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!46490 bugfix, nllloss labels input must be in [0, C-1] 

Merge pull request !46490 from zhangyanhui/develop_mas
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i-robot 2022-12-07 02:02:09 +00:00 committed by Gitee
parent d294c9ecb1 d95affa3b8
commit ea7b2a377d
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2 changed files with 12 additions and 1 deletions
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1
docs/api/api_python/ops/mindspore.ops.NLLLoss.rst
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@ -39,3 +39,4 @@ mindspore.ops.NLLLoss
异常： 异常：
- **TypeError** - `logits` 或 `weight` 的数据类型既不是float16也不是float32， `labels` 不是int32。 - **TypeError** - `logits` 或 `weight` 的数据类型既不是float16也不是float32， `labels` 不是int32。
- **ValueError** - `logits` 不是二维Tensor， `labels` 和 `weight` 不是一维Tensor。 `logits` 的第一个维度不等于 `labels` ， `logits` 的第二个维度不等于 `weight` 。 - **ValueError** - `logits` 不是二维Tensor， `labels` 和 `weight` 不是一维Tensor。 `logits` 的第一个维度不等于 `labels` ， `logits` 的第二个维度不等于 `weight` 。
- **ValueError** - `labels` 的取值超出 :math:`[0, C-1]` ，其中 :math:`C` 表示类的数量。

10
mindspore/ccsrc/plugin/device/cpu/kernel/nllloss_cpu_kernel.cc
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@ -25,6 +25,7 @@ namespace kernel {
namespace { namespace {
constexpr size_t kNLLLossInputsNum = 3; constexpr size_t kNLLLossInputsNum = 3;
constexpr size_t kNLLLossOutputsNum = 2; constexpr size_t kNLLLossOutputsNum = 2;
constexpr int minLabelNum = 0;
const std::map<Reduction, ReductionType> kReductionMap = { const std::map<Reduction, ReductionType> kReductionMap = {
{Reduction::MEAN, Reduction_Mean}, {Reduction::REDUCTION_SUM, Reduction_Sum}, {Reduction::NONE, Reduction_None}}; {Reduction::MEAN, Reduction_Mean}, {Reduction::REDUCTION_SUM, Reduction_Sum}, {Reduction::NONE, Reduction_None}};
} // namespace } // namespace
@ -82,6 +83,15 @@ bool NLLLossCpuKernelMod::Launch(const std::vector<kernel::AddressPtr> &inputs,
const auto *weight = reinterpret_cast<float *>(inputs[kIndex2]->addr); const auto *weight = reinterpret_cast<float *>(inputs[kIndex2]->addr);
auto *loss = reinterpret_cast<float *>(outputs[kIndex0]->addr); auto *loss = reinterpret_cast<float *>(outputs[kIndex0]->addr);
auto *total_weight = reinterpret_cast<float *>(outputs[kIndex1]->addr); auto *total_weight = reinterpret_cast<float *>(outputs[kIndex1]->addr);
if (logits == NULL || labels == NULL || weight == NULL) {
MS_LOG(EXCEPTION) << "Nllloss does not support null input";
}
for (int i = 0; i < nllloss_param_.batch_; i++) {
if (labels[i] < minLabelNum || labels[i] > nllloss_param_.class_num_) {
MS_EXCEPTION(ValueError) << "For '" << kernel_name_ << "', the label must in scope[0, C-1], but got" << labels[i];
}
}
int ret = NLLLoss(logits, labels, weight, loss, total_weight, &nllloss_param_); int ret = NLLLoss(logits, labels, weight, loss, total_weight, &nllloss_param_);
if (ret != static_cast<int>(NNACL_OK)) { if (ret != static_cast<int>(NNACL_OK)) {