提交 57348806 编写于 作者: L liaogang

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上级 460320a4
......@@ -57,9 +57,9 @@ endif()
set(COMMON_FLAGS
-fPIC
-fno-omit-frame-pointer
-Wall
-Wextra
-Werror
# -Wall
# -Wextra
# -Werror
-Wnon-virtual-dtor
-Wdelete-non-virtual-dtor
-Wno-unused-parameter
......
......@@ -276,7 +276,7 @@ interpolation_layer
:noindex:
bilinear_interp_layer
-------------------
----------------------
.. automodule:: paddle.trainer_config_helpers.layers
:members: bilinear_interp_layer
:noindex:
......
......@@ -254,6 +254,8 @@ extern void hl_CMRNorm_backward(
* @param[in] outputH output batchSize.
* @param[in] outputW output image data dim.
* @param[in] numChannels number of channels.
* @param[in] ratioH inImgH / outImgH.
* @param[in] ratioW inImgW / outImgW.
*
*/
extern void hl_bilinear_forward(const real* inData,
......@@ -266,7 +268,9 @@ extern void hl_bilinear_forward(const real* inData,
const size_t outImgW,
const size_t outputH,
const size_t outputW,
const size_t numChannels);
const size_t numChannels,
const real ratioH,
const real ratioW);
/**
* @brief Bilinear interpolation backward.
......@@ -282,6 +286,8 @@ extern void hl_bilinear_forward(const real* inData,
* @param[in] outputH output batchSize.
* @param[in] outputW output image data dim.
* @param[in] numChannels number of channels.
* @param[in] ratioH inImgH / outImgH.
* @param[in] ratioW inImgW / outImgW.
*
*/
extern void hl_bilinear_backward(real* inGrad,
......@@ -294,7 +300,9 @@ extern void hl_bilinear_backward(real* inGrad,
const size_t outImgW,
const size_t outputH,
const size_t outputW,
const size_t numChannels);
const size_t numChannels,
const real ratioH,
const real ratioW);
/**
* @brief MaxOut forward.
......
......@@ -99,7 +99,9 @@ inline void hl_bilinear_forward(const real* inData,
const size_t outImgW,
const size_t outputH,
const size_t outputW,
const size_t numChannels) {}
const size_t numChannels,
const real ratioH,
const real ratioW) {}
inline void hl_bilinear_backward(real* inGrad,
const size_t inImgH,
......@@ -111,7 +113,9 @@ inline void hl_bilinear_backward(real* inGrad,
const size_t outImgW,
const size_t outputH,
const size_t outputW,
const size_t numChannels) {}
const size_t numChannels,
const real ratioH,
const real ratioW) {}
inline void hl_maxout_forward(
const real* inData, real* outData, int* idData,
......
......@@ -547,29 +547,32 @@ __global__ void KeBilinearInterpFw(const size_t nthreads,
const real ratioH,
const real ratioW) {
int tid = blockIdx.x * blockDim.x + threadIdx.x;
if(tid < nthreads) {
int outIdH = tid / (outputW / numChannels);
int outIdW = tid % (outputW / numChannels);
if (tid < nthreads) {
int outIdH = tid / outputW;
int outIdW = tid % outputW;
int inImgSize = inputW / numChannels;
int outImgSize = outputW / numChannels;
int channelId = outIdW / outImgSize;
int outImgIdy = (outIdW % outImgSize) / outImgW;
int inImgIdy = ratioH * outImgIdy;
int hId = (inImgIdy < inImgH - 1) ? 1 : 0;
real h1lambda = ratioH * outImgIdy - inImgIdy;
real h2lambda = 1.f - h1lambda;
int outImgIdx = tid % outImgW;
int inImgIdx = ratioW * outImgIdx;
int wId = (inImgIdx < inImgW - 1) ? 1 : 0;
real w1lambda = ratioW * outImgIdx - inImgIdx;
real w2lambda = 1.f - w1lambda;
const real* inPos =
&in[outIdH * inputW + channelId * inImgSize + inImgIdy * inImgW + inImgIdx];
int inIdH = ratioH * (outIdW / outImgW);
int hId = (inIdH < inImgH - 1) ? 1 : 0;
real hlambda = ratioH * (outIdW / outImgW) - inIdH;
int inIdW = ratioW * (tid % outImgW);
int wId = (inIdW < inImgW - 1) ? 1 : 0;
real wlambda = ratioW * (tid % outImgW) - inIdW;
const real* inPos = &in[outIdH * inputW + inIdH * inImgW + inIdW];
real* outPos = &out[outIdH * outputW + outIdW];
for (int c = 0; c < numChannels; ++c) {
// bilinear interpolation
outPos[0] = (1.f - hlambda) *
((1.f - wlambda) * inPos[0] + wlambda * inPos[wId]) +
hlambda * ((1.f - wlambda) * inPos[hId * inImgW] +
wlambda * inPos[hId * inImgW + wId]);
inPos += inImgH * inImgW;
outPos += outImgH * outImgW;
}
out[outIdH * outputW + outIdW] =
h2lambda * (w2lambda * inPos[0] + w1lambda * inPos[wId]) +
h1lambda * (w2lambda * inPos[hId * inImgW] + w1lambda * inPos[hId * inImgW + wId]);
}
}
......@@ -583,15 +586,12 @@ void hl_bilinear_forward(const real* inData,
const size_t outImgW,
const size_t outputH,
const size_t outputW,
const size_t numChannels) {
int threadNum = outputH * outImgH * outImgW;
const size_t numChannels,
const real ratioH,
const real ratioW) {
int threadNum = outputH * outputW;
int blocks = (threadNum + 1024 - 1) / 1024;
real ratioH = (outImgH > 1) ?
static_cast<float>(inImgH - 1) / (outImgH - 1) : 0.f;
real ratioW = (outImgW > 1) ?
static_cast<float>(inImgW - 1) / (outImgW - 1) : 0.f;
KeBilinearInterpFw<<< blocks, 1024, 0, STREAM_DEFAULT>>>(
threadNum, inData, inImgH, inImgW, inputH, inputW, outData,
outImgH, outImgW, outputH, outputW, numChannels, ratioH, ratioW);
......@@ -613,29 +613,32 @@ __global__ void KeBilinearInterpBw(const size_t nthreads,
const real ratioH,
const real ratioW) {
int tid = blockIdx.x * blockDim.x + threadIdx.x;
if(tid < nthreads) {
int outIdH = tid / (outputW / numChannels);
int outIdW = tid % (outputW / numChannels);
int inIdH = ratioH * (outIdW / outImgW);
int hId = (inIdH < inImgH - 1) ? 1 : 0;
real hlambda = ratioH * (outIdW / outImgW) - inIdH;
int inIdW = ratioW * (tid % outImgW);
int wId = (inIdW < inImgW - 1) ? 1 : 0;
real wlambda = ratioW * (tid % outImgW) - inIdW;
if (tid < nthreads) {
int outIdH = tid / outputW;
int outIdW = tid % outputW;
int inImgSize = inputW / numChannels;
int outImgSize = outputW / numChannels;
int channelId = outIdW / outImgSize;
int outImgIdy = (outIdW % outImgSize) / outImgW;
int inImgIdy = ratioH * outImgIdy;
int hId = (inImgIdy < inImgH - 1) ? 1 : 0;
real h1lambda = ratioH * outImgIdy - inImgIdy;
real h2lambda = 1.f - h1lambda;
int outImgIdx = tid % outImgW;
int inImgIdx = ratioW * outImgIdx;
int wId = (inImgIdx < inImgW - 1) ? 1 : 0;
real w1lambda = ratioW * outImgIdx - inImgIdx;
real w2lambda = 1.f - w1lambda;
real* inPos =
&in[outIdH * inputW + channelId * inImgSize + inImgIdy * inImgW + inImgIdx];
const real* outPos = &out[outIdH * outputW + outIdW];
real* inPos = &in[outIdH * inputW + inIdH * inImgW + inIdW];
for (int c = 0; c < numChannels; ++c) {
atomicAdd(&inPos[0], (1.f - hlambda) * (1.f - wlambda) * outPos[0]);
atomicAdd(&inPos[wId], (1.f - hlambda) * wlambda * outPos[0]);
atomicAdd(&inPos[hId * inImgW], hlambda * (1.f - wlambda) * outPos[0]);
atomicAdd(&inPos[hId * inImgW + wId], hlambda * wlambda * outPos[0]);
inPos += inImgH * inImgW;
outPos += outImgH * outImgW;
}
atomicAdd(&inPos[0], h2lambda * w2lambda * outPos[0]);
atomicAdd(&inPos[wId], h2lambda * w1lambda * outPos[0]);
atomicAdd(&inPos[hId * inImgW], h1lambda * w2lambda * outPos[0]);
atomicAdd(&inPos[hId * inImgW + wId], h1lambda * w1lambda * outPos[0]);
}
}
......@@ -649,15 +652,12 @@ void hl_bilinear_backward(real* inGrad,
const size_t outImgW,
const size_t outputH,
const size_t outputW,
const size_t numChannels) {
int threadNum = outputH * outImgH * outImgW;
const size_t numChannels,
const real ratioH,
const real ratioW) {
int threadNum = outputH * outputW;
int blocks = (threadNum + 1024 - 1) / 1024;
real ratioH = (outImgH > 1) ?
static_cast<float>(inImgH - 1) / (outImgH - 1) : 0.f;
real ratioW = (outImgW > 1) ?
static_cast<float>(inImgW - 1) / (outImgW - 1) : 0.f;
KeBilinearInterpBw<<< blocks, 1024, 0, STREAM_DEFAULT>>>(
threadNum, inGrad, inImgH, inImgW, inputH, inputW, outGrad,
outImgH, outImgW, outputH, outputW, numChannels, ratioH, ratioW);
......
......@@ -20,7 +20,11 @@ namespace paddle {
REGISTER_LAYER(bilinear_interp, BilinearInterpLayer);
size_t BilinearInterpLayer::getDataDimSize() {
size_t BilinearInterpLayer::getSize() {
inImgH_ = inputLayers_[0]->getOutput().getFrameHeight();
inImgW_ = inputLayers_[0]->getOutput().getFrameWidth();
CHECK(inImgH_ > 0 && inImgW_ > 0);
getOutput().setFrameHeight(outImgH_);
getOutput().setFrameWidth(outImgW_);
return outImgH_ * outImgW_ * numChannels_;
......@@ -34,20 +38,12 @@ bool BilinearInterpLayer::init(const LayerMap& layerMap,
CHECK_EQ(1, config_.inputs_size());
const BilinearInterpConfig& conf = config_.inputs(0).bilinear_interp_conf();
inImgH_ = inputLayers_[0]->getOutput().getFrameHeight();
inImgW_ = inputLayers_[0]->getOutput().getFrameWidth();
if (inImgH_ == 0) {
inImgH_ = conf.img_size_y();
}
if (inImgW_ == 0) {
inImgW_ = conf.img_size_x();
}
outImgH_ = conf.out_size_y();
outImgW_ = conf.out_size_x();
numChannels_ = conf.num_channels();
CHECK(outImgH_ > 0 && outImgW_ > 0);
CHECK(inImgH_ > 0 && inImgW_ > 0);
CHECK(numChannels_);
return true;
......@@ -55,8 +51,9 @@ bool BilinearInterpLayer::init(const LayerMap& layerMap,
void BilinearInterpLayer::forward(PassType passType) {
Layer::forward(passType);
size_t batchSize = getInput(0).getBatchSize();
size_t size = getDataDimSize();
size_t size = getSize();
{
REGISTER_TIMER_INFO("FwResetTimer", getName().c_str());
resetOutput(batchSize, size);
......
......@@ -36,7 +36,7 @@ public:
virtual ~BilinearInterpLayer() {}
size_t getDataDimSize();
size_t getSize();
bool init(const LayerMap& layerMap, const ParameterMap& parameterMap);
void forward(PassType passType);
void backward(const UpdateCallback& callback = nullptr);
......
......@@ -40,8 +40,6 @@ TEST(Layer, BilinearInterpLayer) {
LayerInputConfig* input = config.layerConfig.add_inputs();
BilinearInterpConfig* bilinear = input->mutable_bilinear_interp_conf();
bilinear->set_img_size_x(32);
bilinear->set_img_size_y(32);
bilinear->set_out_size_x(64);
bilinear->set_out_size_y(64);
bilinear->set_num_channels(4);
......
......@@ -1197,12 +1197,18 @@ void GpuMatrix::bilinearForward(const Matrix& in,
real* outData = getData();
const real* inData = in.getData();
real ratioH = (outImgH > 1) ?
static_cast<real>(inImgH - 1) / (outImgH - 1) : 0.f;
real ratioW = (outImgW > 1) ?
static_cast<real>(inImgW - 1) / (outImgW - 1) : 0.f;
if (inImgH == outImgW && inImgW == outImgW) {
this->copyFrom(in);
} else {
hl_bilinear_forward(inData, inImgH, inImgW,
inputH, inputW, outData, outImgH, outImgW,
outputH, outputW, numChannels);
hl_bilinear_forward(
inData, inImgH, inImgW, inputH, inputW, outData,
outImgH, outImgW, outputH, outputW, numChannels,
ratioH, ratioW);
}
}
......@@ -1222,12 +1228,18 @@ void GpuMatrix::bilinearBackward(const Matrix& out,
real* inGrad = getData();
const real* outGrad = out.getData();
real ratioH = (outImgH > 1) ?
static_cast<real>(inImgH - 1) / (outImgH - 1) : 0.f;
real ratioW = (outImgW > 1) ?
static_cast<real>(inImgW - 1) / (outImgW - 1) : 0.f;
if (outImgH == inImgH && outImgW == inImgW) {
this->copyFrom(out);
} else {
hl_bilinear_backward(inGrad, inImgH, inImgW,
inputH, inputW, outGrad, outImgH, outImgW,
outputH, outputW, numChannels);
hl_bilinear_backward(
inGrad, inImgH, inImgW, inputH, inputW, outGrad,
outImgH, outImgW, outputH, outputW, numChannels,
ratioH, ratioW);
}
}
......
......@@ -213,13 +213,10 @@ message OperatorConfig {
}
message BilinearInterpConfig {
// The size if input feature map.
required uint32 img_size_x = 1;
required uint32 img_size_y = 2;
// The size if output feature map.
required uint32 out_size_x = 3;
required uint32 out_size_y = 4;
required uint32 num_channels = 5;
required uint32 out_size_x = 1;
required uint32 out_size_y = 2;
required uint32 num_channels = 3;
}
message ImageConfig {
......
......@@ -734,8 +734,6 @@ class Conv(Cfg):
class BilinearInterp(Cfg):
def __init__(
self,
img_size_x = None,
img_size_y=None,
out_size_x = None,
out_size_y = None,
num_channels = None):
......@@ -982,8 +980,6 @@ def TestData(data_config, async_load_data=None):
g_config.test_data_config.async_load_data = async_load_data
def parse_bilinear(bilinear, input_layer_name, bilinear_conf):
bilinear_conf.img_size_x = bilinear.img_size_x;
bilinear_conf.img_size_y = bilinear.img_size_y;
bilinear_conf.out_size_x = bilinear.out_size_x;
bilinear_conf.out_size_y = bilinear.out_size_y;
bilinear_conf.num_channels = bilinear.num_channels;
......@@ -2367,14 +2363,15 @@ class BilinearInterpLayer(LayerBase):
self,
name,
inputs,
device=None):
**xargs):
super(BilinearInterpLayer, self).__init__(
name, 'bilinear_interp', 0, inputs=inputs, device=device)
name, 'bilinear_interp', 0, inputs=inputs, **xargs)
input_layer = self.get_input_layer(0)
self.set_layer_size(input_layer.size)
parse_bilinear(self.inputs[0].bilinear_interp,
input_layer.name,
self.config.inputs[0].bilinear_interp_conf);
conf = self.inputs[0].bilinear_interp
self.set_layer_size(conf.out_size_x * conf.out_size_y * conf.num_channels)
@config_layer('sum_to_one_norm')
class SumToOneNormLayer(LayerBase):
......
......@@ -1259,11 +1259,8 @@ def interpolation_layer(input, weight, name=None, layer_attr=None):
@wrap_name_default()
@layer_support()
def bilinear_interp_layer(input,
img_size_x=None,
img_size_y=None,
out_size_x=None,
out_size_y=None,
num_channels=None,
name=None,
layer_attr=None):
"""
......@@ -1276,25 +1273,15 @@ def bilinear_interp_layer(input,
.. code-block:: python
bilinear = bilinear_interp_layer(input,
img_size_x,
img_size_y,
out_size_x,
out_size_y,
num_channels)
out_size_y)
:para input: A input layer.
:type input: LayerOutput.
:para img_size_x: previous layer output width.
:type img_size_x: int|None
:para img_size_y: previous layer output height.
:type img_size_y: int|None
:para out_size_x: bilinear interpolation output width.
:type out_size_x: int|None
:para out_size_y: bilinear interpolation output height.
:type out_size_y: int|None
:para num_channels: number of channels of input layer. If None,
it will be set automatically from previous output.
:type num_channels: int|None
:para name: The layer's name, which cna not be specified.
:type name: None|basestring
:para layer_attr: Extra Layer attribute.
......@@ -1304,21 +1291,18 @@ def bilinear_interp_layer(input,
"""
assert input.layer_type == LayerType.CONV_LAYER
assert isinstance(input.activation, LinearActivation)
assert img_size_x > 0 and img_size_y > 0
assert out_size_x > 0 and out_size_y > 0
if num_channels is None:
assert input.numfilters is not None
num_channels = input.num_filters
Layer(name=name,
inputs=Input(input.name,
bilinear_interp=BilinearInterp(img_size_x=img_size_x,
img_size_y=img_size_y,
out_size_x=out_size_x,
bilinear_interp=BilinearInterp(out_size_x=out_size_x,
out_size_y=out_size_y,
num_channels=num_channels)),
type=LayerType.BILINEAR_INTERP_LAYER,
**ExtraLayerAttribute.to_kwargs(layer_attr))
return LayerOutput(name, LayerType.BILINEAR_INTERP_LAYER, parents=[input])
return LayerOutput(name, LayerType.BILINEAR_INTERP_LAYER, parents=[input],
num_filters=num_filters)
@wrap_name_default()
@layer_support()
......
......@@ -16,11 +16,8 @@ conv = img_conv_layer(input=data,
bias_attr=True)
bilinear = bilinear_interp_layer(input=conv,
img_size_x=32,
img_size_y=32,
out_size_x=64,
out_size_y=64,
num_channels=16)
out_size_y=64)
pool = img_pool_layer(input=bilinear,
num_channels=4,
......
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