more binary

benchmark/python/ffi/benchmark_ffi.py

@@ -57,6 +57,10 @@ def prepare_workloads():
     OpArgMngr.add_workload("bitwise_or", pool['2x2'].astype(int), pool['2x2'].astype(int))
     OpArgMngr.add_workload("bitwise_xor", pool['2x2'].astype(int), pool['2x2'].astype(int))
     OpArgMngr.add_workload("bitwise_and", pool['2x2'].astype(int), pool['2x2'].astype(int))
+    OpArgMngr.add_workload("copysign", pool['2x2'], pool['2x2'])
+    OpArgMngr.add_workload("arctan2", pool['2x2'], pool['2x2'])
+    OpArgMngr.add_workload("hypot", pool['2x2'], pool['2x2'])
+    OpArgMngr.add_workload("ldexp", pool['2x2'].astype(int), pool['2x2'].astype(int))
     OpArgMngr.add_workload("random.uniform", low=0, high=1, size=1)
 
 

python/mxnet/ndarray/numpy/_op.py

@@ -5001,7 +5001,9 @@ def copysign(x1, x2, out=None, **kwargs):
     >>> np.copysign(a, np.arange(3)-1)
     array([-1.,  0.,  1.])
     """
-    return _ufunc_helper(x1, x2, _npi.copysign, _np.copysign, _npi.copysign_scalar, _npi.rcopysign_scalar, out)
+    if isinstance(x1, numeric_types) and isinstance(x2, numeric_types):
+        return _np.copysign(x1, x2, out=out)
+    return _api_internal.copysign(x1, x2, out)
 
 
 @set_module('mxnet.ndarray.numpy')
@@ -5759,8 +5761,9 @@ def arctan2(x1, x2, out=None, **kwargs):
     >>> np.arctan2(x, y)
     array([ 1.5707964, -1.5707964])
     """
-    return _ufunc_helper(x1, x2, _npi.arctan2, _np.arctan2,
-                         _npi.arctan2_scalar, _npi.rarctan2_scalar, out=out)
+    if isinstance(x1, numeric_types) and isinstance(x2, numeric_types):
+        return _np.arctan2(x1, x2, out=out)
+    return _api_internal.arctan2(x1, x2, out)
 
 
 @set_module('mxnet.ndarray.numpy')
@@ -5808,7 +5811,9 @@ def hypot(x1, x2, out=None, **kwargs):
            [ 5.,  5.,  5.],
            [ 5.,  5.,  5.]])
     """
-    return _ufunc_helper(x1, x2, _npi.hypot, _np.hypot, _npi.hypot_scalar, None, out)
+    if isinstance(x1, numeric_types) and isinstance(x2, numeric_types):
+        return _np.hypot(x1, x2, out=out)
+    return _api_internal.hypot(x1, x2, out)
 
 
 @set_module('mxnet.ndarray.numpy')
@@ -5969,7 +5974,9 @@ def ldexp(x1, x2, out=None, **kwargs):
     >>> np.ldexp(5, np.arange(4))
     array([  5.,  10.,  20.,  40.])
     """
-    return _ufunc_helper(x1, x2, _npi.ldexp, _np.ldexp, _npi.ldexp_scalar, _npi.rldexp_scalar, out)
+    if isinstance(x1, numeric_types) and isinstance(x2, numeric_types):
+        return _np.ldexp(x1, x2, out=out)
+    return _api_internal.ldexp(x1, x2, out)
 
 
 @set_module('mxnet.ndarray.numpy')

src/api/operator/numpy/np_elemwise_broadcast_op.cc

@@ -60,4 +60,36 @@ MXNET_REGISTER_API("_npi.bitwise_and")
   UFuncHelper(args, ret, op, op_scalar, nullptr);
 });
 
+MXNET_REGISTER_API("_npi.copysign")
+.set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
+  using namespace runtime;
+  const nnvm::Op* op = Op::Get("_npi_copysign");
+  const nnvm::Op* op_scalar = Op::Get("_npi_copysign_scalar");
+  UFuncHelper(args, ret, op, op_scalar, nullptr);
+});
+
+MXNET_REGISTER_API("_npi.arctan2")
+.set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
+  using namespace runtime;
+  const nnvm::Op* op = Op::Get("_npi_arctan2");
+  const nnvm::Op* op_scalar = Op::Get("_npi_arctan2_scalar");
+  UFuncHelper(args, ret, op, op_scalar, nullptr);
+});
+
+MXNET_REGISTER_API("_npi.hypot")
+.set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
+  using namespace runtime;
+  const nnvm::Op* op = Op::Get("_npi_hypot");
+  const nnvm::Op* op_scalar = Op::Get("_npi_hypot_scalar");
+  UFuncHelper(args, ret, op, op_scalar, nullptr);
+});
+
+MXNET_REGISTER_API("_npi.ldexp")
+.set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
+  using namespace runtime;
+  const nnvm::Op* op = Op::Get("_npi_ldexp");
+  const nnvm::Op* op_scalar = Op::Get("_npi_ldexp_scalar");
+  UFuncHelper(args, ret, op, op_scalar, nullptr);
+});
+
 }  // namespace mxnet