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Safe LayerNorm #14699

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Safe LayerNorm #14699

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e68225b
try to use safe_acc
sxjscience Apr 15, 2019
4490210
fix layernorm bug
sxjscience May 3, 2019
660b0b0
Merge remote-tracking branch 'apache/master' into safe_float16_layernorm
sxjscience May 3, 2019
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48 changes: 24 additions & 24 deletions src/operator/nn/layer_norm-inl.h
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Original file line number Diff line number Diff line change
Expand Up @@ -111,7 +111,7 @@ void LayerNormCompute(const nnvm::NodeAttrs& attrs,
// Calculate mean
MSHADOW_REAL_TYPE_SWITCH(outputs[0].type_flag_, DType, {
BROADCAST_NDIM_SWITCH(red_dst_shape.ndim(), NDim, {
broadcast::Reduce<red::sum, NDim, DType, op::mshadow_op::identity>(
broadcast::Reduce<mshadow_op::sum, NDim, DType, mshadow_op::identity, true>(
s, mean_data, req[0], workspace, in_data);
Tensor<xpu, 1, DType> mean_data_tensor = mean_data.FlatTo1D<xpu, DType>(s);
mean_data_tensor /= scalar<DType>(channel_size);
Expand All @@ -125,25 +125,25 @@ void LayerNormCompute(const nnvm::NodeAttrs& attrs,
const TBlob centered_out = outputs[0].reshape(red_src_shape);
MSHADOW_REAL_TYPE_SWITCH(outputs[0].type_flag_, DType, {
BROADCAST_NDIM_SWITCH(red_dst_shape.ndim(), NDim, {
broadcast::Reduce<red::sum, NDim, DType, op::mshadow_op::square>(
broadcast::Reduce<mshadow_op::sum, NDim, DType, mshadow_op::square, true>(
s, std_data, req[0], workspace, centered_out);
Tensor<xpu, 1, DType> std_data_tensor = std_data.FlatTo1D<xpu, DType>(s);
std_data_tensor = F<mshadow_op::square_root>(std_data_tensor / scalar<DType>(channel_size)
+ scalar<DType>(param.eps));
});
});
// Calculate data = data / std
BinaryBroadcastCompute<xpu, op::mshadow_op::div>(attrs, ctx,
{outputs[0], outputs[layernorm::kStd]},
{kWriteTo}, {outputs[0]});
BinaryBroadcastCompute<xpu, mshadow_op::div>(attrs, ctx,
{outputs[0], outputs[layernorm::kStd]},
{kWriteTo}, {outputs[0]});
// Calculate data = data * gamma
BinaryBroadcastCompute<xpu, op::mshadow_op::mul>(attrs, ctx,
{outputs[0], gamma},
{kWriteTo}, {outputs[0]});
BinaryBroadcastCompute<xpu, mshadow_op::mul>(attrs, ctx,
{outputs[0], gamma},
{kWriteTo}, {outputs[0]});
// Calculate data = data + beta
BinaryBroadcastCompute<xpu, op::mshadow_op::plus>(attrs, ctx,
{outputs[0], beta},
{kWriteTo}, {outputs[0]});
BinaryBroadcastCompute<xpu, mshadow_op::plus>(attrs, ctx,
{outputs[0], beta},
{kWriteTo}, {outputs[0]});
}

/*
Expand Down Expand Up @@ -222,17 +222,17 @@ void LayerNormGradCompute(const nnvm::NodeAttrs& attrs,
const TBlob red_out = TBlob(workspace.dptr_ + reduce_workspace_size + data_size * 2,
mean.shape_, mean.dev_mask(), mean.type_flag_, mean.dev_id());
// Compute normalized_data = (data - mean) / std
BinaryBroadcastCompute<xpu, op::mshadow_op::minus>(attrs, ctx,
{data, mean},
{kWriteTo}, {normalized_data});
BinaryBroadcastCompute<xpu, op::mshadow_op::div>(attrs, ctx,
{normalized_data, std},
{kWriteTo}, {normalized_data});
BinaryBroadcastCompute<xpu, mshadow_op::minus>(attrs, ctx,
{data, mean},
{kWriteTo}, {normalized_data});
BinaryBroadcastCompute<xpu, mshadow_op::div>(attrs, ctx,
{normalized_data, std},
{kWriteTo}, {normalized_data});
// Calculate grad_beta
if (req[2] != kNullOp) {
MSHADOW_REAL_TYPE_SWITCH(outputs[2].type_flag_, DType, {
BROADCAST_NDIM_SWITCH(red_exclude_dst_shape.ndim(), NDim, {
broadcast::Reduce<red::sum, NDim, DType, op::mshadow_op::identity>(
broadcast::Reduce<mshadow_op::sum, NDim, DType, mshadow_op::identity, true>(
s, outputs[2].reshape(red_exclude_dst_shape), req[2], workspace,
ograd.reshape(red_exclude_src_shape));
});
Expand All @@ -244,7 +244,7 @@ void LayerNormGradCompute(const nnvm::NodeAttrs& attrs,
if (req[1] != kNullOp) {
MSHADOW_REAL_TYPE_SWITCH(outputs[1].type_flag_, DType, {
BROADCAST_NDIM_SWITCH(red_exclude_dst_shape.ndim(), NDim, {
broadcast::Reduce<red::sum, NDim, DType, op::mshadow_op::identity>(
broadcast::Reduce<mshadow_op::sum, NDim, DType, mshadow_op::identity, true>(
s, outputs[1].reshape(red_exclude_dst_shape), req[1], workspace,
ograd_mult.reshape(red_exclude_src_shape));
});
Expand All @@ -263,7 +263,7 @@ void LayerNormGradCompute(const nnvm::NodeAttrs& attrs,
{kWriteTo}, {ograd_mult});
MSHADOW_REAL_TYPE_SWITCH(outputs[0].type_flag_, DType, {
BROADCAST_NDIM_SWITCH(red_dst_shape.ndim(), NDim, {
broadcast::Reduce<red::sum, NDim, DType, op::mshadow_op::identity>(
broadcast::Reduce<mshadow_op::sum, NDim, DType, mshadow_op::identity, true>(
s, red_out.reshape(red_dst_shape), kWriteTo, workspace,
ograd_mult.reshape(red_src_shape));
});
Expand All @@ -277,16 +277,16 @@ void LayerNormGradCompute(const nnvm::NodeAttrs& attrs,
{kWriteTo}, {ograd_mult});
MSHADOW_REAL_TYPE_SWITCH(outputs[0].type_flag_, DType, {
BROADCAST_NDIM_SWITCH(red_dst_shape.ndim(), NDim, {
broadcast::Reduce<red::sum, NDim, DType, op::mshadow_op::identity>(
broadcast::Reduce<mshadow_op::sum, NDim, DType, mshadow_op::identity, true>(
s, red_out.reshape(red_dst_shape), kWriteTo, workspace,
ograd_mult.reshape(red_src_shape));
});
Tensor<xpu, 1, DType> red_out_tensor = red_out.FlatTo1D<xpu, DType>(s);
red_out_tensor /= scalar<DType>(- channel_size);
});
BinaryBroadcastCompute<xpu, op::mshadow_op::mul>(attrs, ctx,
{normalized_data, red_out},
{kAddTo}, {outputs[0]});
BinaryBroadcastCompute<xpu, mshadow_op::mul>(attrs, ctx,
{normalized_data, red_out},
{kAddTo}, {outputs[0]});
}
}

Expand Down