class_docstr: Get parameters for ``translate`` for a random translate transform.
  
  Args:
      translate: tuple of maximum absolute fraction for horizontal
          and vertical translations. For example translate=(a, b), then horizontal shift
          is randomly sampled in the range -img_width * a < dx < img_width * a and vertical shift is
          randomly sampled in the range -img_height * b < dy < img_height * b. Will not translate by default.
  
  Returns:
      A dict of parameters to be passed for transformation.
          - translations (Tensor): element-wise translations with a shape of (B, 2).
  
  Note:
      The generated random numbers are not reproducible across different devices and dtypes. By default,
      the parameters will be generated on CPU in float32. This can be changed by calling
      ``self.set_rng_device_and_dtype(device="cuda", dtype=torch.float64)``.
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code: def __repr__(self) -> str:
      repr = f"translate_x={self.translate_x}, translate_y={self.translate_y}"
      return repr
  
file_path: kornia/kornia/augmentation/random_generator/_2d/translate.py
imports: from typing import Dict, Optional, Tuple, Union
  import torch
  from kornia.augmentation.random_generator.base import RandomGeneratorBase, UniformDistribution
  from kornia.augmentation.utils import _adapted_rsampling, _common_param_check, _range_bound
  from kornia.core import Tensor
  from kornia.utils.helpers import _extract_device_dtype
label_desc: Use image node_id 2 for calling the TranslateGenerator obj's underlying member method code with example usage: obj.__repr__() and returns: repr