[NumPy][Operator] NumPy operator may_share_memory and shares_memory

python/mxnet/ndarray/numpy/_op.py

@@ -38,7 +38,7 @@
            'std', 'var', 'indices', 'copysign', 'ravel', 'hanning', 'hamming', 'blackman', 'flip',
            'around', 'hypot', 'rad2deg', 'deg2rad', 'unique', 'lcm', 'tril', 'identity', 'take',
            'ldexp', 'vdot', 'inner', 'outer', 'equal', 'not_equal', 'greater', 'less', 'greater_equal', 'less_equal',
-           'hsplit', 'rot90', 'einsum', 'true_divide', 'nonzero']
+           'hsplit', 'rot90', 'einsum', 'true_divide', 'nonzero', 'shares_memory', 'may_share_memory']
 
 
 @set_module('mxnet.ndarray.numpy')
@@ -4909,3 +4909,77 @@ def nonzero(a):
     """
     out = _npi.nonzero(a).transpose()
     return tuple([out[i] for i in range(len(out))])
+
+
+@set_module('mxnet.ndarray.numpy')
+def shares_memory(a, b, max_work=None):
+    """
+    Determine if two arrays share memory
+
+    Parameters
+    ----------
+    a, b : ndarray
+        Input arrays
+
+    Returns
+    -------
+    out : bool
+
+    See Also
+    --------
+    may_share_memory
+
+    Examples
+    --------
+    >>> np.may_share_memory(np.array([1,2]), np.array([5,8,9]))
+    False
+
+    This function differs from the original `numpy.shares_memory
+    <https://docs.scipy.org/doc/numpy/reference/generated/numpy.shares_memory.html>`_ in
+    the following way(s):
+
+    - Does not support `max_work`, it is a dummy argument
+    - Actually it is same as `may_share_memory` in MXNet DeepNumPy
+    """
+    return _npi.share_memory(a, b).item()
+
+
+@set_module('mxnet.ndarray.numpy')
+def may_share_memory(a, b, max_work=None):
+    """
+    Determine if two arrays might share memory
+
+    A return of True does not necessarily mean that the two arrays
+    share any element.  It just means that they *might*.
+
+    Only the memory bounds of a and b are checked by default.
+
+    Parameters
+    ----------
+    a, b : ndarray
+        Input arrays
+
+    Returns
+    -------
+    out : bool
+
+    See Also
+    --------
+    shares_memory
+
+    Examples
+    --------
+    >>> np.may_share_memory(np.array([1,2]), np.array([5,8,9]))
+    False
+    >>> x = np.zeros([3, 4])
+    >>> np.may_share_memory(x[:,0], x[:,1])
+    True
+
+    This function differs from the original `numpy.may_share_memory
+    <https://docs.scipy.org/doc/numpy/reference/generated/numpy.may_share_memory.html>`_ in
+    the following way(s):
+
+    - Does not support `max_work`, it is a dummy argument
+    - Actually it is same as `shares_memory` in MXNet DeepNumPy
+    """
+    return _npi.share_memory(a, b).item()

python/mxnet/numpy/multiarray.py

@@ -55,7 +55,8 @@
            'swapaxes', 'clip', 'argmax', 'argmin', 'std', 'var', 'indices', 'copysign', 'ravel', 'hanning', 'hamming',
            'blackman', 'flip', 'around', 'arctan2', 'hypot', 'rad2deg', 'deg2rad', 'unique', 'lcm', 'tril',
            'identity', 'take', 'ldexp', 'vdot', 'inner', 'outer', 'equal', 'not_equal', 'greater', 'less',
-           'greater_equal', 'less_equal', 'hsplit', 'rot90', 'einsum', 'true_divide', 'nonzero']
+           'greater_equal', 'less_equal', 'hsplit', 'rot90', 'einsum', 'true_divide', 'nonzero', 'shares_memory',
+           'may_share_memory']
 
 # Return code for dispatching indexing function call
 _NDARRAY_UNSUPPORTED_INDEXING = -1
@@ -1330,7 +1331,7 @@ def take(self, indices, axis=None, mode='raise'):  # pylint: disable=arguments-d
         The arguments are the same as for :py:func:`take`, with
         this array as data.
         """
-        take(self, indices, axis, mode=mode)
+        return take(self, indices, axis, mode=mode)
 
     def one_hot(self, *args, **kwargs):
         """Convenience fluent method for :py:func:`one_hot`.
@@ -6900,3 +6901,77 @@ def nonzero(a):
     (array([1, 1, 1, 2, 2, 2], dtype=int64), array([0, 1, 2, 0, 1, 2], dtype=int64))
     """
     return _mx_nd_np.nonzero(a)
+
+
+@set_module('mxnet.numpy')
+def shares_memory(a, b, max_work=None):
+    """
+    Determine if two arrays share memory
+
+    Parameters
+    ----------
+    a, b : ndarray
+        Input arrays
+
+    Returns
+    -------
+    out : bool
+
+    See Also
+    --------
+    may_share_memory
+
+    Examples
+    --------
+    >>> np.may_share_memory(np.array([1,2]), np.array([5,8,9]))
+    False
+
+    This function differs from the original `numpy.shares_memory
+    <https://docs.scipy.org/doc/numpy/reference/generated/numpy.shares_memory.html>`_ in
+    the following way(s):
+
+    - Does not support `max_work`, it is a dummy argument
+    - Actually it is same as `may_share_memory` in MXNet DeepNumPy
+    """
+    return _mx_nd_np.shares_memory(a, b, max_work)
+
+
+@set_module('mxnet.numpy')
+def may_share_memory(a, b, max_work=None):
+    """
+    Determine if two arrays might share memory
+
+    A return of True does not necessarily mean that the two arrays
+    share any element.  It just means that they *might*.
+
+    Only the memory bounds of a and b are checked by default.
+
+    Parameters
+    ----------
+    a, b : ndarray
+        Input arrays
+
+    Returns
+    -------
+    out : bool
+
+    See Also
+    --------
+    shares_memory
+
+    Examples
+    --------
+    >>> np.may_share_memory(np.array([1,2]), np.array([5,8,9]))
+    False
+    >>> x = np.zeros([3, 4])
+    >>> np.may_share_memory(x[:,0], x[:,1])
+    True
+
+    This function differs from the original `numpy.may_share_memory
+    <https://docs.scipy.org/doc/numpy/reference/generated/numpy.may_share_memory.html>`_ in
+    the following way(s):
+
+    - Does not support `max_work`, it is a dummy argument
+    - Actually it is same as `shares_memory` in MXNet DeepNumPy
+    """
+    return _mx_nd_np.may_share_memory(a, b, max_work)

python/mxnet/numpy_dispatch_protocol.py

@@ -127,7 +127,9 @@ def _run_with_array_ufunc_proto(*args, **kwargs):
     'tril',
     'meshgrid',
     'outer',
-    'einsum'
+    'einsum',
+    'shares_memory',
+    'may_share_memory',
 ]
 
 

python/mxnet/symbol/numpy/_symbol.py

@@ -40,7 +40,7 @@
            'std', 'var', 'indices', 'copysign', 'ravel', 'hanning', 'hamming', 'blackman', 'flip',
            'around', 'hypot', 'rad2deg', 'deg2rad', 'unique', 'lcm', 'tril', 'identity', 'take',
            'ldexp', 'vdot', 'inner', 'outer', 'equal', 'not_equal', 'greater', 'less', 'greater_equal',
-           'less_equal', 'hsplit', 'rot90', 'einsum', 'true_divide']
+           'less_equal', 'hsplit', 'rot90', 'einsum', 'true_divide', 'shares_memory', 'may_share_memory']
 
 
 def _num_outputs(sym):
@@ -4590,4 +4590,43 @@ def einsum(*operands, **kwargs):
     return _npi.einsum(*operands, subscripts=subscripts, out=out, optimize=int(optimize_arg))
 
 
+@set_module('mxnet.symbol.numpy')
+def shares_memory(a, b, max_work=None):
+    """
+    Determine if two arrays share memory
+
+    Parameters
+    ----------
+    a, b : _Symbol
+        Input arrays
+
+    Returns
+    -------
+    out : _Symbol
+    """
+    return _npi.share_memory(a, b)
+
+
+@set_module('mxnet.symbol.numpy')
+def may_share_memory(a, b, max_work=None):
+    """
+    Determine if two arrays might share memory
+
+    A return of True does not necessarily mean that the two arrays
+    share any element.  It just means that they *might*.
+
+    Only the memory bounds of a and b are checked by default.
+
+    Parameters
+    ----------
+    a, b : _Symbol
+        Input arrays
+
+    Returns
+    -------
+    out : _Symbol
+    """
+    return _npi.share_memory(a, b)
+
+
 _set_np_symbol_class(_Symbol)

src/operator/numpy/np_memory_op.cc

@@ -0,0 +1,62 @@
+/*
+ * 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.
+ */
+
+/*!
+ * Copyright (c) 2019 by Contributors
+ * \file np_memory_op.cc
+ */
+
+#include "./np_memory_op.h"
+
+namespace mxnet {
+namespace op {
+
+inline bool NumpyShareMemoryType(const nnvm::NodeAttrs& attrs,
+                                 std::vector<int> *in_attrs,
+                                 std::vector<int> *out_attrs) {
+  CHECK_EQ(in_attrs->size(), 2U);
+  CHECK_EQ(out_attrs->size(), 1U);
+  TYPE_ASSIGN_CHECK(*out_attrs, 0, mshadow::kBool);
+  return out_attrs->at(0) != -1;
+}
+
+inline bool NumpyShareMemoryShape(const nnvm::NodeAttrs& attrs,
+                                  mxnet::ShapeVector *in_attrs,
+                                  mxnet::ShapeVector *out_attrs) {
+  CHECK_EQ(in_attrs->size(), 2U);
+  CHECK_EQ(out_attrs->size(), 1U);
+  SHAPE_ASSIGN_CHECK(*out_attrs, 0, mxnet::TShape(0, -1));
+  return true;
+}
+
+NNVM_REGISTER_OP(_npi_share_memory)
+.set_num_inputs(2)
+.set_num_outputs(1)
+.set_attr<nnvm::FListInputNames>("FListInputNames",
+  [](const NodeAttrs& attrs) {
+    return std::vector<std::string>{"a", "b"};
+  })
+.set_attr<mxnet::FInferShape>("FInferShape", NumpyShareMemoryShape)
+.set_attr<nnvm::FInferType>("FInferType", NumpyShareMemoryType)
+.set_attr<FCompute>("FCompute<cpu>", NumpyShareMemoryCompute<cpu>)
+.add_argument("a", "NDArray-or-Symbol", "First input")
+.add_argument("b", "NDArray-or-Symbol", "Second input");
+
+}  // namespace op
+}  // namespace mxnet

src/operator/numpy/np_memory_op.cu

@@ -0,0 +1,34 @@
+/*
+ * 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.
+ */
+
+/*!
+ * Copyright (c) 2019 by Contributors
+ * \file np_memory_op.cu
+ */
+
+#include "./np_memory_op.h"
+
+namespace mxnet {
+namespace op {
+
+NNVM_REGISTER_OP(_npi_share_memory)
+.set_attr<FCompute>("FCompute<gpu>", NumpyShareMemoryCompute<gpu>);
+
+}  // namespace op
+}  // namespace mxnet