|
- # Copyright 2021 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.
- # ============================================================================
- '''net
- The sample can be run on Ascend 910 AI processor.
- '''
- import numpy as np
- from mindspore import Tensor, Parameter, ops
- from mindspore.nn import Cell
-
-
- class Net(Cell):
- """Net"""
-
- def __init__(self, matmul_size, transpose_a=False, transpose_b=False, strategy=None):
- """init"""
- super().__init__()
- matmul_np = np.full(matmul_size, 0.5, dtype=np.float32)
- self.matmul_weight = Parameter(Tensor(matmul_np))
- self.matmul = ops.MatMul(transpose_a=transpose_a, transpose_b=transpose_b)
- self.neg = ops.Neg()
- if strategy is not None:
- self.matmul.shard(strategy)
-
- def construct(self, inputs):
- """construct"""
- x = self.matmul(inputs, self.matmul_weight)
- x = self.neg(x)
- return x
|