new ffi

src/api/operator/numpy/np_bincount_op.cc

@@ -21,6 +21,7 @@
  * \file np_bincount_op.cc
  * \brief Implementation of the API of functions in src/operator/numpy/np_bincount_op.cc
  */
+#include <mxnet/api_registry.h>
 #include "../utils.h"
 #include "../../../operator/numpy/np_bincount_op-inl.h"
 
@@ -38,17 +39,21 @@ MXNET_REGISTER_API("_npi.bincount")
     param.minlength = args[2].operator int64_t();
     param.has_weights = false;
     NDArray* inputs[] = {args[0].operator mxnet::NDArray*()};
-    attrs.parsed = param;  // remove std::move() ci error: trivially-copyable type
+    int num_inputs = 1;
+    attrs.parsed = param;
     attrs.op = op;
-    auto ndoutputs = Invoke<op::NumpyBincountParam>(op, &attrs, 1, inputs, &num_outputs, nullptr);
+    SetAttrDict<op::NumpyBincountParam>(&attrs);
+    auto ndoutputs = Invoke(op, &attrs, num_inputs, inputs, &num_outputs, nullptr);
     *ret = reinterpret_cast<mxnet::NDArray*>(ndoutputs[0]);
   } else {
     param.minlength = args[2].operator int64_t();
     param.has_weights = true;
     NDArray* inputs[] = {args[0].operator mxnet::NDArray*(), args[1].operator mxnet::NDArray*()};
-    attrs.parsed = param;  // remove std::move() ci error: trivially-copyable type
+    int num_inputs = 2;
+    attrs.parsed = param;
     attrs.op = op;
-    auto ndoutputs = Invoke<op::NumpyBincountParam>(op, &attrs, 2, inputs, &num_outputs, nullptr);
+    SetAttrDict<op::NumpyBincountParam>(&attrs);
+    auto ndoutputs = Invoke(op, &attrs, num_inputs, inputs, &num_outputs, nullptr);
     *ret = reinterpret_cast<mxnet::NDArray*>(ndoutputs[0]);
     }
 });

src/api/operator/numpy/np_broadcast_reduce_op_boolean.cc

@@ -21,6 +21,8 @@
  * \file np_broadcast_reduce_op_boolean.cc
  * \brief Implementation of the API of functions in src/operator/numpy/np_broadcast_reduce_op_boolean.cc
  */
+#include <mxnet/api_registry.h>
+#include <mxnet/runtime/packed_func.h>
 #include "../utils.h"
 #include "../../../operator/numpy/np_broadcast_reduce_op.h"
 
@@ -45,11 +47,16 @@ MXNET_REGISTER_API("_npi.all")
   }
   param.keepdims = args[2].operator bool();
   NDArray* inputs[] = {args[0].operator mxnet::NDArray*()};
+  int num_inputs = 1;
   attrs.parsed = std::move(param);
   attrs.op = op;
-  auto ndoutputs = Invoke<op::NumpyReduceAxesBoolParam>(
-    op, &attrs, 1, inputs, &num_outputs, outputs);
-  *ret = reinterpret_cast<mxnet::NDArray*>(ndoutputs[0]);
+  SetAttrDict<op::NumpyReduceAxesBoolParam>(&attrs);
+  auto ndoutputs = Invoke(op, &attrs, num_inputs, inputs, &num_outputs, outputs);
+  if (out) {
+    *ret = PythonArg(3);
+  } else {
+    *ret = reinterpret_cast<mxnet::NDArray*>(ndoutputs[0]);
+  }
 });
 
 MXNET_REGISTER_API("_npi.any")
@@ -71,11 +78,16 @@ MXNET_REGISTER_API("_npi.any")
   }
   param.keepdims = args[2].operator bool();
   NDArray* inputs[] = {args[0].operator mxnet::NDArray*()};
+  int num_inputs = 1;
   attrs.parsed = std::move(param);
   attrs.op = op;
-  auto ndoutputs = Invoke<op::NumpyReduceAxesBoolParam>(
-    op, &attrs, 1, inputs, &num_outputs, outputs);
-  *ret = reinterpret_cast<mxnet::NDArray*>(ndoutputs[0]);
+  SetAttrDict<op::NumpyReduceAxesBoolParam>(&attrs);
+  auto ndoutputs = Invoke(op, &attrs, num_inputs, inputs, &num_outputs, outputs);
+  if (out) {
+    *ret = PythonArg(3);
+  } else {
+    *ret = reinterpret_cast<mxnet::NDArray*>(ndoutputs[0]);
+  }
 });
 
 }  // namespace mxnet

src/api/operator/numpy/np_percentile_op.cc

@@ -21,12 +21,14 @@
  * \file np_percentile_op.cc
  * \brief Implementation of the API of functions in src/operator/numpy/np_percentile_op.cc
  */
+#include <mxnet/api_registry.h>
+#include <mxnet/runtime/packed_func.h>
 #include "../utils.h"
 #include "../../../operator/numpy/np_percentile_op-inl.h"
 
 namespace mxnet {
 
-inline int String2MXnetPercentileType(const std::string& s) {
+inline int String2MXNetPercentileType(const std::string& s) {
   using namespace op;
   if (s == "linear") {
     return percentile_enum::kLinear;
@@ -62,22 +64,34 @@ MXNET_REGISTER_API("_npi.percentile")
   } else {
     param.axis = Tuple<int>(args[2].operator ObjectRef());
   }
-  param.interpolation = String2MXnetPercentileType(args[3].operator std::string());
+  param.interpolation = String2MXNetPercentileType(args[3].operator std::string());
   param.keepdims = args[4].operator bool();
   if (args[1].type_code() == kDLInt || args[1].type_code() == kDLFloat) {
     param.q_scalar = args[1].operator double();
     NDArray* inputs[] = {args[0].operator mxnet::NDArray*()};
+    int num_inputs = 1;
     attrs.parsed = std::move(param);
     attrs.op = op;
-    auto ndoutputs = Invoke<op::NumpyPercentileParam>(op, &attrs, 1, inputs, &num_outputs, outputs);
-    *ret = reinterpret_cast<mxnet::NDArray*>(ndoutputs[0]);
+    SetAttrDict<op::NumpyPercentileParam>(&attrs);
+    auto ndoutputs = Invoke(op, &attrs, num_inputs, inputs, &num_outputs, outputs);
+    if (out) {
+      *ret = PythonArg(5);
+    } else {
+      *ret = reinterpret_cast<mxnet::NDArray*>(ndoutputs[0]);
+    }
   } else {
     param.q_scalar = dmlc::nullopt;
     NDArray* inputs[] = {args[0].operator mxnet::NDArray*(), args[1].operator mxnet::NDArray*()};
+    int num_inputs = 2;
     attrs.parsed = std::move(param);
     attrs.op = op;
-    auto ndoutputs = Invoke<op::NumpyPercentileParam>(op, &attrs, 2, inputs, &num_outputs, outputs);
-    *ret = reinterpret_cast<mxnet::NDArray*>(ndoutputs[0]);
+    SetAttrDict<op::NumpyPercentileParam>(&attrs);
+    auto ndoutputs = Invoke(op, &attrs, num_inputs, inputs, &num_outputs, outputs);
+    if (out) {
+      *ret = PythonArg(5);
+    } else {
+      *ret = reinterpret_cast<mxnet::NDArray*>(ndoutputs[0]);
+    }
   }
 });
 

src/api/operator/op_utils.cc

@@ -24,6 +24,7 @@
 
 #include "op_utils.h"
 #include <mxnet/base.h>
+#include "../../operator/numpy/np_percentile_op-inl.h"
 
 namespace mxnet {
 
@@ -52,4 +53,24 @@ std::string String2MXNetTypeWithBool(int dtype) {
   return "";
 }
 
+std::string MXNetPercentileType2String(int interpolation) {
+  using namespace op;
+  switch (interpolation) {
+    case percentile_enum::kLinear:
+      return "linear";
+    case percentile_enum::kLower:
+      return "lower";
+    case percentile_enum::kHigher:
+      return "higher";
+    case percentile_enum::kMidpoint:
+      return "midpoint";
+    case percentile_enum::kNearest:
+      return "nearest";
+    default:
+      LOG(FATAL) << "Unknown type enum " << interpolation;
+  }
+  LOG(FATAL) << "should not reach here ";
+  return "";
+}
+
 }  // namespace mxnet

src/api/operator/op_utils.h

@@ -29,6 +29,7 @@
 namespace mxnet {
 
 std::string String2MXNetTypeWithBool(int dtype);
+std::string MXNetPercentileType2String(int interpolation);
 
 }  // namespace mxnet
 

src/operator/numpy/np_percentile_op-inl.h

@@ -33,6 +33,7 @@
 #include "../operator_common.h"
 #include "../elemwise_op_common.h"
 #include "np_broadcast_reduce_op.h"
+#include "../../api/operator/op_utils.h"
 
 namespace mxnet {
 namespace op {
@@ -67,13 +68,12 @@ struct NumpyPercentileParam : public dmlc::Parameter<NumpyPercentileParam> {
       .describe("inqut q is a scalar");
   }
   void SetAttrDict(std::unordered_map<std::string, std::string>* dict) {
-    std::ostringstream axis_s, interpolation_s, keepdims_s, q_scalar_s;
+    std::ostringstream axis_s, keepdims_s, q_scalar_s;
     axis_s << axis;
-    interpolation_s << interpolation;
     keepdims_s << keepdims;
     q_scalar_s << q_scalar;
     (*dict)["axis"] = axis_s.str();
-    (*dict)["interpolation"] = interpolation_s.str();
+    (*dict)["interpolation"] = MXNetPercentileType2String(interpolation);
     (*dict)["keepdims"] = keepdims_s.str();
     (*dict)["q_scalar"] = q_scalar_s.str();
   }