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Fix some coding styles in batch norm #4

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merged 1 commit into from
Dec 20, 2017
Merged

Fix some coding styles in batch norm #4

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6 changes: 3 additions & 3 deletions src/operator/nn/batch_norm.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -430,7 +430,7 @@ void BatchNormCompute_CPU(const nnvm::NodeAttrs &attrs,

switch (inputs[0].dtype()) {
case mshadow::kFloat32:
MKLDNNBatchNorm_Forward<float>(ctx, param, in_data, req, outputs, aux_states);
MKLDNNBatchNormForward<float>(ctx, param, in_data, req, outputs, aux_states);
return;
}
}
Expand Down Expand Up @@ -472,8 +472,8 @@ void BatchNormGradCompute_CPU(const nnvm::NodeAttrs &attrs,
std::vector<NDArray> in_grad(outputs.begin(), outputs.begin() + 3);

if (inputs[0].dtype() == mshadow::kFloat32) {
MKLDNNBatchNorm_Backward<float>(ctx, param, out_grad, in_data,
out_data, req, in_grad, aux_states);
MKLDNNBatchNormBackward<float>(ctx, param, out_grad, in_data,
out_data, req, in_grad, aux_states);
return;
}
}
Expand Down
62 changes: 33 additions & 29 deletions src/operator/nn/mkldnn/mkldnn_batch_norm-inl.h
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Original file line number Diff line number Diff line change
Expand Up @@ -49,8 +49,8 @@ using mkldnn::forward_training;
using mkldnn::forward_inference;

inline static unsigned _GetFlags(const std::vector<NDArray> &in_data,
const std::vector<NDArray> &aux_states,
const BatchNormParam &param, bool is_train) {
const std::vector<NDArray> &aux_states,
const BatchNormParam &param, bool is_train) {
unsigned flags = 0U;
if (in_data.size() == 3U) {
flags |= use_scale_shift;
Expand All @@ -65,8 +65,10 @@ inline static unsigned _GetFlags(const std::vector<NDArray> &in_data,
}

template <typename DType>
inline static t_bn_f_pdesc _GetFwd(const mkldnn::memory &data_mem, bool is_train,
DType eps, unsigned flags) {
inline static t_bn_f_pdesc _GetFwd(const mkldnn::memory &data_mem,
bool is_train,
DType eps,
unsigned flags) {
auto data_mpd = data_mem.get_primitive_desc();
auto data_md = data_mpd.desc();
auto engine = CpuEngine::Get()->get_engine();
Expand All @@ -81,8 +83,10 @@ inline static t_bn_f_pdesc _GetFwd(const mkldnn::memory &data_mem, bool is_train
}

template <typename DType>
inline static t_bn_b_pdesc _GetBwd(const mkldnn::memory &data_mem, const mkldnn::memory &diff_mem,
DType eps, unsigned flags) {
inline static t_bn_b_pdesc _GetBwd(const mkldnn::memory &data_mem,
const mkldnn::memory &diff_mem,
DType eps,
unsigned flags) {
auto data_mpd = data_mem.get_primitive_desc();
auto data_md = data_mpd.desc();
auto diff_mpd = diff_mem.get_primitive_desc();
Expand All @@ -94,11 +98,11 @@ inline static t_bn_b_pdesc _GetBwd(const mkldnn::memory &data_mem, const mkldnn:
}

template <typename DType>
void MKLDNNBatchNorm_Forward(const OpContext &ctx, const BatchNormParam &param,
const std::vector<NDArray> &in_data,
const std::vector<OpReqType> &req,
const std::vector<NDArray> &out_data,
const std::vector<NDArray> &aux_states) {
void MKLDNNBatchNormForward(const OpContext &ctx, const BatchNormParam &param,
const std::vector<NDArray> &in_data,
const std::vector<OpReqType> &req,
const std::vector<NDArray> &out_data,
const std::vector<NDArray> &aux_states) {
TmpMemMgr::Get()->Init(ctx.requested[batchnorm::kTempSpace]);
unsigned flags = _GetFlags(in_data, aux_states, param, ctx.is_train);
const NDArray &data = in_data[batchnorm::kData];
Expand Down Expand Up @@ -194,13 +198,13 @@ void MKLDNNBatchNorm_Forward(const OpContext &ctx, const BatchNormParam &param,
}

template <typename DType>
void MKLDNNBatchNorm_Backward(const OpContext &ctx, const BatchNormParam &param,
const std::vector<NDArray> &out_grad,
const std::vector<NDArray> &in_data,
const std::vector<NDArray> &out_data,
const std::vector<OpReqType> &req,
const std::vector<NDArray> &in_grad,
const std::vector<NDArray> &aux_states) {
void MKLDNNBatchNormBackward(const OpContext &ctx, const BatchNormParam &param,
const std::vector<NDArray> &out_grad,
const std::vector<NDArray> &in_data,
const std::vector<NDArray> &out_data,
const std::vector<OpReqType> &req,
const std::vector<NDArray> &in_grad,
const std::vector<NDArray> &aux_states) {
TmpMemMgr::Get()->Init(ctx.requested[batchnorm::kTempSpace]);
CHECK_EQ(out_grad.size(), param.output_mean_var ? 3U : 1U);
CHECK_EQ(in_data.size(), 3U);
Expand Down Expand Up @@ -262,12 +266,12 @@ void MKLDNNBatchNorm_Backward(const OpContext &ctx, const BatchNormParam &param,

DType minus_mom = (1.0f - param.momentum);
for (int i = 0; i < channels_; i++) {
moving_mean_ptr[i] = moving_mean_ptr[i] * param.momentum
+ out_mean_ptr[i] * minus_mom;
moving_mean_ptr[i] = moving_mean_ptr[i] * param.momentum +
out_mean_ptr[i] * minus_mom;
float variance = INVSTD_TO_VARIANCE(out_var_ptr[i], param.eps);
tmp_var_ptr[i] = variance;
moving_var_ptr[i] = moving_var_ptr[i] * param.momentum
+ variance * minus_mom;
moving_var_ptr[i] = moving_var_ptr[i] * param.momentum +
variance * minus_mom;
}

std::shared_ptr<const mkldnn::memory> out_mean_mem(
Expand All @@ -276,13 +280,13 @@ void MKLDNNBatchNorm_Backward(const OpContext &ctx, const BatchNormParam &param,
new mkldnn::memory(bwd_pd.variance_primitive_desc(), out_var_ptr));

auto bn_bwd = mkldnn::batch_normalization_backward(bwd_pd,
*data_mem,
mkldnn::primitive::at(*out_mean_mem),
mkldnn::primitive::at(var_mem),
*diff_mem,
*weight_mem,
*gradi_mem,
*gradw_mem);
*data_mem,
mkldnn::primitive::at(*out_mean_mem),
mkldnn::primitive::at(var_mem),
*diff_mem,
*weight_mem,
*gradi_mem,
*gradw_mem);

MKLDNNStream::Get()->RegisterPrim(bn_bwd);
MKLDNNStream::Get()->Submit();
Expand Down