[GitHub] [incubator-mxnet] apeforest commented on a change in pull request #15611: [MXNET-978] n-th order gradient test support.

[GitBox <gi...@apache.org>]

apeforest commented on a change in pull request #15611: [MXNET-978] n-th order gradient test support.
URL: https://github.com/apache/incubator-mxnet/pull/15611#discussion_r324415885
 
 

 ##########
 File path: tests/python/unittest/test_higher_order_grad.py
 ##########
 @@ -302,28 +322,72 @@ def grad_grad_op(x):
 
 
 def check_second_order_unary(x, op, grad_grad_op, rtol=None, atol=None):
+    check_nth_order_unary(x, op, grad_grad_op, 2, rtol, atol)
+
+
+def check_nth_order_unary(x, op, grad_ops, orders, rtol=None, atol=None):
+    """Assert n-th order autograd gradient against expected gradient.
+
+    Multiple order of gradients can be checked by passing list of
+    function computing the particular order gradient and passing the
+    corresponding list of order.
+
+    Note
+    ----
+    1. Orders should always be monotonically increasing.
+    2. Elements of grads_ops should correspond to elements of orders
+    i.e. grads_op = [grad_op, grad_grad_grad_op] should be passed with
+         orders = [1, 3]
+
+    Parameters
+    ----------
+    x : mxnet.NDArray
+        Input Array.
+    op : Callable
+        Operation to perform on Input Array.
+    grad_ops : Callable or List of Callable
+        Function to compute and assert gradient of given order.
+    orders : int or List of int
+        Order/s to assert expected and computed gradients.
+
+    Returns
+    -------
+    None
+
+    """
+    if isinstance(orders, int):
+        orders = [orders]
+        grad_ops = [grad_ops]
+
     x = nd.array(x)
-    grad_grad_x = grad_grad_op(x)
     x.attach_grad()
 
-    # Manual head_grads.
-    y_grad = nd.random.normal(shape=x.shape)
-    head_grad_grads = nd.random.normal(shape=x.shape)
+    order = max(orders)
 
 Review comment:
   If orders is monotonically increasing, should this just be orders[-1]?

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