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