




'''simple docstring'''

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


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






@dataclasses.dataclass(frozen=_lowerCamelCase     )
class 						a				:
				snake_case_      =		42  # [num_res, num_atom_type, 3]

				# Amino-acid type for each residue represented as an integer between 0 and
				# 20, where 20 is 'X'.
				snake_case_      =		42  # [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.
				snake_case_      =		42  # [num_res, num_atom_type]

				# Residue index as used in PDB. It is not necessarily continuous or 0-indexed.
				snake_case_      =		42  # [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.
				snake_case_      =		42  # [num_res, num_atom_type]

				# Chain indices for multi-chain predictions
				snake_case_      =		None

				# Optional remark about the protein. Included as a comment in output PDB
				# files
				snake_case_      =		None

				# Templates used to generate this protein (prediction-only)
				snake_case_      =		None

				# Chain corresponding to each parent
				snake_case_      =		None







def 		__magic_name__    (	__UpperCAmelCase	)		->					Protein:

					'''simple docstring'''

					snake_case_									=				r'''(\[[A-Z]+\]\n)'''
					snake_case_									=				[tag.strip() for tag in re.split(__UpperCAmelCase,      __UpperCAmelCase	) if len(__UpperCAmelCase	) > 0]
					snake_case_									=				zip(tags[0::2],      [l.split('''\n'''	) for l in tags[1::2]]	)

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

					assert aatype is not None

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


def 		__magic_name__    (	__UpperCAmelCase,      __UpperCAmelCase = 0	)		->					List[str]:

					'''simple docstring'''

					snake_case_									=				[]

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

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

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

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

					return pdb_headers


def 		__magic_name__    (	__UpperCAmelCase,      __UpperCAmelCase	)		->					str:

					'''simple docstring'''

					snake_case_									=				[]
					snake_case_									=				pdb_str.split('''\n'''	)

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

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

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

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

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

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

															out_pdb_lines.append(make_parent_line(__UpperCAmelCase	)	)

					return "\n".join(__UpperCAmelCase	)


def 		__magic_name__    (	__UpperCAmelCase	)		->					str:

					'''simple docstring'''

					snake_case_									=				residue_constants.restypes + ['''X''']

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

					snake_case_									=				residue_constants.atom_types

					snake_case_									=				[]

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

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

					snake_case_									=				get_pdb_headers(__UpperCAmelCase	)
					if len(__UpperCAmelCase	) > 0:
										pdb_lines.extend(__UpperCAmelCase	)

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

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

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

															# PDB is a columnar format, every space matters here!
															snake_case_									=				(
															    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(__UpperCAmelCase	)
															atom_index += 1

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

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

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


def 		__magic_name__    (	__UpperCAmelCase	)		->					np.ndarray:

					'''simple docstring'''

					return residue_constants.STANDARD_ATOM_MASK[prot.aatype]


def 		__magic_name__    (	__UpperCAmelCase,      __UpperCAmelCase,      __UpperCAmelCase = None,      __UpperCAmelCase = None,      __UpperCAmelCase = None,      __UpperCAmelCase = None,      __UpperCAmelCase = None,      )		->					Protein:

					'''simple docstring'''

					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=__UpperCAmelCase,      remark=__UpperCAmelCase,      parents=__UpperCAmelCase,      parents_chain_index=__UpperCAmelCase,      )





"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


A     :   Tuple			    =			{
    "configuration_blenderbot": [
        "BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "BlenderbotConfig",
        "BlenderbotOnnxConfig",
    ],
    "tokenization_blenderbot": ["BlenderbotTokenizer"],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A     :   Dict			    =			["BlenderbotTokenizerFast"]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A     :   str			    =			[
	    "BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "BlenderbotForCausalLM",
	    "BlenderbotForConditionalGeneration",
	    "BlenderbotModel",
	    "BlenderbotPreTrainedModel",
	]


try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A     :   List[str]			    =			[
	    "TFBlenderbotForConditionalGeneration",
	    "TFBlenderbotModel",
	    "TFBlenderbotPreTrainedModel",
	]


try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A     :   List[str]			    =			[
	    "FlaxBlenderbotForConditionalGeneration",
	    "FlaxBlenderbotModel",
	    "FlaxBlenderbotPreTrainedModel",
	]


if TYPE_CHECKING:
	from .configuration_blenderbot import (
	    BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    BlenderbotConfig,
	    BlenderbotOnnxConfig,
	)
	from .tokenization_blenderbot import BlenderbotTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_blenderbot_fast import BlenderbotTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_blenderbot import (
		    BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    BlenderbotForCausalLM,
		    BlenderbotForConditionalGeneration,
		    BlenderbotModel,
		    BlenderbotPreTrainedModel,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_blenderbot import (
		    TFBlenderbotForConditionalGeneration,
		    TFBlenderbotModel,
		    TFBlenderbotPreTrainedModel,
		)

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_blenderbot import (
		    FlaxBlenderbotForConditionalGeneration,
		    FlaxBlenderbotModel,
		    FlaxBlenderbotPreTrainedModel,
		)

else:
	import sys

	A     :   Optional[Any]			    =			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




