class_docstr: GridMask class for grid masking augmentation.
class_docstr_tok: ["GridMask","class","for","grid","masking","augmentation","."]
docstr: initialization.
  
  Args:
    prob: probablity of occurance.
    ratio: grid mask ratio i.e if 0.5 grid and spacing will be equal.
    rotate: Rotation of grid mesh.
    gridmask_size_ratio: Grid mask size, grid to image size ratio.
    fill: Fill value for grids.
    interpolation: Interpolation method for rotation.
docstr_tok: ["initialization",".","Args",":","prob",":","probablity","of","occurance",".","ratio",":","grid","mask","ratio","i.e","if","0.5","grid","and","spacing","will","be","equal",".","rotate",":","Rotation","of","grid","mesh",".","gridmask_size_ratio",":","Grid","mask","size",",","grid","to","image","size","ratio",".","fill",":","Fill","value","for","grids",".","interpolation",":","Interpolation","method","for","rotation","."]
code: def __init__(
      self,
      prob=0.6,
      ratio=0.6,
      rotate=10,
      gridmask_size_ratio=0.5,
      fill=1,
      interpolation="BILINEAR",
  ):
      """initialization.
  
      Args:
        prob: probablity of occurance.
        ratio: grid mask ratio i.e if 0.5 grid and spacing will be equal.
        rotate: Rotation of grid mesh.
        gridmask_size_ratio: Grid mask size, grid to image size ratio.
        fill: Fill value for grids.
        interpolation: Interpolation method for rotation.
      """
      self.prob = prob
      self.ratio = ratio
      self.rotate = rotate
      self.gridmask_size_ratio = gridmask_size_ratio
      self.fill = fill
      self.interpolation = interpolation
  
file_path: DALI/docs/examples/use_cases/tensorflow/efficientdet/pipeline/tf/gridmask.py
imports: import math
  import tensorflow
  from tensorflow_addons import image
label_desc: Use image node_id 1 to create a new GridMask object from inherited base classes: object with example: obj = GridMask(prob, ratio, rotate, gridmask_size_ratio, fill, interpolation)