamelCase							)

    _snake_case   :				Any														=	vocab_size
    _snake_case   :				List[str]														=	hidden_size
    _snake_case   :				List[str]														=	num_hidden_layers
    _snake_case   :				Dict														=	num_attention_heads
    _snake_case   :				List[str]														=	hidden_act
    _snake_case   :				Union[str, Any]														=	intermediate_size
    _snake_case   :				Union[str, Any]														=	hidden_dropout_prob
    _snake_case   :				Optional[int]														=	attention_probs_dropout_prob
    _snake_case   :				Dict														=	max_position_embeddings
    _snake_case   :				Optional[int]														=	type_vocab_size
    _snake_case   :				Tuple														=	initializer_range
    _snake_case   :				int														=	layer_norm_eps
    _snake_case   :				Dict														=	position_embedding_type
    _snake_case   :				Union[str, Any]														=	use_cache
    _snake_case   :				str														=	classifier_dropout




class        _lowerCAmelCase    (			UpperCAmelCase_							):


  '''simple docstring'''







  @property
  def UpperCamelCase_ (      self      :					Dict							):


    '''simple docstring'''





    if self.task == "multiple-choice":
      _snake_case   :				Optional[Any]														=	{0: 'batch', 1: 'choice', 2: 'sequence'}
    else:
      _snake_case   :				Dict														=	{0: 'batch', 1: 'sequence'}
    return OrderedDict(
        [
            ('input_ids', dynamic_axis),
            ('attention_mask', dynamic_axis),
        ]							)




