



from typing import Dict

import numpy as np
import torch

from . import residue_constants as rc
from .tensor_utils import tensor_tree_map, tree_map

def 	lowerCAmelCase_     (  _lowercase				:   Dict[str, torch.Tensor])							->       Union[str, Any]:







			"""simple docstring"""
			a__   :						Any						       =  []
			a__   :						Optional[int]						       =  []
			a__   :						Tuple						       =  []

			for rt in rc.restypes:
						a__   :						Dict						       =  rc.restype_name_to_atomaa_names[rc.restype_atoa[rt]]
						restype_atomaa_to_atomaa_list.append([(rc.atom_order[name] if name else 0) for name in atom_names])
						a__   :						str						       =  {name: i for i, name in enumerate(_lowerCamelCase)}
						restype_atomaa_to_atomaa_list.append(
						    [(atom_name_to_idxaa[name] if name in atom_name_to_idxaa else 0) for name in rc.atom_types])

						restype_atomaa_mask_list.append([(1.0 if name else 0.0) for name in atom_names])

			# Add dummy mapping for restype 'UNK'
			restype_atomaa_to_atomaa_list.append([0] * 14)
			restype_atomaa_to_atomaa_list.append([0] * 37)
			restype_atomaa_mask_list.append([0.0] * 14)

			a__   :						Union[str, Any]						       =  torch.tensor(
			    _lowerCamelCase						,   dtype=torch.intaa						,   device=protein["""aatype"""].device						,   )
			a__   :						str						       =  torch.tensor(
			    _lowerCamelCase						,   dtype=torch.intaa						,   device=protein["""aatype"""].device						,   )
			a__   :						List[str]						       =  torch.tensor(
			    _lowerCamelCase						,   dtype=torch.floataa						,   device=protein["""aatype"""].device						,   )
			a__   :						str						       =  protein["aatype"].to(torch.long)

			# create the mapping for (residx, atom14) --> atom37, i.e. an array
			# with shape (num_res, 14) containing the atom37 indices for this protein
			a__   :						Dict						       =  restype_atomaa_to_atomaa[protein_aatype]
			a__   :						str						       =  restype_atomaa_mask[protein_aatype]

			a__   :						List[Any]						       =  residx_atomaa_mask
			a__   :						Optional[Any]						       =  residx_atomaa_to_atomaa.long()

			# create the gather indices for mapping back
			a__   :						str						       =  restype_atomaa_to_atomaa[protein_aatype]
			a__   :						str						       =  residx_atomaa_to_atomaa.long()

			# create the corresponding mask
			a__   :						Optional[Any]						       =  torch.zeros([21, 37]						,   dtype=torch.floataa						,   device=protein["""aatype"""].device)
			for restype, restype_letter in enumerate(rc.restypes):
						a__   :						Tuple						       =  rc.restype_atoa[restype_letter]
						a__   :						List[Any]						       =  rc.residue_atoms[restype_name]
						for atom_name in atom_names:
									a__   :						Optional[int]						       =  rc.atom_order[atom_name]
									a__   :						Tuple						       =  1

			a__   :						Dict						       =  restype_atomaa_mask[protein_aatype]
			a__   :						Any						       =  residx_atomaa_mask

			return protein





def 	lowerCAmelCase_     (  _lowercase				:   Dict[str, torch.Tensor])							->       Optional[Any]:







			"""simple docstring"""
			a__   :						Tuple						       =  tree_map(lambda _lowercase: torch.tensor(_lowerCamelCase						,   device=batch["""aatype"""].device)						,   _lowerCamelCase						,   np.ndarray)
			a__   :						List[str]						       =  tensor_tree_map(lambda _lowercase: np.array(_lowerCamelCase)						,   make_atomaa_masks(_lowerCamelCase))
			return out





import io
import json

import fsspec
import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases

def 			lowercase_				(			_lowerCamelCase							:       Optional[Any]		,	_lowerCamelCase							:       int):
    assert isinstance(_lowerCamelCase		,	_lowerCamelCase)
    assert dataset.num_rows == 4
    assert dataset.num_columns == 3
    assert dataset.column_names == ["col_1", "col_2", "col_3"]
    for feature, expected_dtype in expected_features.items():
        assert dataset.features[feature].dtype == expected_dtype

@pytest.mark.parametrize("keep_in_memory"		,	[False, True])
def 			lowercase_				(			_lowerCamelCase							:       List[Any]		,	_lowerCamelCase							:       Any		,	_lowerCamelCase							:       str):
    lowercase__ :   Optional[int]    					=				tmp_path / "cache"
    lowercase__ :   str    					=				{"col_1": "string", "col_2": "int64", "col_3": "float64"}
    with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
        lowercase__ :   Union[str, Any]    					=				JsonDatasetReader(_lowerCamelCase		,	cache_dir=_lowerCamelCase		,	keep_in_memory=_lowerCamelCase).read()
    _check_json_dataset(_lowerCamelCase		,	_lowerCamelCase)

@pytest.mark.parametrize(
    "features"		,	[
        None,
        {"col_1": "string", "col_2": "int64", "col_3": "float64"},
        {"col_1": "string", "col_2": "string", "col_3": "string"},
        {"col_1": "int32", "col_2": "int32", "col_3": "int32"},
        {"col_1": "float32", "col_2": "float32", "col_3": "float32"},
    ]		,	)
def 			lowercase_				(			_lowerCamelCase							:       List[str]		,	_lowerCamelCase							:       Dict		,	_lowerCamelCase							:       Dict):
    lowercase__ :   List[Any]    					=				tmp_path / "cache"
    lowercase__ :   Union[str, Any]    					=				{"col_1": "string", "col_2": "int64", "col_3": "float64"}
    lowercase__ :   List[Any]    					=				features.copy() if features else default_expected_features
    lowercase__ :   List[Any]    					=				(
        Features({feature: Value(_lowerCamelCase) for feature, dtype in features.items()}) if features is not None else None
    )
    lowercase__ :   Any    					=				JsonDatasetReader(_lowerCamelCase		,	features=_lowerCamelCase		,	cache_dir=_lowerCamelCase).read()
    _check_json_dataset(_lowerCamelCase		,	_lowerCamelCase)

@pytest.mark.parametrize(
    "features"		,	[
        None,
        {"col_3": "float64", "col_1": "string", "col_2": "int64"},
    ]		,	)
def 			lowercase_				(			_lowerCamelCase							:       Any		,	_lowerCamelCase							:       Any		,	_lowerCamelCase							:       List[str]):
    lowercase__ :   Optional[Any]    					=				tmp_path / "cache"
    lowercase__ :   Tuple    					=				{"col_3": "float64", "col_1": "string", "col_2": "int64"}
    lowercase__ :   List[Any]    					=				features.copy() if features else default_expected_features
    lowercase__ :   int    					=				(
        Features({feature: Value(_lowerCamelCase) for feature, dtype in features.items()}) if features is not None else None
    )
    lowercase__ :   Any    					=				JsonDatasetReader(_lowerCamelCase		,	features=_lowerCamelCase		,	cache_dir=_lowerCamelCase).read()
    assert isinstance(_lowerCamelCase		,	_lowerCamelCase)
    assert dataset.num_rows == 2
    assert dataset.num_columns == 3
    assert dataset.column_names == ["col_3", "col_1", "col_2"]
    for feature, expected_dtype in expected_features.items():
        assert dataset.features[feature].dtype == expected_dtype

def 			lowercase_				(			_lowerCamelCase							:       List[Any]		,	_lowerCamelCase							:       Optional[int]):
    # jsonl_312_path features are {"col_3": "float64", "col_1": "string", "col_2": "int64"}
    lowercase__ :   Any    					=				{"col_2": "int64", "col_3": "float64", "col_1": "string"}
    lowercase__ :   str    					=				features.copy()
    lowercase__ :   str    					=				(
        Features({feature: Value(_lowerCamelCase) for feature, dtype in features.items()}) if features is not None else None
    )
    lowercase__ :   Optional[int]    					=				tmp_path / "cache"
    lowercase__ :   Any    					=				JsonDatasetReader(_lowerCamelCase		,	features=_lowerCamelCase		,	cache_dir=_lowerCamelCase).read()
    assert isinstance(_lowerCamelCase		,	_lowerCamelCase)
    assert dataset.num_rows == 2
    assert dataset.num_columns == 3
    assert dataset.column_names == ["col_2", "col_3", "col_1"]
    for feature, expected_dtype in expected_features.items():
        assert dataset.features[feature].dtype == expected_dtype

@pytest.mark.parametrize("split"		,	[None, NamedSplit("train"), "train", "test"])
def 			lowercase_				(			_lowerCamelCase							:       Dict		,	_lowerCamelCase							:       Optional[int]		,	_lowerCamelCase							:       List[str]):
    lowercase__ :   Union[str, Any]    					=				tmp_path / "cache"
    lowercase__ :   List[Any]    					=				{"col_1": "string", "col_2": "int64", "col_3": "float64"}
    lowercase__ :   Union[str, Any]    					=				JsonDatasetReader(_lowerCamelCase		,	cache_dir=_lowerCamelCase		,	split=_lowerCamelCase).read()
    _check_json_dataset(_lowerCamelCase		,	_lowerCamelCase)
    assert dataset.split == split if split else "train"

@pytest.mark.parametrize("path_type"		,	[str, list])
def 			lowercase_				(			_lowerCamelCase							:       Union[str, Any]		,	_lowerCamelCase							:       str		,	_lowerCamelCase							:       int):
    if issubclass(_lowerCamelCase		,	_lowerCamelCase):
        lowercase__ :   Tuple    					=				jsonl_path
    elif issubclass(_lowerCamelCase		,	_lowerCamelCase):
        lowercase__ :   str    					=				[jsonl_path]
    lowercase__ :   str    					=				tmp_path / "cache"
    lowercase__ :   Optional[Any]    					=				{"col_1": "string", "col_2": "int64", "col_3": "float64"}
    lowercase__ :   Tuple    					=				JsonDatasetReader(_lowerCamelCase		,	cache_dir=_lowerCamelCase).read()
    _check_json_dataset(_lowerCamelCase		,	_lowerCamelCase)

def 			lowercase_				(			_lowerCamelCase							:       List[Any]		,	_lowerCamelCase							:       Optional[Any]		,	_lowerCamelCase							:       Optional[int]=("train",)):
    assert isinstance(_lowerCamelCase		,	_lowerCamelCase)
    for split in splits:
        lowercase__ :   Optional[Any]    					=				dataset_dict[split]
        assert dataset.num_rows == 4
        assert dataset.num_columns == 3
        assert dataset.column_names == ["col_1", "col_2", "col_3"]
        for feature, expected_dtype in expected_features.items():
            assert dataset.features[feature].dtype == expected_dtype

@pytest.mark.parametrize("keep_in_memory"		,	[False, True])
def 			lowercase_				(			_lowerCamelCase							:       Union[str, Any]		,	_lowerCamelCase							:       str		,	_lowerCamelCase							:       str):
    lowercase__ :   List[str]    					=				tmp_path / "cache"
    lowercase__ :   str    					=				{"col_1": "string", "col_2": "int64", "col_3": "float64"}
    with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
        lowercase__ :   Optional[Any]    					=				JsonDatasetReader({"train": jsonl_path}		,	cache_dir=_lowerCamelCase		,	keep_in_memory=_lowerCamelCase).read()
    _check_json_datasetdict(_lowerCamelCase		,	_lowerCamelCase)

@pytest.mark.parametrize(
    "features"		,	[
        None,
        {"col_1": "string", "col_2": "int64", "col_3": "float64"},
        {"col_1": "string", "col_2": "string", "col_3": "string"},
        {"col_1": "int32", "col_2": "int32", "col_3": "int32"},
        {"col_1": "float32", "col_2": "float32", "col_3": "float32"},
    ]		,	)
def 			lowercase_				(			_lowerCamelCase							:       Any		,	_lowerCamelCase							:       List[str]		,	_lowerCamelCase							:       List[str]):
    lowercase__ :   str    					=				tmp_path / "cache"
    lowercase__ :   Tuple    					=				{"col_1": "string", "col_2": "int64", "col_3": "float64"}
    lowercase__ :   Tuple    					=				features.copy() if features else default_expected_features
    lowercase__ :   Union[str, Any]    					=				(
        Features({feature: Value(_lowerCamelCase) for feature, dtype in features.items()}) if features is not None else None
    )
    lowercase__ :   Tuple    					=				JsonDatasetReader({"train": jsonl_path}		,	features=_lowerCamelCase		,	cache_dir=_lowerCamelCase).read()
    _check_json_datasetdict(_lowerCamelCase		,	_lowerCamelCase)

@pytest.mark.parametrize("split"		,	[None, NamedSplit("train"), "train", "test"])
def 			lowercase_				(			_lowerCamelCase							:       str		,	_lowerCamelCase							:       Dict		,	_lowerCamelCase							:       Tuple):
    if split:
        lowercase__ :   Tuple    					=				{split: jsonl_path}
    else:
        lowercase__ :   Tuple    					=				"train"
        lowercase__ :   int    					=				{"train": jsonl_path, "test": jsonl_path}
    lowercase__ :   Dict    					=				tmp_path / "cache"
    lowercase__ :   Union[str, Any]    					=				{"col_1": "string", "col_2": "int64", "col_3": "float64"}
    lowercase__ :   Union[str, Any]    					=				JsonDatasetReader(_lowerCamelCase		,	cache_dir=_lowerCamelCase).read()
    _check_json_datasetdict(_lowerCamelCase		,	_lowerCamelCase		,	splits=list(path.keys()))
    assert all(dataset[split].split == split for split in path.keys())

def 			lowercase_				(			_lowerCamelCase							:       Union[str, Any]):
    return json.load(_lowerCamelCase)

def 			lowercase_				(			_lowerCamelCase							:       Optional[int]):
    return [json.loads(_lowerCamelCase) for line in buffer]



class   snake_case_       :






   @pytest.mark.parametrize("lines, load_json_function"	,						[(True, load_json_lines), (False, load_json)]  )
   def       __UpperCamelCase     (      self				:     List[Any]	,						lowercase_				:     Any	,						lowercase_				:     Optional[Any]	,						lowercase_				:     Dict  )					->						Optional[Any]:
       with io.BytesIO() as buffer:
           JsonDatasetWriter(lowercase_	,						lowercase_	,						lines=lowercase_  ).write()
           buffer.seek(0  )
           lowercase__ :   Optional[int]    					=				load_json_function(lowercase_  )
       assert isinstance(lowercase_	,						lowercase_  )
       assert isinstance(exported_content[0]	,						lowercase_  )
       assert len(lowercase_  ) == 10






   @pytest.mark.parametrize(
       "orient, container, keys, len_at"	,						[
           ("records", list, {"tokens", "labels", "answers", "id"}, None),
           ("split", dict, {"columns", "data"}, "data"),
           ("index", dict, set("0123456789"  ), None),
           ("columns", dict, {"tokens", "labels", "answers", "id"}, "tokens"),
           ("values", list, None, None),
           ("table", dict, {"schema", "data"}, "data"),
       ]	,						)
   def       __UpperCamelCase     (      self				:     str	,						lowercase_				:     int	,						lowercase_				:     str	,						lowercase_				:     Union[str, Any]	,						lowercase_				:     Dict	,						lowercase_				:     Tuple  )					->						List[str]:
       with io.BytesIO() as buffer:
           JsonDatasetWriter(lowercase_	,						lowercase_	,						lines=lowercase_	,						orient=lowercase_  ).write()
           buffer.seek(0  )
           lowercase__ :   str    					=				load_json(lowercase_  )
       assert isinstance(lowercase_	,						lowercase_  )
       if keys:
           if container is dict:
               assert exported_content.keys() == keys
           else:
               assert exported_content[0].keys() == keys
       else:
           assert not hasattr(lowercase_	,						"keys"  ) and not hasattr(exported_content[0]	,						"keys"  )
       if len_at:
           assert len(exported_content[len_at]  ) == 10
       else:
           assert len(lowercase_  ) == 10






   @pytest.mark.parametrize("lines, load_json_function"	,						[(True, load_json_lines), (False, load_json)]  )
   def       __UpperCamelCase     (      self				:     List[Any]	,						lowercase_				:     int	,						lowercase_				:     Optional[Any]	,						lowercase_				:     Dict  )					->						Optional[int]:
       with io.BytesIO() as buffer:
           JsonDatasetWriter(lowercase_	,						lowercase_	,						lines=lowercase_	,						num_proc=2  ).write()
           buffer.seek(0  )
           lowercase__ :   str    					=				load_json_function(lowercase_  )
       assert isinstance(lowercase_	,						lowercase_  )
       assert isinstance(exported_content[0]	,						lowercase_  )
       assert len(lowercase_  ) == 10






   @pytest.mark.parametrize(
       "orient, container, keys, len_at"	,						[
           ("records", list, {"tokens", "labels", "answers", "id"}, None),
           ("split", dict, {"columns", "data"}, "data"),
           ("index", dict, set("0123456789"  ), None),
           ("columns", dict, {"tokens", "labels", "answers", "id"}, "tokens"),
           ("values", list, None, None),
           ("table", dict, {"schema", "data"}, "data"),
       ]	,						)
   def       __UpperCamelCase     (      self				:     Union[str, Any]	,						lowercase_				:     Dict	,						lowercase_				:     Dict	,						lowercase_				:     Optional[int]	,						lowercase_				:     Optional[Any]	,						lowercase_				:     Dict  )					->						Any:
       with io.BytesIO() as buffer:
           JsonDatasetWriter(lowercase_	,						lowercase_	,						lines=lowercase_	,						orient=lowercase_	,						num_proc=2  ).write()
           buffer.seek(0  )
           lowercase__ :   Optional[Any]    					=				load_json(lowercase_  )
       assert isinstance(lowercase_	,						lowercase_  )
       if keys:
           if container is dict:
               assert exported_content.keys() == keys
           else:
               assert exported_content[0].keys() == keys
       else:
           assert not hasattr(lowercase_	,						"keys"  ) and not hasattr(exported_content[0]	,						"keys"  )
       if len_at:
           assert len(exported_content[len_at]  ) == 10
       else:
           assert len(lowercase_  ) == 10






   def       __UpperCamelCase     (      self				:     Dict	,						lowercase_				:     List[str]  )					->						str:
       with pytest.raises(lowercase_  ):
           with io.BytesIO() as buffer:
               JsonDatasetWriter(lowercase_	,						lowercase_	,						num_proc=0  )







   @pytest.mark.parametrize("compression, extension"	,						[("gzip", "gz"), ("bz2", "bz2"), ("xz", "xz")]  )
   def       __UpperCamelCase     (      self				:     List[Any]	,						lowercase_				:     Tuple	,						lowercase_				:     List[str]	,						lowercase_				:     Optional[Any]	,						lowercase_				:     str	,						lowercase_				:     List[Any]  )					->						Any:
       lowercase__ :   Dict    					=				tmp_path_factory.mktemp("data"  ) / F'''test.json.{extension}'''
       lowercase__ :   Optional[int]    					=				str(shared_datadir / F'''test_file.json.{extension}'''  )
       JsonDatasetWriter(lowercase_	,						lowercase_	,						compression=lowercase_  ).write()

       with fsspec.open(lowercase_	,						"rb"	,						compression="infer"  ) as f:
           lowercase__ :   List[Any]    					=				f.read()
       with fsspec.open(lowercase_	,						"rb"	,						compression="infer"  ) as f:
           lowercase__ :   str    					=				f.read()
       assert exported_content == original_content



