提交 ba8a5c15 编写于 作者: W wanghaoshuang

Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into pad_op

......@@ -139,7 +139,13 @@ void DetectionOutputLayer::forward(PassType passType) {
allDecodedBBoxes,
&allIndices);
if (numKept > 0) {
resetOutput(numKept, 7);
} else {
MatrixPtr outV = getOutputValue();
outV = NULL;
return;
}
MatrixPtr outV = getOutputValue();
getDetectionOutput(confBuffer_->getData(),
numKept,
......
......@@ -469,7 +469,7 @@ size_t getDetectionIndices(
const size_t numClasses,
const size_t backgroundId,
const size_t batchSize,
const size_t confThreshold,
const real confThreshold,
const size_t nmsTopK,
const real nmsThreshold,
const size_t keepTopK,
......
......@@ -275,7 +275,7 @@ size_t getDetectionIndices(
const size_t numClasses,
const size_t backgroundId,
const size_t batchSize,
const size_t confThreshold,
const real confThreshold,
const size_t nmsTopK,
const real nmsThreshold,
const size_t keepTopK,
......
......@@ -25,10 +25,6 @@ limitations under the License. */
#include "paddle/string/printf.h"
#include "paddle/string/to_string.h"
#ifdef __GNUC__
#include <cxxabi.h> // for __cxa_demangle
#endif
#ifndef PADDLE_ONLY_CPU
#include "paddle/platform/dynload/cublas.h"
......@@ -46,19 +42,6 @@ limitations under the License. */
namespace paddle {
namespace platform {
namespace {
#ifdef __GNUC__
inline std::string demangle(std::string name) {
int status = -4; // some arbitrary value to eliminate the compiler warning
std::unique_ptr<char, void (*)(void*)> res{
abi::__cxa_demangle(name.c_str(), NULL, NULL, &status), std::free};
return (status == 0) ? res.get() : name;
}
#else
inline std::string demangle(std::string name) { return name; }
#endif
}
struct EnforceNotMet : public std::exception {
std::exception_ptr exp_;
std::string err_str_;
......@@ -79,7 +62,7 @@ struct EnforceNotMet : public std::exception {
Dl_info info;
for (int i = 0; i < size; ++i) {
if (dladdr(call_stack[i], &info)) {
auto demangled = demangle(info.dli_sname);
auto demangled = info.dli_sname;
auto addr_offset = static_cast<char*>(call_stack[i]) -
static_cast<char*>(info.dli_saddr);
sout << string::Sprintf("%-3d %*0p %s + %zd\n", i,
......
......@@ -30,6 +30,8 @@ Configuring cmake in /paddle/build ...
-DCMAKE_BUILD_TYPE=Release
-DWITH_DOC=OFF
-DWITH_GPU=${WITH_GPU:-OFF}
-DWITH_MKLDNN=${WITH_MKLDNN:-ON}
-DWITH_MKLML=${WITH_MKLML:-ON}
-DWITH_AVX=${WITH_AVX:-OFF}
-DWITH_GOLANG=${WITH_GOLANG:-ON}
-DWITH_SWIG_PY=ON
......@@ -50,6 +52,8 @@ cmake .. \
-DCMAKE_BUILD_TYPE=Release \
-DWITH_DOC=OFF \
-DWITH_GPU=${WITH_GPU:-OFF} \
-DWITH_MKLDNN=${WITH_MKLDNN:-ON} \
-DWITH_MKLML=${WITH_MKLML:-ON} \
-DWITH_AVX=${WITH_AVX:-OFF} \
-DWITH_GOLANG=${WITH_GOLANG:-ON} \
-DWITH_SWIG_PY=${WITH_SWIG_PY:-ON} \
......
......@@ -3748,8 +3748,8 @@ class SwitchOrderLayer(LayerBase):
def __init__(self, name, inputs, reshape, **xargs):
super(SwitchOrderLayer, self).__init__(
name, 'switch_order', 0, inputs=inputs, **xargs)
self.config.reshape_conf.heightAxis.extend(reshape['height'])
self.config.reshape_conf.widthAxis.extend(reshape['width'])
self.config.reshape_conf.height_axis.extend(reshape['height'])
self.config.reshape_conf.width_axis.extend(reshape['width'])
# Deprecated, use a new layer specific class instead
......
......@@ -1223,7 +1223,8 @@ def detection_output_layer(input_loc,
name=None):
"""
Apply the NMS to the output of network and compute the predict bounding
box location.
box location. The output of this layer could be None if there is no valid
bounding box.
:param name: The Layer Name.
:type name: basestring
......@@ -6460,6 +6461,7 @@ def switch_order_layer(input,
return LayerOutput(
name=name,
layer_type=LayerType.SWITCH_ORDER_LAYER,
activation=act,
parents=input,
size=l.config.size)
......
......@@ -53,10 +53,13 @@ class BeginPass(object):
class EndPass(WithMetric):
"""
Event On One Pass Training Complete.
To get the output of a specific layer, add "event.gm.getLayerOutputs('predict_layer')"
in your event_handler call back
"""
def __init__(self, pass_id, evaluator):
def __init__(self, pass_id, evaluator, gm):
self.pass_id = pass_id
self.gm = gm
WithMetric.__init__(self, evaluator)
......@@ -73,10 +76,13 @@ class BeginIteration(object):
class EndIteration(WithMetric):
"""
Event On One Batch Training Complete.
To get the output of a specific layer, add "event.gm.getLayerOutputs('predict_layer')"
in your event_handler call back
"""
def __init__(self, pass_id, batch_id, cost, evaluator):
def __init__(self, pass_id, batch_id, cost, evaluator, gm):
self.pass_id = pass_id
self.batch_id = batch_id
self.cost = cost
self.gm = gm
WithMetric.__init__(self, evaluator)
......@@ -174,13 +174,18 @@ class SGD(object):
pass_id=pass_id,
batch_id=batch_id,
cost=cost,
evaluator=batch_evaluator))
evaluator=batch_evaluator,
gm=self.__gradient_machine__))
self.__parameter_updater__.finishBatch(cost)
batch_evaluator.finish()
self.__parameter_updater__.finishPass()
pass_evaluator.finish()
event_handler(v2_event.EndPass(pass_id, evaluator=pass_evaluator))
event_handler(
v2_event.EndPass(
pass_id,
evaluator=pass_evaluator,
gm=self.__gradient_machine__))
self.__gradient_machine__.finish()
def test(self, reader, feeding=None):
......
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