[Numpy] Kron operator

benchmark/python/ffi/benchmark_ffi.py

@@ -55,6 +55,7 @@ def prepare_workloads():
     OpArgMngr.add_workload("ediff1d", pool['2x2'], pool['2x2'], pool['2x2'])
     OpArgMngr.add_workload("nan_to_num", pool['2x2'])
     OpArgMngr.add_workload("tensordot", pool['2x2'], pool['2x2'], ((1, 0), (0, 1)))
+    OpArgMngr.add_workload("kron", pool['2x2'], pool['2x2'])
     OpArgMngr.add_workload("cumsum", pool['3x2'], axis=0, out=pool['3x2'])
     OpArgMngr.add_workload("add", pool['2x2'], pool['2x2'])
     OpArgMngr.add_workload("linalg.svd", pool['3x3'])

python/mxnet/ndarray/numpy/_op.py

@@ -42,7 +42,7 @@
            'swapaxes', 'clip', 'argmax', 'argmin', 'std', 'var', 'indices', 'copysign', 'ravel', 'unravel_index',
            'diag_indices_from', 'hanning', 'hamming', 'blackman', 'flip', 'flipud', 'fliplr',
            'hypot', 'bitwise_and', 'bitwise_xor', 'bitwise_or', 'rad2deg', 'deg2rad', 'unique', 'lcm',
-           'tril', 'identity', 'take', 'ldexp', 'vdot', 'inner', 'outer',
+           'tril', 'identity', 'take', 'ldexp', 'vdot', 'inner', 'outer', 'kron',
            'equal', 'not_equal', 'greater', 'less', 'greater_equal', 'less_equal', 'roll', 'rot90', 'einsum',
            'true_divide', 'nonzero', 'quantile', 'percentile', 'shares_memory', 'may_share_memory',
            'diff', 'ediff1d', 'resize', 'polyval', 'nan_to_num', 'isnan', 'isinf', 'isposinf', 'isneginf', 'isfinite',
@@ -6074,6 +6074,51 @@ def outer(a, b):
     return tensordot(a.flatten(), b.flatten(), 0)
 
 
+@set_module('mxnet.ndarray.numpy')
+def kron(a, b):
+    r"""
+    Kronecker product of two arrays.
+    Computes the Kronecker product, a composite array made of blocks of the
+    second array scaled by the first.
+
+    Parameters
+    ----------
+    a, b : ndarray
+
+    Returns
+    -------
+    out : ndarray
+
+    See Also
+    --------
+    outer : The outer product
+
+    Notes
+    -----
+    The function assumes that the number of dimensions of `a` and `b`
+    are the same, if necessary prepending the smallest with ones.
+    If `a.shape = (r0,r1,..,rN)` and `b.shape = (s0,s1,...,sN)`,
+    the Kronecker product has shape `(r0*s0, r1*s1, ..., rN*SN)`.
+    The elements are products of elements from `a` and `b`, organized
+    explicitly by::
+        kron(a,b)[k0,k1,...,kN] = a[i0,i1,...,iN] * b[j0,j1,...,jN]
+    where::
+        kt = it * st + jt,  t = 0,...,N
+    In the common 2-D case (N=1), the block structure can be visualized::
+        [[ a[0,0]*b,   a[0,1]*b,  ... , a[0,-1]*b  ],
+        [  ...                              ...   ],
+        [ a[-1,0]*b,  a[-1,1]*b, ... , a[-1,-1]*b ]]
+
+    Examples
+    --------
+    >>> np.kron([1,10,100], [5,6,7])
+    array([  5,   6,   7,  50,  60,  70, 500, 600, 700])
+    >>> np.kron([5,6,7], [1,10,100])
+    array([  5,  50, 500,   6,  60, 600,   7,  70, 700])
+    """
+    return _api_internal.kron(a, b)
+
+
 @set_module('mxnet.ndarray.numpy')
 def vdot(a, b):
     r"""

python/mxnet/numpy/multiarray.py

@@ -65,7 +65,8 @@
            'indices', 'copysign', 'ravel', 'unravel_index', 'diag_indices_from', 'hanning', 'hamming', 'blackman',
            'flip', 'flipud', 'fliplr', 'around', 'round', 'round_', 'arctan2', 'hypot',
            'bitwise_and', 'bitwise_xor', 'bitwise_or', 'rad2deg', 'deg2rad',
-           'unique', 'lcm', 'tril', 'identity', 'take', 'ldexp', 'vdot', 'inner', 'outer', 'equal', 'not_equal',
+           'unique', 'lcm', 'tril', 'identity', 'take', 'ldexp', 'vdot', 'inner', 'outer', 'kron',
+           'equal', 'not_equal',
            'greater', 'less', 'greater_equal', 'less_equal', 'roll', 'rot90', 'einsum', 'true_divide', 'nonzero',
            'quantile', 'percentile', 'shares_memory', 'may_share_memory', 'diff', 'ediff1d', 'resize', 'matmul',
            'nan_to_num', 'isnan', 'isinf', 'isposinf', 'isneginf', 'isfinite', 'polyval', 'where', 'bincount',
@@ -7937,6 +7938,51 @@ def outer(a, b):
     return tensordot(a.flatten(), b.flatten(), 0)
 
 
+@set_module('mxnet.numpy')
+def kron(a, b):
+    r"""
+    Kronecker product of two arrays.
+    Computes the Kronecker product, a composite array made of blocks of the
+    second array scaled by the first.
+
+    Parameters
+    ----------
+    a, b : ndarray
+
+    Returns
+    -------
+    out : ndarray
+
+    See Also
+    --------
+    outer : The outer product
+
+    Notes
+    -----
+    The function assumes that the number of dimensions of `a` and `b`
+    are the same, if necessary prepending the smallest with ones.
+    If `a.shape = (r0,r1,..,rN)` and `b.shape = (s0,s1,...,sN)`,
+    the Kronecker product has shape `(r0*s0, r1*s1, ..., rN*SN)`.
+    The elements are products of elements from `a` and `b`, organized
+    explicitly by::
+        kron(a,b)[k0,k1,...,kN] = a[i0,i1,...,iN] * b[j0,j1,...,jN]
+    where::
+        kt = it * st + jt,  t = 0,...,N
+    In the common 2-D case (N=1), the block structure can be visualized::
+        [[ a[0,0]*b,   a[0,1]*b,  ... , a[0,-1]*b  ],
+        [  ...                              ...   ],
+        [ a[-1,0]*b,  a[-1,1]*b, ... , a[-1,-1]*b ]]
+
+    Examples
+    --------
+    >>> np.kron([1,10,100], [5,6,7])
+    array([  5,   6,   7,  50,  60,  70, 500, 600, 700])
+    >>> np.kron([5,6,7], [1,10,100])
+    array([  5,  50, 500,   6,  60, 600,   7,  70, 700])
+    """
+    return _mx_nd_np.kron(a, b)
+
+
 @set_module('mxnet.numpy')
 def vdot(a, b):
     r"""

python/mxnet/numpy_dispatch_protocol.py

@@ -168,6 +168,7 @@ def _run_with_array_ufunc_proto(*args, **kwargs):
     'tril',
     'meshgrid',
     'outer',
+    'kron',
     'einsum',
     'polyval',
     'shares_memory',

python/mxnet/symbol/numpy/_symbol.py

@@ -47,7 +47,7 @@
            'swapaxes', 'clip', 'argmax', 'argmin', 'std', 'var', 'indices', 'copysign', 'ravel', 'unravel_index',
            'diag_indices_from', 'hanning', 'hamming', 'blackman', 'flip', 'flipud', 'fliplr',
            'hypot', 'bitwise_and', 'bitwise_xor', 'bitwise_or', 'rad2deg', 'deg2rad', 'unique', 'lcm',
-           'tril', 'identity', 'take', 'ldexp', 'vdot', 'inner', 'outer',
+           'tril', 'identity', 'take', 'ldexp', 'vdot', 'inner', 'outer', 'kron',
            'equal', 'not_equal', 'greater', 'less', 'greater_equal', 'less_equal', 'roll', 'rot90', 'einsum',
            'true_divide', 'quantile', 'percentile', 'shares_memory', 'may_share_memory', 'diff', 'ediff1d',
            'resize', 'polyval', 'nan_to_num', 'isnan', 'isinf', 'isposinf', 'isneginf', 'isfinite',
@@ -5606,6 +5606,52 @@ def outer(a, b):
     return tensordot(a.flatten(), b.flatten(), 0)
 
 
+@set_module('mxnet.symbol.numpy')
+def kron(a, b):
+    r"""
+    kron(a, b)
+    Kronecker product of two arrays.
+    Computes the Kronecker product, a composite array made of blocks of the
+    second array scaled by the first.
+
+    Parameters
+    ----------
+    a, b : ndarray
+
+    Returns
+    -------
+    out : ndarray
+
+    See Also
+    --------
+    outer : The outer product
+
+    Notes
+    -----
+    The function assumes that the number of dimensions of `a` and `b`
+    are the same, if necessary prepending the smallest with ones.
+    If `a.shape = (r0,r1,..,rN)` and `b.shape = (s0,s1,...,sN)`,
+    the Kronecker product has shape `(r0*s0, r1*s1, ..., rN*SN)`.
+    The elements are products of elements from `a` and `b`, organized
+    explicitly by::
+        kron(a,b)[k0,k1,...,kN] = a[i0,i1,...,iN] * b[j0,j1,...,jN]
+    where::
+        kt = it * st + jt,  t = 0,...,N
+    In the common 2-D case (N=1), the block structure can be visualized::
+        [[ a[0,0]*b,   a[0,1]*b,  ... , a[0,-1]*b  ],
+        [  ...                              ...   ],
+        [ a[-1,0]*b,  a[-1,1]*b, ... , a[-1,-1]*b ]]
+
+    Examples
+    --------
+    >>> np.kron([1,10,100], [5,6,7])
+    array([  5,   6,   7,  50,  60,  70, 500, 600, 700])
+    >>> np.kron([5,6,7], [1,10,100])
+    array([  5,  50, 500,   6,  60, 600,   7,  70, 700])
+    """
+    return _npi.kron(a, b)
+
+
 @set_module('mxnet.symbol.numpy')
 def vdot(a, b):
     r"""

src/api/operator/numpy/np_kron.cc

@@ -0,0 +1,44 @@
+/*
+ * 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_kron.cc
+ * \brief Implementation of the API of functions in src/operator/numpy/np_kron.cc
+ */
+#include <mxnet/api_registry.h>
+#include <mxnet/runtime/packed_func.h>
+#include "../utils.h"
+#include "../../../operator/numpy/np_kron-inl.h"
+
+namespace mxnet {
+
+MXNET_REGISTER_API("_npi.kron")
+.set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
+  using namespace runtime;
+  nnvm::NodeAttrs attrs;
+  const nnvm::Op* op = Op::Get("_npi_kron");
+  attrs.op = op;
+  NDArray* inputs[] = {args[0].operator NDArray*(), args[1].operator NDArray*()};
+  int num_inputs = 2;
+  int num_outputs = 0;
+  auto ndoutputs = Invoke(op, &attrs, num_inputs, inputs, &num_outputs, nullptr);
+  *ret = reinterpret_cast<mxnet::NDArray*>(ndoutputs[0]);
+});
+
+}  // namespace mxnet