ResNet/resnet_model.py
def mish_fn(x, name):
  """Self Regularized Non-Monotonic Activation Function.

  Original paper: https://arxiv.org/pdf/1908.08681.pdf

  Args:
    x: float Tensor to perform activation.

  Returns:
    `x` with the Mish activation applied.
  """
  with tf.compat.v1.name_scope(name):
    return x * tf.tanh(tf.math.softplus(x))
Self Regularized Non-Monotonic Activation Function.

  Original paper: https://arxiv.org/pdf/1908.08681.pdf

  Args:
    x: float Tensor to perform activation.

  Returns:
    `x` with the Mish activation applied.
  
Self Regularized Non-Monotonic Activation Function.
Self Regularized Non - Monotonic Activation Function .
def mish_fn(x, name):
  with tf.compat.v1.name_scope(name):
    return x * tf.tanh(tf.math.softplus(x))
def mish_fn ( x , name ) : with tf . compat . v1 . name_scope ( name ) : return x * tf . tanh ( tf . math . softplus ( x ) )
Self Regularized Non-Monotonic Activation Function.
Self Regularized Non - Monotonic Activation Function .
"""Self Regularized Non-Monotonic Activation Function.

  Original paper: https://arxiv.org/pdf/1908.08681.pdf

  Args:
    x: float Tensor to perform activation.

  Returns:
    `x` with the Mish activation applied.
  """
`x` with the Mish activation applied.
` x ` with the Mish activation applied .
x
float Tensor to perform activation.
float Tensor to perform activation .
name