[Numpy] FFI: random.shuffle, equal, not_equal, less_equal, greater_equal, less, maximum and minimum

benchmark/python/ffi/benchmark_ffi.py

@@ -56,6 +56,14 @@ def prepare_workloads():
     OpArgMngr.add_workload("nan_to_num", pool['2x2'])
     OpArgMngr.add_workload("tensordot", pool['2x2'], pool['2x2'], ((1, 0), (0, 1)))
     OpArgMngr.add_workload("cumsum", pool['3x2'], axis=0, out=pool['3x2'])
+    OpArgMngr.add_workload("random.shuffle", pool['3'])
+    OpArgMngr.add_workload("equal", pool['2x2'], pool['2x2'])
+    OpArgMngr.add_workload("not_equal", pool['2x2'], pool['2x2'])
+    OpArgMngr.add_workload("less", pool['2x2'], pool['2x2'])
+    OpArgMngr.add_workload("greater_equal", pool['2x2'], pool['2x2'])
+    OpArgMngr.add_workload("less_equal", pool['2x2'], pool['2x2'])
+    OpArgMngr.add_workload("maximum", pool['2x2'], pool['2x2'])
+    OpArgMngr.add_workload("minimum", pool['2x2'], pool['2x2'])
     OpArgMngr.add_workload("add", pool['2x2'], pool['2x2'])
     OpArgMngr.add_workload("linalg.svd", pool['3x3'])
     OpArgMngr.add_workload("split", pool['3x3'], (0, 1, 2), axis=1)

python/mxnet/ndarray/numpy/_op.py

@@ -4363,7 +4363,9 @@ def maximum(x1, x2, out=None, **kwargs):
     -------
     out : mxnet.numpy.ndarray or scalar
         The maximum of x1 and x2, element-wise. This is a scalar if both x1 and x2 are scalars."""
-    return _ufunc_helper(x1, x2, _npi.maximum, _np.maximum, _npi.maximum_scalar, None, out)
+    if isinstance(x1, numeric_types) and isinstance(x2, numeric_types):
+        return _np.maximum(x1, x2, out=out)
+    return _api_internal.maximum(x1, x2, out)
 
 
 @set_module('mxnet.ndarray.numpy')
@@ -4382,7 +4384,9 @@ def minimum(x1, x2, out=None, **kwargs):
     -------
     out : mxnet.numpy.ndarray or scalar
         The minimum of x1 and x2, element-wise. This is a scalar if both x1 and x2 are scalars."""
-    return _ufunc_helper(x1, x2, _npi.minimum, _np.minimum, _npi.minimum_scalar, None, out)
+    if isinstance(x1, numeric_types) and isinstance(x2, numeric_types):
+        return _np.minimum(x1, x2, out=out)
+    return _api_internal.minimum(x1, x2, out)
 
 
 @set_module('mxnet.ndarray.numpy')
@@ -6143,7 +6147,9 @@ def equal(x1, x2, out=None):
     >>> np.equal(1, np.ones(1))
     array([ True])
     """
-    return _ufunc_helper(x1, x2, _npi.equal, _np.equal, _npi.equal_scalar, None, out)
+    if isinstance(x1, numeric_types) and isinstance(x2, numeric_types):
+        return _np.equal(x1, x2, out=out)
+    return _api_internal.equal(x1, x2, out)
 
 
 @set_module('mxnet.ndarray.numpy')
@@ -6175,7 +6181,10 @@ def not_equal(x1, x2, out=None):
     >>> np.not_equal(1, np.ones(1))
     array([False])
     """
-    return _ufunc_helper(x1, x2, _npi.not_equal, _np.not_equal, _npi.not_equal_scalar, None, out)
+    if isinstance(x1, numeric_types) and isinstance(x2, numeric_types):
+        return _np.not_equal(x1, x2, out=out)
+    return _api_internal.not_equal(x1, x2, out)
+
 
 
 @set_module('mxnet.ndarray.numpy')
@@ -6240,7 +6249,9 @@ def less(x1, x2, out=None):
     >>> np.less(1, np.ones(1))
     array([False])
     """
-    return _ufunc_helper(x1, x2, _npi.less, _np.less, _npi.less_scalar, _npi.greater_scalar, out)
+    if isinstance(x1, numeric_types) and isinstance(x2, numeric_types):
+        return _np.less(x1, x2, out=out)
+    return _api_internal.less(x1, x2, out)
 
 
 @set_module('mxnet.ndarray.numpy')
@@ -6272,8 +6283,10 @@ def greater_equal(x1, x2, out=None):
     >>> np.greater_equal(1, np.ones(1))
     array([True])
     """
-    return _ufunc_helper(x1, x2, _npi.greater_equal, _np.greater_equal, _npi.greater_equal_scalar,
-                         _npi.less_equal_scalar, out)
+    if isinstance(x1, numeric_types) and isinstance(x2, numeric_types):
+        return _np.greater_equal(x1, x2, out=out)
+    return _api_internal.greater_equal(x1, x2, out)
+
 
 
 @set_module('mxnet.ndarray.numpy')
@@ -6305,8 +6318,9 @@ def less_equal(x1, x2, out=None):
     >>> np.less_equal(1, np.ones(1))
     array([True])
     """
-    return _ufunc_helper(x1, x2, _npi.less_equal, _np.less_equal, _npi.less_equal_scalar,
-                         _npi.greater_equal_scalar, out)
+    if isinstance(x1, numeric_types) and isinstance(x2, numeric_types):
+        return _np.less_equal(x1, x2, out=out)
+    return _api_internal.less_equal(x1, x2, out)
 
 
 @set_module('mxnet.ndarray.numpy')

python/mxnet/ndarray/numpy/random.py

@@ -1068,7 +1068,7 @@ def shuffle(x):
            [3., 4., 5.],
            [0., 1., 2.]])
     """
-    _npi.shuffle(x, out=x)
+    _api_internal.shuffle(x, x)
 
 
 def laplace(loc=0.0, scale=1.0, size=None, dtype=None, ctx=None, out=None):

src/api/operator/numpy/np_elemwise_broadcast_logic_op.cc

@@ -0,0 +1,71 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ * 
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ * 
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * \file np_elemwise_broadcast_logic_op.cc
+ * \brief Implementation of the API of functions in src/operator/numpy/np_elemwise_broadcast_logic_op.cc
+ */
+#include <mxnet/api_registry.h>
+#include <mxnet/runtime/packed_func.h>
+#include "../utils.h"
+#include "../ufunc_helper.h"
+
+namespace mxnet {
+
+MXNET_REGISTER_API("_npi.equal")
+.set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
+  using namespace runtime;
+  const nnvm::Op* op = Op::Get("_npi_equal");
+  const nnvm::Op* op_scalar = Op::Get("_npi_equal_scalar");
+  UFuncHelper(args, ret, op, op_scalar, nullptr);
+});
+
+MXNET_REGISTER_API("_npi.not_equal")
+.set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
+  using namespace runtime;
+  const nnvm::Op* op = Op::Get("_npi_not_equal");
+  const nnvm::Op* op_scalar = Op::Get("_npi_not_equal_scalar");
+  UFuncHelper(args, ret, op, op_scalar, nullptr);
+});
+
+MXNET_REGISTER_API("_npi.less")
+.set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
+  using namespace runtime;
+  const nnvm::Op* op = Op::Get("_npi_less");
+  const nnvm::Op* op_scalar = Op::Get("_npi_less_scalar");
+  UFuncHelper(args, ret, op, op_scalar, nullptr);
+});
+
+MXNET_REGISTER_API("_npi.greater_equal")
+.set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
+  using namespace runtime;
+  const nnvm::Op* op = Op::Get("_npi_greater_equal");
+  const nnvm::Op* op_scalar = Op::Get("_npi_greater_equal_scalar");
+  UFuncHelper(args, ret, op, op_scalar, nullptr);
+});
+
+MXNET_REGISTER_API("_npi.less_equal")
+.set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
+  using namespace runtime;
+  const nnvm::Op* op = Op::Get("_npi_less_equal");
+  const nnvm::Op* op_scalar = Op::Get("_npi_less_equal_scalar");
+  UFuncHelper(args, ret, op, op_scalar, nullptr);
+});
+
+}  // namespace mxnet

src/api/operator/random/shuffle_op.cc

@@ -0,0 +1,57 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ * 
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ * 
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * \file shuffle_op.cc
+ * \brief Implementation of the API of functions in src/operator/random/shuffle_op.cc
+ */
+#include <mxnet/api_registry.h>
+#include <mxnet/runtime/packed_func.h>
+#include "../utils.h"
+#include "../../../operator/elemwise_op_common.h"
+
+namespace mxnet {
+
+MXNET_REGISTER_API("_npi.shuffle")
+.set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
+  using namespace runtime;
+  const nnvm::Op* op = Op::Get("_npi_shuffle");
+  nnvm::NodeAttrs attrs;
+
+  NDArray* inputs[1];
+  int num_inputs = 1;
+
+  if (args[0].type_code() != kNull) {
+    inputs[0] = args[0].operator mxnet::NDArray *();
+  }
+
+  attrs.op = op;
+
+  NDArray* out = args[1].operator mxnet::NDArray*();
+  NDArray** outputs = out == nullptr ? nullptr : &out;
+  int num_outputs = out != nullptr;
+  auto ndoutputs = Invoke(op, &attrs, num_inputs, inputs, &num_outputs, outputs);
+  if (out) {
+    *ret = PythonArg(1);
+  } else {
+    *ret = ndoutputs[0];
+  }
+});
+
+}  // namespace mxnet

src/api/operator/tensor/elemwise_binary_broadcast_op_extended.cc

@@ -0,0 +1,47 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ * 
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ * 
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * \file elemwise_binary_broadcast_op_extended.cc
+ * \brief Implementation of the API of functions in src/operator/tensor/elemwise_binary_broadcast_op_extended.cc
+ */
+#include <mxnet/api_registry.h>
+#include <mxnet/runtime/packed_func.h>
+#include "../utils.h"
+#include "../ufunc_helper.h"
+
+namespace mxnet {
+
+MXNET_REGISTER_API("_npi.maximum")
+.set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
+  using namespace runtime;
+  const nnvm::Op* op = Op::Get("_npi_maximum");
+  const nnvm::Op* op_scalar = Op::Get("_npi_maximum_scalar");
+  UFuncHelper(args, ret, op, op_scalar, nullptr);
+});
+
+MXNET_REGISTER_API("_npi.minimum")
+.set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
+  using namespace runtime;
+  const nnvm::Op* op = Op::Get("_npi_minimum");
+  const nnvm::Op* op_scalar = Op::Get("_npi_minimum_scalar");
+  UFuncHelper(args, ret, op, op_scalar, nullptr);
+});
+
+}  // namespace mxnet