forked from mindspore-Ecosystem/mindspore
!8554 Add expand_as function to tensor
From: @liangzhibo Reviewed-by: @zh_qh,@chenfei52 Signed-off-by: @zh_qh
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c11c79170e
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@ -156,6 +156,12 @@ def enumerate_(x, start=0):
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return ret
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def expand_tensor_as(x, y):
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"""Expand tensor"""
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broadcast_to = P.BroadcastTo(shape_(y))
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return broadcast_to(x)
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def isinstance_(x, base_type):
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"""Determine whether x is an instance of base_type."""
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x_type = F.typeof(x)
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@ -147,34 +147,35 @@ BuiltInTypeMap &GetMethodMap() {
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}},
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{kObjectTypeTensorType,
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{
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{"all", std::string("all_")}, // C.reduce_all
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{"any", std::string("any_")}, // C.reduce_any
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{"__add__", std::string("add")}, // C.add
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{"__sub__", std::string("sub")}, // C.sub
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{"__mul__", std::string("mul")}, // C.mul
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{"__truediv__", std::string("truediv")}, // C.truediv
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{"__floordiv__", std::string("floordiv")}, // C.floordiv
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{"__mod__", std::string("mod")}, // C.mod
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{"__pow__", std::string("pow_")}, // C.pow
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{"__floor__", std::string("array_floor")}, // C.array_floor
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{"__trunc__", std::string("array_trunc")}, // C.array_trunc
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{"__pos__", std::string("array_uadd")}, // C.array_uadd
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{"__neg__", std::string("array_usub")}, // C.array_usub
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{"__eq__", std::string("eq")}, // C.eq
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{"__ne__", std::string("ne")}, // C.ne
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{"__lt__", std::string("lt")}, // C.lt
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{"__gt__", std::string("gt")}, // C.gt
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{"__le__", std::string("le")}, // C.le
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{"__ge__", std::string("ge")}, // C.ge
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{"__matmul__", prim::kPrimDot}, // P.dot,
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{"__len__", prim::kPrimArrayLen}, // P.array_len,
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{"__getitem__", prim::kPrimArrayGetItem}, // P.array_getitem,
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{"__setitem__", prim::kPrimArraySetItem}, // P.array_setitem,
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{"__ms_iter__", std::string("array_iter")}, // C.array_iter
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{"__ms_to_array__", prim::kPrimIdentity}, // P.identity,
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{"item", prim::kPrimArrayToScalar}, // P.array_to_scalar,
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{"transpose", std::string("transpose")}, // P.transpose
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{"__bool__", std::string("tensor_bool")}, // C.tensor_bool
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{"all", std::string("all_")}, // C.reduce_all
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{"any", std::string("any_")}, // C.reduce_any
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{"__add__", std::string("add")}, // C.add
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{"__sub__", std::string("sub")}, // C.sub
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{"__mul__", std::string("mul")}, // C.mul
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{"__truediv__", std::string("truediv")}, // C.truediv
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{"__floordiv__", std::string("floordiv")}, // C.floordiv
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{"__mod__", std::string("mod")}, // C.mod
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{"__pow__", std::string("pow_")}, // C.pow
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{"__floor__", std::string("array_floor")}, // C.array_floor
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{"__trunc__", std::string("array_trunc")}, // C.array_trunc
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{"__pos__", std::string("array_uadd")}, // C.array_uadd
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{"__neg__", std::string("array_usub")}, // C.array_usub
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{"__eq__", std::string("eq")}, // C.eq
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{"__ne__", std::string("ne")}, // C.ne
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{"__lt__", std::string("lt")}, // C.lt
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{"__gt__", std::string("gt")}, // C.gt
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{"__le__", std::string("le")}, // C.le
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{"__ge__", std::string("ge")}, // C.ge
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{"expand_as", std::string("expand_tensor_as")}, // C.expand_as
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{"__matmul__", prim::kPrimDot}, // P.dot,
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{"__len__", prim::kPrimArrayLen}, // P.array_len,
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{"__getitem__", prim::kPrimArrayGetItem}, // P.array_getitem,
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{"__setitem__", prim::kPrimArraySetItem}, // P.array_setitem,
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{"__ms_iter__", std::string("array_iter")}, // C.array_iter
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{"__ms_to_array__", prim::kPrimIdentity}, // P.identity,
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{"item", prim::kPrimArrayToScalar}, // P.array_to_scalar,
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{"transpose", std::string("transpose")}, // P.transpose
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{"__bool__", std::string("tensor_bool")}, // C.tensor_bool
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}},
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{kObjectTypeJTagged, {}},
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{kObjectTypeSymbolicKeyType, {}},
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@ -0,0 +1,60 @@
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# Copyright 2020 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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""" test expand_as"""
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import mindspore.nn as nn
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from mindspore import Tensor
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from mindspore import context
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context.set_context(mode=context.GRAPH_MODE)
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def test_expand_as():
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class Net(nn.Cell):
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def __init__(self):
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super(Net, self).__init__()
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self.t1 = Tensor([1, 2, 3])
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self.t2 = Tensor([[1, 1, 1], [1, 1, 1]])
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def construct(self):
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return self.t1.expand_as(self.t2)
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net = Net()
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net()
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def test_expand_as_parameter():
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class Net(nn.Cell):
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def __init__(self):
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super(Net, self).__init__()
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self.t1 = Tensor([1, 2, 3])
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def construct(self, x):
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return self.t1.expand_as(x)
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net = Net()
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net(Tensor([[1, 1, 1], [1, 1, 1]]))
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def test_expand_tensor_as_parameter_1():
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class Net(nn.Cell):
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def __init__(self):
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super(Net, self).__init__()
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self.t2 = Tensor([[1, 1, 1], [1, 1, 1]])
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def construct(self, x):
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return x.expand_as(self.t2)
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net = Net()
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net(Tensor([1, 2, 3]))
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