[GitHub] [incubator-mxnet] gyshi commented on a change in pull request #15902: Numpy add numpy op roll

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

gyshi commented on a change in pull request #15902: Numpy add numpy op roll
URL: https://github.com/apache/incubator-mxnet/pull/15902#discussion_r325607539
 
 

 ##########
 File path: src/operator/numpy/np_matrix_op.cc
 ##########
 @@ -345,5 +346,73 @@ Examples::
 .add_argument("data", "NDArray-or-Symbol[]", "List of arrays to stack")
 .add_arguments(StackParam::__FIELDS__());
 
+inline bool NumpyRollShape(const nnvm::NodeAttrs& attrs,
+                           mxnet::ShapeVector *in_attrs,
+                           mxnet::ShapeVector *out_attrs) {
+  using namespace mshadow;
+  const NumpyRollParam& param = nnvm::get<NumpyRollParam>(attrs.parsed);
+
+  if (!param.shift.has_value()) {
+    LOG(FATAL) << "roll missing 1 required positional argument: 'shift'.";
+  }
+  if (param.shift.value().ndim() > 1 &&
+      param.axis.has_value() &&
+      param.axis.value().ndim() != param.shift.value().ndim()) {
+    LOG(FATAL) << "shift and `axis` must be a tuple of the same size.";
+  }
+  if (!param.axis.has_value() && param.shift.has_value() && param.shift.value().ndim() > 1) {
+    LOG(FATAL) << "shift must be an int.";
+  }
+  if (param.axis.has_value()) {
+    mxnet::TShape axes(param.axis.value());
+    const index_t ndim = (*in_attrs)[0].ndim();
+    for (index_t i = 0; i < axes.ndim(); i++) {
+      if (axes[i] < 0) {
+        axes[i] += ndim;
+      }
+    }
+    std::sort(axes.begin(), axes.end());
+    for (index_t i = 1; i < axes.ndim(); i++) {
+      CHECK_LT(axes[i - 1], axes[i])
+        << "axes have duplicates " << axes;
+    }
+    CHECK_LT(axes[axes.ndim() - 1], ndim)
+      << "axis " << axes[axes.ndim() - 1]
+      << " Exceeds input dimensions " << (*in_attrs)[0];
+    CHECK_GE(axes[0], 0)
+      << "Reduction axis " << param.axis.value()
+      << " Exceeds input dimensions " << (*in_attrs)[0];
+  }
+  return ElemwiseShape<1, 1>(attrs, in_attrs, out_attrs);
+}
+
+NNVM_REGISTER_OP(_np_roll)
+.set_num_inputs(1)
+.set_num_outputs(1)
+.set_attr_parser(ParamParser<NumpyRollParam>)
+.set_attr<nnvm::FListInputNames>("FListInputNames",
+  [](const NodeAttrs& attrs) {
+     return std::vector<std::string>{"data"};
+})
+.set_attr<mxnet::FInferShape>("FInferShape", NumpyRollShape)
+.set_attr<nnvm::FInferType>("FInferType", ElemwiseType<1, 1>)
+.set_attr<mxnet::FCompute>("FCompute<cpu>", NumpyRollCompute<cpu>)
+.set_attr<nnvm::FGradient>("FGradient",
+  [](const nnvm::NodePtr& n, const std::vector<nnvm::NodeEntry>& ograds) {
+     const NumpyRollParam& param = nnvm::get<NumpyRollParam>(n->attrs.parsed);
+     std::ostringstream os1;
+     os1 << param.shift;
+     std::ostringstream os2;
+     os2 << param.axis;
+     return MakeNonlossGradNode("_np_roll", n, ograds, {},
+                                {{"shift", os1.str()}, {"axis", os2.str()}});
 
 Review comment:
   i think the value of backward is 1, or it has no backward.  

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