提交 5b2f9939 编写于 作者: G gongweibao

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

......@@ -7,8 +7,17 @@ INCLUDE_DIRECTORIES(${EIGEN_SOURCE_DIR}/src/eigen3)
ExternalProject_Add(
eigen3
${EXTERNAL_PROJECT_LOG_ARGS}
URL "https://bitbucket.org/eigen/eigen/get/3.3.4.tar.gz"
URL_MD5 "1a47e78efe365a97de0c022d127607c3"
# for latest version, please get from official website
# URL "https://bitbucket.org/eigen/eigen/get/3.3.4.tar.gz"
# URL_MD5 "1a47e78efe365a97de0c022d127607c3"
# for no-ssl http support, please get from bazel's mirror
# URL "http://mirror.bazel.build/bitbucket.org/eigen/eigen/get/f3a22f35b044.tar.gz"
# URL_MD5 "4645c66075982da6fa0bcf6b20f3e8f7"
# get from github mirror
GIT_REPOSITORY "https://github.com/RLovelett/eigen.git"
GIT_TAG "a46d2e7337c4656f00abe54a8115f6d76153a048"
PREFIX ${EIGEN_SOURCE_DIR}
UPDATE_COMMAND ""
CONFIGURE_COMMAND ""
......
......@@ -13,6 +13,10 @@
# limitations under the License.
INCLUDE(ExternalProject)
# Always invoke `FIND_PACKAGE(Protobuf)` for importing function protobuf_generate_cpp
FIND_PACKAGE(Protobuf QUIET)
SET(PROTOBUF_FOUND "OFF")
# Print and set the protobuf library information,
# finish this cmake process and exit from this file.
......@@ -39,12 +43,19 @@ macro(PROMPT_PROTOBUF_LIB)
ADD_LIBRARY(protobuf_lite ${protobuf_LIBTYPE} IMPORTED GLOBAL)
SET_PROPERTY(TARGET protobuf_lite PROPERTY IMPORTED_LOCATION ${PROTOBUF_LITE_LIBRARY})
ADD_LIBRARY(protoc ${protobuf_LIBTYPE} IMPORTED GLOBAL)
SET_PROPERTY(TARGET protoc PROPERTY IMPORTED_LOCATION ${PROTOC_LIBRARY})
ADD_LIBRARY(libprotoc ${protobuf_LIBTYPE} IMPORTED GLOBAL)
SET_PROPERTY(TARGET libprotoc PROPERTY IMPORTED_LOCATION ${PROTOC_LIBRARY})
ADD_EXECUTABLE(protoc IMPORTED GLOBAL)
SET_PROPERTY(TARGET protoc PROPERTY IMPORTED_LOCATION ${PROTOBUF_PROTOC_EXECUTABLE})
# FIND_Protobuf.cmake uses `Protobuf_PROTOC_EXECUTABLE`.
# make `protobuf_generate_cpp` happy.
SET(Protobuf_PROTOC_EXECUTABLE ${PROTOBUF_PROTOC_EXECUTABLE})
FOREACH(dep ${protobuf_DEPS})
ADD_DEPENDENCIES(protobuf ${dep})
ADD_DEPENDENCIES(protobuf_lite ${dep})
ADD_DEPENDENCIES(libprotoc ${dep})
ADD_DEPENDENCIES(protoc ${dep})
ENDFOREACH()
......
......@@ -87,6 +87,9 @@
# go_library(example SHARED)
#
# including binary directory for generated headers.
include_directories(${CMAKE_BINARY_DIR})
if(NOT APPLE)
find_package(Threads REQUIRED)
link_libraries(${CMAKE_THREAD_LIBS_INIT})
......@@ -331,3 +334,13 @@ function(go_test TARGET_NAME)
add_custom_target(${TARGET_NAME} ALL DEPENDS ${TARGET_NAME}_timestamp ${go_test_DEPS})
add_test(${TARGET_NAME} ${CMAKE_CURRENT_BINARY_DIR}/${TARGET_NAME})
endfunction(go_test)
function(proto_library TARGET_NAME)
set(oneValueArgs "")
set(multiValueArgs SRCS)
cmake_parse_arguments(proto_library "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
set(proto_srcs)
set(proto_hdrs)
protobuf_generate_cpp(proto_srcs proto_hdrs ${proto_library_SRCS})
cc_library(${TARGET_NAME} SRCS ${proto_srcs} DEPS protobuf)
endfunction()
......@@ -27,10 +27,6 @@ sphinx_add_target(paddle_docs
${CMAKE_CURRENT_SOURCE_DIR}
${SPHINX_HTML_DIR_EN})
add_dependencies(paddle_docs
gen_proto_py)
# configured documentation tools and intermediate build results
set(BINARY_BUILD_DIR_CN "${CMAKE_CURRENT_BINARY_DIR}/cn/_build")
......@@ -51,6 +47,3 @@ sphinx_add_target(paddle_docs_cn
${SPHINX_CACHE_DIR_CN}
${CMAKE_CURRENT_SOURCE_DIR}
${SPHINX_HTML_DIR_CN})
add_dependencies(paddle_docs_cn
gen_proto_py)
......@@ -41,7 +41,7 @@ class Scope {
const Variable* GetVariable(const std::string& name) const;
private:
std::unordered_map<std::string, std::unique_ptr<Vairable>> vars_;
std::unordered_map<std::string, std::unique_ptr<Variable>> vars_;
};
```
......@@ -59,9 +59,9 @@ class Scope {
Scope(const std::shared_ptr<Scope>& scope): parent_(scope) {}
Variable* GetVariable(const std::string& name) const {
Variable* var = GetVarLocally(name);
if (var != nullptr) {
return var;
auto it = vars_.find(name);
if (it != vars_.end()) {
return it->second.get();
} else if (parent_ != nullptr) {
return parent_->GetVariable(name);
} else {
......@@ -97,8 +97,8 @@ class Scope {
// return nullptr if not found.
Variable* GetVariable(const std::string& name) const;
// return Error if already contains same name variable.
Error CreateVariable(const std::string& name);
// return if already contains same name variable.
Variable* CreateVariable(const std::string& name);
private:
std::shared_ptr<Scope> parent_;
......
......@@ -13,10 +13,13 @@ typedef int paddle_master_client;
import "C"
import (
"strings"
"sync"
"time"
"unsafe"
"github.com/PaddlePaddle/Paddle/go/master"
"github.com/coreos/etcd/clientv3"
log "github.com/sirupsen/logrus"
)
......@@ -48,16 +51,33 @@ func remove(client C.paddle_master_client) *master.Client {
return h
}
type addresser string
func (a addresser) Address() string {
return string(a)
//export paddle_new_etcd_master_client
func paddle_new_etcd_master_client(etcdEndpoints *C.char, timeout int, bufSize int) C.paddle_master_client {
p := C.GoString(etcdEndpoints)
cli, err := clientv3.New(clientv3.Config{
Endpoints: strings.Split(p, ","),
DialTimeout: time.Second * time.Duration(timeout),
})
if err != nil {
panic(err)
}
ch := make(chan string, 1)
a, err := master.GetKey(cli, master.DefaultAddrPath, timeout)
if err != nil {
panic(err)
}
ch <- a
go master.WatchKey(cli, master.DefaultAddrPath, ch)
c := master.NewClient(ch, bufSize)
return add(c)
}
//export paddle_new_master_client
func paddle_new_master_client(addr *C.char, bufSize int) C.paddle_master_client {
a := C.GoString(addr)
c := master.NewClient(addresser(a), bufSize)
ch := make(chan string, 1)
ch <- a
c := master.NewClient(ch, bufSize)
return add(c)
}
......
......@@ -2,18 +2,12 @@ package master
import (
"os"
"time"
"github.com/PaddlePaddle/Paddle/go/connection"
"github.com/PaddlePaddle/recordio"
log "github.com/sirupsen/logrus"
)
// Addresser provide the address of the master server.
type Addresser interface {
Address() string
}
// Client is the client of the master server.
type Client struct {
conn *connection.Conn
......@@ -24,11 +18,11 @@ type Client struct {
//
// bufSize is the record buffer size. NextRecord will read from this
// buffer.
func NewClient(addr Addresser, bufSize int) *Client {
func NewClient(addrCh <-chan string, bufSize int) *Client {
c := &Client{}
c.conn = connection.New()
c.ch = make(chan []byte, bufSize)
go c.monitorMaster(addr)
go c.monitorMaster(addrCh)
go c.getRecords()
return c
}
......@@ -72,12 +66,10 @@ func (c *Client) getRecords() {
}
}
func (c *Client) monitorMaster(addr Addresser) {
func (c *Client) monitorMaster(addrCh <-chan string) {
lastMaster := ""
monitor := func() {
// get the lastest address of the master server,
for curMaster := range addrCh {
// connect to the new address once address changed.
curMaster := addr.Address()
if curMaster != lastMaster {
if curMaster == "" {
err := c.conn.Close()
......@@ -94,18 +86,10 @@ func (c *Client) monitorMaster(addr Addresser) {
// to retry next time.
curMaster = lastMaster
}
}
}
lastMaster = curMaster
}
monitor()
ticker := time.NewTicker(10 * time.Second)
for _ = range ticker.C {
monitor()
}
}
// SetDataset set dataset for the master server to dispatch.
......
......@@ -26,12 +26,6 @@ func init() {
log.SetLevel(log.ErrorLevel)
}
type TestAddresser string
func (a TestAddresser) Address() string {
return string(a)
}
func TestGetFinishTask(t *testing.T) {
const path = "/tmp/master_client_test_0"
......@@ -45,7 +39,6 @@ func TestGetFinishTask(t *testing.T) {
if err != nil {
panic(err)
}
go func(l net.Listener) {
s, err := NewService(&InMemStore{}, chunkPerTask, time.Second, 1)
if err != nil {
......@@ -82,9 +75,11 @@ func TestGetFinishTask(t *testing.T) {
// Manually intialize client to avoid calling c.getRecords()
c := &Client{}
c.conn = connection.New()
go c.monitorMaster(TestAddresser(fmt.Sprintf(":%d", p)))
addr := fmt.Sprintf(":%d", p)
ch := make(chan string, 1)
ch <- addr
go c.monitorMaster(ch)
c.SetDataset([]string{path})
checkOnePass := func(i int) {
var tasks []Task
for idx := 0; idx < totalTask; idx++ {
......
......@@ -20,7 +20,6 @@ func TestNextRecord(t *testing.T) {
path = "/tmp/master_client_TestFull"
total = 50
)
l, err := net.Listen("tcp", ":0")
if err != nil {
panic(err)
......@@ -31,7 +30,6 @@ func TestNextRecord(t *testing.T) {
if err != nil {
panic(err)
}
go func(l net.Listener) {
s, err := master.NewService(&master.InMemStore{}, 10, time.Second, 1)
if err != nil {
......@@ -63,10 +61,10 @@ func TestNextRecord(t *testing.T) {
}
w.Close()
f.Close()
c := master.NewClient(master.TestAddresser(fmt.Sprintf(":%d", p)), 10)
curAddr := make(chan string, 1)
curAddr <- fmt.Sprintf(":%d", p)
c := master.NewClient(curAddr, 10)
c.SetDataset([]string{path})
for pass := 0; pass < 50; pass++ {
received := make(map[byte]bool)
for i := 0; i < total; i++ {
......
......@@ -142,3 +142,31 @@ func (e *EtcdClient) Load() ([]byte, error) {
state := kvs[0].Value
return state, nil
}
// GetKey gets the value by the specify key.
func GetKey(c *clientv3.Client, key string, timeout int) (string, error) {
ctx, cancel := context.WithTimeout(context.Background(), time.Second*time.Duration(timeout))
resp, err := c.Get(ctx, key)
cancel()
if err != nil {
return "", err
}
kvs := resp.Kvs
if len(kvs) == 0 {
return "", nil
}
v := kvs[0].Value
return string(v), nil
}
// WatchKey watches the specify key and send to valChan if there is some event.
func WatchKey(c *clientv3.Client, key string, valChan chan<- string) {
rch := c.Watch(context.Background(), key)
for wresp := range rch {
for _, ev := range wresp.Events {
// if received event is DELETE, the value will be an empty string
log.Infof("received event %s, %q : %q\n", ev.Type, ev.Kv.Key, ev.Kv.Value)
valChan <- string(ev.Kv.Value)
}
}
}
package pserver
import (
"errors"
"hash/fnv"
"sort"
"time"
......@@ -123,6 +124,9 @@ func (c *Client) FinishInitParams() error {
// SendGrads sends gradients to parameter servers for updating
// parameters.
func (c *Client) SendGrads(grads []Gradient) error {
if len(grads) == 0 {
return errors.New("no gradient received")
}
errCh := make(chan error, len(grads))
for _, g := range grads {
go func(g Gradient) {
......
......@@ -16,7 +16,7 @@ set(API_HEADER
Internal.h)
add_library(paddle_api STATIC ${API_SOURCES})
add_dependencies(paddle_api gen_proto_cpp paddle_trainer_lib)
add_dependencies(paddle_api paddle_proto paddle_trainer_lib)
INCLUDE(${SWIG_USE_FILE})
INCLUDE_DIRECTORIES(${PROJ_ROOT}/paddle)
......
......@@ -26,7 +26,7 @@ target_include_directories(paddle_capi PUBLIC ${CMAKE_CURRENT_BINARY_DIR})
add_style_check_target(paddle_capi ${CAPI_SOURCES} ${CAPI_HEADER}
${CAPI_PRIVATE_HEADER})
add_dependencies(paddle_capi gen_proto_cpp)
add_dependencies(paddle_capi paddle_proto)
# combine all paddle static libraries together, into libpaddle_capi_whole.a
......
......@@ -83,7 +83,7 @@ else()
${CUDA_CXX_SOURCES})
endif()
add_dependencies(paddle_cuda ${external_project_dependencies})
add_dependencies(paddle_cuda paddle_proto ${external_project_dependencies})
add_style_check_target(paddle_cuda
${CUDA_SOURCES}
......
# ddim lib
cc_library(ddim SRCS ddim.cc)
cc_test(ddim_test SRCS ddim_test.cc DEPS ddim)
nv_test(dim_test SRCS dim_test.cu DEPS ddim)
cc_test(variable_test SRCS variable_test.cc)
cc_test(scope_test SRCS scope_test.cc)
cc_test(enforce_test SRCS enforce_test.cc)
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#include <paddle/string/printf.h>
#include <exception>
#include <sstream>
namespace paddle {
namespace framework {
/**
* @brief Enforce exception. Inherits std::exception
*
* All enforce condition not met, will throw an EnforceNotMet exception.
*/
class EnforceNotMet : public std::exception {
public:
EnforceNotMet(const std::string& msg, const char* file, int fileline) {
std::ostringstream sout;
sout << msg << " at [" << file << ":" << fileline << "];";
all_msg_ = sout.str();
}
const char* what() const noexcept override { return all_msg_.c_str(); }
private:
std::string all_msg_;
};
// From https://stackoverflow.com/questions/30130930/
// __buildin_expect is in C++ 11 standard. Since the condition which enforced
// should be true in most situation, it will make the compiler generate faster
// code by adding `UNLIKELY` macro.
#define UNLIKELY(condition) __builtin_expect(static_cast<bool>(condition), 0)
/**
* @brief Throw a EnforceNotMet exception, automatically filled __FILE__ &
* __LINE__
*
* This macro take __VA_ARGS__, user can pass any type if that type can
* serialize to std::ostream
*/
#define PADDLE_THROW(...) \
do { \
throw ::paddle::framework::EnforceNotMet( \
::paddle::string::Sprintf(__VA_ARGS__), __FILE__, __LINE__); \
} while (0)
/**
* @brief Enforce a condition, otherwise throw an EnforceNotMet
*/
#define PADDLE_ENFORCE(condition, ...) \
do { \
if (UNLIKELY(!(condition))) { \
PADDLE_THROW(__VA_ARGS__); \
} \
} while (0)
} // namespace framework
} // namespace paddle
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include <gtest/gtest.h>
#include <paddle/framework/enforce.h>
TEST(ENFORCE, OK) {
PADDLE_ENFORCE(true, "Enforce is ok %d now %f", 123, 0.345);
size_t val = 1;
const size_t limit = 10;
PADDLE_ENFORCE(val < limit, "Enforce is OK too");
}
TEST(ENFORCE, FAILED) {
bool in_catch = false;
try {
PADDLE_ENFORCE(false, "Enforce is not ok %d at all", 123);
} catch (paddle::framework::EnforceNotMet err) {
in_catch = true;
std::string msg = "Enforce is not ok 123 at all";
const char* what = err.what();
for (size_t i = 0; i < msg.length(); ++i) {
ASSERT_EQ(what[i], msg[i]);
}
}
ASSERT_TRUE(in_catch);
}
\ No newline at end of file
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#include <string>
#include <unordered_map>
#include <vector>
#include "paddle/framework/variable.h"
namespace paddle {
namespace framework {
/**
* @brief Scope that manage all variables.
*
* Scope is an association of a name to Variable. All variables belong to
* Scope. You need to specify a scope to run a Net, i.e., `net.Run(&scope)`.
* One net can run in different scopes and update different variable in the
* scope.
*/
class Scope {
public:
/**
* @brief Initialize s Scope without parent.
*/
Scope() {}
/**
* @brief Initialize a Scope with parent.
*/
explicit Scope(const std::shared_ptr<Scope>& parent) : parent_(parent) {}
/**
* @brief Create Variable
*
* Create Variable in this Scope. Return the exist one if Variable already
* been created.
*/
Variable* CreateVariable(const std::string& name) {
auto var = GetVariable(name);
if (var) {
return var;
} else {
vars_[name] = std::unique_ptr<Variable>(new Variable());
return GetVariable(name);
}
}
/**
* @brief Get Variable.
*
* Get Variable from this Scope, this function will recursive find Variable
* from it's parent scope. Return nullptr if not found.
*/
Variable* GetVariable(const std::string& name) const {
auto it = vars_.find(name);
if (it != vars_.end()) {
return it->second.get();
} else if (parent_ != nullptr) {
return parent_->GetVariable(name);
} else {
return nullptr;
}
}
/**
* @brief If this scope has a Var named name.
*
* Find if there is a Variable in this scope and it's parent scope
*/
bool HasVariable(const std::string& name) const {
return (vars_.find(name) != vars_.end() ||
(parent_ && parent_->HasVariable(name)));
}
private:
std::unordered_map<std::string, std::unique_ptr<Variable>> vars_;
std::shared_ptr<Scope> parent_{nullptr};
};
} // namespace framework
} // namespace paddle
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/framework/scope.h"
#include "gtest/gtest.h"
TEST(Scope, Create) {
using paddle::framework::Scope;
using paddle::framework::Variable;
auto scope = std::make_shared<Scope>();
Variable* var0 = scope->CreateVariable("");
EXPECT_NE(var0, nullptr);
/// GetVariable will return nullptr if not exist.
Variable* var1 = scope->GetVariable("a");
EXPECT_EQ(var1, nullptr);
/// CreateVariable will return one.
Variable* var2 = scope->CreateVariable("a");
EXPECT_NE(var2, nullptr);
/// Get the created variable.
Variable* var3 = scope->GetVariable("a");
EXPECT_EQ(var2, var3);
/// CreateVariable will just return the variable if it's
/// already exist.
Variable* var4 = scope->CreateVariable("a");
EXPECT_EQ(var4, var2);
}
TEST(Scope, Parent) {
using paddle::framework::Scope;
using paddle::framework::Variable;
auto parent_scope = std::make_shared<Scope>();
auto scope = std::make_shared<Scope>(parent_scope);
Variable* var0 = parent_scope->CreateVariable("a");
EXPECT_NE(var0, nullptr);
/// GetVariable will get Variable from parent scope if exist.
Variable* var1 = scope->GetVariable("a");
EXPECT_EQ(var0, var1);
}
......@@ -12,7 +12,7 @@ endif()
add_library(paddle_function STATIC ${cpp_files} ${cu_objs})
add_dependencies(paddle_function ${external_project_dependencies})
add_dependencies(paddle_function gen_proto_cpp)
add_dependencies(paddle_function paddle_proto)
if(WITH_TESTING)
if(WITH_GPU)
......
......@@ -58,7 +58,7 @@ endif()
add_style_check_target(paddle_gserver ${GSERVER_SOURCES})
add_style_check_target(paddle_gserver ${GSERVER_HEADER})
add_dependencies(paddle_gserver gen_proto_cpp)
add_dependencies(paddle_gserver paddle_proto ${external_project_dependencies})
if(WITH_TESTING)
add_subdirectory(tests)
endif()
......@@ -33,7 +33,7 @@ endif()
add_style_check_target(paddle_math ${MATH_SOURCES})
add_style_check_target(paddle_math ${MATH_HEADERS})
add_dependencies(paddle_math gen_proto_cpp) # depends
add_dependencies(paddle_math paddle_proto ${external_project_dependencies}) # depends
if(WITH_TESTING)
add_subdirectory(tests)
endif()
......@@ -10,7 +10,7 @@ set(OPITMIZER_SRCS
)
add_library(paddle_optimizer STATIC ${OPITMIZER_SRCS})
add_dependencies(paddle_optimizer gen_proto_cpp)
add_dependencies(paddle_optimizer paddle_proto ${external_project_dependencies})
if(WITH_TESTING)
add_simple_unittest(serialization_test)
......
......@@ -7,7 +7,7 @@ add_library(paddle_parameter STATIC
${PARAMETERS_SOURCES})
add_style_check_target(paddle_parameter ${PARAMETERS_SOURCES})
add_style_check_target(paddle_parameter ${PARAMETERS_HEADERS})
add_dependencies(paddle_parameter gen_proto_cpp)
add_dependencies(paddle_parameter paddle_proto ${external_project_dependencies})
if(WITH_TESTING)
add_subdirectory(tests)
endif()
......@@ -17,7 +17,7 @@ add_library(paddle_network STATIC
add_style_check_target(paddle_network ${NETWORK_SOURCES})
add_style_check_target(paddle_network ${NETWORK_HEADERS})
add_dependencies(paddle_network gen_proto_cpp)
add_dependencies(paddle_network paddle_proto ${external_project_dependencies})
################### paddle_pserver ######################
set(PSERVER_SOURCES
......@@ -40,7 +40,7 @@ add_library(paddle_pserver STATIC
add_style_check_target(paddle_pserver ${PSERVER_SOURCES})
add_style_check_target(paddle_pserver ${PSERVER_HEADERS})
add_dependencies(paddle_pserver gen_proto_cpp)
add_dependencies(paddle_pserver paddle_proto ${external_project_dependencies})
set(PSERVER_MAIN_SOURCES
ParameterServer2Main.cpp)
......
......@@ -144,7 +144,7 @@ class DenseScanner(IScanner):
if len(self.__shape__) > 1:
# The last-two dimenstions are the frame height and width.
# For example, the layout is CHW for 3-D feature of image.
# The H and W are the fram height and width.
# The H and W are the frame height and width.
h, w = self.__shape__[-2:]
argument.setSlotFrameHeight(self.pos, h)
argument.setSlotFrameWidth(self.pos, w)
......
cc_library(stringpiece SRCS piece.cc)
cc_test(stringpiece_test SRCS piece_test.cc DEPS stringpiece glog gflags)
cc_test(stringprintf_test SRCS printf_test.cc DEPS glog gflags)
/*
Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
// Compared with std::stringstream, there are primary purpose of
// string::Printf:
//
// 1. Type-safe printing, with why and how explained in
// http://www.drdobbs.com/stringprintf-a-typesafe-printf-family-fo/184401999.
// Implementation includes
//
// https://github.com/c42f/tinyformat
// boost::format
// std::stringstream
//
// std::stringstream is not convenient enough in many cases. For example:
//
// std::cout << std::setprecision(2) << std::fixed << 1.23456 << "\n";
//
// boost::format is the most convenient one. We can have
//
// std::cout << format("%2% %1%") % 36 % 77;
//
// or
//
// format fmter("%2% %1%");
// fmter % 36; fmter % 77;
// std::cout << fmter.c_str();
//
// But the overloading of % might be overkilling and it would be
// more efficient if it can write to std::cout directly.
//
// tinyformat has an interface compatible with the C-printf style,
// and it can writes to a stream or returns a std::string:
//
// std::cout << tfm::printf(
// "%s, %s %d, %.2d:%.2d\n",
// weekday, month, day, hour, min);
//
// or
//
// tfm::format(std::cout,
// "%s, %s %d, %.2d:%.2d\n",
// weekday, month, day, hour, min);
//
// 2. High-performance -- most printed strings are not too long and
// doens't need dynamic memory allocation. Many StringPrintf
// implementations doesn't enforce type-safe, but are
// high-performance, including
//
// https://developers.google.com/optimization/reference/base/stringprintf/
// https://github.com/adobe/chromium/blob/master/base/stringprintf.h
// https://github.com/google/protobuf/blob/master/src/google/protobuf/stubs/stringprintf.h
//
// According to
// https://github.com/c42f/tinyformat#compile-time-and-code-bloat,
// boost::format runs too slow and results in large executable binary
// files. So here we port tinyformat.
#pragma once
#include <iostream>
#include <sstream>
#include "paddle/string/tinyformat/tinyformat.h" // https://github.com/c42f/tinyformat
namespace paddle {
namespace string {
template <typename... Args>
void Fprintf(std::ostream& out, const char* fmt, const Args&... args) {
tinyformat::vformat(out, fmt, tinyformat::makeFormatList(args...));
}
template <typename... Args>
std::string Sprintf(const char* fmt, const Args&... args) {
std::ostringstream oss;
Fprintf(oss, fmt, args...);
return oss.str();
}
template <typename... Args>
void Printf(const char* fmt, const Args&... args) {
Fprintf(std::cout, fmt, args...);
}
} // namespace string
} // namespace paddle
#include "paddle/string/printf.h"
#include <string>
#include "gtest/gtest.h"
TEST(StringPrintf, StringPrintf) {
std::string weekday = "Wednesday";
const char* month = "July";
size_t day = 27;
long hour = 14;
int min = 44;
EXPECT_EQ(std::string("Wednesday, July 27, 14:44"),
paddle::string::Sprintf(
"%s, %s %d, %.2d:%.2d", weekday, month, day, hour, min));
}
此差异已折叠。
......@@ -2,7 +2,7 @@
if(WITH_TESTING)
add_library(paddle_test_main STATIC TestMain.cpp)
add_dependencies(paddle_test_main gen_proto_cpp)
add_dependencies(paddle_test_main paddle_proto ${external_project_dependencies})
add_library(paddle_test_util STATIC TestUtil.cpp)
add_dependencies(paddle_test_util gen_proto_cpp)
add_dependencies(paddle_test_util paddle_proto ${external_project_dependencies})
endif()
......@@ -41,7 +41,8 @@ add_style_check_target(paddle_trainer_lib
add_style_check_target(paddle_trainer_lib
${TRAINER_HEADERS})
add_dependencies(paddle_trainer_lib
gen_proto_cpp)
paddle_proto
${external_project_dependencies})
macro(add_paddle_exe TARGET_NAME)
add_executable(${TARGET_NAME} ${ARGN})
......
......@@ -17,7 +17,7 @@ add_library(paddle_utils STATIC
add_style_check_target(paddle_utils ${UTIL_HEADERS})
add_style_check_target(paddle_utils ${UTIL_SOURCES}
${UTIL_ARCH_SOURCES})
add_dependencies(paddle_utils gen_proto_cpp)
add_dependencies(paddle_utils paddle_proto ${external_project_dependencies})
if(WITH_TESTING)
add_subdirectory(tests)
endif()
set(proto_filenames
DataConfig.proto
DataFormat.proto
ModelConfig.proto
ParameterConfig.proto
ParameterService.proto
TrainerConfig.proto
OptimizerConfig.proto
ParameterServerConfig.proto)
file(GLOB proto_filenames . *.proto)
include_directories(${CMAKE_CURRENT_BINARY_DIR})
proto_library(paddle_proto SRCS ${proto_filenames})
set(PROTO_GEN)
set(PROTO_GEN_PY)
foreach(filename ${proto_filenames})
get_filename_component(base_filename ${filename} NAME_WE)
set(CUR_PROTO_GEN
${CMAKE_CURRENT_BINARY_DIR}/${base_filename}.pb.h
${CMAKE_CURRENT_BINARY_DIR}/${base_filename}.pb.cc)
set(PROTO_GEN
${PROTO_GEN}
${CUR_PROTO_GEN})
add_custom_command(OUTPUT ${CUR_PROTO_GEN}
COMMAND env ${py_env} ${PROTOBUF_PROTOC_EXECUTABLE}
--cpp_out ${CMAKE_CURRENT_BINARY_DIR}
--proto_path ${PROJ_ROOT}/proto ${PROJ_ROOT}/proto/${filename}
DEPENDS ${filename} ${external_project_dependencies})
get_filename_component(ABS_FIL ${filename} ABSOLUTE)
get_filename_component(FIL_WE ${filename} NAME_WE)
set(CUR_PROTO_GEN_PY
${PROJ_ROOT}/paddle/python/paddle/proto/${base_filename}_pb2.py)
${PROJ_ROOT}/paddle/python/paddle/proto/${FIL_WE}_pb2.py)
set(PROTO_GEN_PY
${CUR_PROTO_GEN_PY}
${PROTO_GEN_PY})
add_custom_command(OUTPUT ${CUR_PROTO_GEN_PY}
COMMAND env ${py_env} ${PROTOBUF_PROTOC_EXECUTABLE} --python_out ${PROJ_ROOT}/python/paddle/proto
--proto_path ${PROJ_ROOT}/proto ${PROJ_ROOT}/proto/${filename}
DEPENDS ${filename} ${external_project_dependencies})
COMMAND ${PROTOBUF_PROTOC_EXECUTABLE}
ARGS "--python_out=${PROJ_ROOT}/python/paddle/proto"
"-I" ${CMAKE_CURRENT_SOURCE_DIR} ${ABS_FIL}
DEPENDS ${ABS_FIL} ${external_project_dependencies})
endforeach()
add_custom_target(gen_proto_cpp ALL DEPENDS ${PROTO_GEN})
add_custom_target(gen_proto_py ALL DEPENDS ${PROTO_GEN_PY})
add_library(paddle_proto STATIC ${PROTO_GEN})
target_include_directories(paddle_proto PUBLIC ${CMAKE_CURRENT_BINARY_DIR})
......@@ -1149,10 +1149,10 @@ def pooling_layer(input,
@layer_support(DROPOUT)
def lstmemory(input,
name=None,
size=None,
reverse=False,
act=None,
gate_act=None,
size=None,
state_act=None,
bias_attr=None,
param_attr=None,
......@@ -1194,6 +1194,8 @@ def lstmemory(input,
:param name: The lstmemory layer name.
:type name: basestring
:param size: DEPRECATED. size of the lstm cell
:type size: int
:param input: input layer name.
:type input: LayerOutput
:param reverse: is sequence process reversed or not.
......@@ -1220,15 +1222,15 @@ def lstmemory(input,
assert state_act.support_hppl
assert act.support_hppl
assert input.size is not None and input.size % 4 == 0
if size is not None:
if input.size / 4 == size:
plog = logger.warning
else:
plog = logger.fatal
plog("NOTE: The lstmemory layer[%s]'s size is set by previous input "
"layer. The lstm size should be equal with input layer size/4. The"
" size which is set explicitly will be ignored." % name)
plog("size of lstmemory layer: %s is automatically set to "
"size of input layer / 4. The parameter size passing to "
"this layer is ignored." % (name))
Layer(
name=name,
......@@ -1255,11 +1257,11 @@ def lstmemory(input,
@wrap_name_default("gru")
@layer_support(DROPOUT)
def grumemory(input,
size=None,
name=None,
reverse=False,
act=None,
gate_act=None,
size=None,
bias_attr=None,
param_attr=None,
layer_attr=None):
......@@ -1318,6 +1320,8 @@ def grumemory(input,
:type name: None|basestring
:param input: input layer.
:type input: LayerOutput.
:param size: DEPRECATED. size of the gru cell
:type size: int
:param reverse: Whether sequence process is reversed or not.
:type reverse: bool
:param act: activation type, TanhActivation by default. This activation
......@@ -1334,9 +1338,6 @@ def grumemory(input,
:type param_attr: ParameterAttribute|None|False
:param layer_attr: Extra Layer attribute
:type layer_attr: ExtraLayerAttribute|None
:param size: Stub parameter of size, but actually not used. If set this size
will get a warning.
:type size: None
:return: LayerOutput object.
:rtype: LayerOutput
"""
......@@ -1348,9 +1349,9 @@ def grumemory(input,
plog = logger.warning
else:
plog = logger.fatal
plog("NOTE: the gru memory layer's size is set by previous input layer,"
" and should be input size / 3. Set size explicitly will be "
"ignored.")
plog("size of grumemory layer: %s is automatically set to "
"size of input layer / 3. The parameter size passing to this "
"layer is ignored." % (name))
Layer(
name=name,
......@@ -2524,8 +2525,8 @@ def img_cmrnorm_layer(input,
@wrap_bias_attr_default()
@wrap_param_attr_default(default_factory=lambda _: ParamAttr(initial_mean=1.0,
initial_std=0.))
@wrap_param_attr_default(
default_factory=lambda _: ParamAttr(initial_mean=1.0, initial_std=0.))
@wrap_act_default(act=ReluActivation())
@wrap_name_default("batch_norm")
@layer_support(DROPOUT)
......@@ -3013,25 +3014,25 @@ def lstm_step_layer(input,
bias_attr=None,
layer_attr=None):
"""
LSTM Step Layer. It used in recurrent_group. The lstm equations are shown
as follow.
LSTM Step Layer. This function is used only in recurrent_group.
The lstm equations are shown as follows.
.. math::
i_t & = \\sigma(W_{xi}x_{t} + W_{hi}h_{t-1} + W_{ci}c_{t-1} + b_i)
i_t & = \\sigma(W_{x_i}x_{t} + W_{h_i}h_{t-1} + W_{c_i}c_{t-1} + b_i)
f_t & = \\sigma(W_{xf}x_{t} + W_{hf}h_{t-1} + W_{cf}c_{t-1} + b_f)
f_t & = \\sigma(W_{x_f}x_{t} + W_{h_f}h_{t-1} + W_{c_f}c_{t-1} + b_f)
c_t & = f_tc_{t-1} + i_t tanh (W_{xc}x_t+W_{hc}h_{t-1} + b_c)
c_t & = f_tc_{t-1} + i_t tanh (W_{x_c}x_t+W_{h_c}h_{t-1} + b_c)
o_t & = \\sigma(W_{xo}x_{t} + W_{ho}h_{t-1} + W_{co}c_t + b_o)
o_t & = \\sigma(W_{x_o}x_{t} + W_{h_o}h_{t-1} + W_{c_o}c_t + b_o)
h_t & = o_t tanh(c_t)
The input of lstm step is :math:`Wx_t + Wh_{t-1}`, and user should use
:code:`mixed_layer` and :code:`full_matrix_projection` to calculate these
input vector.
input vectors.
The state of lstm step is :math:`c_{t-1}`. And lstm step layer will do
......@@ -3042,14 +3043,14 @@ def lstm_step_layer(input,
...
This layer contains two outputs. Default output is :math:`h_t`. The other
output is :math:`o_t`, which name is 'state' and can use
This layer has two outputs. Default output is :math:`h_t`. The other
output is :math:`o_t`, whose name is 'state' and can use
:code:`get_output_layer` to extract this output.
:param name: Layer's name.
:type name: basestring
:param size: Layer's size. NOTE: lstm layer's size, should be equal as
:code:`input.size/4`, and should be equal as
:param size: Layer's size. NOTE: lstm layer's size, should be equal to
:code:`input.size/4`, and should be equal to
:code:`state.size`.
:type size: int
:param input: input layer. :math:`Wx_t + Wh_{t-1}`
......
......@@ -614,6 +614,7 @@ def simple_lstm(input,
@wrap_name_default('lstm_unit')
def lstmemory_unit(input,
memory_boot=None,
name=None,
size=None,
param_attr=None,
......@@ -626,9 +627,9 @@ def lstmemory_unit(input,
lstm_layer_attr=None,
get_output_layer_attr=None):
"""
Define calculations that a LSTM unit performs in a single time step.
This function itself is not a recurrent layer, so that it can not be
directly applied to sequence input. This function is always used in
Define calculations that a LSTM unit performs during a single time step.
This function itself is not a recurrent layer, so it can not be
directly used to process sequence inputs. This function is always used in
recurrent_group (see layers.py for more details) to implement attention
mechanism.
......@@ -638,13 +639,13 @@ def lstmemory_unit(input,
.. math::
i_t & = \\sigma(W_{xi}x_{t} + W_{hi}h_{t-1} + W_{ci}c_{t-1} + b_i)
i_t & = \\sigma(W_{x_i}x_{t} + W_{h_i}h_{t-1} + W_{c_i}c_{t-1} + b_i)
f_t & = \\sigma(W_{xf}x_{t} + W_{hf}h_{t-1} + W_{cf}c_{t-1} + b_f)
f_t & = \\sigma(W_{x_f}x_{t} + W_{h_f}h_{t-1} + W_{c_f}c_{t-1} + b_f)
c_t & = f_tc_{t-1} + i_t tanh (W_{xc}x_t+W_{hc}h_{t-1} + b_c)
c_t & = f_tc_{t-1} + i_t tanh (W_{x_c}x_t+W_{h_c}h_{t-1} + b_c)
o_t & = \\sigma(W_{xo}x_{t} + W_{ho}h_{t-1} + W_{co}c_t + b_o)
o_t & = \\sigma(W_{x_o}x_{t} + W_{h_o}h_{t-1} + W_{c_o}c_t + b_o)
h_t & = o_t tanh(c_t)
......@@ -661,6 +662,8 @@ def lstmemory_unit(input,
:param input: input layer name.
:type input: LayerOutput
:param memory_boot: the initialization state of the LSTM cell.
:type memory_boot: LayerOutput | None
:param name: lstmemory unit name.
:type name: basestring
:param size: lstmemory unit size.
......@@ -692,7 +695,8 @@ def lstmemory_unit(input,
assert input.size % 4 == 0
size = input.size / 4
out_mem = memory(name=name, size=size)
state_mem = memory(name="%s_state" % name, size=size)
state_mem = memory(
name="%s_state" % name, size=size, boot_layer=memory_boot)
with mixed_layer(
name="%s_input_recurrent" % name,
......@@ -726,6 +730,7 @@ def lstmemory_unit(input,
def lstmemory_group(input,
size=None,
name=None,
memory_boot=None,
reverse=False,
param_attr=None,
act=None,
......@@ -737,7 +742,7 @@ def lstmemory_group(input,
lstm_layer_attr=None,
get_output_layer_attr=None):
"""
lstm_group is a recurrent layer group version of Long Short Term Memory. It
lstm_group is a recurrent_group version of Long Short Term Memory. It
does exactly the same calculation as the lstmemory layer (see lstmemory in
layers.py for the maths) does. A promising benefit is that LSTM memory
cell states, or hidden states in every time step are accessible to the
......@@ -748,8 +753,8 @@ def lstmemory_group(input,
NOTE: In PaddlePaddle's implementation, the following input-to-hidden
multiplications:
:math:`W_{xi}x_{t}` , :math:`W_{xf}x_{t}`,
:math:`W_{xc}x_t`, :math:`W_{xo}x_{t}` are not done in lstmemory_unit to
:math:`W_{x_i}x_{t}` , :math:`W_{x_f}x_{t}`,
:math:`W_{x_c}x_t`, :math:`W_{x_o}x_{t}` are not done in lstmemory_unit to
speed up the calculations. Consequently, an additional mixed_layer with
full_matrix_projection must be included before lstmemory_unit is called.
......@@ -765,10 +770,12 @@ def lstmemory_group(input,
:param input: input layer name.
:type input: LayerOutput
:param name: lstmemory group name.
:type name: basestring
:param size: lstmemory group size.
:type size: int
:param name: name of the lstmemory group.
:type name: basestring
:param memory_boot: the initialization state of LSTM cell.
:type memory_boot: LayerOutput | None
:param reverse: is lstm reversed
:type reverse: bool
:param param_attr: Parameter config, None if use default.
......@@ -798,6 +805,7 @@ def lstmemory_group(input,
def __lstm_step__(ipt):
return lstmemory_unit(
input=ipt,
memory_boot=memory_boot,
name=name,
size=size,
mixed_bias_attr=mixed_bias_attr,
......@@ -819,6 +827,7 @@ def lstmemory_group(input,
@wrap_name_default('gru_unit')
def gru_unit(input,
memory_boot=None,
size=None,
name=None,
gru_bias_attr=None,
......@@ -829,8 +838,8 @@ def gru_unit(input,
naive=False):
"""
Define calculations that a gated recurrent unit performs in a single time
step. This function itself is not a recurrent layer, so that it can not be
directly applied to sequence input. This function is almost always used in
step. This function itself is not a recurrent layer, so it can not be
directly used to process sequence inputs. This function is always used in
the recurrent_group (see layers.py for more details) to implement attention
mechanism.
......@@ -838,6 +847,8 @@ def gru_unit(input,
:param input: input layer name.
:type input: LayerOutput
:param memory_boot: the initialization state of the LSTM cell.
:type memory_boot: LayerOutput | None
:param name: name of the gru group.
:type name: basestring
:param size: hidden size of the gru.
......@@ -856,7 +867,7 @@ def gru_unit(input,
if size is None:
size = input.size / 3
out_mem = memory(name=name, size=size)
out_mem = memory(name=name, size=size, boot_layer=memory_boot)
if naive:
__step__ = gru_step_naive_layer
......@@ -878,6 +889,7 @@ def gru_unit(input,
@wrap_name_default('gru_group')
def gru_group(input,
memory_boot=None,
size=None,
name=None,
reverse=False,
......@@ -888,7 +900,7 @@ def gru_group(input,
gru_layer_attr=None,
naive=False):
"""
gru_group is a recurrent layer group version of Gated Recurrent Unit. It
gru_group is a recurrent_group version of Gated Recurrent Unit. It
does exactly the same calculation as the grumemory layer does. A promising
benefit is that gru hidden states are accessible to the user. This is
especially useful in attention model. If you do not need to access
......@@ -908,6 +920,8 @@ def gru_group(input,
:param input: input layer name.
:type input: LayerOutput
:param memory_boot: the initialization state of the LSTM cell.
:type memory_boot: LayerOutput | None
:param name: name of the gru group.
:type name: basestring
:param size: hidden size of the gru.
......@@ -929,6 +943,7 @@ def gru_group(input,
def __gru_step__(ipt):
return gru_unit(
input=ipt,
memory_boot=memory_boot,
name=name,
size=size,
gru_bias_attr=gru_bias_attr,
......@@ -1083,7 +1098,6 @@ def simple_gru2(input,
return grumemory(
name=name,
size=size,
input=m,
reverse=reverse,
bias_attr=gru_bias_attr,
......
......@@ -25,8 +25,9 @@ import uci_housing
import sentiment
import wmt14
import mq2007
import flowers
__all__ = [
'mnist', 'imikolov', 'imdb', 'cifar', 'movielens', 'conll05', 'sentiment'
'uci_housing', 'wmt14', 'mq2007'
'uci_housing', 'wmt14', 'mq2007', 'flowers'
]
......@@ -34,9 +34,9 @@ from common import download
import tarfile
import scipy.io as scio
from paddle.v2.image import *
from paddle.v2.reader import *
import os
import numpy as np
import paddle.v2 as paddle
from multiprocessing import cpu_count
__all__ = ['train', 'test', 'valid']
......@@ -46,6 +46,12 @@ SETID_URL = 'http://www.robots.ox.ac.uk/~vgg/data/flowers/102/setid.mat'
DATA_MD5 = '52808999861908f626f3c1f4e79d11fa'
LABEL_MD5 = 'e0620be6f572b9609742df49c70aed4d'
SETID_MD5 = 'a5357ecc9cb78c4bef273ce3793fc85c'
# In official 'readme', tstid is the flag of test data
# and trnid is the flag of train data. But test data is more than train data.
# So we exchange the train data and test data.
TRAIN_FLAG = 'tstid'
TEST_FLAG = 'trnid'
VALID_FLAG = 'valid'
def default_mapper(sample):
......@@ -53,8 +59,8 @@ def default_mapper(sample):
map image bytes data to type needed by model input layer
'''
img, label = sample
img = paddle.image.load_image_bytes(img)
img = paddle.image.simple_transform(img, 256, 224, True)
img = load_image_bytes(img)
img = simple_transform(img, 256, 224, True)
return img.flatten().astype('float32'), label
......@@ -63,7 +69,8 @@ def reader_creator(data_file,
setid_file,
dataset_name,
mapper=default_mapper,
buffered_size=1024):
buffered_size=1024,
use_xmap=True):
'''
1. read images from tar file and
merge images into batch files in 102flowers.tgz_batch/
......@@ -105,11 +112,13 @@ def reader_creator(data_file,
for sample, label in itertools.izip(data, batch['label']):
yield sample, int(label)
return paddle.reader.xmap_readers(mapper, reader,
cpu_count(), buffered_size)
if use_xmap:
return xmap_readers(mapper, reader, cpu_count(), buffered_size)
else:
return map_readers(mapper, reader)
def train(mapper=default_mapper, buffered_size=1024):
def train(mapper=default_mapper, buffered_size=1024, use_xmap=True):
'''
Create flowers training set reader.
It returns a reader, each sample in the reader is
......@@ -128,11 +137,11 @@ def train(mapper=default_mapper, buffered_size=1024):
return reader_creator(
download(DATA_URL, 'flowers', DATA_MD5),
download(LABEL_URL, 'flowers', LABEL_MD5),
download(SETID_URL, 'flowers', SETID_MD5), 'trnid', mapper,
buffered_size)
download(SETID_URL, 'flowers', SETID_MD5), TRAIN_FLAG, mapper,
buffered_size, use_xmap)
def test(mapper=default_mapper, buffered_size=1024):
def test(mapper=default_mapper, buffered_size=1024, use_xmap=True):
'''
Create flowers test set reader.
It returns a reader, each sample in the reader is
......@@ -151,11 +160,11 @@ def test(mapper=default_mapper, buffered_size=1024):
return reader_creator(
download(DATA_URL, 'flowers', DATA_MD5),
download(LABEL_URL, 'flowers', LABEL_MD5),
download(SETID_URL, 'flowers', SETID_MD5), 'tstid', mapper,
buffered_size)
download(SETID_URL, 'flowers', SETID_MD5), TEST_FLAG, mapper,
buffered_size, use_xmap)
def valid(mapper=default_mapper, buffered_size=1024):
def valid(mapper=default_mapper, buffered_size=1024, use_xmap=True):
'''
Create flowers validation set reader.
It returns a reader, each sample in the reader is
......@@ -174,8 +183,8 @@ def valid(mapper=default_mapper, buffered_size=1024):
return reader_creator(
download(DATA_URL, 'flowers', DATA_MD5),
download(LABEL_URL, 'flowers', LABEL_MD5),
download(SETID_URL, 'flowers', SETID_MD5), 'valid', mapper,
buffered_size)
download(SETID_URL, 'flowers', SETID_MD5), VALID_FLAG, mapper,
buffered_size, use_xmap)
def fetch():
......
......@@ -31,13 +31,13 @@ class TestFlowers(unittest.TestCase):
def test_train(self):
instances, max_label_value = self.check_reader(
paddle.v2.dataset.flowers.train())
self.assertEqual(instances, 1020)
self.assertEqual(instances, 6149)
self.assertEqual(max_label_value, 102)
def test_test(self):
instances, max_label_value = self.check_reader(
paddle.v2.dataset.flowers.test())
self.assertEqual(instances, 6149)
self.assertEqual(instances, 1020)
self.assertEqual(max_label_value, 102)
def test_valid(self):
......
......@@ -51,7 +51,7 @@ class Parameters(object):
def __init__(self):
self.__param_conf__ = dict()
self.__gradient_machines__ = []
self.__tmp_params__ = []
self.__tmp_params__ = dict()
def __append_config__(self, param_conf):
"""
......@@ -128,12 +128,9 @@ class Parameters(object):
if len(self.__gradient_machines__) == 0:
# create new parameter in python numpy.
if len(self.__tmp_params__) != 0:
ret_list = [
mat for name, mat in self.__tmp_params__ if name == key
]
if len(ret_list) == 1:
return ret_list[0]
if key in self.__tmp_params__:
return self.__tmp_params__[key]
else:
return np.ndarray(shape=shape, dtype=np.float32)
else:
for each_gradient_machine in self.__gradient_machines__:
......@@ -187,7 +184,7 @@ class Parameters(object):
(shape, value.shape))
if len(self.__gradient_machines__) == 0:
self.__tmp_params__.append((key, value))
self.__tmp_params__[key] = value
else:
for each_gradient_machine in self.__gradient_machines__:
__copy_parameter_to_gradient_machine__(each_gradient_machine,
......@@ -231,7 +228,7 @@ class Parameters(object):
raise ValueError("gradient_machine should be api.GradientMachine")
if len(self.__tmp_params__) != 0:
for name, val in self.__tmp_params__:
for name, val in self.__tmp_params__.iteritems():
try:
__copy_parameter_to_gradient_machine__(gradient_machine,
name, val)
......@@ -287,6 +284,18 @@ class Parameters(object):
@staticmethod
def from_tar(f):
"""
Create a `Parameters` object from the given file. And
the `Parameters` only contains the parameters in this
file. It is adapted the parameters are same in the
defined network and the given file. For example, it
can be used in the inference.
:param f: the initialized model file.
:type f: tar file
:return: A Parameters object.
:rtype: Parameters.
"""
params = Parameters()
tar = tarfile.TarFile(fileobj=f, mode='r')
for finfo in tar:
......@@ -302,6 +311,21 @@ class Parameters(object):
params.deserialize(param_name, f)
return params
def init_from_tar(self, f):
"""
Different from `from_tar`, this interface can be used to
init partial network parameters from another saved model.
:param f: the initialized model file.
:type f: tar file
:return: Nothing.
"""
tar_param = Parameters.from_tar(f)
for pname in tar_param.names():
if pname in self.names():
self.set(pname, tar_param.get(pname))
def __get_parameter_in_gradient_machine__(gradient_machine, name):
"""
......
......@@ -248,9 +248,6 @@ def xmap_readers(mapper, reader, process_num, buffer_size, order=False):
:rtype: callable
"""
end = XmapEndSignal()
in_queue = Queue(buffer_size)
out_queue = Queue(buffer_size)
out_order = [0]
# define a worker to read samples from reader to in_queue
def read_worker(reader, in_queue):
......@@ -266,12 +263,6 @@ def xmap_readers(mapper, reader, process_num, buffer_size, order=False):
in_order += 1
in_queue.put(end)
# start a read worker in a thread
target = order_read_worker if order else read_worker
t = Thread(target=target, args=(reader, in_queue))
t.daemon = True
t.start()
# define a worker to handle samples from in_queue by mapper
# and put mapped samples into out_queue
def handle_worker(in_queue, out_queue, mapper):
......@@ -298,6 +289,15 @@ def xmap_readers(mapper, reader, process_num, buffer_size, order=False):
in_queue.put(end)
out_queue.put(end)
def xreader():
in_queue = Queue(buffer_size)
out_queue = Queue(buffer_size)
out_order = [0]
# start a read worker in a thread
target = order_read_worker if order else read_worker
t = Thread(target=target, args=(reader, in_queue))
t.daemon = True
t.start()
# start several handle_workers
target = order_handle_worker if order else handle_worker
args = (in_queue, out_queue, mapper, out_order) if order else (
......@@ -310,7 +310,6 @@ def xmap_readers(mapper, reader, process_num, buffer_size, order=False):
for w in workers:
w.start()
def xreader():
sample = out_queue.get()
while not isinstance(sample, XmapEndSignal):
yield sample
......
......@@ -132,10 +132,12 @@ class TestXmap(unittest.TestCase):
for order in orders:
for tNum in thread_nums:
for size in buffered_size:
result = []
for i in paddle.v2.reader.xmap_readers(mapper,
reader = paddle.v2.reader.xmap_readers(mapper,
reader_creator_10(0),
tNum, size, order)():
tNum, size, order)
for n in xrange(3):
result = []
for i in reader():
result.append(i)
if not order:
result.sort()
......
......@@ -20,14 +20,17 @@ import cStringIO
import numpy
def __rand_param_config__(name):
def __rand_param_config__(name, psize=None):
conf = ParameterConfig()
conf.name = name
size = 1
if psize is None:
for i in xrange(2):
dim = random.randint(1, 1000)
conf.dims.append(dim)
size *= dim
else:
size = psize
conf.size = size
assert conf.IsInitialized()
return conf
......@@ -77,6 +80,50 @@ class TestParameters(unittest.TestCase):
expected = numpy.array([[1, 1], [1, 2], [1, 1]], numpy.float32)
assert numpy.logical_and.reduce(numpy.reshape(val == expected, 6))
def test_init_from_tar(self):
def get_param(names, size):
p = parameters.Parameters()
for k, v in zip(names, size):
p.__append_config__(__rand_param_config__(k, v))
for name in p.names():
param = p.get(name)
param[:] = numpy.random.uniform(
-1.0, 1.0, size=p.get_shape(name))
p.set(name, param)
return p
def get_parames():
name1 = ['param_0', 'param_1']
size1 = [128, 256]
p1 = get_param(name1, size1)
file1 = cStringIO.StringIO()
p1.to_tar(file1)
file1.seek(0)
name2 = ['param_0', 'param_1', 'param_2']
size2 = [128, 256, 288]
p2 = get_param(name2, size2)
file2 = cStringIO.StringIO()
p2.to_tar(file2)
file2.seek(0)
return p1, file1, p2, file2
p1, file1, p2, file2 = get_parames()
p2.init_from_tar(file1)
for name in p1.names():
self.assertEqual(p1.get_shape(name), p2.get_shape(name))
v1 = p1.get(name)
v2 = p2.get(name)
self.assertTrue(numpy.isclose(v1, v2).all())
p1, file1, p2, file2 = get_parames()
p1.init_from_tar(file2)
for name in p1.names():
self.assertEqual(p1.get_shape(name), p2.get_shape(name))
v1 = p1.get(name)
v2 = p2.get(name)
self.assertTrue(numpy.isclose(v1, v2).all())
if __name__ == '__main__':
unittest.main()
......@@ -15,7 +15,8 @@ setup_requires=["requests",
"protobuf==3.1",
"recordio",
"matplotlib",
"rarfile"]
"rarfile",
"scipy>=0.19.0"]
if '${CMAKE_SYSTEM_PROCESSOR}' not in ['arm', 'armv7-a', 'aarch64']:
setup_requires+=["opencv-python"]
......
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