def _cosine_similarity(self, x, y, eps, view_func):
x = view_func(x)
y = view_func(y)
x_norm = math_ops.euclidean_norm(x, axis=-1) + eps
y_norm = math_ops.euclidean_norm(y, axis=-1) + eps
dot = math_ops.reduce_sum(x * y, axis=-1)
return math_ops.abs(dot) / x_norm / y_norm
def layer_true_fn(self, var, perturb, wd_ratio, eps):
expand_size = [-1] + [1] * (len(var.shape) - 1)
var_n = var / (array_ops.reshape(math_ops.euclidean_norm(
self._layer_view(var), axis=-1),
shape=expand_size) + eps)
perturb -= var_n * array_ops.reshape(math_ops.reduce_sum(
self._layer_view(var_n * perturb), axis=-1),
shape=expand_size)
wd = wd_ratio
return perturb, wd
def channel_true_fn(self, var, perturb, wd_ratio, eps):
expand_size = [-1] + [1] * (len(var.shape) - 1)
var_n = var / (array_ops.reshape(math_ops.euclidean_norm(
self._channel_view(var), axis=-1),
shape=expand_size) + eps)
perturb = state_ops.assign_sub(
perturb,
var_n * array_ops.reshape(math_ops.reduce_sum(
self._channel_view(var_n * perturb), axis=-1),
shape=expand_size))
wd = wd_ratio
return perturb, wd