<reponame>leelige/mindspore
# 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.
# ============================================================================
"""NLLLoss cell"""
import mindspore.ops.operations as P
from mindspore.nn.loss.loss import LossBase
from mindspore.ops import functional as F

class NLLLoss(LossBase):
    '''
       NLLLoss function
    '''
    def __init__(self, reduction='mean'):
        super(NLLLoss, self).__init__(reduction)
        self.one_hot = P.OneHot()
        self.reduce_sum = P.ReduceSum()

    def construct(self, logits, label):
        label_one_hot = self.one_hot(label, F.shape(logits)[-1], F.scalar_to_array(1.0), F.scalar_to_array(0.0))
        loss = self.reduce_sum(-1.0 * logits * label_one_hot, (1,))
        return self.get_loss(loss)

# 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.
# ============================================================================
"""NLLLoss cell"""
import mindspore.ops.operations as P
from mindspore.nn.loss.loss import LossBase
from mindspore.ops import functional as F

class NLLLoss(LossBase):
    '''
       NLLLoss function
    '''
    def __init__(self, reduction='mean'):
        super(NLLLoss, self).__init__(reduction)
        self.one_hot = P.OneHot()
        self.reduce_sum = P.ReduceSum()

    def construct(self, logits, label):
        label_one_hot = self.one_hot(label, F.shape(logits)[-1], F.scalar_to_array(1.0), F.scalar_to_array(0.0))
        loss = self.reduce_sum(-1.0 * logits * label_one_hot, (1,))
        return self.get_loss(loss)
# 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. # ============================================================================ NLLLoss cell NLLLoss function