# 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 nn ops """ import numpy as np import mindspore.nn as nn import mindspore.common.dtype as mstype from mindspore import Tensor from mindspore.ops import operations as P from mindspore import context context.set_context(mode=context.GRAPH_MODE, save_graphs=True) def test_cast_op_attr(): class CastNet(nn.Cell): def __init__(self): super(CastNet, self).__init__() self.cast = P.Cast() def construct(self, x, t): return self.cast(x, t) class CastTypeTest(nn.Cell): def __init__(self, net): super(CastTypeTest, self).__init__() self.net = net self.cast = P.Cast() def construct(self, x, y, z): cast_op = self.cast t1 = cast_op(x, mstype.float32) t2 = cast_op(y, mstype.int32) cast_net = self.net t3 = cast_net(x, mstype.float16) t4 = cast_net(y, mstype.int32) t5 = cast_net(z, mstype.float16) return (t1, t2, t3, t4, t5) net = CastTypeTest(CastNet()) t1 = Tensor(np.ones([1, 16, 1, 1918]).astype(np.int32)) t2 = Tensor(np.ones([1, 16, 1, 3840]).astype(np.float32)) t3 = Tensor(np.ones([1, 16, 1, 1918]).astype(np.int32)) out = net(t1, t2, t3) assert out[0].asnumpy().dtype == np.float32 assert out[1].asnumpy().dtype == np.int32 assert out[2].asnumpy().dtype == np.float16 assert out[3].asnumpy().dtype == np.int32 assert out[4].asnumpy().dtype == np.float16