Merge pull request !537 from VectorSL/logical_and_or_newtags/v0.2.0-alpha
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| # 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. | |||
| """logical_and""" | |||
| import _akg.tvm | |||
| from _akg.ops.math import logical_and | |||
| from _akg.topi.generic import schedule_elemwise | |||
| def LogicalAnd(x, y): | |||
| """LogicalAnd.""" | |||
| return logical_and.logical_and(x, y) | |||
| def gpu_schedule_LogicalAnd(outs): | |||
| """ | |||
| GPU schedule for LogicalAnd. | |||
| Args: | |||
| outs (tvm.tensor.Tensor): outputs of compute. | |||
| Returns: | |||
| sch (schedule.Schedule): The created schedule. | |||
| """ | |||
| device = 'cuda' | |||
| ctx = _akg.tvm.context(device, 0) | |||
| if not ctx.exist: | |||
| raise SystemError("Skip because %s is not enabled" % device) | |||
| with _akg.tvm.target.create(device): | |||
| sch = schedule_elemwise(outs) | |||
| return sch | |||
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| # 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. | |||
| """logical_or""" | |||
| import _akg.tvm | |||
| from _akg.ops.math import logical_or | |||
| from _akg.topi.generic import schedule_elemwise | |||
| def LogicalOr(x, y): | |||
| """LogicalOr.""" | |||
| return logical_or.logical_or(x, y) | |||
| def gpu_schedule_LogicalOr(outs): | |||
| """ | |||
| GPU schedule for LogicalOr. | |||
| Args: | |||
| outs (tvm.tensor.Tensor): outputs of compute. | |||
| Returns: | |||
| sch (schedule.Schedule): The created schedule. | |||
| """ | |||
| device = 'cuda' | |||
| ctx = _akg.tvm.context(device, 0) | |||
| if not ctx.exist: | |||
| raise SystemError("Skip because %s is not enabled" % device) | |||
| with _akg.tvm.target.create(device): | |||
| sch = schedule_elemwise(outs) | |||
| return sch | |||
| @@ -0,0 +1,41 @@ | |||
| # 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. | |||
| """operator dsl function: logical_and""" | |||
| import _akg.tvm | |||
| import _akg.topi | |||
| from _akg.utils import validation_check as vc_util | |||
| @vc_util.check_input_type(_akg.tvm.tensor.Tensor, _akg.tvm.tensor.Tensor) | |||
| def logical_and(input1, input2): | |||
| """ | |||
| Compute logical_and of input1 and input2. | |||
| Args: | |||
| input1 (tvm.tensor.Tensor): Tensor. | |||
| input2 (tvm.tensor.Tensor): Tensor. | |||
| Returns: | |||
| tvm.tensor.Tensor. LogicalAnd of input1 and input2. | |||
| """ | |||
| vc_util.elemwise_dtype_check(input1.dtype, input2.dtype) | |||
| shape1 = [x.value for x in input1.shape] | |||
| shape2 = [x.value for x in input2.shape] | |||
| vc_util.check_shape(shape1) | |||
| vc_util.check_shape(shape2) | |||
| res = _akg.topi.logical_and(input1, input2) | |||
| return res | |||
| @@ -0,0 +1,41 @@ | |||
| # 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. | |||
| """operator dsl function: logical_or""" | |||
| import _akg.tvm | |||
| import _akg.topi | |||
| from _akg.utils import validation_check as vc_util | |||
| @vc_util.check_input_type(_akg.tvm.tensor.Tensor, _akg.tvm.tensor.Tensor) | |||
| def logical_or(input1, input2): | |||
| """ | |||
| Compute logical_or of input1 and input2. | |||
| Args: | |||
| input1 (tvm.tensor.Tensor): Tensor. | |||
| input2 (tvm.tensor.Tensor): Tensor. | |||
| Returns: | |||
| tvm.tensor.Tensor. LogicalOr of input1 and input2. | |||
| """ | |||
| vc_util.elemwise_dtype_check(input1.dtype, input2.dtype) | |||
| shape1 = [x.value for x in input1.shape] | |||
| shape2 = [x.value for x in input2.shape] | |||
| vc_util.check_shape(shape1) | |||
| vc_util.check_shape(shape2) | |||
| res = _akg.topi.logical_or(input1, input2) | |||
| return res | |||
| @@ -0,0 +1,29 @@ | |||
| # 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. | |||
| """LogicalAnd op""" | |||
| from mindspore.ops.op_info_register import op_info_register, AkgRegOp, DataType | |||
| logicaland_op_info = AkgRegOp("LogicalAnd") \ | |||
| .fusion_type("OPAQUE") \ | |||
| .input(0, "x") \ | |||
| .input(1, "y") \ | |||
| .output(0, "output") \ | |||
| .dtype_format(DataType.BOOL_Default, DataType.BOOL_Default, DataType.BOOL_Default) \ | |||
| .get_op_info() | |||
| @op_info_register(logicaland_op_info) | |||
| def _logical_and_akg(): | |||
| """LogicalAnd register""" | |||
| return | |||
| @@ -0,0 +1,29 @@ | |||
| # 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. | |||
| """LogicalOr op""" | |||
| from mindspore.ops.op_info_register import op_info_register, AkgRegOp, DataType | |||
| logicalor_op_info = AkgRegOp("LogicalOr") \ | |||
| .fusion_type("OPAQUE") \ | |||
| .input(0, "x") \ | |||
| .input(1, "y") \ | |||
| .output(0, "output") \ | |||
| .dtype_format(DataType.BOOL_Default, DataType.BOOL_Default, DataType.BOOL_Default) \ | |||
| .get_op_info() | |||
| @op_info_register(logicalor_op_info) | |||
| def _logical_or_akg(): | |||
| """LogicalOr register""" | |||
| return | |||