




'''simple docstring'''



from collections import defaultdict
from typing import Optional

from ..image_utils import load_image
from ..utils import (
    add_end_docstrings,
    is_torch_available,
    logging,
    requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline


if is_torch_available():
      import torch

      from ..models.auto.modeling_auto import MODEL_FOR_MASK_GENERATION_MAPPING

UpperCamelCase_    	=				logging.get_logger(__name__)






@add_end_docstrings(SCREAMING_SNAKE_CASE )
class 							_a				(			SCREAMING_SNAKE_CASE ):





       '''simple docstring'''






       def __init__(      self,							**A  ):







             '''simple docstring'''







             super().__init__(**A  )
             requires_backends(self,							'vision'  )
             requires_backends(self,							'torch'  )

             if self.framework != "pt":
                   raise ValueError(F"The {self.__class__} is only available in PyTorch."  )

             self.check_model_type(A  )







       def        UpperCamelCase_							(      self,							**A  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      Any    					=						{}
             SCREAMING_SNAKE_CASE   :      Optional[Any]    					=						{}
             SCREAMING_SNAKE_CASE   :      Tuple    					=						{}
             # preprocess args
             if "points_per_batch" in kwargs:
                   SCREAMING_SNAKE_CASE   :      List[Any]    					=						kwargs['points_per_batch']
             if "points_per_crop" in kwargs:
                   SCREAMING_SNAKE_CASE   :      str    					=						kwargs['points_per_crop']
             if "crops_n_layers" in kwargs:
                   SCREAMING_SNAKE_CASE   :      Any    					=						kwargs['crops_n_layers']
             if "crop_overlap_ratio" in kwargs:
                   SCREAMING_SNAKE_CASE   :      Dict    					=						kwargs['crop_overlap_ratio']
             if "crop_n_points_downscale_factor" in kwargs:
                   SCREAMING_SNAKE_CASE   :      Tuple    					=						kwargs['crop_n_points_downscale_factor']
             # postprocess args
             if "pred_iou_thresh" in kwargs:
                   SCREAMING_SNAKE_CASE   :      Optional[Any]    					=						kwargs['pred_iou_thresh']
             if "stability_score_offset" in kwargs:
                   SCREAMING_SNAKE_CASE   :      Tuple    					=						kwargs['stability_score_offset']
             if "mask_threshold" in kwargs:
                   SCREAMING_SNAKE_CASE   :      Dict    					=						kwargs['mask_threshold']
             if "stability_score_thresh" in kwargs:
                   SCREAMING_SNAKE_CASE   :      Optional[int]    					=						kwargs['stability_score_thresh']
             if "crops_nms_thresh" in kwargs:
                   SCREAMING_SNAKE_CASE   :      int    					=						kwargs['crops_nms_thresh']
             if "output_rle_mask" in kwargs:
                   SCREAMING_SNAKE_CASE   :      List[str]    					=						kwargs['output_rle_mask']
             if "output_bboxes_mask" in kwargs:
                   SCREAMING_SNAKE_CASE   :      Dict    					=						kwargs['output_bboxes_mask']
             return preprocess_kwargs, forward_params, postprocess_kwargs







       def __call__(      self,							A,							*A,							A=None,							A=None,							**A  ):







             '''simple docstring'''







             return super().__call__(A,							*A,							num_workers=A,							batch_size=A,							**A  )







       def        UpperCamelCase_							(      self,							A,							A=64,							A = 0,							A = 512 / 1_500,							A = 32,							A = 1,							):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      str    					=						load_image(A  )
             SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						self.image_processor.size['longest_edge']
             SCREAMING_SNAKE_CASE					,    SCREAMING_SNAKE_CASE					,    SCREAMING_SNAKE_CASE					,    SCREAMING_SNAKE_CASE   :      Tuple    					=						self.image_processor.generate_crop_boxes(
                 A,							A,							A,							A,							A,							A  )
             SCREAMING_SNAKE_CASE   :      Any    					=						self.image_processor(images=A,							return_tensors='pt'  )

             with self.device_placement():
                   if self.framework == "pt":
                         SCREAMING_SNAKE_CASE   :      int    					=						self.get_inference_context()
                         with inference_context():
                               SCREAMING_SNAKE_CASE   :      Optional[int]    					=						self._ensure_tensor_on_device(A,							device=self.device  )
                               SCREAMING_SNAKE_CASE   :      int    					=						self.model.get_image_embeddings(model_inputs.pop('pixel_values'  )  )
                               SCREAMING_SNAKE_CASE   :      str    					=						image_embeddings

             SCREAMING_SNAKE_CASE   :      List[str]    					=						grid_points.shape[1]
             SCREAMING_SNAKE_CASE   :      Dict    					=						points_per_batch if points_per_batch is not None else n_points

             if points_per_batch <= 0:
                   raise ValueError(
                       'Cannot have points_per_batch<=0. Must be >=1 to returned batched outputs. '
                       'To return all points at once, set points_per_batch to None'  )

             for i in range(0,							A,							A  ):
                   SCREAMING_SNAKE_CASE   :      Optional[int]    					=						grid_points[:, i : i + points_per_batch, :, :]
                   SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						input_labels[:, i : i + points_per_batch]
                   SCREAMING_SNAKE_CASE   :      str    					=						i == n_points - points_per_batch
                   yield {
                       "input_points": batched_points,
                       "input_labels": labels,
                       "input_boxes": crop_boxes,
                       "is_last": is_last,
                       **model_inputs,
                   }







       def        UpperCamelCase_							(      self,							A,							A=0.88,							A=0.95,							A=0,							A=1,							):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						model_inputs.pop('input_boxes'  )
             SCREAMING_SNAKE_CASE   :      Any    					=						model_inputs.pop('is_last'  )
             SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						model_inputs.pop('original_sizes'  ).tolist()
             SCREAMING_SNAKE_CASE   :      Dict    					=						model_inputs.pop('reshaped_input_sizes'  ).tolist()

             SCREAMING_SNAKE_CASE   :      List[str]    					=						self.model(**A  )

             # post processing happens here in order to avoid CPU GPU copies of ALL the masks
             SCREAMING_SNAKE_CASE   :      List[str]    					=						model_outputs['pred_masks']
             SCREAMING_SNAKE_CASE   :      Dict    					=						self.image_processor.post_process_masks(
                 A,							A,							A,							A,							binarize=A  )
             SCREAMING_SNAKE_CASE   :      List[str]    					=						model_outputs['iou_scores']
             SCREAMING_SNAKE_CASE					,    SCREAMING_SNAKE_CASE					,    SCREAMING_SNAKE_CASE   :      str    					=						self.image_processor.filter_masks(
                 masks[0],							iou_scores[0],							original_sizes[0],							input_boxes[0],							A,							A,							A,							A,							)
             return {
                 "masks": masks,
                 "is_last": is_last,
                 "boxes": boxes,
                 "iou_scores": iou_scores,
             }







       def        UpperCamelCase_							(      self,							A,							A=False,							A=False,							A=0.7,							):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      int    					=						[]
             SCREAMING_SNAKE_CASE   :      Dict    					=						[]
             SCREAMING_SNAKE_CASE   :      List[Any]    					=						[]
             for model_output in model_outputs:
                   all_scores.append(model_output.pop('iou_scores'  )  )
                   all_masks.extend(model_output.pop('masks'  )  )
                   all_boxes.append(model_output.pop('boxes'  )  )

             SCREAMING_SNAKE_CASE   :      str    					=						torch.cat(A  )
             SCREAMING_SNAKE_CASE   :      Optional[Any]    					=						torch.cat(A  )
             SCREAMING_SNAKE_CASE					,    SCREAMING_SNAKE_CASE					,    SCREAMING_SNAKE_CASE					,    SCREAMING_SNAKE_CASE   :      Optional[int]    					=						self.image_processor.post_process_for_mask_generation(
                 A,							A,							A,							A  )

             SCREAMING_SNAKE_CASE   :      Optional[Any]    					=						defaultdict(A  )
             for output in model_outputs:
                   for k, v in output.items():
                         extra[k].append(A  )

             SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						{}
             if output_rle_mask:
                   SCREAMING_SNAKE_CASE   :      Optional[Any]    					=						rle_mask

             if output_bboxes_mask:
                   SCREAMING_SNAKE_CASE   :      str    					=						bounding_boxes

             return {"masks": output_masks, "scores": iou_scores, **optional, **extra}








'''simple docstring'''



from typing import Any






class 							_a				:





       '''simple docstring'''






       def __init__(      self,							A  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      str    					=						data
             SCREAMING_SNAKE_CASE   :      Any    					=						None







       def __repr__(      self  ):







             '''simple docstring'''







             return F"Node({self.data})"






class 							_a				:





       '''simple docstring'''






       def __init__(      self  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      List[str]    					=						None







       def __iter__(      self  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      Optional[Any]    					=						self.head
             while node:
                   yield node.data
                   SCREAMING_SNAKE_CASE   :      List[str]    					=						node.next







       def __len__(      self  ):







             '''simple docstring'''







             return sum(1 for _ in self  )







       def __repr__(      self  ):







             '''simple docstring'''







             return "->".join([str(A  ) for item in self]  )







       def __getitem__(      self,							A  ):







             '''simple docstring'''







             if not 0 <= index < len(self  ):
                   raise ValueError('list index out of range.'  )
             for i, node in enumerate(self  ):
                   if i == index:
                         return node
             return None







       def __setitem__(      self,							A,							A  ):







             '''simple docstring'''







             if not 0 <= index < len(self  ):
                   raise ValueError('list index out of range.'  )
             SCREAMING_SNAKE_CASE   :      Optional[Any]    					=						self.head
             for _ in range(A  ):
                   SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						current.next
             SCREAMING_SNAKE_CASE   :      Any    					=						data







       def        UpperCamelCase_							(      self,							A  ):







             '''simple docstring'''







             self.insert_nth(len(self  ),							A  )







       def        UpperCamelCase_							(      self,							A  ):







             '''simple docstring'''







             self.insert_nth(0,							A  )







       def        UpperCamelCase_							(      self,							A,							A  ):







             '''simple docstring'''







             if not 0 <= index <= len(self  ):
                   raise IndexError('list index out of range'  )
             SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						Node(A  )
             if self.head is None:
                   SCREAMING_SNAKE_CASE   :      Optional[int]    					=						new_node
             elif index == 0:
                   SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						self.head  # link new_node to head
                   SCREAMING_SNAKE_CASE   :      Tuple    					=						new_node
             else:
                   SCREAMING_SNAKE_CASE   :      Optional[int]    					=						self.head
                   for _ in range(index - 1  ):
                         SCREAMING_SNAKE_CASE   :      str    					=						temp.next
                   SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						temp.next
                   SCREAMING_SNAKE_CASE   :      List[str]    					=						new_node







       def        UpperCamelCase_							(      self  ):  # print every node data







             '''simple docstring'''







             print(self  )







       def        UpperCamelCase_							(      self  ):







             '''simple docstring'''







             return self.delete_nth(0  )







       def        UpperCamelCase_							(      self  ):  # delete from tail







             '''simple docstring'''







             return self.delete_nth(len(self  ) - 1  )







       def        UpperCamelCase_							(      self,							A = 0  ):







             '''simple docstring'''







             if not 0 <= index <= len(self  ) - 1:  # test if index is valid
                   raise IndexError('List index out of range.'  )
             SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						self.head  # default first node
             if index == 0:
                   SCREAMING_SNAKE_CASE   :      List[str]    					=						self.head.next
             else:
                   SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						self.head
                   for _ in range(index - 1  ):
                         SCREAMING_SNAKE_CASE   :      Any    					=						temp.next
                   SCREAMING_SNAKE_CASE   :      List[str]    					=						temp.next
                   SCREAMING_SNAKE_CASE   :      Optional[int]    					=						temp.next.next
             return delete_node.data







       def        UpperCamelCase_							(      self  ):







             '''simple docstring'''







             return self.head is None







       def        UpperCamelCase_							(      self  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      int    					=						None
             SCREAMING_SNAKE_CASE   :      Any    					=						self.head

             while current:
                   # Store the current node's next node.
                   SCREAMING_SNAKE_CASE   :      Optional[int]    					=						current.next
                   # Make the current node's next point backwards
                   SCREAMING_SNAKE_CASE   :      int    					=						prev
                   # Make the previous node be the current node
                   SCREAMING_SNAKE_CASE   :      int    					=						current
                   # Make the current node the next node (to progress iteration)
                   SCREAMING_SNAKE_CASE   :      List[Any]    					=						next_node
             # Return prev in order to put the head at the end
             SCREAMING_SNAKE_CASE   :      List[Any]    					=						prev




def   lowercase__(			):

      """simple docstring"""






      SCREAMING_SNAKE_CASE   :      Dict    					=						LinkedList()
      assert linked_list.is_empty() is True
      assert str(__UpperCamelCase    ) == ""

      try:
            linked_list.delete_head()
            raise AssertionError  # This should not happen.
      except IndexError:
            assert True  # This should happen.

      try:
            linked_list.delete_tail()
            raise AssertionError  # This should not happen.
      except IndexError:
            assert True  # This should happen.

      for i in range(10    ):
            assert len(__UpperCamelCase    ) == i
            linked_list.insert_nth(__UpperCamelCase      ,i + 1    )
      assert str(__UpperCamelCase    ) == "->".join(str(__UpperCamelCase    ) for i in range(1      ,11    )    )

      linked_list.insert_head(0    )
      linked_list.insert_tail(11    )
      assert str(__UpperCamelCase    ) == "->".join(str(__UpperCamelCase    ) for i in range(0      ,12    )    )

      assert linked_list.delete_head() == 0
      assert linked_list.delete_nth(9    ) == 10
      assert linked_list.delete_tail() == 11
      assert len(__UpperCamelCase    ) == 9
      assert str(__UpperCamelCase    ) == "->".join(str(__UpperCamelCase    ) for i in range(1      ,10    )    )

      assert all(linked_list[i] == i + 1 for i in range(0      ,9    )    ) is True

      for i in range(0      ,9    ):
            SCREAMING_SNAKE_CASE   :      Any    					=						-i
      assert all(linked_list[i] == -i for i in range(0      ,9    )    ) is True

      linked_list.reverse()
      assert str(__UpperCamelCase    ) == "->".join(str(__UpperCamelCase    ) for i in range(-8      ,1    )    )




def   lowercase__(			):

      """simple docstring"""






      SCREAMING_SNAKE_CASE   :      List[str]    					=						[
          -9,
          1_00,
          Node(77_34_51_12    ),
          'dlrow olleH',
          7,
          55_55,
          0,
          -1_9_2.5_5_5_5_5,
          'Hello, world!',
          7_7.9,
          Node(10    ),
          None,
          None,
          1_2.2_0,
      ]
      SCREAMING_SNAKE_CASE   :      Optional[int]    					=						LinkedList()

      for i in test_input:
            linked_list.insert_tail(__UpperCamelCase    )

      # Check if it's empty or not
      assert linked_list.is_empty() is False
      assert (
          str(__UpperCamelCase    ) == "-9->100->Node(77345112)->dlrow olleH->7->5555->0->"
          "-192.55555->Hello, world!->77.9->Node(10)->None->None->12.2"
      )

      # Delete the head
      SCREAMING_SNAKE_CASE   :      str    					=						linked_list.delete_head()
      assert result == -9
      assert (
          str(__UpperCamelCase    ) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
          "Hello, world!->77.9->Node(10)->None->None->12.2"
      )

      # Delete the tail
      SCREAMING_SNAKE_CASE   :      Dict    					=						linked_list.delete_tail()
      assert result == 1_2.2
      assert (
          str(__UpperCamelCase    ) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
          "Hello, world!->77.9->Node(10)->None->None"
      )

      # Delete a node in specific location in linked list
      SCREAMING_SNAKE_CASE   :      str    					=						linked_list.delete_nth(10    )
      assert result is None
      assert (
          str(__UpperCamelCase    ) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
          "Hello, world!->77.9->Node(10)->None"
      )

      # Add a Node instance to its head
      linked_list.insert_head(Node('Hello again, world!'    )    )
      assert (
          str(__UpperCamelCase    )
          == "Node(Hello again, world!)->100->Node(77345112)->dlrow olleH->"
          "7->5555->0->-192.55555->Hello, world!->77.9->Node(10)->None"
      )

      # Add None to its tail
      linked_list.insert_tail(__UpperCamelCase    )
      assert (
          str(__UpperCamelCase    )
          == "Node(Hello again, world!)->100->Node(77345112)->dlrow olleH->"
          "7->5555->0->-192.55555->Hello, world!->77.9->Node(10)->None->None"
      )

      # Reverse the linked list
      linked_list.reverse()
      assert (
          str(__UpperCamelCase    )
          == "None->None->Node(10)->77.9->Hello, world!->-192.55555->0->5555->"
          "7->dlrow olleH->Node(77345112)->100->Node(Hello again, world!)"
      )




def   lowercase__(			):

      """simple docstring"""






      from doctest import testmod

      testmod()

      SCREAMING_SNAKE_CASE   :      Dict    					=						LinkedList()
      linked_list.insert_head(input('Inserting 1st at head '    ).strip()    )
      linked_list.insert_head(input('Inserting 2nd at head '    ).strip()    )
      print('\nPrint list:'    )
      linked_list.print_list()
      linked_list.insert_tail(input('\nInserting 1st at tail '    ).strip()    )
      linked_list.insert_tail(input('Inserting 2nd at tail '    ).strip()    )
      print('\nPrint list:'    )
      linked_list.print_list()
      print('\nDelete head'    )
      linked_list.delete_head()
      print('Delete tail'    )
      linked_list.delete_tail()
      print('\nPrint list:'    )
      linked_list.print_list()
      print('\nReverse linked list'    )
      linked_list.reverse()
      print('\nPrint list:'    )
      linked_list.print_list()
      print('\nString representation of linked list:'    )
      print(__UpperCamelCase    )
      print('\nReading/changing Node data using indexing:'    )
      print(f"Element at Position 1: {linked_list[1]}"    )
      SCREAMING_SNAKE_CASE   :      str    					=						input('Enter New Value: '    ).strip()
      print('New list:'    )
      print(__UpperCamelCase    )
      print(f"length of linked_list is : {len(__UpperCamelCase    )}"    )


if __name__ == "__main__":
      main()


