!217 support operator ** // % for scalar and tensor, and "in" "not in" key word, and string concat
Merge pull request !217 from zhangbuxue/support_pow_operatorpull/217/MERGE
mindspore-ci-bot
5 years ago
committed by
Gitee
commit
31621467a4
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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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"""Implementation for internal polymorphism `floordiv` operations."""
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from ...composite import base
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from ... import functional as F
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floordiv = base.MultitypeFuncGraph("floordiv")
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"""
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`floordiv` is a metafuncgraph object which will compute the floordiv of two objects
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using ".register" decorator.
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"""
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@floordiv.register("Number", "Number")
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def _floordiv_scalar(x, y):
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"""Returns x // y where x and y are all scalars."""
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return F.scalar_floordiv(x, y)
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@floordiv.register("Tensor", "Tensor")
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def _floordiv_tensor(x, y):
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"""Returns x // y where x and y are all tensors and have save dtype."""
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return F.tensor_floordiv(x, y)
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@floordiv.register("Tensor", "Number")
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def _tensor_floordiv_scalar(x, y):
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"""Returns x // y where x is a tensor and y is a scalar. x and y should have same dtype."""
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return F.tensor_floordiv(x, y)
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@floordiv.register("Number", "Tensor")
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def _scalar_floordiv_tensor(x, y):
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"""Returns x // y where x is a scalar and y is a tensor. x and y should have same dtype."""
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return F.tensor_floordiv(x, y)
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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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"""Implementation for internal polymorphism `mod` operations."""
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from ...composite import base
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from ... import functional as F
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mod = base.MultitypeFuncGraph("mod")
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"""
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`mod` is a metafuncgraph object which will compute the mod of two objects
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using ".register" decorator.
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"""
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@mod.register("Number", "Number")
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def _mod_scalar(x, y):
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"""Returns x % y where x and y are all scalars."""
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return F.scalar_mod(x, y)
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@mod.register("Tensor", "Tensor")
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def _mod_tensor(x, y):
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"""Returns x % y where x and y are all tensors and have save dtype."""
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return F.tensor_mod(x, y)
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@mod.register("Tensor", "Number")
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def _tensor_mod_scalar(x, y):
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"""Returns x % y where x is a tensor and y is a scalar. x and y should have same dtype."""
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return F.tensor_mod(x, y)
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@mod.register("Number", "Tensor")
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def _scalar_mod_tensor(x, y):
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"""Returns x % y where x is a scalar and y is a tensor. x and y should have same dtype."""
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return F.tensor_mod(x, y)
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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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"""Implementation for internal polymorphism `pow` operations."""
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from ...composite import base
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from ... import functional as F
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pow_ = base.MultitypeFuncGraph("pow")
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"""
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`pow` is a metafuncgraph object which will compute the pow of two objects
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using ".register" decorator.
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"""
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@pow_.register("Number", "Number")
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def _pow_scalar(x, y):
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"""Returns x ** y where x and y are all scalars."""
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return F.scalar_pow(x, y)
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@pow_.register("Tensor", "Tensor")
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def _pow_tensor(x, y):
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"""Returns x ** y where x and y are all tensors and have save dtype."""
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return F.tensor_pow(x, y)
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@pow_.register("Tensor", "Number")
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def _tensor_pow_scalar(x, y):
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"""Returns x ** y where x is a tensor and y is a scalar. x and y should have same dtype."""
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return F.tensor_pow(x, y)
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@pow_.register("Number", "Tensor")
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def _scalar_pow_tensor(x, y):
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"""Returns x ** y where x is a scalar and y is a tensor. x and y should have same dtype."""
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return F.tensor_pow(x, y)
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