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From wan...@apache.org
Subject [19/60] incubator-singa git commit: SINGA-163 - Reorganize the project folder layout
Date Fri, 03 Jun 2016 07:48:24 GMT
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/dd1e4afa/examples/alexnet/Makefile.example
----------------------------------------------------------------------
diff --git a/examples/alexnet/Makefile.example b/examples/alexnet/Makefile.example
deleted file mode 100644
index f895146..0000000
--- a/examples/alexnet/Makefile.example
+++ /dev/null
@@ -1,29 +0,0 @@
-#/**
-# * Licensed to the Apache Software Foundation (ASF) under one
-# * or more contributor license agreements.  See the NOTICE file
-# * distributed with this work for additional information
-# * regarding copyright ownership.  The ASF licenses this file
-# * to you 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.
-# */
-
-libs :=singa glog protobuf
-
-.PHONY: all create
-
-create:
-	$(CXX) im2rec.cc `pkg-config opencv --cflags --libs` -std=c++11 -lsinga -lprotobuf -lglog \
-		-I../../include -L../../.libs/ -Wl,-unresolved-symbols=ignore-in-shared-libs \
-		-Wl,-rpath=../../.libs/  -o im2rec.bin
-	$(CXX) rec2im_test.cc `pkg-config opencv --cflags --libs` -std=c++11 -lsinga -lprotobuf -lglog \
-		-I../../include -L../../.libs/ -Wl,-unresolved-symbols=ignore-in-shared-libs \
-		-Wl,-rpath=../../.libs/  -o rec2im_test.bin

http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/dd1e4afa/examples/alexnet/cudnn.conf
----------------------------------------------------------------------
diff --git a/examples/alexnet/cudnn.conf b/examples/alexnet/cudnn.conf
deleted file mode 100644
index e8d14c6..0000000
--- a/examples/alexnet/cudnn.conf
+++ /dev/null
@@ -1,448 +0,0 @@
-name: "alexnet"
-train_steps: 450000
-test_steps: 500
-test_freq: 1000
-disp_freq: 20
-checkpoint_freq: 100000
-checkpoint_after: 100000
-gpu: 0
-#debug: true
-#checkpoint_path: "examples/alexnet/checkpoint/step10000-worker0"
-train_one_batch {
-  alg: kBP
-}
-updater{
-  type: kSGD
-  weight_decay: 0.0005
-  momentum: 0.9
-  learning_rate {
-    type: kStep
-    base_lr: 0.01
-    step_conf {
-      gamma: 0.1
-      change_freq: 100000
-    }
-  }
-}
-neuralnet {
-  layer{
-    name: "data"
-    type: kRecordInput
-    store_conf {
-      backend: "kvfile"
-      path :"/data/dataset/imagenet/train_record.bin"
-      mean_file: "/data/dataset/imagenet/image_mean.bin"
-      batchsize: 256
-      #random_skip: 1000
-      shape: 3
-      shape: 256
-      shape: 256
-    }
-    include: kTrain
-  }
-  layer{
-    name: "data"
-    type: kRecordInput
-    store_conf {
-      backend: "kvfile"
-      path :"/data/dataset/imagenet/val_record.bin"
-      mean_file: "/data/dataset/imagenet/image_mean.bin"
-      batchsize: 100
-      shape: 3
-      shape: 256
-      shape: 256
-    }
-    include: kTest
-  }
-  layer{
-    name: "image"
-    type: kImagePreprocess
-    rgbimage_conf {
-      cropsize: 227
-      mirror: true
-    }
-#    partition_dim: 0
-    srclayers: "data"
-  }
-  layer{
-    name: "conv1"
-    type: kCudnnConv
-    srclayers: "image"
-    convolution_conf {
-      num_filters: 96
-      kernel: 11
-      stride: 4
-    }
-#    partition_dim: 0
-    param {
-      name: "w1"
-      init {
-        type: kGaussian
-        std: 0.01
-      }
-    }
-    param {
-      name: "b1"
-      lr_scale: 2
-      wd_scale: 0
-      init {
-        type: kConstant
-        value: 0
-      }
-    }
-  }
-  layer {
-    name: "relu1"
-    type: kCudnnActivation
-    activation_conf {
-      type: RELU
-    }
-    share_src_blobs: true
-    srclayers: "conv1"
-#    partition_dim: 0
-  }
-  layer {
-    name: "pool1"
-    type: kCudnnPool
-    pooling_conf {
-      pool: MAX
-      kernel: 3
-      stride: 2
-    }
-    srclayers: "relu1"
-#    partition_dim: 0
-  }
-  layer {
-    name: "norm1"
-    type: kCudnnLRN
-    lrn_conf {
-      local_size: 5
-      alpha: 0.0001
-      beta: 0.75
-      knorm: 1
-    }
-    srclayers: "pool1"
-#    partition_dim: 0
-  }
-
-  layer{
-    name: "conv2"
-    type: kCudnnConv
-    srclayers: "norm1"
-    convolution_conf {
-      num_filters: 256
-      kernel: 5
-      pad: 2
-    }
-#    partition_dim: 0
-    param {
-      name: "w2"
-      init {
-        type: kGaussian
-        std: 0.01
-      }
-    }
-    param {
-      name: "b2"
-      lr_scale: 2
-      wd_scale: 0
-      init {
-        type: kConstant
-        value: 1
-      }
-    }
-  }
-  layer {
-    name: "relu2"
-    type: kCudnnActivation
-    activation_conf {
-      type: RELU
-    }
-    share_src_blobs: true
-    srclayers: "conv2"
-#    partition_dim: 0
-  }
-  layer {
-    name: "pool2"
-    type: kCudnnPool
-    pooling_conf {
-      pool: MAX
-      kernel: 3
-      stride: 2
-    }
-    srclayers: "relu2"
-#    partition_dim: 0
-  }
-
-  layer {
-    name: "norm2"
-    type: kCudnnLRN
-    lrn_conf {
-      local_size: 5
-      alpha: 0.0001
-      beta: 0.75
-      knorm: 1
-    }
-    srclayers: "pool2"
-#    partition_dim: 0
-  }
-  layer{
-    name: "conv3"
-    type: kCudnnConv
-    srclayers: "norm2"
-    convolution_conf {
-      num_filters: 384
-      kernel: 3
-      pad: 1
-    }
-#    partition_dim: 0
-    param {
-      name: "w3"
-      init {
-        type: kGaussian
-        std: 0.01
-      }
-    }
-    param {
-      name: "b3"
-      lr_scale: 2
-      wd_scale: 0
-      init {
-        type: kConstant
-        value: 0
-      }
-    }
-  }
-  layer {
-    name: "relu3"
-    type: kCudnnActivation
-    activation_conf {
-      type: RELU
-    }
-    share_src_blobs: true
-    srclayers: "conv3"
-#    partition_dim: 0
-  }
-  layer{
-    name: "conv4"
-    type: kCudnnConv
-    srclayers: "relu3"
-    convolution_conf {
-      num_filters: 384
-      kernel: 3
-      pad: 1
-    }
-#    partition_dim: 0
-    param {
-      name: "w4"
-      init {
-        type: kGaussian
-        std: 0.01
-      }
-    }
-    param {
-      name: "b4"
-      lr_scale:2
-      wd_scale:0
-      init {
-        type: kConstant
-        value: 1
-      }
-    }
-  }
-  layer {
-    name: "relu4"
-    type: kCudnnActivation
-    activation_conf {
-      type: RELU
-    }
-    share_src_blobs: true
-    srclayers: "conv4"
-#    partition_dim: 0
-  }
-  layer{
-    name: "conv5"
-    type: kCudnnConv
-    srclayers: "relu4"
-    convolution_conf {
-      num_filters: 256
-      kernel: 3
-      pad: 1
-    }
-#    partition_dim: 0
-    param {
-      name: "w5"
-      init {
-        type: kGaussian
-        std: 0.01
-      }
-    }
-    param {
-      name: "b5"
-      lr_scale: 2
-      wd_scale: 0
-      init {
-        type: kConstant
-        value: 1
-      }
-    }
-  }
-  layer {
-    name: "relu5"
-    type: kCudnnActivation
-    activation_conf {
-      type: RELU
-    }
-    share_src_blobs: true
-    srclayers: "conv5"
-#    partition_dim: 0
-  }
-  layer {
-    name: "pool5"
-    type: kCudnnPool
-    pooling_conf {
-      pool: MAX
-      kernel: 3
-      stride: 2
-    }
-    srclayers: "relu5"
-#    partition_dim: 0
-  }
-  layer {
-    name: "ip6"
-    type: kInnerProduct
-    innerproduct_conf {
-      num_output: 4096
-    }
-    param {
-      name: "w6"
-      init {
-        type: kGaussian
-        std: 0.005
-      }
-    }
-    param {
-      name: "b6"
-      lr_scale: 2
-      wd_scale: 0
-      init {
-        type: kConstant
-        value: 1
-      }
-    }
-    srclayers: "pool5"
-#    partition_dim: 1
-  }
-  layer {
-    name: "relu6"
-    type: kCudnnActivation
-    activation_conf {
-      type: RELU
-    }
-    share_src_blobs: true
-    srclayers: "ip6"
-#    partition_dim: 1
-  }
-  layer {
-    name: "drop6"
-    type: kDropout
-    srclayers: "relu6"
-#    partition_dim: 1
-  }
-  layer {
-    name: "ip7"
-    type: kInnerProduct
-    innerproduct_conf {
-      num_output: 4096
-    }
-#    partition_dim: 1
-    param {
-      name: "w7"
-      init {
-        type: kGaussian
-        std: 0.005
-      }
-    }
-    param {
-      name: "b7"
-      lr_scale: 2
-      wd_scale: 0
-      init {
-        type: kConstant
-        value: 1
-      }
-    }
-    srclayers: "drop6"
-  }
-  layer {
-    name: "relu7"
-    type: kCudnnActivation
-    activation_conf {
-      type: RELU
-    }
-    share_src_blobs: true
-    srclayers: "ip7"
-#    partition_dim: 1
-  }
-  layer {
-    name: "drop7"
-    type: kDropout
-    srclayers: "relu7"
-#    partition_dim: 1
-  }
-  layer {
-    name: "ip8"
-    type: kInnerProduct
-    innerproduct_conf {
-      num_output: 1000
-    }
-#    partition_dim: 1
-    param {
-      name: "w8"
-      init {
-        type: kGaussian
-        std: 0.01
-      }
-    }
-    param {
-      name: "b8"
-      lr_scale: 2
-      wd_scale: 0
-      init {
-        type: kConstant
-        value: 0
-      }
-    }
-    srclayers: "drop7"
-  }
-  layer {
-    name: "loss"
-    type: kCudnnSoftmaxLoss
-    softmaxloss_conf {
-      topk:1
-    }
-    srclayers: "ip8"
-    srclayers: "data"
-    include: kTrain
-  }
-  layer {
-   name : "softmax"
-   type: kCudnnSoftmax
-   srclayers: "ip8"
-   include: kTest
-  }
-  layer {
-   name : "accuracy"
-   type: kAccuracy
-   srclayers: "softmax"
-   srclayers: "data"
-   include: kTest
-  }
-}
-cluster {
-  nworker_groups: 1
-  nserver_groups: 1
-  nworkers_per_group: 1
-  nworkers_per_procs: 1
-  workspace: "examples/alexnet"
-}

http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/dd1e4afa/examples/alexnet/im2rec.cc
----------------------------------------------------------------------
diff --git a/examples/alexnet/im2rec.cc b/examples/alexnet/im2rec.cc
deleted file mode 100644
index 58ee44f..0000000
--- a/examples/alexnet/im2rec.cc
+++ /dev/null
@@ -1,157 +0,0 @@
-/************************************************************
-*
-* Licensed to the Apache Software Foundation (ASF) under one
-* or more contributor license agreements.  See the NOTICE file
-* distributed with this work for additional information
-* regarding copyright ownership.  The ASF licenses this file
-* to you 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 <glog/logging.h>
-#include <opencv2/opencv.hpp>
-#include <algorithm>
-#include <random>
-#include <chrono>
-#include <fstream>
-#include <string>
-#include <cstdint>
-#include <iostream>
-#include <vector>
-
-#include "singa/io/store.h"
-#include "singa/proto/common.pb.h"
-
-using std::string;
-
-const int kImageSize = 256;
-const int kImageNBytes = 256*256*3;
-
-void create_data(const string& image_list,
-    const string& input_folder,
-    const string& output_folder,
-    const string& backend = "kvfile") {
-  singa::RecordProto image;
-  image.add_shape(3);
-  image.add_shape(kImageSize);
-  image.add_shape(kImageSize);
-
-  singa::RecordProto mean;
-  mean.CopyFrom(image);
-  for (int i = 0; i < kImageNBytes; ++i)
-    mean.add_data(0.f);
-
-  auto store = singa::io::CreateStore(backend);
-  if (backend == "lmdb")
-    CHECK(store->Open(output_folder + "/image_record", singa::io::kCreate));
-  else
-    CHECK(store->Open(output_folder + "/image_record.bin", singa::io::kCreate));
-
-  LOG(INFO) << "Generating image record";
-
-  std::ifstream image_list_file(image_list.c_str(), std::ios::in);
-  CHECK(image_list_file.is_open()) << "Unable to open image list";
-
-  string image_file_name;
-  int label;
-  char str_buffer[kImageNBytes];
-  string rec_buf;
-  cv::Mat img, res;
-  std::vector<std::pair<string, int>> file_list;
-  while (image_list_file >> image_file_name >> label)
-    file_list.push_back(std::make_pair(image_file_name, label));
-  LOG(INFO) << "Data Shuffling";
-  unsigned seed = std::chrono::system_clock::now().time_since_epoch().count();
-  std::shuffle(file_list.begin(), file_list.end()
-      , std::default_random_engine());
-  LOG(INFO) << "Total number of images is " << file_list.size();
-  int ImageNum = file_list.size();
-
-  for (int imageid = 0; imageid < ImageNum; ++imageid) {
-    string path = input_folder + "/" + file_list[imageid].first;
-    img = cv::imread(path, CV_LOAD_IMAGE_COLOR);
-    CHECK(img.data != NULL) << "OpenCV load image fail" << path;
-    cv::resize(img, res, cv::Size(kImageSize, kImageSize),
-        0, 0, CV_INTER_LINEAR);
-    for (int h = 0; h < kImageSize; ++h) {
-      const uchar* ptr = res.ptr<uchar>(h);
-      int img_index = 0;
-      for (int w = 0; w < kImageSize; ++w)
-        for (int c = 0; c < 3; ++c)
-          str_buffer[(c*kImageSize+h)*kImageSize+w] =
-            static_cast<uint8_t>(ptr[img_index++]);
-    }
-    /*
-    for (int i = 0; i < kImageSize; ++i) {
-      for (int j = 0; j < kImageSize; ++j) {
-        cv::Vec3b pixel = res.at<cv::Vec3b>(j, i);
-        str_buffer[i*kImageSize+j] = static_cast<uint8_t>(pixel.val[2]);
-        str_buffer[kImageSize*kImageSize+i*kImageSize+j] = static_cast<uint8_t>(pixel.val[1]);
-        str_buffer[kImageSize*kImageSize*2+i*kImageSize+j] = static_cast<uint8_t>(pixel.val[0]);
-      }
-    }
-    */
-    image.set_label(file_list[imageid].second);
-    image.set_pixel(str_buffer, kImageNBytes);
-    image.SerializeToString(&rec_buf);
-
-    int length = snprintf(str_buffer, kImageNBytes, "%08d", imageid);
-    CHECK(store->Write(string(str_buffer, length), rec_buf));
-    if ((imageid+1) % 1000 == 0) {
-      store->Flush();
-      LOG(INFO) << imageid+1 << " files processed.";
-    }
-    const string& pixels = image.pixel();
-    for (int i = 0; i < kImageNBytes; ++i)
-      mean.set_data(i, mean.data(i) + static_cast<uint8_t>(pixels[i]));
-  }
-  if (ImageNum % 1000 != 0)
-      LOG(INFO) << ImageNum << " files processed.";
-
-  store->Flush();
-  store->Close();
-
-  LOG(INFO) << "Create image mean";
-  if (backend == "lmdb")
-    CHECK(store->Open(output_folder + "/image_mean", singa::io::kCreate));
-  else
-    CHECK(store->Open(output_folder + "/image_mean.bin", singa::io::kCreate));
-  for (int i = 0; i < kImageNBytes; i++)
-    mean.set_data(i, mean.data(i) / ImageNum);
-  mean.SerializeToString(&rec_buf);
-  store->Write("mean", rec_buf);
-  store->Flush();
-  store->Close();
-  delete store;
-
-  LOG(INFO) << "Done!";
-}
-
-int main(int argc, char** argv) {
-  if (argc < 4) {
-    std::cout << "Create data stores for ImageNet dataset.\n"
-      << "Usage: <image_list_file> <input_image_folder> <output_folder>"
-      << " <Optional: backend {lmdb, kvfile} default: kvfile>\n";
-  } else {
-    google::InitGoogleLogging(argv[0]);
-    FLAGS_alsologtostderr = 1;
-    if (argc == 4)
-      create_data(string(argv[1]), string(argv[2]), string(argv[3]));
-    else
-      create_data(string(argv[1]), string(argv[2]),
-          string(argv[3]), string(argv[4]));
-  }
-  return 0;
-}

http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/dd1e4afa/examples/alexnet/job.conf
----------------------------------------------------------------------
diff --git a/examples/alexnet/job.conf b/examples/alexnet/job.conf
deleted file mode 100644
index 3b7eaf4..0000000
--- a/examples/alexnet/job.conf
+++ /dev/null
@@ -1,403 +0,0 @@
-name: "alexnet"
-train_steps: 450000
-test_steps: 500
-test_freq: 1000
-disp_freq: 20
-checkpoint_freq: 100000
-checkpoint_after: 100000
-train_one_batch {
-  alg: kBP
-}
-updater{
-  type: kSGD
-  weight_decay: 0.0005
-  momentum: 0.9
-  learning_rate {
-    type: kStep
-    base_lr: 0.01
-    step_conf {
-      gamma: 0.1
-      change_freq: 100000
-    }
-  }
-}
-neuralnet {
-  layer{
-    name: "data"
-    type: kRecordInput
-    store_conf {
-      backend: "kvfile"
-      path :"/data/dataset/imagenet/train_record.bin"
-      mean_file: "/data/dataset/imagenet/image_mean.bin"
-      batchsize: 256
-      #random_skip: 1000
-      shape: 3
-      shape: 256
-      shape: 256
-    }
-    include: kTrain
-  }
-  layer{
-    name: "data"
-    type: kRecordInput
-    store_conf {
-      backend: "kvfile"
-      path :"/data/dataset/imagenet/val_record.bin"
-      mean_file: "/data/dataset/imagenet/image_mean.bin"
-      batchsize: 100
-      shape: 3
-      shape: 256
-      shape: 256
-    }
-    include: kTest
-  }
-  layer{
-    name: "image"
-    type: kImagePreprocess
-    rgbimage_conf {
-      cropsize: 227
-      mirror: true
-    }
-#    partition_dim: 0
-    srclayers: "data"
-  }
-  layer{
-    name: "conv1"
-    type: kConvolution
-    srclayers: "image"
-    convolution_conf {
-      num_filters: 96
-      kernel: 11
-      stride: 4
-    }
-#    partition_dim: 0
-    param {
-      name: "w1"
-      init {
-        type: kGaussian
-        std: 0.01
-      }
-    }
-    param {
-      name: "b1"
-      lr_scale: 2
-      wd_scale: 0
-      init {
-        type: kConstant
-        value: 0
-      }
-    }
-  }
-  layer {
-    name: "relu1"
-    type: kReLU
-    srclayers: "conv1"
-#    partition_dim: 0
-  }
-  layer {
-    name: "pool1"
-    type: kPooling
-    pooling_conf {
-      pool: MAX
-      kernel: 3
-      stride: 2
-    }
-    srclayers: "relu1"
-#    partition_dim: 0
-  }
-  layer {
-    name: "norm1"
-    type: kLRN
-    lrn_conf {
-      local_size: 5
-      alpha: 0.0001
-      beta: 0.75
-      knorm: 1
-    }
-    srclayers: "pool1"
-#    partition_dim: 0
-  }
-
-  layer{
-    name: "conv2"
-    type: kConvolution
-    srclayers: "norm1"
-    convolution_conf {
-      num_filters: 256
-      kernel: 5
-      pad: 2
-    }
-#    partition_dim: 0
-    param {
-      name: "w2"
-      init {
-        type: kGaussian
-        std: 0.01
-      }
-    }
-    param {
-      name: "b2"
-      lr_scale: 2
-      wd_scale: 0
-      init {
-        type: kConstant
-        value: 1
-      }
-    }
-  }
-  layer {
-    name: "relu2"
-    type: kReLU
-    srclayers: "conv2"
-#    partition_dim: 0
-  }
-  layer {
-    name: "pool2"
-    type: kPooling
-    pooling_conf {
-      pool: MAX
-      kernel: 3
-      stride: 2
-    }
-    srclayers: "relu2"
-#    partition_dim: 0
-  }
-
-  layer {
-    name: "norm2"
-    type: kLRN
-    lrn_conf {
-      local_size: 5
-      alpha: 0.0001
-      beta: 0.75
-      knorm: 1
-    }
-    srclayers: "pool2"
-#    partition_dim: 0
-  }
-  layer{
-    name: "conv3"
-    type: kConvolution
-    srclayers: "norm2"
-    convolution_conf {
-      num_filters: 384
-      kernel: 3
-      pad: 1
-    }
-#    partition_dim: 0
-    param {
-      name: "w3"
-      init {
-        type: kGaussian
-        std: 0.01
-      }
-    }
-    param {
-      name: "b3"
-      lr_scale: 2
-      wd_scale: 0
-      init {
-        type: kConstant
-        value: 0
-      }
-    }
-  }
-  layer {
-    name: "relu3"
-    type: kReLU
-    srclayers: "conv3"
-#    partition_dim: 0
-  }
-  layer{
-    name: "conv4"
-    type: kConvolution
-    srclayers: "relu3"
-    convolution_conf {
-      num_filters: 384
-      kernel: 3
-      pad: 1
-    }
-#    partition_dim: 0
-    param {
-      name: "w4"
-      init {
-        type: kGaussian
-        std: 0.01
-      }
-    }
-    param {
-      name: "b4"
-      lr_scale:2
-      wd_scale:0
-      init {
-        type: kConstant
-        value: 1
-      }
-    }
-  }
-  layer {
-    name: "relu4"
-    type: kReLU
-    srclayers: "conv4"
-#    partition_dim: 0
-  }
-  layer{
-    name: "conv5"
-    type: kConvolution
-    srclayers: "relu4"
-    convolution_conf {
-      num_filters: 256
-      kernel: 3
-      pad: 1
-    }
-#    partition_dim: 0
-    param {
-      name: "w5"
-      init {
-        type: kGaussian
-        std: 0.01
-      }
-    }
-    param {
-      name: "b5"
-      lr_scale: 2
-      wd_scale: 0
-      init {
-        type: kConstant
-        value: 1
-      }
-    }
-  }
-  layer {
-    name: "relu5"
-    type: kReLU
-    srclayers: "conv5"
-#    partition_dim: 0
-  }
-  layer {
-    name: "pool5"
-    type: kPooling
-    pooling_conf {
-      pool: MAX
-      kernel: 3
-      stride: 2
-    }
-    srclayers: "relu5"
-#    partition_dim: 0
-  }
-  layer {
-    name: "ip6"
-    type: kInnerProduct
-    innerproduct_conf {
-      num_output: 4096
-    }
-    param {
-      name: "w6"
-      init {
-        type: kGaussian
-        std: 0.005
-      }
-    }
-    param {
-      name: "b6"
-      lr_scale: 2
-      wd_scale: 0
-      init {
-        type: kConstant
-        value: 1
-      }
-    }
-    srclayers: "pool5"
-#    partition_dim: 1
-  }
-  layer {
-    name: "relu6"
-    type: kReLU
-    srclayers: "ip6"
-#    partition_dim: 1
-  }
-  layer {
-    name: "drop6"
-    type: kDropout
-    srclayers: "relu6"
-#    partition_dim: 1
-  }
-  layer {
-    name: "ip7"
-    type: kInnerProduct
-    innerproduct_conf {
-      num_output: 4096
-    }
-#    partition_dim: 1
-    param {
-      name: "w7"
-      init {
-        type: kGaussian
-        std: 0.005
-      }
-    }
-    param {
-      name: "b7"
-      lr_scale: 2
-      wd_scale: 0
-      init {
-        type: kConstant
-        value: 1
-      }
-    }
-    srclayers: "drop6"
-  }
-  layer {
-    name: "relu7"
-    type: kReLU
-    srclayers: "ip7"
-#    partition_dim: 1
-  }
-  layer {
-    name: "drop7"
-    type: kDropout
-    srclayers: "relu7"
-#    partition_dim: 1
-  }
-  layer {
-    name: "ip8"
-    type: kInnerProduct
-    innerproduct_conf {
-      num_output: 1000
-    }
-#    partition_dim: 1
-    param {
-      name: "w8"
-      init {
-        type: kGaussian
-        std: 0.01
-      }
-    }
-    param {
-      name: "b8"
-      lr_scale: 2
-      wd_scale: 0
-      init {
-        type: kConstant
-        value: 0
-      }
-    }
-    srclayers: "drop7"
-  }
-  layer {
-    name: "loss"
-    type: kSoftmaxLoss
-    softmaxloss_conf {
-      topk:1
-    }
-    srclayers: "ip8"
-    srclayers: "data"
-  }
-}
-cluster {
-  nworker_groups: 1
-  nserver_groups: 1
-  nworkers_per_group: 1
-  nworkers_per_procs: 1
-  workspace: "examples/alexnet"
-}

http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/dd1e4afa/examples/alexnet/rec2im_test.cc
----------------------------------------------------------------------
diff --git a/examples/alexnet/rec2im_test.cc b/examples/alexnet/rec2im_test.cc
deleted file mode 100644
index bb92d95..0000000
--- a/examples/alexnet/rec2im_test.cc
+++ /dev/null
@@ -1,116 +0,0 @@
-/************************************************************
-*
-* Licensed to the Apache Software Foundation (ASF) under one
-* or more contributor license agreements.  See the NOTICE file
-* distributed with this work for additional information
-* regarding copyright ownership.  The ASF licenses this file
-* to you 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 <glog/logging.h>
-#include <opencv2/opencv.hpp>
-
-#include <algorithm>
-#include <random>
-#include <chrono>
-#include <fstream>
-#include <string>
-#include <cstdint>
-#include <iostream>
-#include <vector>
-
-#include "singa/io/store.h"
-#include "singa/proto/common.pb.h"
-
-using std::string;
-
-const int kImageSize = 256;
-const int kImageNBytes = 256*256*3;
-
-void generate_image(const string& output_folder,
-    const string& key,
-    const string& val) {
-  float image_buf[kImageNBytes];
-  singa::RecordProto image;
-  image.ParseFromString(val);
-  cv::Mat img = cv::Mat::zeros(kImageSize, kImageSize, CV_8UC3);
-  string pixel = image.pixel();
-  int label = image.label();
-  string image_name = output_folder+"/"+key+"_"+std::to_string(label)+".jpg";
-  std::cout << "Writing to " << image_name << "...\n";
-  for (int h = 0; h < kImageSize; ++h) {
-    uchar* ptr = img.ptr<uchar>(h);
-    int img_index = 0;
-    for (int w = 0; w < kImageSize; ++w) {
-      for (int c = 0; c < 3; ++c)
-        ptr[img_index++] =
-          static_cast<uchar>(
-              static_cast<uint8_t>(
-                pixel[(c * kImageSize + h) * kImageSize + w]));
-    }
-  }
-
-  cv::imwrite(image_name, img);
-}
-
-void visualize(const string& input_file,
-    const string& output_folder,
-    const string& id_list) {
-  auto store = singa::io::OpenStore("kvfile", input_file,
-      singa::io::kRead);
-
-  std::vector<int> image_id_list;
-
-  std::ifstream id_list_file(id_list.c_str(), std::ios::in);
-  CHECK(id_list_file.is_open()) << "Unable to open image id list";
-  string id_;
-  while (id_list_file >> id_) {
-    int x;
-    x = std::stoi(id_);
-    image_id_list.push_back(x);
-  }
-  std::sort(image_id_list.begin(), image_id_list.end());
-
-  string key, val;
-  for (int i = 0; i < image_id_list[0]; ++i)
-    if (!store->Read(&key, &val)) {
-      store->SeekToFirst();
-      CHECK(store->Read(&key, &val));
-    }
-  generate_image(output_folder, key, val);
-
-  for (size_t i = 1; i != image_id_list.size(); ++i) {
-    for (int j = 0; j < image_id_list[i]-image_id_list[i-1]; ++j)
-      if (!store->Read(&key, &val)) {
-        store->SeekToFirst();
-        CHECK(store->Read(&key, &val));
-      }
-    generate_image(output_folder, key, val);
-  }
-}
-
-int main(int argc, char** argv) {
-  if (argc != 4) {
-    std::cout << "Visualize images from binary kvfile records.\n"
-      << "Usage: <input_file> <output_folder> <id_list>\n";
-  } else {
-    google::InitGoogleLogging(argv[0]);
-    FLAGS_alsologtostderr = 1;
-    visualize(string(argv[1]), string(argv[2]), string(argv[3]));
-  }
-
-  return 0;
-}

http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/dd1e4afa/examples/char-rnn/data.py
----------------------------------------------------------------------
diff --git a/examples/char-rnn/data.py b/examples/char-rnn/data.py
deleted file mode 100644
index 20e7262..0000000
--- a/examples/char-rnn/data.py
+++ /dev/null
@@ -1,32 +0,0 @@
-#!/usr/bin/env python
-
-#/************************************************************
-#*
-#* Licensed to the Apache Software Foundation (ASF) under one
-#* or more contributor license agreements.  See the NOTICE file
-#* distributed with this work for additional information
-#* regarding copyright ownership.  The ASF licenses this file
-#* to you 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.
-#*
-#*************************************************************/
-
-
-# pls get linux_input.txt from http://cs.stanford.edu/people/karpathy/char-rnn/
-data = open('linux_input.txt', 'r').read() # should be simple plain text file
-chars = list(set(data))
-data_size, vocab_size = len(data), len(chars)
-print 'data has %d characters, %d unique.' % (data_size, vocab_size)
-with open('vocab.txt', 'w') as fd:
-  fd.write("".join(chars))
-  fd.flush()

http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/dd1e4afa/examples/char-rnn/job.conf
----------------------------------------------------------------------
diff --git a/examples/char-rnn/job.conf b/examples/char-rnn/job.conf
deleted file mode 100644
index bd648f1..0000000
--- a/examples/char-rnn/job.conf
+++ /dev/null
@@ -1,253 +0,0 @@
-name:"char-rnn"
-train_steps: 100000
-disp_freq: 100
-#debug: true
-gpu: 0
-train_one_batch {
-  alg: kBPTT
-}
-
-updater {
-  type: kRMSProp
-  rmsprop_conf {
-    rho: 0.95
-  }
-  learning_rate {
-    type: kStep
-    base_lr: 0.002
-    step_conf {
-      gamma: 0.97
-      change_freq: 2000
-    }
-  }
-  clip_low: -5
-  clip_high: 5
-}
-
-neuralnet {
-  unroll_len: 50
-  layer {
-    name: "data"
-    type: kCharRNN
-    unroll_len: 1
-    char_rnn_conf {
-      path: "examples/char-rnn/linux_input.txt"
-      vocab_path:"examples/char-rnn/vocab.txt"
-      batchsize: 50
-      unroll_len: 50
-    }
-  }
-  layer {
-    name: "onehot"
-    type: kOneHot
-    srclayers: "data"
-    unroll_conn_type: kUnrollOneToAll
-    onehot_conf {
-      vocab_size: 101
-    }
-  }
-
-  layer {
-    name: "label"
-    type: kRNNLabel
-    srclayers: "data"
-    unroll_conn_type: kUnrollOneToAll
-  }
-
-  layer {
-    name: "gru1"
-    type: kGRU
-    srclayers: "onehot"
-    gru_conf {
-      dim_hidden: 512
-    }
-    param {
-      name: "z_hx"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-    param {
-      name: "r_hx"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-    param {
-      name: "c_hx"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-    param {
-      name: "z_hh"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-    param {
-      name: "r_hh"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-    param {
-      name: "c_hh"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-    param {
-      name: "z_b"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-    param {
-      name: "r_b"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-    param {
-      name: "c_b"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-
-  }
-#  layer {
-#    name: "gru2"
-#    type: kGRU
-#    srclayers: "gru1"
-#    gru_conf {
-#      dim_hidden: 512
-#    }
-#    param {
-#      name: "z_hx2"
-#      init {
-#        type: kUniform
-#        low: -0.08
-#        high: 0.08
-#      }
-#    }
-#    param {
-#      name: "r_hx2"
-#      init {
-#        type: kUniform
-#        low: -0.08
-#        high: 0.08
-#      }
-#    }
-#    param {
-#      name: "c_hx2"
-#      init {
-#        type: kUniform
-#        low: -0.08
-#        high: 0.08
-#      }
-#    }
-#    param {
-#      name: "z_hh2"
-#      init {
-#        type: kUniform
-#        low: -0.08
-#        high: 0.08
-#      }
-#    }
-#    param {
-#      name: "r_hh2"
-#      init {
-#        type: kUniform
-#        low: -0.08
-#        high: 0.08
-#      }
-#    }
-#    param {
-#      name: "c_hh2"
-#      init {
-#        type: kUniform
-#        low: -0.08
-#        high: 0.08
-#      }
-#    }
-#    param {
-#      name: "z_b2"
-#      init {
-#        type: kUniform
-#        low: -0.08
-#        high: 0.08
-#      }
-#    }
-#    param {
-#      name: "r_b2"
-#      init {
-#        type: kUniform
-#        low: -0.08
-#        high: 0.08
-#      }
-#    }
-#    param {
-#      name: "c_b2"
-#      init {
-#        type: kUniform
-#        low: -0.08
-#        high: 0.08
-#      }
-#    }
-#  }
-#
-  layer {
-    name: "ip1"
-    type: kInnerProduct
-    srclayers: "gru1"
-    innerproduct_conf {
-      num_output: 101
-    }
-    param {
-      name: "w"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-    param {
-      name: "b"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-  }
-  layer {
-    name: "loss"
-    type: kSoftmaxLoss
-    srclayers: "ip1"
-    srclayers: "label"
-  }
-}
-
-cluster {
-  workspace: "examples/char-rnn/"
-}

http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/dd1e4afa/examples/char-rnn/sample.conf
----------------------------------------------------------------------
diff --git a/examples/char-rnn/sample.conf b/examples/char-rnn/sample.conf
deleted file mode 100644
index b15ef9e..0000000
--- a/examples/char-rnn/sample.conf
+++ /dev/null
@@ -1,212 +0,0 @@
-name:"char-rnn"
-test_steps: 100
-#debug: true
-gpu: 0
-checkpoint_path: "examples/char-rnn/checkpoint/step2000-worker0"
-train_one_batch {
-  alg: kBPTT
-}
-
-neuralnet {
-  layer {
-    name: "data"
-    type: kRNNDummy
-    rnn_dummy_conf {
-      shape: 1
-      integer: true
-      low: 0
-      high: 101
-      dynamic_srclayer: "argsort"
-    }
-  }
-  layer {
-    name: "onehot"
-    type: kOneHot
-    srclayers: "data"
-  }
-
-  layer {
-    name: "gru1"
-    type: kGRU
-    srclayers: "onehot"
-    gru_conf {
-      dim_hidden: 512
-    }
-    param {
-      name: "z_hx"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-    param {
-      name: "r_hx"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-    param {
-      name: "c_hx"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-    param {
-      name: "z_hh"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-    param {
-      name: "r_hh"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-    param {
-      name: "c_hh"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-    param {
-      name: "z_b"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-    param {
-      name: "r_b"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-    param {
-      name: "c_b"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-  }
-  layer {
-    name: "gru2"
-    type: kGRU
-    srclayers: "gru1"
-    gru_conf {
-      dim_hidden: 512
-    }
-    param {
-      name: "z_hx2"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-    param {
-      name: "r_hx2"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-    param {
-      name: "c_hx2"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-    param {
-      name: "z_hh2"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-    param {
-      name: "r_hh2"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-    param {
-      name: "c_hh2"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-  }
-
-
-  layer {
-    name: "ip1"
-    type: kInnerProduct
-    srclayers: "gru2"
-    innerproduct_conf {
-      num_output: 101
-    }
-    param {
-      name: "w"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-    param {
-      name: "b"
-      init {
-        type: kUniform
-        low: -0.08
-        high: 0.08
-      }
-    }
-  }
-  layer {
-    name: "softmax"
-    type: kSoftmax
-    srclayers: "ip1"
-  }
-  layer {
-    name: "argsort"
-    type: kArgSort
-    srclayers: "softmax"
-  }
-  layer {
-    name: "sampling"
-    type: kCharRNNOutput
-    srclayers: "argsort"
-    char_rnn_conf {
-      vocab_path: "examples/char-rnn/vocab.txt"
-    }
-  }
-}
-
-cluster {
-  workspace: "examples/char-rnn/"
-}

http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/dd1e4afa/examples/cifar10/Makefile.example
----------------------------------------------------------------------
diff --git a/examples/cifar10/Makefile.example b/examples/cifar10/Makefile.example
deleted file mode 100644
index 40e85b1..0000000
--- a/examples/cifar10/Makefile.example
+++ /dev/null
@@ -1,41 +0,0 @@
-#/**
-# * Licensed to the Apache Software Foundation (ASF) under one
-# * or more contributor license agreements.  See the NOTICE file
-# * distributed with this work for additional information
-# * regarding copyright ownership.  The ASF licenses this file
-# * to you 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.
-# */
-
-libs :=singa glog protobuf
-
-.PHONY: all download create
-
-HDFS_DIR := hdfs://node0:9000/examples/cifar10
-
-download: cifar-10-binary-bin
-
-cifar-10-binary-bin:
-	wget http://www.cs.toronto.edu/~kriz/cifar-10-binary.tar.gz
-	tar xf cifar-10-binary.tar.gz
-
-create:
-	$(CXX) create_data.cc -std=c++11 -lsinga -lprotobuf -lglog \
-		-I../../include -L../../.libs/ -Wl,-unresolved-symbols=ignore-in-shared-libs \
-		-Wl,-rpath=../../.libs/  -o create_data.bin
-	./create_data.bin cifar-10-batches-bin .
-
-create_hdfs:
-	$(CXX) create_data.cc -std=c++11 -lsinga -lprotobuf -lglog -lhdfs3 \
-		-I../../include -L../../.libs/ -Wl,-unresolved-symbols=ignore-in-shared-libs \
-		-Wl,-rpath=../../.libs/  -o create_data.bin
-	./create_data.bin cifar-10-batches-bin $(HDFS_DIR)

http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/dd1e4afa/examples/cifar10/create_data.cc
----------------------------------------------------------------------
diff --git a/examples/cifar10/create_data.cc b/examples/cifar10/create_data.cc
deleted file mode 100644
index 5564c38..0000000
--- a/examples/cifar10/create_data.cc
+++ /dev/null
@@ -1,138 +0,0 @@
-/************************************************************
-*
-* Licensed to the Apache Software Foundation (ASF) under one
-* or more contributor license agreements.  See the NOTICE file
-* distributed with this work for additional information
-* regarding copyright ownership.  The ASF licenses this file
-* to you 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.
-*
-*************************************************************/
-
-
-/**
- * Create training and test DataShard for CIFAR dataset. 
- * It is adapted from convert_cifar_data from Caffe. 
- *    create_shard.bin <input> <output_folder> 
- * 
- * Read from JobConf object the option to use KVfile, HDFS or other (1st layer
- * store_conf object). 
- * To load to HDFS, specify "hdfs://namenode/examples" as the output folder
- */
-
-#include <glog/logging.h>
-#include <fstream>
-#include <string>
-#include <cstdint>
-#include <iostream>
-
-#include "singa/io/store.h"
-#include "singa/proto/common.pb.h"
-#include "singa/utils/common.h"
-
-using std::string;
-
-const int kCIFARSize = 32;
-const int kCIFARImageNBytes = 3072;
-const int kCIFARBatchSize = 10000;
-const int kCIFARTrainBatches = 5;
-
-void read_image(std::ifstream* file, int* label, char* buffer) {
-  char label_char;
-  file->read(&label_char, 1);
-  *label = label_char;
-  file->read(buffer, kCIFARImageNBytes);
-  return;
-}
-
-void create_data(const string& input_folder, const string& output_folder) {
-  int label;
-  char str_buffer[kCIFARImageNBytes];
-  string rec_buf;
-  singa::RecordProto image;
-  image.add_shape(3);
-  image.add_shape(kCIFARSize);
-  image.add_shape(kCIFARSize);
-
-  singa::RecordProto mean;
-  mean.CopyFrom(image);
-  for (int i = 0; i < kCIFARImageNBytes; i++)
-    mean.add_data(0.f);
-
-  string store_backend = output_folder.find("hdfs") !=-1 ?
-                         "hdfsfile" : "kvfile";
-  auto store = singa::io::CreateStore(store_backend);
-  CHECK(store->Open(output_folder + "/train_data.bin", singa::io::kCreate));
-  LOG(INFO) << "Preparing training data";
-  int count = 0;
-  for (int fileid = 0; fileid < kCIFARTrainBatches; ++fileid) {
-    LOG(INFO) << "Training Batch " << fileid + 1;
-    snprintf(str_buffer, kCIFARImageNBytes, "/data_batch_%d.bin", fileid + 1);
-    std::ifstream data_file((input_folder + str_buffer).c_str(),
-        std::ios::in | std::ios::binary);
-    CHECK(data_file.is_open()) << "Unable to open train file #" << fileid + 1;
-    for (int itemid = 0; itemid < kCIFARBatchSize; ++itemid) {
-      read_image(&data_file, &label, str_buffer);
-      image.set_label(label);
-      image.set_pixel(str_buffer, kCIFARImageNBytes);
-      image.SerializeToString(&rec_buf);
-      int length = snprintf(str_buffer, kCIFARImageNBytes, "%05d", count);
-      CHECK(store->Write(string(str_buffer, length), rec_buf));
-
-      const string& pixels = image.pixel();
-      for (int i = 0; i < kCIFARImageNBytes; i++)
-        mean.set_data(i, mean.data(i) + static_cast<uint8_t>(pixels[i]));
-      count += 1;
-    }
-  }
-  store->Flush();
-  store->Close();
-
-  LOG(INFO) << "Create image mean";
-  store->Open(output_folder + "/image_mean.bin", singa::io::kCreate);
-  for (int i = 0; i < kCIFARImageNBytes; i++)
-    mean.set_data(i, mean.data(i) / count);
-  mean.SerializeToString(&rec_buf);
-  store->Write("mean", rec_buf);
-  store->Flush();
-  store->Close();
-
-  LOG(INFO) << "Create test data";
-  store->Open(output_folder + "/test_data.bin", singa::io::kCreate);
-  std::ifstream data_file((input_folder + "/test_batch.bin").c_str(),
-      std::ios::in | std::ios::binary);
-  CHECK(data_file.is_open()) << "Unable to open test file.";
-  for (int itemid = 0; itemid < kCIFARBatchSize; ++itemid) {
-    read_image(&data_file, &label, str_buffer);
-    image.set_label(label);
-    image.set_pixel(str_buffer, kCIFARImageNBytes);
-    image.SerializeToString(&rec_buf);
-    int length = snprintf(str_buffer, kCIFARImageNBytes, "%05d", itemid);
-    CHECK(store->Write(string(str_buffer, length), rec_buf));
-  }
-  store->Flush();
-  store->Close();
-}
-
-int main(int argc, char** argv) {
-  if (argc != 3) {
-    std::cout <<"Create train and test DataShard for Cifar dataset.\n"
-      << "Usage:\n"
-      << "    create_data.bin input_folder output_folder\n"
-      << "Where the input folder should contain the binary batch files.\n";
-  } else {
-    google::InitGoogleLogging(argv[0]);
-    create_data(string(argv[1]), string(argv[2]));
-  }
-  return 0;
-}

http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/dd1e4afa/examples/cifar10/cudnn.conf
----------------------------------------------------------------------
diff --git a/examples/cifar10/cudnn.conf b/examples/cifar10/cudnn.conf
deleted file mode 100644
index 0f9402e..0000000
--- a/examples/cifar10/cudnn.conf
+++ /dev/null
@@ -1,297 +0,0 @@
-name: "cifar10-convnet"
-train_steps: 70000
-test_steps: 100
-test_freq: 1000
-#validate_steps: 100
-#validate_freq: 300
-disp_freq: 200
-gpu: 0
-#checkpoint_path: "examples/cifar10/checkpoint/step1000-worker0"
-train_one_batch {
-  alg: kBP
-}
-updater{
-  type: kSGD
-  weight_decay:0.004
-  momentum:0.9
-  learning_rate {
-    type: kFixedStep
-    fixedstep_conf:{
-      step:0
-      step:60000
-      step:65000
-      step_lr:0.001
-      step_lr:0.0001
-      step_lr:0.00001
-    }
-  }
-}
-neuralnet {
-  layer{
-    name: "data"
-    type: kRecordInput
-    store_conf {
-      backend: "kvfile"
-      path: "examples/cifar10/train_data.bin"
-      mean_file: "examples/cifar10/image_mean.bin"
-      batchsize: 100
-      #random_skip: 5000
-      shape: 3
-      shape: 32
-      shape: 32
-    }
-    include: kTrain
-  }
-#  layer{
-#    name: "data"
-#    type: kRecordInput
-#    store_conf {
-#      backend: "kvfile"
-#      path: "examples/cifar10/val_data.bin"
-#      mean_file: "examples/cifar10/image_mean.bin"
-#      batchsize: 64
-#      random_skip: 5000
-#      shape: 3
-#      shape: 32
-#      shape: 32
-#    }
-#    include: kVal
-#  }
-  layer{
-    name: "data"
-    type: kRecordInput
-    store_conf {
-      backend: "kvfile"
-      path: "examples/cifar10/test_data.bin"
-      mean_file: "examples/cifar10/image_mean.bin"
-      batchsize: 100
-      shape: 3
-      shape: 32
-      shape: 32
-    }
-    include: kTest
-  }
-
-  layer {
-    name: "conv1"
-    type: kCudnnConv
-    srclayers: "data"
-    convolution_conf {
-      num_filters: 32
-      kernel: 5
-      stride: 1
-      pad:2
-    }
-    param {
-      name: "w1"
-      init {
-        type:kGaussian
-        std:0.0001
-      }
-    }
-    param {
-      name: "b1"
-      lr_scale:2.0
-      wd_scale: 0
-      init {
-        type: kConstant
-        value:0
-      }
-    }
-  }
-
-  layer {
-    name: "pool1"
-    type: kCudnnPool
-    srclayers: "conv1"
-    pooling_conf {
-      pool: MAX
-      kernel: 3
-      stride: 2
-    }
-  }
-  layer {
-    name: "relu1"
-    type: kCudnnActivation
-    activation_conf {
-      type: RELU
-    }
-    share_src_blobs: true
-    srclayers:"pool1"
-  }
-  layer {
-    name: "norm1"
-    type: kCudnnLRN
-    lrn_conf {
-      local_size: 3
-      alpha: 5e-05
-      beta: 0.75
-    }
-    srclayers:"relu1"
-  }
-  layer {
-    name: "conv2"
-    type: kCudnnConv
-    srclayers: "norm1"
-    convolution_conf {
-      num_filters: 32
-      kernel: 5
-      stride: 1
-      pad:2
-    }
-    param {
-      name: "w2"
-      init {
-        type:kGaussian
-        std:0.01
-      }
-    }
-    param {
-      name: "b2"
-      lr_scale:2.0
-      wd_scale: 0
-      init {
-        type: kConstant
-        value:0
-      }
-    }
-  }
-  layer {
-    name: "relu2"
-    type: kCudnnActivation
-    activation_conf {
-      type: RELU
-    }
-    share_src_blobs: true
-    srclayers:"conv2"
-  }
-  layer {
-    name: "pool2"
-    type: kCudnnPool
-    srclayers: "relu2"
-    pooling_conf {
-      pool: AVG
-      kernel: 3
-      stride: 2
-    }
-  }
-  layer {
-    name: "norm2"
-    type: kCudnnLRN
-    lrn_conf {
-      local_size: 3
-      alpha: 5e-05
-      beta: 0.75
-    }
-    srclayers:"pool2"
-  }
-  layer {
-    name: "conv3"
-    type: kCudnnConv
-    srclayers: "norm2"
-    convolution_conf {
-      num_filters: 64
-      kernel: 5
-      stride: 1
-      pad:2
-    }
-    param {
-      name: "w3"
-      init {
-        type:kGaussian
-        std:0.01
-      }
-    }
-    param {
-      name: "b3"
-      lr_scale: 2
-      wd_scale: 0
-      init {
-        type: kConstant
-        value:0
-      }
-    }
-  }
-  layer {
-    name: "relu3"
-    type: kCudnnActivation
-    activation_conf {
-      type: RELU
-    }
-    share_src_blobs: true
-    srclayers:"conv3"
-  }
-  layer {
-    name: "pool3"
-    type: kCudnnPool
-    srclayers: "relu3"
-    pooling_conf {
-      pool: AVG
-      kernel: 3
-      stride: 2
-    }
-  }
-  layer {
-    name: "ip1"
-    type: kInnerProduct
-    srclayers:"pool3"
-    innerproduct_conf {
-      num_output: 10
-    }
-    param {
-      name: "w4"
-      wd_scale:250
-      init {
-        type:kGaussian
-        std:0.01
-      }
-    }
-    param {
-      name: "b4"
-      lr_scale:2.0
-      wd_scale:0
-      init {
-        type: kConstant
-        value:0
-      }
-    }
-  }
-  layer {
-   name : "softmax"
-   type: kCudnnSoftmax
-   srclayers: "ip1"
-   include: kTest
-  }
-
-  layer {
-   name : "accuracy"
-   type: kAccuracy
-   srclayers: "softmax"
-   srclayers: "data"
-   include: kTest
-  }
-  layer{
-    name: "loss"
-    type: kSoftmaxLoss
-    srclayers:"ip1"
-    srclayers: "data"
-    include : kTrain
-  }
-# uncomment "softmax", "argsort", "output" layer and comment "loss" layer
-# to extract features from argsort
-#  layer {
-#    name : "output"
-#    type: kCSVOutput
-#    srclayers: "argsort"
-#    store_conf {
-#      path: "examples/cifar10/out.csv"
-#    }
-#  }
-}
-cluster {
-  nworker_groups: 1
-  nserver_groups: 1
-  nworkers_per_group: 1
-  nworkers_per_procs: 1
-  workspace: "examples/cifar10"
-}

http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/dd1e4afa/examples/cifar10/cudnn_bm.conf
----------------------------------------------------------------------
diff --git a/examples/cifar10/cudnn_bm.conf b/examples/cifar10/cudnn_bm.conf
deleted file mode 100644
index 2ca30cb..0000000
--- a/examples/cifar10/cudnn_bm.conf
+++ /dev/null
@@ -1,376 +0,0 @@
-name: "cifar10-convnet"
-train_steps: 70000
-test_steps: 100
-test_freq: 1000
-#validate_steps: 100
-#validate_freq: 300
-disp_freq: 200
-gpu: 0
-#checkpoint_path: "examples/cifar10/checkpoint/step1000-worker0"
-train_one_batch {
-  alg: kBP
-}
-updater{
-  type: kSGD
-  weight_decay:0.004
-  momentum:0.9
-  learning_rate {
-    type: kFixedStep
-    fixedstep_conf:{
-      step:0
-      step:60000
-      step:65000
-      step_lr:0.001
-      step_lr:0.0001
-      step_lr:0.00001
-    }
-  }
-}
-neuralnet {
-  layer{
-    name: "data"
-    type: kRecordInput
-    store_conf {
-      backend: "kvfile"
-      path: "examples/cifar10/train_data.bin"
-      mean_file: "examples/cifar10/image_mean.bin"
-      batchsize: 100
-      #random_skip: 5000
-      shape: 3
-      shape: 32
-      shape: 32
-    }
-    include: kTrain
-  }
-#  layer{
-#    name: "data"
-#    type: kRecordInput
-#    store_conf {
-#      backend: "kvfile"
-#      path: "examples/cifar10/val_data.bin"
-#      mean_file: "examples/cifar10/image_mean.bin"
-#      batchsize: 64
-#      random_skip: 5000
-#      shape: 3
-#      shape: 32
-#      shape: 32
-#    }
-#    include: kVal
-#  }
-  layer{
-    name: "data"
-    type: kRecordInput
-    store_conf {
-      backend: "kvfile"
-      path: "examples/cifar10/test_data.bin"
-      mean_file: "examples/cifar10/image_mean.bin"
-      batchsize: 100
-      shape: 3
-      shape: 32
-      shape: 32
-    }
-    include: kTest
-  }
-
-  layer {
-    name: "conv1"
-    type: kCudnnConv
-    srclayers: "data"
-    convolution_conf {
-      num_filters: 32
-      kernel: 5
-      stride: 1
-      pad:2
-    }
-    param {
-      name: "w1"
-      init {
-        type:kGaussian
-        std:0.0001
-      }
-    }
-    param {
-      name: "b1"
-      lr_scale:2.0
-      wd_scale: 0
-      init {
-        type: kConstant
-        value:0
-      }
-    }
-  }
-
-  layer {
-    name: "pool1"
-    type: kCudnnPool
-    srclayers: "conv1"
-    pooling_conf {
-      pool: MAX
-      kernel: 3
-      stride: 2
-    }
-  }
-  layer {
-    name: "bm1"
-    type: kCudnnBM
-      param {
-        name: "s11"
-        init {
- 		  type:kConstant
- 		  value:1
-        }
-      }
-	  param {
-		name: "s12"
-		init {
-		  type:kConstant
-		  value:0
-		}
-	  }
-	  param {
-		name: "s13"
-		init {
-		  type:kConstant
-		  value:0
-		}
-	  }
-	  param {
-		name: "s14"
-		init {
-		  type:kConstant
-		  value:0
-		}
-	  }
-    srclayers:"pool1"
-  }
-  layer {
-    name: "relu1"
-    type: kCudnnActivation
-    activation_conf {
-      type: RELU
-    }
-    share_src_blobs: true
-    srclayers:"bm1"
-  }
-  layer {
-    name: "conv2"
-    type: kCudnnConv
-    srclayers: "relu1"
-    convolution_conf {
-      num_filters: 32
-      kernel: 5
-      stride: 1
-      pad:2
-    }
-    param {
-      name: "w2"
-      init {
-        type:kGaussian
-        std:0.01
-      }
-    }
-    param {
-      name: "b2"
-      lr_scale:2.0
-      wd_scale: 0
-      init {
-        type: kConstant
-        value:0
-      }
-    }
-  }
-  layer {
-    name: "bm2"
-    type: kCudnnBM
-      param {
-        name: "s21"
-        init {
- 		  type:kConstant
- 		  value:1
-        }
-      }
-	  param {
-		name: "s22"
-		init {
-		  type:kConstant
-		  value:0
-		}
-	  }
-	  param {
-		name: "s23"
-		init {
-		  type:kConstant
-		  value:0
-		}
-	  }
-	  param {
-		name: "s24"
-		init {
-		  type:kConstant
-		  value:0
-		}
-	  }
-    srclayers:"conv2"
-  }
-  layer {
-    name: "relu2"
-    type: kCudnnActivation
-    activation_conf {
-      type: RELU
-    }
-    share_src_blobs: true
-    srclayers:"bm2"
-  }
-  layer {
-    name: "pool2"
-    type: kCudnnPool
-    srclayers: "relu2"
-    pooling_conf {
-      pool: AVG
-      kernel: 3
-      stride: 2
-    }
-  }
-  layer {
-    name: "conv3"
-    type: kCudnnConv
-    srclayers: "relu2"
-    convolution_conf {
-      num_filters: 64
-      kernel: 5
-      stride: 1
-      pad:2
-    }
-    param {
-      name: "w3"
-      init {
-        type:kGaussian
-        std:0.01
-      }
-    }
-    param {
-      name: "b3"
-      lr_scale: 2
-      wd_scale: 0
-      init {
-        type: kConstant
-        value:0
-      }
-    }
-  }
-  layer {
-    name: "bm3"
-    type: kCudnnBM
-      param {
-        name: "s31"
-        init {
- 		  type:kConstant
- 		  value:1
-        }
-      }
-	  param {
-		name: "s32"
-		init {
-		  type:kConstant
-		  value:0
-		}
-	  }
-	  param {
-		name: "s33"
-		init {
-		  type:kConstant
-		  value:0
-		}
-	  }
-	  param {
-		name: "s34"
-		init {
-		  type:kConstant
-		  value:0
-		}
-	  }
-    srclayers:"conv3"
-  }
-  layer {
-    name: "relu3"
-    type: kCudnnActivation
-    activation_conf {
-      type: RELU
-    }
-    share_src_blobs: true
-    srclayers:"bm3"
-  }
-  layer {
-    name: "pool3"
-    type: kCudnnPool
-    srclayers: "relu3"
-    pooling_conf {
-      pool: AVG
-      kernel: 3
-      stride: 2
-    }
-  }
-  layer {
-    name: "ip1"
-    type: kInnerProduct
-    srclayers:"pool3"
-    innerproduct_conf {
-      num_output: 10
-    }
-    param {
-      name: "w4"
-      wd_scale:250
-      init {
-        type:kGaussian
-        std:0.01
-      }
-    }
-    param {
-      name: "b4"
-      lr_scale:2.0
-      wd_scale:0
-      init {
-        type: kConstant
-        value:0
-      }
-    }
-  }
-  layer {
-   name : "softmax"
-   type: kCudnnSoftmax
-   srclayers: "ip1"
-   include: kTest
-  }
-
-  layer {
-   name : "accuracy"
-   type: kAccuracy
-   srclayers: "softmax"
-   srclayers: "data"
-   include: kTest
-  }
-  layer{
-    name: "loss"
-    type: kSoftmaxLoss
-    srclayers:"ip1"
-    srclayers: "data"
-    include : kTrain
-  }
-# uncomment "softmax", "argsort", "output" layer and comment "loss" layer
-# to extract features from argsort
-#  layer {
-#    name : "output"
-#    type: kCSVOutput
-#    srclayers: "argsort"
-#    store_conf {
-#      path: "examples/cifar10/out.csv"
-#    }
-#  }
-}
-cluster {
-  nworker_groups: 1
-  nserver_groups: 1
-  nworkers_per_group: 1
-  nworkers_per_procs: 1
-  workspace: "examples/cifar10"
-}

http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/dd1e4afa/examples/cifar10/cudnn_hybrid.conf
----------------------------------------------------------------------
diff --git a/examples/cifar10/cudnn_hybrid.conf b/examples/cifar10/cudnn_hybrid.conf
deleted file mode 100644
index a11145c..0000000
--- a/examples/cifar10/cudnn_hybrid.conf
+++ /dev/null
@@ -1,306 +0,0 @@
-name: "cifar10-convnet"
-train_steps: 10000
-test_steps: 0
-test_freq: 200
-#validate_steps: 100
-#validate_freq: 300
-disp_freq: 200
-gpu: 0
-gpu: 1
-#debug: true
-#checkpoint_path: "examples/cifar10/checkpoint/step1000-worker0"
-train_one_batch {
-  alg: kBP
-}
-updater{
-  type: kSGD
-  weight_decay:0.004
-  momentum:0.9
-  learning_rate {
-    type: kFixedStep
-    fixedstep_conf:{
-      step:0
-      step:60000
-      step:65000
-      step_lr:0.001
-      step_lr:0.0001
-      step_lr:0.00001
-    }
-  }
-}
-neuralnet {
-  layer{
-    name: "data"
-    type: kRecordInput
-    store_conf {
-      backend: "kvfile"
-      path: "examples/cifar10/train_data.bin"
-      mean_file: "examples/cifar10/image_mean.bin"
-      batchsize: 100
-      #random_skip: 5000
-      shape: 3
-      shape: 32
-      shape: 32
-    }
-    include: kTrain
-    partition_dim: 0
-  }
-#  layer{
-#    name: "data"
-#    type: kRecordInput
-#    store_conf {
-#      backend: "kvfile"
-#      path: "examples/cifar10/val_data.bin"
-#      mean_file: "examples/cifar10/image_mean.bin"
-#      batchsize: 64
-#      random_skip: 5000
-#      shape: 3
-#      shape: 32
-#      shape: 32
-#    }
-#    include: kVal
-#  }
-  layer{
-    name: "data"
-    type: kRecordInput
-    store_conf {
-      backend: "kvfile"
-      path: "examples/cifar10/test_data.bin"
-      mean_file: "examples/cifar10/image_mean.bin"
-      batchsize: 100
-      shape: 3
-      shape: 32
-      shape: 32
-    }
-    include: kTest
-    partition_dim: 0
-  }
-
-  layer {
-    partition_dim: 0
-    name: "conv1"
-    type: kCudnnConv
-    srclayers: "data"
-    convolution_conf {
-      num_filters: 32
-      kernel: 5
-      stride: 1
-      pad:2
-    }
-    param {
-      name: "w1"
-      init {
-        type:kGaussian
-        std:0.0001
-      }
-    }
-    param {
-      name: "b1"
-      lr_scale:2.0
-      init {
-        type: kConstant
-        value:0
-      }
-    }
-  }
-
-  layer {
-    partition_dim: 0
-    name: "pool1"
-    type: kCudnnPool
-    srclayers: "conv1"
-    pooling_conf {
-      pool: MAX
-      kernel: 3
-      stride: 2
-    }
-  }
-  layer {
-    partition_dim: 0
-    name: "relu1"
-    type: kCudnnActivation
-    activation_conf {
-      type: RELU
-    }
-    srclayers:"pool1"
-  }
-  layer {
-    partition_dim: 0
-    name: "norm1"
-    type: kCudnnLRN
-    lrn_conf {
-      local_size: 3
-      alpha: 5e-05
-      beta: 0.75
-    }
-    srclayers:"relu1"
-  }
-  layer {
-    partition_dim: 0
-    name: "conv2"
-    type: kCudnnConv
-    srclayers: "norm1"
-    convolution_conf {
-      num_filters: 32
-      kernel: 5
-      stride: 1
-      pad:2
-    }
-    param {
-      name: "w2"
-      init {
-        type:kGaussian
-        std:0.01
-      }
-    }
-    param {
-      name: "b2"
-      lr_scale:2.0
-      init {
-        type: kConstant
-        value:0
-      }
-    }
-  }
-  layer {
-    partition_dim: 0
-    name: "relu2"
-    type: kCudnnActivation
-    activation_conf {
-      type: RELU
-    }
-    srclayers:"conv2"
-  }
-  layer {
-    partition_dim: 0
-    name: "pool2"
-    type: kCudnnPool
-    srclayers: "relu2"
-    pooling_conf {
-      pool: AVG
-      kernel: 3
-      stride: 2
-    }
-  }
-  layer {
-    partition_dim: 0
-    name: "norm2"
-    type: kCudnnLRN
-    lrn_conf {
-      local_size: 3
-      alpha: 5e-05
-      beta: 0.75
-    }
-    srclayers:"pool2"
-  }
-  layer {
-    partition_dim: 0
-    name: "conv3"
-    type: kCudnnConv
-    srclayers: "norm2"
-    convolution_conf {
-      num_filters: 64
-      kernel: 5
-      stride: 1
-      pad:2
-    }
-    param {
-      name: "w3"
-      init {
-        type:kGaussian
-        std:0.01
-      }
-    }
-    param {
-      name: "b3"
-      init {
-        type: kConstant
-        value:0
-      }
-    }
-  }
-  layer {
-    partition_dim: 0
-    name: "relu3"
-    type: kCudnnActivation
-    activation_conf {
-      type: RELU
-    }
-    srclayers:"conv3"
-  }
-  layer {
-    partition_dim: 0
-    name: "pool3"
-    type: kCudnnPool
-    srclayers: "relu3"
-    pooling_conf {
-      pool: AVG
-      kernel: 3
-      stride: 2
-    }
-  }
-  layer {
-    partition_dim: 1
-    name: "ip1"
-    type: kInnerProduct
-    srclayers:"pool3"
-    innerproduct_conf {
-      num_output: 10
-    }
-    param {
-      name: "w4"
-      wd_scale:250
-      init {
-        type:kGaussian
-        std:0.01
-      }
-    }
-    param {
-      name: "b4"
-      lr_scale:2.0
-      wd_scale:0
-      init {
-        type: kConstant
-        value:0
-      }
-    }
-  }
-#  layer {
-#   name : "softmax"
-#   type: kSoftmax
-#   srclayers: "ip1"
-#  }
-#
-#  layer {
-#   name : "argsort"
-#   type: kArgSort
-#   srclayers: "softmax"
-#  }
-  layer{
-    partition_dim: 0
-    name: "loss"
-    type: kSoftmaxLoss
-    softmaxloss_conf{
-      topk:1
-    }
-    srclayers:"ip1"
-    srclayers: "data"
-  }
-# uncomment "softmax", "argsort", "output" layer and comment "loss" layer
-# to extract features from argsort
-#  layer {
-#    name : "output"
-#    type: kCSVOutput
-#    srclayers: "argsort"
-#    store_conf {
-#      path: "examples/cifar10/out.csv"
-#    }
-#  }
-}
-cluster {
-  nworker_groups: 1
-  nserver_groups: 1
-  nworkers_per_group: 2
-  nworkers_per_procs: 2
-  workspace: "examples/cifar10"
-}

http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/dd1e4afa/examples/cifar10/hybrid.conf
----------------------------------------------------------------------
diff --git a/examples/cifar10/hybrid.conf b/examples/cifar10/hybrid.conf
deleted file mode 100644
index ec3da0c..0000000
--- a/examples/cifar10/hybrid.conf
+++ /dev/null
@@ -1,292 +0,0 @@
-name: "cifar10-convnet"
-train_steps: 1000
-test_steps: 0
-test_freq: 200
-#validate_steps: 100
-#validate_freq: 300
-disp_freq: 30
-#debug: true
-#checkpoint_path: "examples/cifar10/checkpoint/step1000-worker0"
-train_one_batch {
-  alg: kBP
-}
-updater{
-  type: kSGD
-  weight_decay:0.004
-  momentum:0.9
-  learning_rate {
-    type: kFixedStep
-    fixedstep_conf:{
-      step:0
-      step:60000
-      step:65000
-      step_lr:0.001
-      step_lr:0.0001
-      step_lr:0.00001
-    }
-  }
-}
-neuralnet {
-  layer{
-    name: "data"
-    type: kRecordInput
-    store_conf {
-      backend: "kvfile"
-      path: "examples/cifar10/train_data.bin"
-      mean_file: "examples/cifar10/image_mean.bin"
-      batchsize: 100
-      #random_skip: 5000
-      shape: 3
-      shape: 32
-      shape: 32
-    }
-    include: kTrain
-  }
-#  layer{
-#    name: "data"
-#    type: kRecordInput
-#    store_conf {
-#      backend: "kvfile"
-#      path: "examples/cifar10/val_data.bin"
-#      mean_file: "examples/cifar10/image_mean.bin"
-#      batchsize: 64
-#      random_skip: 5000
-#      shape: 3
-#      shape: 32
-#      shape: 32
-#    }
-#    include: kVal
-#  }
-  layer{
-    name: "data"
-    type: kRecordInput
-    store_conf {
-      backend: "kvfile"
-      path: "examples/cifar10/test_data.bin"
-      mean_file: "examples/cifar10/image_mean.bin"
-      batchsize: 100
-      shape: 3
-      shape: 32
-      shape: 32
-    }
-    include: kTest
-  }
-
-  layer {
-    partition_dim: 0
-    name: "conv1"
-    type: kCConvolution
-    srclayers: "data"
-    convolution_conf {
-      num_filters: 32
-      kernel: 5
-      stride: 1
-      pad:2
-    }
-    param {
-      name: "w1"
-      init {
-        type:kGaussian
-        std:0.0001
-      }
-    }
-    param {
-      name: "b1"
-      lr_scale:2.0
-      init {
-        type: kConstant
-        value:0
-      }
-    }
-  }
-
-  layer {
-    partition_dim: 0
-    name: "pool1"
-    type: kCPooling
-    srclayers: "conv1"
-    pooling_conf {
-      pool: MAX
-      kernel: 3
-      stride: 2
-    }
-  }
-  layer {
-    partition_dim: 0
-    name: "relu1"
-    type: kReLU
-    srclayers:"pool1"
-  }
-  layer {
-    partition_dim: 0
-    name: "norm1"
-    type: kLRN
-    lrn_conf {
-      local_size: 3
-      alpha: 5e-05
-      beta: 0.75
-    }
-    srclayers:"relu1"
-  }
-  layer {
-    partition_dim: 0
-    name: "conv2"
-    type: kCConvolution
-    srclayers: "norm1"
-    convolution_conf {
-      num_filters: 32
-      kernel: 5
-      stride: 1
-      pad:2
-    }
-    param {
-      name: "w2"
-      init {
-        type:kGaussian
-        std:0.01
-      }
-    }
-    param {
-      name: "b2"
-      lr_scale:2.0
-      init {
-        type: kConstant
-        value:0
-      }
-    }
-  }
-  layer {
-    partition_dim: 0
-    name: "relu2"
-    type: kReLU
-    srclayers:"conv2"
-  }
-  layer {
-    partition_dim: 0
-    name: "pool2"
-    type: kCPooling
-    srclayers: "relu2"
-    pooling_conf {
-      pool: AVG
-      kernel: 3
-      stride: 2
-    }
-  }
-  layer {
-    partition_dim: 0
-    name: "norm2"
-    type: kLRN
-    lrn_conf {
-      local_size: 3
-      alpha: 5e-05
-      beta: 0.75
-    }
-    srclayers:"pool2"
-  }
-  layer {
-    partition_dim: 0
-    name: "conv3"
-    type: kCConvolution
-    srclayers: "norm2"
-    convolution_conf {
-      num_filters: 64
-      kernel: 5
-      stride: 1
-      pad:2
-    }
-    param {
-      name: "w3"
-      init {
-        type:kGaussian
-        std:0.01
-      }
-    }
-    param {
-      name: "b3"
-      init {
-        type: kConstant
-        value:0
-      }
-    }
-  }
-  layer {
-    partition_dim: 0
-    name: "relu3"
-    type: kReLU
-    srclayers:"conv3"
-  }
-  layer {
-    partition_dim: 0
-    name: "pool3"
-    type: kCPooling
-    srclayers: "relu3"
-    pooling_conf {
-      pool: AVG
-      kernel: 3
-      stride: 2
-    }
-  }
-  layer {
-    partition_dim: 1
-    name: "ip1"
-    type: kInnerProduct
-    srclayers:"pool3"
-    innerproduct_conf {
-      num_output: 10
-    }
-    param {
-      name: "w4"
-      wd_scale:250
-      init {
-        type:kGaussian
-        std:0.01
-      }
-    }
-    param {
-      name: "b4"
-      lr_scale:2.0
-      wd_scale:0
-      init {
-        type: kConstant
-        value:0
-      }
-    }
-  }
-#  layer {
-#   name : "softmax"
-#   type: kSoftmax
-#   srclayers: "ip1"
-#  }
-#
-#  layer {
-#   name : "argsort"
-#   type: kArgSort
-#   srclayers: "softmax"
-#  }
-  layer{
-    name: "loss"
-    type: kSoftmaxLoss
-    softmaxloss_conf{
-      topk:1
-    }
-    srclayers:"ip1"
-    srclayers: "data"
-  }
-# uncomment "softmax", "argsort", "output" layer and comment "loss" layer
-# to extract features from argsort
-#  layer {
-#    name : "output"
-#    type: kCSVOutput
-#    srclayers: "argsort"
-#    store_conf {
-#      path: "examples/cifar10/out.csv"
-#    }
-#  }
-}
-cluster {
-  nworker_groups: 1
-  nserver_groups: 1
-  nworkers_per_group: 2
-  nworkers_per_procs: 2
-  workspace: "examples/cifar10"
-}

http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/dd1e4afa/examples/cifar10/job.conf
----------------------------------------------------------------------
diff --git a/examples/cifar10/job.conf b/examples/cifar10/job.conf
deleted file mode 100644
index d20b452..0000000
--- a/examples/cifar10/job.conf
+++ /dev/null
@@ -1,279 +0,0 @@
-name: "cifar10-convnet"
-train_steps: 1000
-test_steps: 100
-test_freq: 200
-#validate_steps: 100
-#validate_freq: 300
-disp_freq: 50
-#checkpoint_path: "examples/cifar10/checkpoint/step1000-worker0"
-train_one_batch {
-  alg: kBP
-}
-updater{
-  type: kSGD
-  weight_decay:0.004
-  momentum:0.9
-  learning_rate {
-    type: kFixedStep
-    fixedstep_conf:{
-      step:0
-      step:60000
-      step:65000
-      step_lr:0.001
-      step_lr:0.0001
-      step_lr:0.00001
-    }
-  }
-}
-neuralnet {
-  layer{
-    name: "data"
-    type: kRecordInput
-    store_conf {
-      backend: "kvfile"
-      path: "examples/cifar10/train_data.bin"
-      mean_file: "examples/cifar10/image_mean.bin"
-      batchsize: 100
-      #random_skip: 5000
-      shape: 3
-      shape: 32
-      shape: 32
-    }
-    include: kTrain
-  }
-#  layer{
-#    name: "data"
-#    type: kRecordInput
-#    store_conf {
-#      backend: "kvfile"
-#      path: "examples/cifar10/val_data.bin"
-#      mean_file: "examples/cifar10/image_mean.bin"
-#      batchsize: 64
-#      random_skip: 5000
-#      shape: 3
-#      shape: 32
-#      shape: 32
-#    }
-#    include: kVal
-#  }
-  layer{
-    name: "data"
-    type: kRecordInput
-    store_conf {
-      backend: "kvfile"
-      path: "examples/cifar10/test_data.bin"
-      mean_file: "examples/cifar10/image_mean.bin"
-      batchsize: 100
-      shape: 3
-      shape: 32
-      shape: 32
-    }
-    include: kTest
-  }
-
-  layer {
-    name: "conv1"
-    type: kCConvolution
-    srclayers: "data"
-    convolution_conf {
-      num_filters: 32
-      kernel: 5
-      stride: 1
-      pad:2
-    }
-    param {
-      name: "w1"
-      init {
-        type:kGaussian
-        std:0.0001
-      }
-    }
-    param {
-      name: "b1"
-      lr_scale:2.0
-      init {
-        type: kConstant
-        value:0
-      }
-    }
-  }
-
-  layer {
-    name: "pool1"
-    type: kCPooling
-    srclayers: "conv1"
-    pooling_conf {
-      pool: MAX
-      kernel: 3
-      stride: 2
-    }
-  }
-  layer {
-    name: "relu1"
-    type: kReLU
-    srclayers:"pool1"
-  }
-  layer {
-    name: "norm1"
-    type: kLRN
-    lrn_conf {
-      local_size: 3
-      alpha: 5e-05
-      beta: 0.75
-    }
-    srclayers:"relu1"
-  }
-  layer {
-    name: "conv2"
-    type: kCConvolution
-    srclayers: "norm1"
-    convolution_conf {
-      num_filters: 32
-      kernel: 5
-      stride: 1
-      pad:2
-    }
-    param {
-      name: "w2"
-      init {
-        type:kGaussian
-        std:0.01
-      }
-    }
-    param {
-      name: "b2"
-      lr_scale:2.0
-      init {
-        type: kConstant
-        value:0
-      }
-    }
-  }
-  layer {
-    name: "relu2"
-    type: kReLU
-    srclayers:"conv2"
-  }
-  layer {
-    name: "pool2"
-    type: kCPooling
-    srclayers: "relu2"
-    pooling_conf {
-      pool: AVG
-      kernel: 3
-      stride: 2
-    }
-  }
-  layer {
-    name: "norm2"
-    type: kLRN
-    lrn_conf {
-      local_size: 3
-      alpha: 5e-05
-      beta: 0.75
-    }
-    srclayers:"pool2"
-  }
-  layer {
-    name: "conv3"
-    type: kCConvolution
-    srclayers: "norm2"
-    convolution_conf {
-      num_filters: 64
-      kernel: 5
-      stride: 1
-      pad:2
-    }
-    param {
-      name: "w3"
-      init {
-        type:kGaussian
-        std:0.01
-      }
-    }
-    param {
-      name: "b3"
-      init {
-        type: kConstant
-        value:0
-      }
-    }
-  }
-  layer {
-    name: "relu3"
-    type: kReLU
-    srclayers:"conv3"
-  }
-  layer {
-    name: "pool3"
-    type: kCPooling
-    srclayers: "relu3"
-    pooling_conf {
-      pool: AVG
-      kernel: 3
-      stride: 2
-    }
-  }
-  layer {
-    name: "ip1"
-    type: kInnerProduct
-    srclayers:"pool3"
-    innerproduct_conf {
-      num_output: 10
-    }
-    param {
-      name: "w4"
-      wd_scale:250
-      init {
-        type:kGaussian
-        std:0.01
-      }
-    }
-    param {
-      name: "b4"
-      lr_scale:2.0
-      wd_scale:0
-      init {
-        type: kConstant
-        value:0
-      }
-    }
-  }
-#  layer {
-#   name : "softmax"
-#   type: kSoftmax
-#   srclayers: "ip1"
-#  }
-#
-#  layer {
-#   name : "argsort"
-#   type: kArgSort
-#   srclayers: "softmax"
-#  }
-  layer{
-    name: "loss"
-    type: kSoftmaxLoss
-    softmaxloss_conf{
-      topk:1
-    }
-    srclayers:"ip1"
-    srclayers: "data"
-  }
-# uncomment "softmax", "argsort", "output" layer and comment "loss" layer
-# to extract features from argsort
-#  layer {
-#    name : "output"
-#    type: kCSVOutput
-#    srclayers: "argsort"
-#    store_conf {
-#      path: "examples/cifar10/out.csv"
-#    }
-#  }
-}
-cluster {
-  nworker_groups: 1
-  nserver_groups: 1
-  nworkers_per_group: 1
-  nworkers_per_procs: 1
-  workspace: "examples/cifar10"
-}

http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/dd1e4afa/examples/mnist/Makefile.example
----------------------------------------------------------------------
diff --git a/examples/mnist/Makefile.example b/examples/mnist/Makefile.example
deleted file mode 100644
index a041359..0000000
--- a/examples/mnist/Makefile.example
+++ /dev/null
@@ -1,49 +0,0 @@
-#
-#/**
-# * Licensed to the Apache Software Foundation (ASF) under one
-# * or more contributor license agreements.  See the NOTICE file
-# * distributed with this work for additional information
-# * regarding copyright ownership.  The ASF licenses this file
-# * to you 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.
-# */
-
-libs :=singa glog protobuf
-
-.PHONY: all download create
-
-HDFS_MNIST_TRAIN := hdfs://node0:9000/examples/mnist/train_data.bin
-HDFS_MNIST_TEST := hdfs://node0:9000/examples/mnist/test_data.bin
-
-download: mnist
-
-mnist:
-	wget http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz
-	wget http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz
-	wget http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz
-	wget http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz
-	gunzip train-images-idx3-ubyte.gz && gunzip train-labels-idx1-ubyte.gz
-	gunzip t10k-images-idx3-ubyte.gz && gunzip t10k-labels-idx1-ubyte.gz
-
-create:
-	$(CXX) create_data.cc -std=c++11 -lsinga -lprotobuf -lglog -I../../include \
-		-L../../.libs/ -Wl,-unresolved-symbols=ignore-in-shared-libs -Wl,-rpath=../../.libs/ \
-		-o create_data.bin
-	./create_data.bin train-images-idx3-ubyte train-labels-idx1-ubyte train_data.bin
-	./create_data.bin t10k-images-idx3-ubyte t10k-labels-idx1-ubyte test_data.bin
-
-create_hdfs:
-	$(CXX) create_data.cc -std=c++11 -lsinga -lprotobuf -lglog -lhdfs3 -I../../include \
-		-L../../.libs/ -Wl,-unresolved-symbols=ignore-in-shared-libs -Wl,-rpath=../../.libs/ \
-		-o create_data.bin
-	./create_data.bin train-images-idx3-ubyte train-labels-idx1-ubyte $(HDFS_MNIST_TRAIN)
-	./create_data.bin t10k-images-idx3-ubyte t10k-labels-idx1-ubyte $(HDFS_MNIST_TEST)

http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/dd1e4afa/examples/mnist/conv.conf
----------------------------------------------------------------------
diff --git a/examples/mnist/conv.conf b/examples/mnist/conv.conf
deleted file mode 100644
index 7818af1..0000000
--- a/examples/mnist/conv.conf
+++ /dev/null
@@ -1,187 +0,0 @@
-name: "conv"
-train_steps: 10000
-test_steps:100
-test_freq:500
-disp_freq:50
-train_one_batch {
-  alg: kBP
-}
-updater {
-  momentum:0.9
-  weight_decay:0.0005
-  type: kSGD
-  learning_rate {
-    type : kInverse
-    base_lr:0.01
-    inverse_conf {
-      gamma:0.0001
-      pow:0.75
-    }
-  }
-}
-neuralnet {
-  layer {
-    name: "data"
-    type: kRecordInput
-    store_conf {
-      backend: "kvfile"
-      path: "examples/mnist/train_data.bin"
-      batchsize: 64
-      std_value: 255
-      random_skip: 5000
-      shape: 1
-      shape: 28
-      shape: 28
-    }
-    include: kTrain
-  }
-
-  layer {
-    name: "data"
-    type: kRecordInput
-    store_conf {
-      backend: "kvfile"
-      path: "examples/mnist/test_data.bin"
-      std_value: 255
-      batchsize: 100
-      shape: 1
-      shape: 28
-      shape: 28
-    }
-    include: kTest
-  }
-
-  layer {
-    name: "conv1"
-    type: kCConvolution
-    srclayers: "data"
-    convolution_conf {
-      num_filters: 20
-      kernel: 5
-      stride: 1
-    }
-    param{
-      name: "w1"
-      init {
-        type : kUniformSqrtFanIn
-      }
-    }
-    param{
-      name: "b1"
-      init {
-        type : kConstant
-        value:0
-      }
-      lr_scale:2.0
-    }
-  }
-  layer {
-    name: "pool1"
-    type: kCPooling
-    srclayers: "conv1"
-    pooling_conf {
-      pool: MAX
-      kernel: 2
-      stride: 2
-    }
-  }
-  layer {
-    name: "conv2"
-    type: kCConvolution
-    srclayers: "pool1"
-    convolution_conf {
-      num_filters: 50
-      kernel: 5
-      stride: 1
-    }
-    param{
-      name: "w2"
-      init {
-        type :kUniformSqrtFanIn
-      }
-    }
-    param{
-      name: "b2"
-      init {
-        type : kConstant
-        value:0
-      }
-      lr_scale:2.0
-    }
-  }
-  layer {
-    name: "pool2"
-    type: kCPooling
-    srclayers: "conv2"
-    pooling_conf {
-      pool: MAX
-      kernel: 2
-      stride: 2
-    }
-  }
-  layer {
-    name: "ip1"
-    type: kInnerProduct
-    srclayers:"pool2"
-    innerproduct_conf {
-      num_output: 500
-    }
-    param{
-      name: "w3"
-      init {
-        type :kUniformSqrtFanIn
-      }
-    }
-    param{
-      name: "b3"
-      init {
-        type : kConstant
-        value:0
-      }
-      lr_scale:2.0
-    }
-  }
-
-  layer {
-    name: "relu1"
-    type: kReLU
-    srclayers:"ip1"
-  }
-
-  layer {
-    name: "ip2"
-    type: kInnerProduct
-    srclayers:"relu1"
-    innerproduct_conf {
-      num_output: 10
-    }
-    param {
-      name: "w4"
-      init {
-        type :kUniformSqrtFanIn
-      }
-    }
-    param {
-      name: "b4"
-      init {
-        type : kConstant
-        value:0
-      }
-      lr_scale:2
-    }
-  }
-  layer{
-    name: "loss"
-    type: kSoftmaxLoss
-    softmaxloss_conf{
-      topk:1
-    }
-    srclayers:"ip2"
-    srclayers:"data"
-  }
-}
-cluster {
-  nworker_groups: 1
-  nserver_groups: 1
-  workspace: "examples/mnist"
-}

http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/dd1e4afa/examples/mnist/create_data.cc
----------------------------------------------------------------------
diff --git a/examples/mnist/create_data.cc b/examples/mnist/create_data.cc
deleted file mode 100644
index 34c287f..0000000
--- a/examples/mnist/create_data.cc
+++ /dev/null
@@ -1,125 +0,0 @@
-/************************************************************
-*
-* Licensed to the Apache Software Foundation (ASF) under one
-* or more contributor license agreements.  See the NOTICE file
-* distributed with this work for additional information
-* regarding copyright ownership.  The ASF licenses this file
-* to you 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.
-*
-*************************************************************/
-
-//
-// This code creates DataShard for MNIST dataset.
-// It is adapted from the convert_mnist_data from Caffe
-//
-// Usage:
-//    create_shard.bin input_image_file input_label_file output_folder
-// The MNIST dataset could be downloaded at
-//    http://yann.lecun.com/exdb/mnist/
-
-#include <glog/logging.h>
-#include <cstdint>
-#include <iostream>
-
-#include <fstream>
-#include <string>
-
-#include "singa/io/store.h"
-#include "singa/utils/common.h"
-#include "singa/proto/common.pb.h"
-
-using std::string;
-
-uint32_t swap_endian(uint32_t val) {
-    val = ((val << 8) & 0xFF00FF00) | ((val >> 8) & 0xFF00FF);
-    return (val << 16) | (val >> 16);
-}
-
-// output is the full path, unlike create_data in CIFAR with only
-// specifies the directory
-void create_data(const char* image_filename, const char* label_filename,
-        const char* output) {
-  // Open files
-  std::ifstream image_file(image_filename, std::ios::in | std::ios::binary);
-  std::ifstream label_file(label_filename, std::ios::in | std::ios::binary);
-  CHECK(image_file) << "Unable to open file " << image_filename;
-  CHECK(label_file) << "Unable to open file " << label_filename;
-  // Read the magic and the meta data
-  uint32_t magic;
-  uint32_t num_items;
-  uint32_t num_labels;
-  uint32_t rows;
-  uint32_t cols;
-
-  image_file.read(reinterpret_cast<char*>(&magic), 4);
-  magic = swap_endian(magic);
-  CHECK_EQ(magic, 2051) << "Incorrect image file magic.";
-  label_file.read(reinterpret_cast<char*>(&magic), 4);
-  magic = swap_endian(magic);
-  CHECK_EQ(magic, 2049) << "Incorrect label file magic.";
-  image_file.read(reinterpret_cast<char*>(&num_items), 4);
-  num_items = swap_endian(num_items);
-  label_file.read(reinterpret_cast<char*>(&num_labels), 4);
-  num_labels = swap_endian(num_labels);
-  CHECK_EQ(num_items, num_labels);
-  image_file.read(reinterpret_cast<char*>(&rows), 4);
-  rows = swap_endian(rows);
-  image_file.read(reinterpret_cast<char*>(&cols), 4);
-  cols = swap_endian(cols);
-
-  // read backend from the job.conf
-  string store_backend = string(output).find("hdfs") != -1 ?
-                         "hdfsfile" : "kvfile";
-  auto store = singa::io::OpenStore(store_backend, output, singa::io::kCreate);
-  char label;
-  char* pixels = new char[rows * cols];
-  int count = 0;
-  const int kMaxKeyLength = 10;
-  char key[kMaxKeyLength];
-  string value;
-
-  singa::RecordProto image;
-  image.add_shape(rows);
-  image.add_shape(cols);
-  LOG(INFO) << "A total of " << num_items << " items.";
-  LOG(INFO) << "Rows: " << rows << " Cols: " << cols;
-  for (int item_id = 0; item_id < num_items; ++item_id) {
-    image_file.read(pixels, rows * cols);
-    label_file.read(&label, 1);
-    image.set_pixel(pixels, rows*cols);
-    image.set_label(label);
-    snprintf(key, kMaxKeyLength, "%08d", item_id);
-    image.SerializeToString(&value);
-    store->Write(string(key), value);
-  }
-  delete pixels;
-  store->Flush();
-  delete store;
-}
-
-int main(int argc, char** argv) {
-  if (argc != 4) {
-    std::cout << "This program create a DataShard for a MNIST dataset\n"
-        "Usage:\n"
-        "    create_shard.bin  input_image_file input_label_file"
-        " output_db_file\n"
-        "The MNIST dataset could be downloaded at\n"
-        "    http://yann.lecun.com/exdb/mnist/\n"
-        "You should gunzip them after downloading.";
-  } else {
-    google::InitGoogleLogging(argv[0]);
-    create_data(argv[1], argv[2], argv[3]);
-  }
-  return 0;
-}

http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/dd1e4afa/examples/mnist/job.conf
----------------------------------------------------------------------
diff --git a/examples/mnist/job.conf b/examples/mnist/job.conf
deleted file mode 100644
index 41d6b6f..0000000
--- a/examples/mnist/job.conf
+++ /dev/null
@@ -1,241 +0,0 @@
-name: "mlp"
-train_steps: 1000
-test_steps:10
-test_freq:60
-disp_freq:10
-train_one_batch {
-  alg: kBP
-}
-updater{
-  type: kSGD
-  learning_rate{
-    type : kStep
-    base_lr: 0.001
-    step_conf{
-      change_freq: 60
-      gamma: 0.997
-    }
-  }
-}
-
-neuralnet {
-  layer {
-    name: "data"
-    type: kRecordInput
-    store_conf {
-      backend: "kvfile"
-      path: "examples/mnist/train_data.bin"
-      random_skip: 5000
-      batchsize: 64
-      shape: 784
-      std_value: 127.5
-      mean_value: 127.5
-    }
-    include: kTrain
-  }
-
-  layer {
-    name: "data"
-    type: kRecordInput
-    store_conf {
-      backend: "kvfile"
-      path: "examples/mnist/test_data.bin"
-      batchsize: 100
-      shape: 784
-      std_value: 127.5
-      mean_value: 127.5
-    }
-    include: kTest
-  }
-
-  layer{
-    name: "fc1"
-    type: kInnerProduct
-    srclayers:"data"
-    innerproduct_conf{
-      num_output: 2500
-    }
-    param{
-      name: "w1"
-      init {
-        type: kUniform
-        low:-0.05
-        high:0.05
-      }
-    }
-    param{
-      name: "b1"
-      init {
-        type : kUniform
-        low: -0.05
-        high:0.05
-      }
-    }
-  }
-
-  layer{
-    name: "tanh1"
-    type: kSTanh
-    srclayers:"fc1"
-  }
-  layer{
-    name: "fc2"
-    type: kInnerProduct
-    srclayers:"tanh1"
-    innerproduct_conf{
-      num_output: 2000
-    }
-    param{
-      name: "w2"
-      init {
-        type: kUniform
-        low:-0.05
-        high:0.05
-      }
-    }
-    param{
-      name: "b2"
-      init {
-        type: kUniform
-        low: -0.05
-        high:0.05
-      }
-    }
-  }
-
-  layer{
-    name: "tanh2"
-    type: kSTanh
-    srclayers:"fc2"
-  }
-  layer{
-    name: "fc3"
-    type:  kInnerProduct
-    srclayers:"tanh2"
-    innerproduct_conf{
-      num_output: 1500
-    }
-    param{
-      name: "w3"
-      init{
-        type: kUniform
-        low:-0.05
-        high:0.05
-      }
-    }
-    param{
-      name: "b3"
-      init {
-        type : kUniform
-        low: -0.05
-        high:0.05
-      }
-    }
-
-  }
-
-  layer{
-    name: "tanh3"
-    type: kSTanh
-    srclayers:"fc3"
-  }
-  layer{
-    name: "fc4"
-    type: kInnerProduct
-    srclayers:"tanh3"
-    innerproduct_conf{
-      num_output: 1000
-    }
-    param{
-      name: "w4"
-      init {
-        type : kUniform
-        low:-0.05
-        high:0.05
-      }
-    }
-    param{
-      name: "b4"
-      init {
-        type : kUniform
-        low: -0.05
-        high:0.05
-      }
-    }
-
-  }
-
-  layer{
-    name: "tanh4"
-    type: kSTanh
-    srclayers:"fc4"
-  }
-  layer{
-    name: "fc5"
-    type: kInnerProduct
-    srclayers:"tanh4"
-    innerproduct_conf{
-      num_output: 500
-    }
-    param{
-      name: "w5"
-      init {
-        type : kUniform
-        low:-0.05
-        high:0.05
-      }
-    }
-    param{
-      name: "b5"
-      init {
-        type : kUniform
-        low: -0.05
-        high:0.05
-      }
-    }
-  }
-
-  layer{
-    name: "tanh5"
-    type: kSTanh
-    srclayers:"fc5"
-  }
-  layer{
-    name: "fc6"
-    type: kInnerProduct
-    srclayers:"tanh5"
-    innerproduct_conf{
-      num_output: 10
-    }
-    param{
-      name: "w6"
-      init {
-        type : kUniform
-        low:-0.05
-        high:0.05
-      }
-    }
-    param{
-      name: "b6"
-      init {
-        type : kUniform
-        low: -0.05
-        high:0.05
-      }
-    }
-  }
-  layer{
-    name: "loss"
-    type:kSoftmaxLoss
-    softmaxloss_conf{
-      topk:1
-    }
-    srclayers:"fc6"
-    srclayers:"data"
-  }
-}
-cluster {
-  nworker_groups: 1
-  nserver_groups: 1
-  workspace: "examples/mnist"
-}

http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/dd1e4afa/examples/mnist/rbm_job.conf
----------------------------------------------------------------------
diff --git a/examples/mnist/rbm_job.conf b/examples/mnist/rbm_job.conf
deleted file mode 100644
index 59a58dd..0000000
--- a/examples/mnist/rbm_job.conf
+++ /dev/null
@@ -1,95 +0,0 @@
-cluster {
-  nworker_groups: 1
-  nserver_groups: 1
-  nservers_per_group: 1
-  nworkers_per_group: 1
-  workspace: "examples/mnist"
-}
-
-model {
-  name: "deep-big-simple-dbm"
-  train_steps: 46000
-  test_steps:1
-  test_frequency:1000
-  display_frequency: 100
-  alg: kContrastiveDivergence
-  pcd_k: 15
-  updater{
-    base_lr: 0.1
-    lr_change: kFixed
-    type: kSGD
-  }
-
-  neuralnet {
-  layer {
-    name: "data"
-    type: kShardData
-    sharddata_conf {
-      path: "examples/mnist/mnist_train_shard"
-      batchsize: 20
-    }
-    include: kTrain
-  }
-
-
-  layer {
-    name: "data"
-    type: kShardData
-    sharddata_conf {
-      path: "examples/mnist/mnist_test_shard"
-      batchsize: 20
-    }
-    include: kTest
-  }
-
-
-  layer{
-    name:"mnist"
-    type: kMnist
-    srclayers: "data"
-    mnist_conf {
-      norm_a: 255
-      norm_b: 0
-    }
-  }
-
-  layer{
-    name: "RBMVis"
-    type: kRBMVis
-    srclayers:"mnist"
-    srclayers:"RBMHid"
-    rbmvis_conf{
-      num_output: 500
-    }
-    param{
-      name: "w1"
-      init_method: kUniformSqrtFanInOut
-      low:-9.79
-      high:9.79
-    }
-    param{
-      name: "b1"
-      init_method: kConstant
-      value: 0.0
-    }
-  }
-
-  layer{
-    name: "RBMHid"
-    type: kRBMHid
-    srclayers:"RBMVis"
-    rbmhid_conf{
-      hid_dim: 500
-    }
-    param{
-      name: "w2"
-      share_from: "w1"
-    }
-    param{
-      name: "b2"
-      init_method: kConstant
-      value: 0.0
-    }
-  }
-  }
-}



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