# 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
