tf.raw_ops.LRNGrad

Gradients for Local Response Normalization.

tf.raw_ops.LRNGrad(
    input_grads, input_image, output_image, depth_radius=5, bias=1, alpha=1,
    beta=0.5, name=None
)

Args:

  • input_grads: A Tensor. Must be one of the following types: half, bfloat16, float32. 4-D with shape [batch, height, width, channels].
  • input_image: A Tensor. Must have the same type as input_grads. 4-D with shape [batch, height, width, channels].
  • output_image: A Tensor. Must have the same type as input_grads. 4-D with shape [batch, height, width, channels].
  • depth_radius: An optional int. Defaults to 5. A depth radius.
  • bias: An optional float. Defaults to 1. An offset (usually > 0 to avoid dividing by 0).
  • alpha: An optional float. Defaults to 1. A scale factor, usually positive.
  • beta: An optional float. Defaults to 0.5. An exponent.
  • name: A name for the operation (optional).

Returns:

A Tensor. Has the same type as input_grads.