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[TF-TRT] Avoid padding calculations when not needed #28878

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merged 4 commits into from May 22, 2019
Merged

[TF-TRT] Avoid padding calculations when not needed #28878

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a9fc24e
Avoid calculating padding when it is not necessary i.e. TRT 5.1.3+
trevor-m May 20, 2019
ed0a8b6
Remove padding debug prints
trevor-m May 20, 2019
594db0f
Formatting
trevor-m May 20, 2019
14438d5
Clarify why we aren't using setPrePadding/setPostPadding for conv
trevor-m May 20, 2019
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44 changes: 15 additions & 29 deletions tensorflow/compiler/tf2tensorrt/convert/convert_nodes.cc
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Expand Up @@ -1950,7 +1950,8 @@ Status ConvertConv2DHelper(OpConverterParams* params, int group,
kernel_size.h() = weights.shape_.d[2];
kernel_size.w() = weights.shape_.d[3];

// Add padding.
// Before TRT 5.1.3, we have to calculate padding ourselves.
#if !IS_TRT_VERSION_GE(5, 1, 3, 0)
std::vector<std::pair<int, int>> padding;
if (attrs.get<string>("padding") == "SAME") {
nvinfer1::DimsHW effective_kernel_size = kernel_size;
Expand All @@ -1977,12 +1978,12 @@ Status ConvertConv2DHelper(OpConverterParams* params, int group,
padding = {{0, 0}, {0, 0}};
}

// TensorRT 5.1 added support for asymmetric padding. Due to a bug in 5.1.2, we
// can only use asymmetric padding in convolutions with 5.1.3+.
#if !IS_TRT_VERSION_GE(5, 1, 3, 0)
// Handle asymmetric padding. TensorRT 5.1 added support for asymmetric
// padding via setPrePadding and setPostPadding. Due to a bug in 5.1.2, we can
// only use asymmetric padding in convolutions with 5.1.3+. But in 5.1.3, we
// will always use setPaddingMode for simplicity.
if (padding[0].first != padding[0].second ||
padding[1].first != padding[1].second) {
// Handle asymmetric padding.
auto pad_layer = params->converter->network()->addPadding(
*tensor, nvinfer1::DimsHW(padding[0].first, padding[1].first),
nvinfer1::DimsHW(padding[0].second, padding[1].second));
Expand All @@ -2005,20 +2006,13 @@ Status ConvertConv2DHelper(OpConverterParams* params, int group,
layer->setStride(stride);
// TensorRT 5.1.3 added support for padding modes.
#if IS_TRT_VERSION_GE(5, 1, 3, 0)
// VALID padding is the default TRT behavior.
if (attrs.get<string>("padding") == "SAME") {
VLOG(2) << "Using SAME padding";
// SAME_UPPER means that post padding is preferred.
layer->setPaddingMode(nvinfer1::PaddingMode::kSAME_UPPER);
}
// For VALID padding, we need to manually set the padding.
layer->setPrePadding(nvinfer1::DimsHW{padding[0].first, padding[1].first});
layer->setPostPadding(
nvinfer1::DimsHW{padding[0].second, padding[1].second});
VLOG(2) << "Set pre-padding to: " << DebugString(layer->getPrePadding())
<< " and post-padding to: " << DebugString(layer->getPostPadding());
#else
layer->setPadding(nvinfer1::DimsHW{padding[0].first, padding[1].first});
VLOG(2) << "Set padding to: " << DebugString(layer->getPadding());
#endif
layer->setName(node_def.name().c_str());
layer->setNbGroups(num_groups);
Expand All @@ -2032,17 +2026,10 @@ Status ConvertConv2DHelper(OpConverterParams* params, int group,
layer->setStride(stride);
#if IS_TRT_VERSION_GE(5, 1, 3, 0)
if (attrs.get<string>("padding") == "SAME") {
VLOG(2) << "Using SAME padding";
layer->setPaddingMode(nvinfer1::PaddingMode::kSAME_UPPER);
}
layer->setPrePadding(nvinfer1::DimsHW{padding[0].first, padding[1].first});
layer->setPostPadding(
nvinfer1::DimsHW{padding[0].second, padding[1].second});
VLOG(2) << "Set pre-padding to: " << DebugString(layer->getPrePadding())
<< " and post-padding to: " << DebugString(layer->getPostPadding());
#else
layer->setPadding(nvinfer1::DimsHW{padding[0].first, padding[1].first});
VLOG(2) << "Set padding to: " << DebugString(layer->getPadding());
#endif
layer->setName(node_def.name().c_str());
layer->setNbGroups(num_groups);
Expand Down Expand Up @@ -2776,6 +2763,8 @@ Status ConvertPool(OpConverterParams* params) {
const auto tf_kernel = attrs.get<std::vector<int64>>("ksize");
const nvinfer1::DimsHW ksize(tf_kernel[h_index], tf_kernel[w_index]);

// Before TRT 5.1.3, we have to calculate padding ourselves.
#if !IS_TRT_VERSION_GE(5, 1, 3, 0)
auto tensor_dim = tensor->getDimensions();
std::vector<std::pair<int, int>> padding;
if (padding_type == "SAME") {
Expand All @@ -2788,13 +2777,13 @@ Status ConvertPool(OpConverterParams* params) {
} else if (padding_type == "VALID") {
padding = {{0, 0}, {0, 0}};
}

// TensorRT 5.1 added support for asymmetric padding.
#endif
// TensorRT 5.1 added support for asymmetric padding. Before that, we need an
// extra padding layer.
#if !IS_TRT_VERSION_GE(5, 1, 0, 0)
// Asymmetric padding case.
if (padding[0].first != padding[0].second ||
padding[1].first != padding[1].second) {
VLOG(2) << "Padding!!!: " << padding[0].first << padding[0].second
<< padding[1].first << padding[1].second;
auto pad_layer = params->converter->network()->addPadding(
*tensor, nvinfer1::DimsHW(padding[0].first, padding[1].first),
nvinfer1::DimsHW(padding[0].second, padding[1].second));
Expand All @@ -2816,16 +2805,13 @@ Status ConvertPool(OpConverterParams* params) {
layer->getOutput(0));

layer->setStride(stride);
// TensorRT 5.1.3 added support for padding modes.
#if IS_TRT_VERSION_GE(5, 1, 3, 0)
// VALID padding is the default TRT behavior.
if (attrs.get<string>("padding") == "SAME") {
// SAME_UPPER means that post padding is preferred.
layer->setPaddingMode(nvinfer1::PaddingMode::kSAME_UPPER);
}
#endif
// TensorRT 5.1 has support for asymmetric padding.
#if IS_TRT_VERSION_GE(5, 1, 0, 0)
// If padding mode is not SAME, then these values will be used instead.
#elif IS_TRT_VERSION_GE(5, 1, 0, 0)
layer->setPrePadding(nvinfer1::DimsHW{padding[0].first, padding[1].first});
layer->setPostPadding(nvinfer1::DimsHW{padding[0].second, padding[1].second});
#else
Expand Down