!8554 Add expand_as function to tensor

From: @liangzhibo
Reviewed-by: @zh_qh,@chenfei52
Signed-off-by: @zh_qh

mindspore/_extends/parse/standard_method.py

@@ -156,6 +156,12 @@ def enumerate_(x, start=0):
     return ret
 
 
+def expand_tensor_as(x, y):
+    """Expand tensor"""
+    broadcast_to = P.BroadcastTo(shape_(y))
+    return broadcast_to(x)
+
+
 def isinstance_(x, base_type):
     """Determine whether x is an instance of base_type."""
     x_type = F.typeof(x)

mindspore/ccsrc/pipeline/jit/resource.cc

@@ -147,34 +147,35 @@ BuiltInTypeMap &GetMethodMap() {
                                        }},
                                       {kObjectTypeTensorType,
                                        {
-                                         {"all", std::string("all_")},                // C.reduce_all
-                                         {"any", std::string("any_")},                // C.reduce_any
-                                         {"__add__", std::string("add")},             // C.add
-                                         {"__sub__", std::string("sub")},             // C.sub
-                                         {"__mul__", std::string("mul")},             // C.mul
-                                         {"__truediv__", std::string("truediv")},     // C.truediv
-                                         {"__floordiv__", std::string("floordiv")},   // C.floordiv
-                                         {"__mod__", std::string("mod")},             // C.mod
-                                         {"__pow__", std::string("pow_")},            // C.pow
-                                         {"__floor__", std::string("array_floor")},   // C.array_floor
-                                         {"__trunc__", std::string("array_trunc")},   // C.array_trunc
-                                         {"__pos__", std::string("array_uadd")},      // C.array_uadd
-                                         {"__neg__", std::string("array_usub")},      // C.array_usub
-                                         {"__eq__", std::string("eq")},               // C.eq
-                                         {"__ne__", std::string("ne")},               // C.ne
-                                         {"__lt__", std::string("lt")},               // C.lt
-                                         {"__gt__", std::string("gt")},               // C.gt
-                                         {"__le__", std::string("le")},               // C.le
-                                         {"__ge__", std::string("ge")},               // C.ge
-                                         {"__matmul__", prim::kPrimDot},              // P.dot,
-                                         {"__len__", prim::kPrimArrayLen},            // P.array_len,
-                                         {"__getitem__", prim::kPrimArrayGetItem},    // P.array_getitem,
-                                         {"__setitem__", prim::kPrimArraySetItem},    // P.array_setitem,
-                                         {"__ms_iter__", std::string("array_iter")},  // C.array_iter
-                                         {"__ms_to_array__", prim::kPrimIdentity},    // P.identity,
-                                         {"item", prim::kPrimArrayToScalar},          // P.array_to_scalar,
-                                         {"transpose", std::string("transpose")},     // P.transpose
-                                         {"__bool__", std::string("tensor_bool")},    // C.tensor_bool
+                                         {"all", std::string("all_")},                    // C.reduce_all
+                                         {"any", std::string("any_")},                    // C.reduce_any
+                                         {"__add__", std::string("add")},                 // C.add
+                                         {"__sub__", std::string("sub")},                 // C.sub
+                                         {"__mul__", std::string("mul")},                 // C.mul
+                                         {"__truediv__", std::string("truediv")},         // C.truediv
+                                         {"__floordiv__", std::string("floordiv")},       // C.floordiv
+                                         {"__mod__", std::string("mod")},                 // C.mod
+                                         {"__pow__", std::string("pow_")},                // C.pow
+                                         {"__floor__", std::string("array_floor")},       // C.array_floor
+                                         {"__trunc__", std::string("array_trunc")},       // C.array_trunc
+                                         {"__pos__", std::string("array_uadd")},          // C.array_uadd
+                                         {"__neg__", std::string("array_usub")},          // C.array_usub
+                                         {"__eq__", std::string("eq")},                   // C.eq
+                                         {"__ne__", std::string("ne")},                   // C.ne
+                                         {"__lt__", std::string("lt")},                   // C.lt
+                                         {"__gt__", std::string("gt")},                   // C.gt
+                                         {"__le__", std::string("le")},                   // C.le
+                                         {"__ge__", std::string("ge")},                   // C.ge
+                                         {"expand_as", std::string("expand_tensor_as")},  // C.expand_as
+                                         {"__matmul__", prim::kPrimDot},                  // P.dot,
+                                         {"__len__", prim::kPrimArrayLen},                // P.array_len,
+                                         {"__getitem__", prim::kPrimArrayGetItem},        // P.array_getitem,
+                                         {"__setitem__", prim::kPrimArraySetItem},        // P.array_setitem,
+                                         {"__ms_iter__", std::string("array_iter")},      // C.array_iter
+                                         {"__ms_to_array__", prim::kPrimIdentity},        // P.identity,
+                                         {"item", prim::kPrimArrayToScalar},              // P.array_to_scalar,
+                                         {"transpose", std::string("transpose")},         // P.transpose
+                                         {"__bool__", std::string("tensor_bool")},        // C.tensor_bool
                                        }},
                                       {kObjectTypeJTagged, {}},
                                       {kObjectTypeSymbolicKeyType, {}},

tests/ut/python/pipeline/parse/test_expand_as.py

@@ -0,0 +1,60 @@
+# Copyright 2020 Huawei Technologies Co., Ltd
+#
+# Licensed 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.
+# ============================================================================
+""" test expand_as"""
+import mindspore.nn as nn
+from mindspore import Tensor
+from mindspore import context
+
+context.set_context(mode=context.GRAPH_MODE)
+
+
+def test_expand_as():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+            self.t1 = Tensor([1, 2, 3])
+            self.t2 = Tensor([[1, 1, 1], [1, 1, 1]])
+
+        def construct(self):
+            return self.t1.expand_as(self.t2)
+
+    net = Net()
+    net()
+
+
+def test_expand_as_parameter():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+            self.t1 = Tensor([1, 2, 3])
+
+        def construct(self, x):
+            return self.t1.expand_as(x)
+
+    net = Net()
+    net(Tensor([[1, 1, 1], [1, 1, 1]]))
+
+
+def test_expand_tensor_as_parameter_1():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+            self.t2 = Tensor([[1, 1, 1], [1, 1, 1]])
+
+        def construct(self, x):
+            return x.expand_as(self.t2)
+
+    net = Net()
+    net(Tensor([1, 2, 3]))