



"""simple docstring"""





import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def      a__			(   lowerCAmelCase__			,    lowerCAmelCase__   ):
      assert isinstance(lowerCAmelCase__			,    lowerCAmelCase__   )
      assert dataset.num_rows == 4
      assert dataset.num_columns == 1
      assert dataset.column_names == ["text"]
      for feature, expected_dtype in expected_features.items():
            assert dataset.features[feature].dtype == expected_dtype
@pytest.mark.parametrize("keep_in_memory"			,    [False, True]   )
def      a__			(   lowerCAmelCase__			,    lowerCAmelCase__			,    lowerCAmelCase__   ):
      UpperCAmelCase_    				=							tmp_path / "cache"
      UpperCAmelCase_    				=							{"text": "string"}
      with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
            UpperCAmelCase_    				=							TextDatasetReader(lowerCAmelCase__			,    cache_dir=lowerCAmelCase__			,    keep_in_memory=lowerCAmelCase__   ).read()
      _check_text_dataset(lowerCAmelCase__			,    lowerCAmelCase__   )
@pytest.mark.parametrize(
    "features"			,    [
        None,
        {"text": "string"},
        {"text": "int32"},
        {"text": "float32"},
    ]			,    )
def      a__			(   lowerCAmelCase__			,    lowerCAmelCase__			,    lowerCAmelCase__   ):
      UpperCAmelCase_    				=							tmp_path / "cache"
      UpperCAmelCase_    				=							{"text": "string"}
      UpperCAmelCase_    				=							features.copy() if features else default_expected_features
      UpperCAmelCase_    				=							(
          Features({feature: Value(lowerCAmelCase__   ) for feature, dtype in features.items()}   ) if features is not None else None
      )
      UpperCAmelCase_    				=							TextDatasetReader(lowerCAmelCase__			,    features=lowerCAmelCase__			,    cache_dir=lowerCAmelCase__   ).read()
      _check_text_dataset(lowerCAmelCase__			,    lowerCAmelCase__   )
@pytest.mark.parametrize("split"			,    [None, NamedSplit("train"   ), "train", "test"]   )
def      a__			(   lowerCAmelCase__			,    lowerCAmelCase__			,    lowerCAmelCase__   ):
      UpperCAmelCase_    				=							tmp_path / "cache"
      UpperCAmelCase_    				=							{"text": "string"}
      UpperCAmelCase_    				=							TextDatasetReader(lowerCAmelCase__			,    cache_dir=lowerCAmelCase__			,    split=lowerCAmelCase__   ).read()
      _check_text_dataset(lowerCAmelCase__			,    lowerCAmelCase__   )
      assert dataset.split == split if split else "train"
@pytest.mark.parametrize("path_type"			,    [str, list]   )
def      a__			(   lowerCAmelCase__			,    lowerCAmelCase__			,    lowerCAmelCase__   ):



      if issubclass(lowerCAmelCase__			,    lowerCAmelCase__   ):
            UpperCAmelCase_    				=							text_path
      elif issubclass(lowerCAmelCase__			,    lowerCAmelCase__   ):
            UpperCAmelCase_    				=							[text_path]
      UpperCAmelCase_    				=							tmp_path / "cache"
      UpperCAmelCase_    				=							{"text": "string"}
      UpperCAmelCase_    				=							TextDatasetReader(lowerCAmelCase__			,    cache_dir=lowerCAmelCase__   ).read()
      _check_text_dataset(lowerCAmelCase__			,    lowerCAmelCase__   )
def      a__			(   lowerCAmelCase__			,    lowerCAmelCase__			,    lowerCAmelCase__=("train",)   ):
      assert isinstance(lowerCAmelCase__			,    lowerCAmelCase__   )
      for split in splits:
            UpperCAmelCase_    				=							dataset_dict[split]
            assert dataset.num_rows == 4
            assert dataset.num_columns == 1
            assert dataset.column_names == ["text"]
            for feature, expected_dtype in expected_features.items():
                  assert dataset.features[feature].dtype == expected_dtype
@pytest.mark.parametrize("keep_in_memory"			,    [False, True]   )
def      a__			(   lowerCAmelCase__			,    lowerCAmelCase__			,    lowerCAmelCase__   ):
      UpperCAmelCase_    				=							tmp_path / "cache"
      UpperCAmelCase_    				=							{"text": "string"}
      with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
            UpperCAmelCase_    				=							TextDatasetReader({"train": text_path}			,    cache_dir=lowerCAmelCase__			,    keep_in_memory=lowerCAmelCase__   ).read()
      _check_text_datasetdict(lowerCAmelCase__			,    lowerCAmelCase__   )
@pytest.mark.parametrize(
    "features"			,    [
        None,
        {"text": "string"},
        {"text": "int32"},
        {"text": "float32"},
    ]			,    )
def      a__			(   lowerCAmelCase__			,    lowerCAmelCase__			,    lowerCAmelCase__   ):
      UpperCAmelCase_    				=							tmp_path / "cache"
      # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
      UpperCAmelCase_    				=							{"text": "string"}
      UpperCAmelCase_    				=							features.copy() if features else default_expected_features
      UpperCAmelCase_    				=							(
          Features({feature: Value(lowerCAmelCase__   ) for feature, dtype in features.items()}   ) if features is not None else None
      )
      UpperCAmelCase_    				=							TextDatasetReader({"train": text_path}			,    features=lowerCAmelCase__			,    cache_dir=lowerCAmelCase__   ).read()
      _check_text_datasetdict(lowerCAmelCase__			,    lowerCAmelCase__   )
@pytest.mark.parametrize("split"			,    [None, NamedSplit("train"   ), "train", "test"]   )
def      a__			(   lowerCAmelCase__			,    lowerCAmelCase__			,    lowerCAmelCase__   ):



      if split:
            UpperCAmelCase_    				=							{split: text_path}
      else:
            UpperCAmelCase_    				=							"train"
            UpperCAmelCase_    				=							{"train": text_path, "test": text_path}
      UpperCAmelCase_    				=							tmp_path / "cache"
      UpperCAmelCase_    				=							{"text": "string"}
      UpperCAmelCase_    				=							TextDatasetReader(lowerCAmelCase__			,    cache_dir=lowerCAmelCase__   ).read()
      _check_text_datasetdict(lowerCAmelCase__			,    lowerCAmelCase__			,    splits=list(path.keys()   )   )
      assert all(dataset[split].split == split for split in path.keys()   )









"""simple docstring"""





from heapq import heappop, heappush

import numpy as np
def      a__			(   lowerCAmelCase__			,    lowerCAmelCase__			,    lowerCAmelCase__			,    lowerCAmelCase__			,    ):
      UpperCAmelCase_				,					UpperCAmelCase_    				=							grid.shape
      UpperCAmelCase_    				=							[-1, 1, 0, 0]
      UpperCAmelCase_    				=							[0, 0, -1, 1]
      if allow_diagonal:
            dx += [-1, -1, 1, 1]
            dy += [-1, 1, -1, 1]

      UpperCAmelCase_				,					UpperCAmelCase_    				=							[(0, source)], set()
      UpperCAmelCase_    				=							np.full((rows, cols)			,    np.inf   )
      UpperCAmelCase_    				=							0
      UpperCAmelCase_    				=							np.empty((rows, cols)			,    dtype=lowerCAmelCase__   )
      UpperCAmelCase_    				=							None

      while queue:
            ((UpperCAmelCase_)				,					(UpperCAmelCase_))    				=							heappop(lowerCAmelCase__   )
            if (x, y) in visited:
                  continue
            visited.add((x, y)   )

            if (x, y) == destination:
                  UpperCAmelCase_    				=							[]
                  while (x, y) != source:
                        path.append((x, y)   )
                        UpperCAmelCase_				,					UpperCAmelCase_    				=							predecessors[x, y]
                  path.append(lowerCAmelCase__   )  # add the source manually
                  path.reverse()
                  return matrix[destination], path

            for i in range(len(lowerCAmelCase__   )   ):
                  UpperCAmelCase_				,					UpperCAmelCase_    				=							x + dx[i], y + dy[i]
                  if 0 <= nx < rows and 0 <= ny < cols:
                        UpperCAmelCase_    				=							grid[nx][ny]
                        if next_node == 1 and matrix[nx, ny] > dist + 1:
                              heappush(lowerCAmelCase__			,    (dist + 1, (nx, ny))   )
                              UpperCAmelCase_    				=							dist + 1
                              UpperCAmelCase_    				=							(x, y)

      return np.inf, []


if __name__ == "__main__":
  import doctest

  doctest.testmod()




