[GitHub] [incubator-mxnet] hgt312 commented on a change in pull request #16750: [Numpy] add custom op sort

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

hgt312 commented on a change in pull request #16750: [Numpy] add custom op sort
URL: https://github.com/apache/incubator-mxnet/pull/16750#discussion_r344021464
 
 

 ##########
 File path: python/mxnet/numpy_op_fallback.py
 ##########
 @@ -49,6 +49,48 @@ def _register_helper(prop_cls):
     return _register_helper
 
 
+@use_np  # enforce np shape and array semantics for all the methods in this class
+class Sort(operator.CustomOp):
+    """Fallback to NumPy sort operator."""
+    def __init__(self, axis, kind):
+        super(Sort, self).__init__()
+        self._axis = axis
+        self._kind = kind
+
+    def forward(self, is_train, req, in_data, out_data, aux):
+        out = np.sort(in_data[0].asnumpy(), self._axis, self._kind)
+        self.assign(out_data[0], req[0], _mx_np.array(out, dtype=out.dtype, ctx=out_data[0].ctx))
+
+    def backward(self, req, out_grad, in_data, out_data, in_grad, aux):
+        raise NotImplementedError('Operator sort does not support gradient computation')
+
+
+@register('sort_fallback')
+class SortProp(operator.CustomOpProp):
+    """Fallback sort operator properties."""
+    def __init__(self, axis, kind):
+        super(SortProp, self).__init__(need_top_grad=True)
+        self._axis = ast.literal_eval(axis)
+        self._kind = None if kind == 'None' else kind
+
+    def list_arguments(self):
+        return ['a']
+
+    def infer_shape(self, in_shape):
+        if self._axis is None and len(in_shape[0]) == 0:
+            out_shape = (1,)
+        elif self._axis is None:
+            out_shape = (np.prod(in_shape[0]),)
+        elif (self._axis + 1) > len(in_shape[0]) or abs(self._axis) > len(in_shape[0]):
 
 Review comment:
   same here

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