提交 9580c450 编写于 作者: P peterzhang2029

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

......@@ -76,11 +76,9 @@ set(IOS_PLATFORM ${IOS_PLATFORM} CACHE STRING "Type of iOS Platform")
# Set the architecture for iOS
if(NOT DEFINED IOS_ARCH)
if(IOS_PLATFORM STREQUAL "OS")
# FIXME(liuyiqun): support "armv7;armv7s;arm64" future
set(IOS_ARCH "arm64")
set(IOS_ARCH "armv7;armv7s;arm64")
elseif(IOS_PLATFORM STREQUAL "SIMULATOR")
# FIXME(liuyiqun): support "i386;x86_64" future
set(IOS_ARCH "x86_64")
set(IOS_ARCH "i386;x86_64")
endif()
endif()
set(CMAKE_OSX_ARCHITECTURES ${IOS_ARCH} CACHE string "Build architecture for iOS")
......@@ -248,7 +246,7 @@ set(IOS_COMPILER_FLAGS "${XCODE_IOS_PLATFORM_VERSION_FLAGS} ${XCODE_IOS_BITCODE_
# Hidden visibilty is required for cxx on iOS
set(CMAKE_C_FLAGS "${IOS_COMPILER_FLAGS} ${CMAKE_C_FLAGS}" CACHE STRING "C flags")
set(CMAKE_CXX_FLAGS "${IOS_COMPILER_FLAGS} -fvisibility-inlines-hidden ${CMAKE_CXX_FLAGS}" CACHE STRING "CXX flags")
set(CMAKE_CXX_FLAGS "${IOS_COMPILER_FLAGS} -fvisibility=hidden -fvisibility-inlines-hidden ${CMAKE_CXX_FLAGS}" CACHE STRING "CXX flags")
set(IOS_LINK_FLAGS "${XCODE_IOS_PLATFORM_VERSION_FLAGS} -Wl,-search_paths_first")
......
......@@ -45,15 +45,14 @@ IF(NOT ${CBLAS_FOUND})
SET(OPTIONAL_ARGS ${OPTIONAL_ARGS} TARGET=ARMV8 BINARY=64 USE_THREAD=0)
ENDIF()
ELSEIF(IOS)
# FIXME(liuyiqun): support multiple architectures
IF(CMAKE_OSX_ARCHITECTURES MATCHES "arm64")
SET(OPENBLAS_COMMIT "b5c96fcfcdc82945502a2303116a64d89985daf5")
SET(OPENBLAS_CC "${OPENBLAS_CC} ${CMAKE_C_FLAGS} -isysroot ${CMAKE_OSX_SYSROOT}")
IF(CMAKE_OSX_ARCHITECTURES MATCHES "armv7")
SET(OPENBLAS_CC "${OPENBLAS_CC} -arch armv7")
SET(OPTIONAL_ARGS ${OPTIONAL_ARGS} TARGET=ARMV7 ARM_SOFTFP_ABI=1 USE_THREAD=0)
ELSEIF(CMAKE_OSX_ARCHITECTURES MATCHES "arm64")
SET(OPENBLAS_CC "${OPENBLAS_CC} -arch arm64")
SET(OPTIONAL_ARGS ${OPTIONAL_ARGS} TARGET=ARMV8 BINARY=64 USE_THREAD=0 CROSS_SUFFIX=${CROSS_SUFFIX})
ELSE()
MESSAGE(FATAL_ERROR "OpenBLAS only support arm64 architectures on iOS. "
"You can set IOS_USE_VECLIB_FOR_BLAS=ON or USE_EIGEN_FOR_BLAS=ON to use other blas library instead.")
ENDIF()
ELSEIF(RPI)
# use hardfp
......
......@@ -12,6 +12,10 @@
# See the License for the specific language governing permissions and
# limitations under the License.
IF(MOBILE_INFERENCE)
return()
ENDIF()
INCLUDE(ExternalProject)
SET(WARPCTC_SOURCES_DIR ${THIRD_PARTY_PATH}/warpctc)
......
# 构建Android平台上的PaddlePaddle库
# Android平台编译指南
用户可通过如下两种方式,交叉编译Android平台上适用的PaddlePaddle库:
- 基于Docker容器的编译方式
......
# 构建iOS平台上的PaddlePaddle库
# iOS平台编译指南
交叉编译iOS平台上适用的PaddlePaddle库,需要在MacOS系统上进行。本文的将介绍在MacOS上,从源码交叉编译iOS平台上适用的PaddlePaddle库。
## 准备交叉编译环境
......@@ -25,7 +25,7 @@ iOS平台可选配置参数:
- `IOS_PLATFORM`,可设置为`OS/SIMULATOR`,默认值为`OS`
- `OS`,构建目标为`arm`架构的iPhone或者iPad等物理设备。
- `SIMULATOR`,构建目标为`x86`架构的模拟器平台。
- `IOS_ARCH`,目标架构。针对不同的`IOS_PLATFORM`,可设置的目标架构如下表所示:
- `IOS_ARCH`,目标架构。针对不同的`IOS_PLATFORM`,可设置的目标架构如下表所示,默认编译所有架构
<table class="docutils">
<colgroup>
......@@ -41,11 +41,11 @@ iOS平台可选配置参数:
<tbody valign="top">
<tr class="row-even">
<td>OS</td>
<td>armv7, armv7s, arm64 (默认)</td>
<td>armv7, armv7s, arm64 </td>
</tr>
<tr class="row-odd">
<td>SIMULATOR</td>
<td>i386, x86_64 (默认)</td>
<td>i386, x86_64 </td>
</tr>
</tbody>
</table>
......@@ -66,7 +66,7 @@ iOS平台可选配置参数:
```bash
cmake -DCMAKE_SYSTEM_NAME=iOS \
-DIOS_PLATFORM=OS \
-DIOS_ARCH="arm64" \
-DIOS_ARCH="armv7;arm64" \
-DIOS_ENABLE_BITCODE=ON \
-DIOS_USE_VECLIB_FOR_BLAS=ON \
-DCMAKE_INSTALL_PREFIX=your/path/to/install \
......@@ -112,6 +112,6 @@ $ make install
- `lib`目录,其中包含PaddlePaddle的C-API静态库
- `third_party`目录,其中包含所依赖的所有第三方库
注意,不同架构的PaddlePaddle库建议安装到不同的目录下,然后使用`lipo`工具将多个静态库合并成一个支持多个架构的fat库。
注意,如果PaddlePaddle库需要同时支持真机和模拟器,则需要分别编译真机和模拟器版本,然后使用`lipo`工具合并fat库。
自此,PaddlePaddle库已经安装完成,用户可将合成的fat库用于深度学习相关的iOS App中,调用方法见C-API文档。
# 构建Raspberry Pi平台上的PaddlePaddle库
# Raspberry Pi平台编译指南
通常有两个方法来构建基于 Rasspberry Pi 的版本:
......
......@@ -25,7 +25,9 @@ limitations under the License. */
#include "hl_matrix.h"
#include "hl_sequence.h"
#include "hl_sparse.h"
#ifndef PADDLE_MOBILE_INFERENCE
#include "hl_warpctc_wrap.h"
#endif
#ifdef HPPL_STUB_FUNC
#include "stub/hl_aggregate_stub.h"
......
......@@ -41,7 +41,7 @@ bool BatchNormBaseLayer::init(const LayerMap& layerMap,
useGlobalStats_ = config_.use_global_stats();
}
movingAvgFraction_ = config_.moving_average_fraction();
EPS = config_.epsilon();
epsilon_ = config_.epsilon();
weight_.reset(new Weight(1, channels_, parameters_[0]));
movingMean_.reset(new Weight(1, channels_, parameters_[1]));
......
......@@ -94,8 +94,8 @@ protected:
bool useGlobalStats_;
// use to compute moving mean and variance.
real movingAvgFraction_;
// Epsilon value used in the batch normalization formula.
real EPS;
// Epsilon is a small random noise used in batch normalization for stability.
real epsilon_;
};
} // namespace paddle
......@@ -51,7 +51,7 @@ void BatchNormalizationLayer::calMeanAndStd(const MatrixPtr& mat) {
calMovingMeanAndVar();
savedInvVar_->subScalar(-EPS);
savedInvVar_->subScalar(-epsilon_);
savedInvVar_->sqrt2(*savedInvVar_);
}
......@@ -72,7 +72,7 @@ void BatchNormalizationLayer::setMeanAndStd() {
savedInvVar_->copyFrom(*(movingVar_->getW()));
savedInvVar_->downClip(real(0.0));
savedInvVar_->subScalar(-EPS);
savedInvVar_->subScalar(-epsilon_);
savedInvVar_->sqrt2(*savedInvVar_);
}
......
......@@ -60,7 +60,15 @@ void CudnnBatchNormLayer::forward(PassType passType) {
real* beta = biases_->getW()->getData();
real* movingMean = movingMean_->getW()->getData();
real* movingVar = movingVar_->getW()->getData();
EPS_ = std::max(MIN_EPS, static_cast<double>(EPS));
/**
* If epsilon_ equals to 1e-5 and eps_ is assigned the value of
* static_cast<double>(epsilon_), The CUDNN_STATUS_BAD_PARAM error
* will occur due to eps_ value is less than
* CUDNN_BN_MIN_EPSILON.
* The following code is to ensure that the eps_ meets requirement.
*/
eps_ = std::max(MIN_EPS, static_cast<double>(epsilon_));
if (!useGlobalStats_) {
REGISTER_TIMER_INFO("CudnnBatchFwTimer", getName().c_str());
......@@ -76,7 +84,7 @@ void CudnnBatchNormLayer::forward(PassType passType) {
1.0 - movingAvgFraction_,
movingMean,
movingVar,
EPS_,
eps_,
savedMean,
savedInvVar);
} else {
......@@ -91,7 +99,7 @@ void CudnnBatchNormLayer::forward(PassType passType) {
beta,
movingMean,
movingVar,
EPS_);
eps_);
} else {
// There is a limitation in cudnn library.
// When the batch size is larger than 1024 in cuDNN v5.1,
......@@ -102,7 +110,7 @@ void CudnnBatchNormLayer::forward(PassType passType) {
beta,
movingMean,
movingVar,
EPS_,
eps_,
batchSize,
channels_,
imageH_ * imageD_,
......@@ -128,7 +136,15 @@ void CudnnBatchNormLayer::backward(const UpdateCallback& callback) {
real* gamma = weight_->getW()->getData();
real* savedMean = savedMean_->getData();
real* savedInvVar = savedInvVar_->getData();
EPS_ = std::max(MIN_EPS, static_cast<double>(EPS));
/**
* If epsilon_ equals to 1e-5 and eps_ is assigned the value of
* static_cast<double>(epsilon_), The CUDNN_STATUS_BAD_PARAM error
* will occur due to eps_ value is less than
* CUDNN_BN_MIN_EPSILON.
* The following code is to ensure that the eps_ meets requirement.
*/
eps_ = std::max(MIN_EPS, static_cast<double>(epsilon_));
auto create = [](MatrixPtr& m, size_t h, size_t w, real** p) {
Matrix::resizeOrCreate(m, h, w, false, true);
......@@ -159,7 +175,7 @@ void CudnnBatchNormLayer::backward(const UpdateCallback& callback) {
gamma,
gammaGrad,
betaGrad,
EPS_,
eps_,
savedMean,
savedInvVar);
......
......@@ -46,15 +46,12 @@ public:
void backward(const UpdateCallback& callback = nullptr) override;
protected:
/**
* Minimum allowed value is CUDNN_BN_MIN_EPSILON defined in cudnn.h.
* Same epsilon value should be used in forward and backward functions.
*/
/// Minimum allowed value is CUDNN_BN_MIN_EPSILON defined in cudnn.h.
static const double MIN_EPS;
/// Epsilon value used in the batch normalization formula.
/// If EPS_ is smaller than MIN_EPS, MIN_EPS will be used.
double EPS_;
/// Same epsilon value should be used in forward and backward functions.
double eps_;
/// Input/output tensor descriptor desc
hl_tensor_descriptor ioDesc_;
......
......@@ -48,7 +48,7 @@ bool MKLDNNBatchNormLayer::init(const LayerMap& layerMap,
useGlobalStats_ = config_.use_global_stats();
}
movingAvgFraction_ = config_.moving_average_fraction();
EPS = config_.epsilon();
epsilon_ = config_.epsilon();
VLOG(MKLDNN_BASE) << "--- " << (useGlobalStats_ ? "use" : "do not use")
<< " --- global stats";
......@@ -213,7 +213,7 @@ void MKLDNNBatchNormLayer::resetFwdPD(
if (wgt) {
flags_ = (flags_ | batch_normalization_flag::use_scale_shift);
}
auto fwdDesc = bn_fwd::desc(pk, in->getMemoryDesc(), EPS, flags_);
auto fwdDesc = bn_fwd::desc(pk, in->getMemoryDesc(), epsilon_, flags_);
pd.reset(new bn_fwd::primitive_desc(fwdDesc, engine_));
CHECK_PRIMITIVE_DESC_EQ(out, pd->dst_primitive_desc());
if (wgt) {
......@@ -280,7 +280,7 @@ void MKLDNNBatchNormLayer::resetBwdPD(
}
CHECK_PRIMITIVE_DESC_EQ(out, in->getPrimitiveDesc());
auto md = in->getMemoryDesc();
auto bwdDesc = bn_bwd::desc(prop_kind::backward, md, md, EPS, flags_);
auto bwdDesc = bn_bwd::desc(prop_kind::backward, md, md, epsilon_, flags_);
pd.reset(new bn_bwd::primitive_desc(bwdDesc, engine_, *fwdPD_));
CHECK(pd->weights_primitive_desc() == fwdPD_->weights_primitive_desc());
CHECK_PRIMITIVE_DESC_EQ(wgt, pd->diff_weights_primitive_desc());
......
......@@ -32,7 +32,7 @@ protected:
std::shared_ptr<bn_fwd::primitive_desc> fwdPD_;
// Epsilon value used in the batch normalization formula.
real EPS;
real epsilon_;
// weight and bias in paddle
std::unique_ptr<Weight> weight_;
......
......@@ -2483,7 +2483,7 @@ class BatchNormLayer(LayerBase):
self.config.use_global_stats = use_global_stats
if moving_average_fraction is not None:
self.config.moving_average_fraction = moving_average_fraction
if epsilon is not None:
self.config.epsilon = epsilon
input_layer = self.get_input_layer(0)
......
......@@ -3127,7 +3127,7 @@ def batch_norm_layer(input,
(batch_norm_type == "mkldnn_batch_norm") or \
(batch_norm_type == "cudnn_batch_norm")
assert epsilon >= 1e-5, "Parameter epsilon must be no less than 1e-5."
assert epsilon >= 1e-5, "epsilon must be no less than 1e-5."
l = Layer(
name=name,
......
......@@ -65,6 +65,7 @@ layers {
height: 227
width: 227
depth: 1
epsilon: 1e-05
}
layers {
name: "__crmnorm_0__"
......
......@@ -65,6 +65,7 @@ layers {
height: 256
width: 256
depth: 1
epsilon: 1e-05
}
layers {
name: "__crmnorm_0__"
......
......@@ -36,6 +36,7 @@ layers {
height: 6
width: 20
depth: 3
epsilon: 1e-05
}
parameters {
name: "___batch_norm_0__.w0"
......
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