From eafe24961d9178ce5a4df4042b7a7a4b8476e524 Mon Sep 17 00:00:00 2001
From: Evan Shelhamer <shelhamer@imaginarynumber.net>
Date: Thu, 28 Aug 2014 16:12:01 -0700
Subject: [PATCH 1/2] ignore caffe generated files and stop ignoring examples

- ignore models and snapshots, means, and input databases
- excluding exceptions to commits is easier than including exhaustively
---
 .gitignore | 9 +++++++--
 1 file changed, 7 insertions(+), 2 deletions(-)

diff --git a/.gitignore b/.gitignore
index d162cb42bb0..07eebe34591 100644
--- a/.gitignore
+++ b/.gitignore
@@ -47,11 +47,16 @@ python/caffe/proto/
 # User's build configuration
 Makefile.config
 
-# Data and examples are either
+# Data and models are either
 # 1. reference, and not casually committed
 # 2. custom, and live on their own unless they're deliberated contributed
 data/*
-examples/*
+*model
+*_iter_*
+*.solverstate
+*.binaryproto
+*leveldb
+*lmdb
 
 # Generated documentation
 docs/_site

From e79380631f036722c890430eef4eb6ebafb2a477 Mon Sep 17 00:00:00 2001
From: Evan Shelhamer <shelhamer@imaginarynumber.net>
Date: Thu, 28 Aug 2014 16:34:57 -0700
Subject: [PATCH 2/2] set examples paths relative to root

---
 examples/cifar10/cifar10_full_solver.prototxt     |  4 ++--
 examples/cifar10/cifar10_full_solver_lr1.prototxt |  4 ++--
 examples/cifar10/cifar10_full_solver_lr2.prototxt |  4 ++--
 examples/cifar10/cifar10_full_train_test.prototxt |  8 ++++----
 examples/cifar10/cifar10_quick_solver.prototxt    |  4 ++--
 .../cifar10/cifar10_quick_solver_lr1.prototxt     |  4 ++--
 .../cifar10/cifar10_quick_train_test.prototxt     |  8 ++++----
 examples/cifar10/convert_cifar_data.cpp           |  4 ++--
 examples/cifar10/create_cifar10.sh                | 13 ++++++-------
 .../pascal_finetune_solver.prototxt               | 14 ++++++++++++++
 .../pascal_finetune_train.prototxt                |  4 ++--
 .../pascal_finetune_val.prototxt                  |  4 ++--
 examples/imagenet/alexnet_solver.prototxt         |  4 ++--
 examples/imagenet/alexnet_train_val.prototxt      |  8 ++++----
 examples/imagenet/create_imagenet.sh              | 13 +++++++------
 examples/imagenet/get_caffe_alexnet_model.sh      |  2 +-
 .../imagenet/get_caffe_rcnn_imagenet_model.sh     |  3 ++-
 .../get_caffe_reference_imagenet_model.sh         |  2 +-
 examples/imagenet/imagenet_solver.prototxt        |  4 ++--
 examples/imagenet/imagenet_train_val.prototxt     |  8 ++++----
 examples/imagenet/make_imagenet_mean.sh           |  6 ++----
 examples/imagenet/resume_training.sh              |  8 +++-----
 examples/imagenet/time_imagenet.sh                |  6 +++---
 examples/imagenet/train_alexnet.sh                |  4 +---
 examples/imagenet/train_imagenet.sh               |  4 +---
 examples/mnist/create_mnist.sh                    | 15 +++++++++------
 examples/mnist/lenet_consolidated_solver.prototxt |  8 ++++----
 examples/mnist/lenet_solver.prototxt              |  4 ++--
 examples/mnist/lenet_train_test.prototxt          |  4 ++--
 examples/mnist/mnist_autoencoder.prototxt         |  4 ++--
 examples/mnist/mnist_autoencoder_solver.prototxt  |  4 ++--
 examples/mnist/train_lenet.sh                     |  4 +---
 examples/mnist/train_lenet_consolidated.sh        |  5 ++---
 examples/mnist/train_mnist_autoencoder.sh         |  6 +++---
 .../pascal_finetune_solver.prototxt               | 14 --------------
 35 files changed, 104 insertions(+), 111 deletions(-)
 create mode 100644 examples/finetune_pascal_detection/pascal_finetune_solver.prototxt
 rename examples/{pascal-finetuning => finetune_pascal_detection}/pascal_finetune_train.prototxt (97%)
 rename examples/{pascal-finetuning => finetune_pascal_detection}/pascal_finetune_val.prototxt (97%)
 delete mode 100644 examples/pascal-finetuning/pascal_finetune_solver.prototxt

diff --git a/examples/cifar10/cifar10_full_solver.prototxt b/examples/cifar10/cifar10_full_solver.prototxt
index d8e0bb27c44..f30b3986142 100644
--- a/examples/cifar10/cifar10_full_solver.prototxt
+++ b/examples/cifar10/cifar10_full_solver.prototxt
@@ -2,7 +2,7 @@
 # then another factor of 10 after 10 more epochs (5000 iters)
 
 # The train/test net protocol buffer definition
-net: "cifar10_full_train_test.prototxt"
+net: "examples/cifar10/cifar10_full_train_test.prototxt"
 # test_iter specifies how many forward passes the test should carry out.
 # In the case of CIFAR10, we have test batch size 100 and 100 test iterations,
 # covering the full 10,000 testing images.
@@ -21,6 +21,6 @@ display: 200
 max_iter: 60000
 # snapshot intermediate results
 snapshot: 10000
-snapshot_prefix: "cifar10_full"
+snapshot_prefix: "examples/cifar10/cifar10_full"
 # solver mode: CPU or GPU
 solver_mode: GPU
diff --git a/examples/cifar10/cifar10_full_solver_lr1.prototxt b/examples/cifar10/cifar10_full_solver_lr1.prototxt
index 746f4fba15a..59bc5721f4c 100644
--- a/examples/cifar10/cifar10_full_solver_lr1.prototxt
+++ b/examples/cifar10/cifar10_full_solver_lr1.prototxt
@@ -2,7 +2,7 @@
 # then another factor of 10 after 10 more epochs (5000 iters)
 
 # The train/test net protocol buffer definition
-net: "cifar10_full_train_test.prototxt"
+net: "examples/cifar10/cifar10_full_train_test.prototxt"
 # test_iter specifies how many forward passes the test should carry out.
 # In the case of CIFAR10, we have test batch size 100 and 100 test iterations,
 # covering the full 10,000 testing images.
@@ -21,6 +21,6 @@ display: 200
 max_iter: 65000
 # snapshot intermediate results
 snapshot: 5000
-snapshot_prefix: "cifar10_full"
+snapshot_prefix: "examples/cifar10/cifar10_full"
 # solver mode: CPU or GPU
 solver_mode: GPU
diff --git a/examples/cifar10/cifar10_full_solver_lr2.prototxt b/examples/cifar10/cifar10_full_solver_lr2.prototxt
index 5a549ffc96d..d4ed5d8e041 100644
--- a/examples/cifar10/cifar10_full_solver_lr2.prototxt
+++ b/examples/cifar10/cifar10_full_solver_lr2.prototxt
@@ -2,7 +2,7 @@
 # then another factor of 10 after 10 more epochs (5000 iters)
 
 # The train/test net protocol buffer definition
-net: "cifar10_full_train_test.prototxt"
+net: "examples/cifar10/cifar10_full_train_test.prototxt"
 # test_iter specifies how many forward passes the test should carry out.
 # In the case of CIFAR10, we have test batch size 100 and 100 test iterations,
 # covering the full 10,000 testing images.
@@ -21,6 +21,6 @@ display: 200
 max_iter: 70000
 # snapshot intermediate results
 snapshot: 5000
-snapshot_prefix: "cifar10_full"
+snapshot_prefix: "examples/cifar10/cifar10_full"
 # solver mode: CPU or GPU
 solver_mode: GPU
diff --git a/examples/cifar10/cifar10_full_train_test.prototxt b/examples/cifar10/cifar10_full_train_test.prototxt
index c01fef46ac0..ffecceb2a39 100644
--- a/examples/cifar10/cifar10_full_train_test.prototxt
+++ b/examples/cifar10/cifar10_full_train_test.prototxt
@@ -5,10 +5,10 @@ layers {
   top: "data"
   top: "label"
   data_param {
-    source: "cifar10-leveldb/cifar-train-leveldb"
+    source: "examples/cifar10/cifar10_train_leveldb"
     batch_size: 100
     transform_param {
-      mean_file: "mean.binaryproto"
+      mean_file: "examples/cifar10/mean.binaryproto"
     }
   }
   include: { phase: TRAIN }
@@ -19,10 +19,10 @@ layers {
   top: "data"
   top: "label"
   data_param {
-    source: "cifar10-leveldb/cifar-test-leveldb"
+    source: "examples/cifar10/cifar10_test_leveldb"
     batch_size: 100
     transform_param {
-      mean_file: "mean.binaryproto"
+      mean_file: "examples/cifar10/mean.binaryproto"
     }
   }
   include: { phase: TEST }
diff --git a/examples/cifar10/cifar10_quick_solver.prototxt b/examples/cifar10/cifar10_quick_solver.prototxt
index cdd0722b3a0..14b4401ba16 100644
--- a/examples/cifar10/cifar10_quick_solver.prototxt
+++ b/examples/cifar10/cifar10_quick_solver.prototxt
@@ -1,7 +1,7 @@
 # reduce the learning rate after 8 epochs (4000 iters) by a factor of 10
 
 # The train/test net protocol buffer definition
-net: "cifar10_quick_train_test.prototxt"
+net: "examples/cifar10/cifar10_quick_train_test.prototxt"
 # test_iter specifies how many forward passes the test should carry out.
 # In the case of MNIST, we have test batch size 100 and 100 test iterations,
 # covering the full 10,000 testing images.
@@ -20,6 +20,6 @@ display: 100
 max_iter: 4000
 # snapshot intermediate results
 snapshot: 4000
-snapshot_prefix: "cifar10_quick"
+snapshot_prefix: "examples/cifar10/cifar10_quick"
 # solver mode: CPU or GPU
 solver_mode: GPU
diff --git a/examples/cifar10/cifar10_quick_solver_lr1.prototxt b/examples/cifar10/cifar10_quick_solver_lr1.prototxt
index 2ed54ad980f..d3af70c05e7 100644
--- a/examples/cifar10/cifar10_quick_solver_lr1.prototxt
+++ b/examples/cifar10/cifar10_quick_solver_lr1.prototxt
@@ -1,7 +1,7 @@
 # reduce the learning rate after 8 epochs (4000 iters) by a factor of 10
 
 # The train/test net protocol buffer definition
-net: "cifar10_quick_train_test.prototxt"
+net: "examples/cifar10/cifar10_quick_train_test.prototxt"
 # test_iter specifies how many forward passes the test should carry out.
 # In the case of MNIST, we have test batch size 100 and 100 test iterations,
 # covering the full 10,000 testing images.
@@ -20,6 +20,6 @@ display: 100
 max_iter: 5000
 # snapshot intermediate results
 snapshot: 5000
-snapshot_prefix: "cifar10_quick"
+snapshot_prefix: "examples/cifar10/cifar10_quick"
 # solver mode: CPU or GPU
 solver_mode: GPU
diff --git a/examples/cifar10/cifar10_quick_train_test.prototxt b/examples/cifar10/cifar10_quick_train_test.prototxt
index 779dacf6758..f708798c71c 100644
--- a/examples/cifar10/cifar10_quick_train_test.prototxt
+++ b/examples/cifar10/cifar10_quick_train_test.prototxt
@@ -5,10 +5,10 @@ layers {
   top: "data"
   top: "label"
   data_param {
-    source: "cifar10-leveldb/cifar-train-leveldb"
+    source: "examples/cifar10/cifar10_train_leveldb"
     batch_size: 100
     transform_param {
-      mean_file: "mean.binaryproto"
+      mean_file: "examples/cifar10/mean.binaryproto"
     }
   }
   include: { phase: TRAIN }
@@ -19,10 +19,10 @@ layers {
   top: "data"
   top: "label"
   data_param {
-    source: "cifar10-leveldb/cifar-test-leveldb"
+    source: "examples/cifar10/cifar10_test_leveldb"
     batch_size: 100
     transform_param {
-      mean_file: "mean.binaryproto"
+      mean_file: "examples/cifar10/mean.binaryproto"
     }
   }
   include: { phase: TEST }
diff --git a/examples/cifar10/convert_cifar_data.cpp b/examples/cifar10/convert_cifar_data.cpp
index 2d5589bd30a..90ecb6d9a88 100644
--- a/examples/cifar10/convert_cifar_data.cpp
+++ b/examples/cifar10/convert_cifar_data.cpp
@@ -48,7 +48,7 @@ void convert_dataset(const string& input_folder, const string& output_folder) {
   LOG(INFO) << "Writing Training data";
   leveldb::DB* train_db;
   leveldb::Status status;
-  status = leveldb::DB::Open(options, output_folder + "/cifar-train-leveldb",
+  status = leveldb::DB::Open(options, output_folder + "/cifar10_train_leveldb",
       &train_db);
   CHECK(status.ok()) << "Failed to open leveldb.";
   for (int fileid = 0; fileid < kCIFARTrainBatches; ++fileid) {
@@ -71,7 +71,7 @@ void convert_dataset(const string& input_folder, const string& output_folder) {
 
   LOG(INFO) << "Writing Testing data";
   leveldb::DB* test_db;
-  CHECK(leveldb::DB::Open(options, output_folder + "/cifar-test-leveldb",
+  CHECK(leveldb::DB::Open(options, output_folder + "/cifar10_test_leveldb",
       &test_db).ok()) << "Failed to open leveldb.";
   // Open files
   std::ifstream data_file((input_folder + "/test_batch.bin").c_str(),
diff --git a/examples/cifar10/create_cifar10.sh b/examples/cifar10/create_cifar10.sh
index 85757f345ef..ad5038e0c3e 100755
--- a/examples/cifar10/create_cifar10.sh
+++ b/examples/cifar10/create_cifar10.sh
@@ -1,19 +1,18 @@
 #!/usr/bin/env sh
 # This script converts the cifar data into leveldb format.
 
-EXAMPLES=../../build/examples/cifar10
-DATA=../../data/cifar10
-TOOLS=../../build/tools
+EXAMPLE=examples/cifar10
+DATA=data/cifar10
 
 echo "Creating leveldb..."
 
-rm -rf cifar10-leveldb
-mkdir cifar10-leveldb
+rm -rf $EXAMPLE/cifar10_train_leveldb $EXAMPLE/cifar10_test_leveldb
 
-$EXAMPLES/convert_cifar_data.bin $DATA ./cifar10-leveldb
+./build/examples/cifar10/convert_cifar_data.bin $DATA $EXAMPLE
 
 echo "Computing image mean..."
 
-$TOOLS/compute_image_mean.bin ./cifar10-leveldb/cifar-train-leveldb mean.binaryproto
+./build/tools/compute_image_mean $EXAMPLE/cifar10_train_leveldb \
+  $EXAMPLE/mean.binaryproto
 
 echo "Done."
diff --git a/examples/finetune_pascal_detection/pascal_finetune_solver.prototxt b/examples/finetune_pascal_detection/pascal_finetune_solver.prototxt
new file mode 100644
index 00000000000..54ba6350448
--- /dev/null
+++ b/examples/finetune_pascal_detection/pascal_finetune_solver.prototxt
@@ -0,0 +1,14 @@
+train_net: "examples/finetuning_pascal_detection/pascal_finetune_train.prototxt"
+test_net: "examples/finetuning_pascal_detection/pascal_finetune_val.prototxt"
+test_iter: 100
+test_interval: 1000
+base_lr: 0.001
+lr_policy: "step"
+gamma: 0.1
+stepsize: 20000
+display: 20
+max_iter: 100000
+momentum: 0.9
+weight_decay: 0.0005
+snapshot: 10000
+snapshot_prefix: "examples/finetuning_pascal_detection/pascal_det_finetune"
diff --git a/examples/pascal-finetuning/pascal_finetune_train.prototxt b/examples/finetune_pascal_detection/pascal_finetune_train.prototxt
similarity index 97%
rename from examples/pascal-finetuning/pascal_finetune_train.prototxt
rename to examples/finetune_pascal_detection/pascal_finetune_train.prototxt
index dfc60fe4b8a..ae7ee4ccf88 100644
--- a/examples/pascal-finetuning/pascal_finetune_train.prototxt
+++ b/examples/finetune_pascal_detection/pascal_finetune_train.prototxt
@@ -5,8 +5,8 @@ layers {
   top: "data"
   top: "label"
   window_data_param {
-    source: "window_file_2007_trainval.txt"
-    mean_file: "../../data/ilsvrc12/imagenet_mean.binaryproto"
+    source: "examples/finetune_pascal_detection/window_file_2007_trainval.txt"
+    mean_file: "data/ilsvrc12/imagenet_mean.binaryproto"
     batch_size: 128
     crop_size: 227
     mirror: true
diff --git a/examples/pascal-finetuning/pascal_finetune_val.prototxt b/examples/finetune_pascal_detection/pascal_finetune_val.prototxt
similarity index 97%
rename from examples/pascal-finetuning/pascal_finetune_val.prototxt
rename to examples/finetune_pascal_detection/pascal_finetune_val.prototxt
index 91ded585d85..30dd164c4fa 100644
--- a/examples/pascal-finetuning/pascal_finetune_val.prototxt
+++ b/examples/finetune_pascal_detection/pascal_finetune_val.prototxt
@@ -5,8 +5,8 @@ layers {
   top: "data"
   top: "label"
   window_data_param {
-    source: "window_file_2007_test.txt"
-    mean_file: "../../data/ilsvrc12/imagenet_mean.binaryproto"
+    source: "examples/finetune_pascal_detection/window_file_2007_test.txt"
+    mean_file: "data/ilsvrc12/imagenet_mean.binaryproto"
     batch_size: 128
     crop_size: 227
     mirror: true
diff --git a/examples/imagenet/alexnet_solver.prototxt b/examples/imagenet/alexnet_solver.prototxt
index a3aeae07dc7..94bda7f36a5 100644
--- a/examples/imagenet/alexnet_solver.prototxt
+++ b/examples/imagenet/alexnet_solver.prototxt
@@ -1,4 +1,4 @@
-net: "alexnet_train_val.prototxt"
+net: "examples/imagenet/alexnet_train_val.prototxt"
 test_iter: 1000
 test_interval: 1000
 base_lr: 0.01
@@ -10,5 +10,5 @@ max_iter: 450000
 momentum: 0.9
 weight_decay: 0.0005
 snapshot: 10000
-snapshot_prefix: "caffe_alexnet_train"
+snapshot_prefix: "examples/imagenet/caffe_alexnet"
 solver_mode: GPU
diff --git a/examples/imagenet/alexnet_train_val.prototxt b/examples/imagenet/alexnet_train_val.prototxt
index 8ffdb7a8f69..b0f5815e007 100644
--- a/examples/imagenet/alexnet_train_val.prototxt
+++ b/examples/imagenet/alexnet_train_val.prototxt
@@ -5,11 +5,11 @@ layers {
   top: "data"
   top: "label"
   data_param {
-    source: "ilsvrc12_train_leveldb"
+    source: "examples/imagenet/ilsvrc12_train_leveldb"
     batch_size: 256
     transform_param {
       crop_size: 227
-      mean_file: "../../data/ilsvrc12/imagenet_mean.binaryproto"
+      mean_file: "data/ilsvrc12/imagenet_mean.binaryproto"
       mirror: true
     }
   }
@@ -21,11 +21,11 @@ layers {
   top: "data"
   top: "label"
   data_param {
-    source: "ilsvrc12_val_leveldb"
+    source: "examples/imagenet/ilsvrc12_val_leveldb"
     batch_size: 50
     transform_param {
       crop_size: 227
-      mean_file: "../../data/ilsvrc12/imagenet_mean.binaryproto"
+      mean_file: "data/ilsvrc12/imagenet_mean.binaryproto"
       mirror: false
     }
   }
diff --git a/examples/imagenet/create_imagenet.sh b/examples/imagenet/create_imagenet.sh
index 79cb17c4692..a286b8fe74c 100755
--- a/examples/imagenet/create_imagenet.sh
+++ b/examples/imagenet/create_imagenet.sh
@@ -2,8 +2,9 @@
 # Create the imagenet leveldb inputs
 # N.B. set the path to the imagenet train + val data dirs
 
-TOOLS=../../build/tools
-DATA=../../data/ilsvrc12
+EXAMPLE=examples/imagenet
+DATA=data/ilsvrc12
+TOOLS=build/tools
 
 TRAIN_DATA_ROOT=/path/to/imagenet/train/
 VAL_DATA_ROOT=/path/to/imagenet/val/
@@ -35,22 +36,22 @@ fi
 
 echo "Creating train leveldb..."
 
-GLOG_logtostderr=1 $TOOLS/convert_imageset.bin \
+GLOG_logtostderr=1 $TOOLS/convert_imageset \
     --resize_height=$RESIZE_HEIGHT \
     --resize_width=$RESIZE_WIDTH \
     --shuffle \
     $TRAIN_DATA_ROOT \
     $DATA/train.txt \
-    ilsvrc12_train_leveldb
+    $EXAMPLE/ilsvrc12_train_leveldb
 
 echo "Creating val leveldb..."
 
-GLOG_logtostderr=1 $TOOLS/convert_imageset.bin \
+GLOG_logtostderr=1 $TOOLS/convert_imageset \
     --resize_height=$RESIZE_HEIGHT \
     --resize_width=$RESIZE_WIDTH \
     --shuffle \
     $VAL_DATA_ROOT \
     $DATA/val.txt \
-    ilsvrc12_val_leveldb
+    $EXAMPLE/ilsvrc12_val_leveldb
 
 echo "Done."
diff --git a/examples/imagenet/get_caffe_alexnet_model.sh b/examples/imagenet/get_caffe_alexnet_model.sh
index b680a32d1cc..7312ed93070 100755
--- a/examples/imagenet/get_caffe_alexnet_model.sh
+++ b/examples/imagenet/get_caffe_alexnet_model.sh
@@ -23,6 +23,6 @@ fi
 
 echo "Downloading..."
 
-wget http://dl.caffe.berkeleyvision.org/caffe_alexnet_model
+wget http://dl.caffe.berkeleyvision.org/$MODEL examples/imagenet/$MODEL
 
 echo "Done. Please run this command again to verify that checksum = $CHECKSUM."
diff --git a/examples/imagenet/get_caffe_rcnn_imagenet_model.sh b/examples/imagenet/get_caffe_rcnn_imagenet_model.sh
index c7f36edcbf0..9a8d0a155a0 100755
--- a/examples/imagenet/get_caffe_rcnn_imagenet_model.sh
+++ b/examples/imagenet/get_caffe_rcnn_imagenet_model.sh
@@ -23,5 +23,6 @@ fi
 
 echo "Downloading..."
 
-wget http://dl.caffe.berkeleyvision.org/$MODEL
+wget http://dl.caffe.berkeleyvision.org/$MODEL examples/imagenet/$MODEL
+
 echo "Done. Please run this command again to verify that checksum = $CHECKSUM."
diff --git a/examples/imagenet/get_caffe_reference_imagenet_model.sh b/examples/imagenet/get_caffe_reference_imagenet_model.sh
index 85007994051..f687ebfa79e 100755
--- a/examples/imagenet/get_caffe_reference_imagenet_model.sh
+++ b/examples/imagenet/get_caffe_reference_imagenet_model.sh
@@ -23,6 +23,6 @@ fi
 
 echo "Downloading..."
 
-wget http://dl.caffe.berkeleyvision.org/$MODEL
+wget http://dl.caffe.berkeleyvision.org/$MODEL examples/imagenet/$MODEL
 
 echo "Done. Please run this command again to verify that checksum = $CHECKSUM."
diff --git a/examples/imagenet/imagenet_solver.prototxt b/examples/imagenet/imagenet_solver.prototxt
index 1ad40fe71e7..5b5be4bb8a9 100644
--- a/examples/imagenet/imagenet_solver.prototxt
+++ b/examples/imagenet/imagenet_solver.prototxt
@@ -1,4 +1,4 @@
-net: "imagenet_train_val.prototxt"
+net: "examples/imagenet/imagenet_train_val.prototxt"
 test_iter: 1000
 test_interval: 1000
 base_lr: 0.01
@@ -10,5 +10,5 @@ max_iter: 450000
 momentum: 0.9
 weight_decay: 0.0005
 snapshot: 10000
-snapshot_prefix: "caffe_imagenet_train"
+snapshot_prefix: "examples/imagenet/caffe_imagenet"
 solver_mode: GPU
diff --git a/examples/imagenet/imagenet_train_val.prototxt b/examples/imagenet/imagenet_train_val.prototxt
index 5f9c83949f5..766d546a385 100644
--- a/examples/imagenet/imagenet_train_val.prototxt
+++ b/examples/imagenet/imagenet_train_val.prototxt
@@ -5,11 +5,11 @@ layers {
   top: "data"
   top: "label"
   data_param {
-    source: "ilsvrc12_train_leveldb"
+    source: "examples/imagenet/ilsvrc12_train_leveldb"
     batch_size: 256
     transform_param {
       crop_size: 227
-      mean_file: "../../data/ilsvrc12/imagenet_mean.binaryproto"
+      mean_file: "data/ilsvrc12/imagenet_mean.binaryproto"
       mirror: true
     }
   }
@@ -21,11 +21,11 @@ layers {
   top: "data"
   top: "label"
   data_param {
-    source: "ilsvrc12_val_leveldb"
+    source: "examples/imagenet/ilsvrc12_val_leveldb"
     batch_size: 50
     transform_param {
       crop_size: 227
-      mean_file: "../../data/ilsvrc12/imagenet_mean.binaryproto"
+      mean_file: "data/ilsvrc12/imagenet_mean.binaryproto"
       mirror: false
     }
   }
diff --git a/examples/imagenet/make_imagenet_mean.sh b/examples/imagenet/make_imagenet_mean.sh
index f3d69cf2f64..d3d0c9af5d2 100755
--- a/examples/imagenet/make_imagenet_mean.sh
+++ b/examples/imagenet/make_imagenet_mean.sh
@@ -2,9 +2,7 @@
 # Compute the mean image from the imagenet training leveldb
 # N.B. this is available in data/ilsvrc12
 
-TOOLS=../../build/tools
-DATA=../../data/ilsvrc12
-
-$TOOLS/compute_image_mean.bin ilsvrc12_train_leveldb $DATA/imagenet_mean.binaryproto
+./build/tools/compute_image_mean examples/imagenet/ilsvrc12_train_leveldb \
+  data/ilsvrc12/imagenet_mean.binaryproto
 
 echo "Done."
diff --git a/examples/imagenet/resume_training.sh b/examples/imagenet/resume_training.sh
index 9e00d93c469..3c964b56ffc 100755
--- a/examples/imagenet/resume_training.sh
+++ b/examples/imagenet/resume_training.sh
@@ -1,9 +1,7 @@
 #!/usr/bin/env sh
 
-TOOLS=../../build/tools
-
-$TOOLS/caffe train\
-    --solver=imagenet_solver.prototxt \
-    --snapshot=caffe_imagenet_train_10000.solverstate
+./build/tools/caffe train \
+    --solver=examples/imagenet/imagenet_solver.prototxt \
+    --snapshot=examples/imagenet/caffe_imagenet_10000.solverstate
 
 echo "Done."
diff --git a/examples/imagenet/time_imagenet.sh b/examples/imagenet/time_imagenet.sh
index c448b4977ce..3f46e0e0f97 100755
--- a/examples/imagenet/time_imagenet.sh
+++ b/examples/imagenet/time_imagenet.sh
@@ -1,7 +1,5 @@
 #!/usr/bin/env sh
 
-TOOLS=../../build/tools
-
 if [ -z "$1" ]; then
   echo "Using CPU! To time GPU mode, use:"
   echo "    ./time_imagenet.sh <device ID>"
@@ -12,6 +10,8 @@ else
   GPU="--gpu=$1"
 fi
 
-$TOOLS/caffe time --model=imagenet_train_val.prototxt ${GPU}
+./build/tools/caffe time \
+  --model=examples/imagenet/imagenet_train_val.prototxt \
+  ${GPU}
 
 echo "Done."
diff --git a/examples/imagenet/train_alexnet.sh b/examples/imagenet/train_alexnet.sh
index 6a7c0577413..1ddcbeee4b0 100755
--- a/examples/imagenet/train_alexnet.sh
+++ b/examples/imagenet/train_alexnet.sh
@@ -1,7 +1,5 @@
 #!/usr/bin/env sh
 
-TOOLS=../../build/tools
-
-$TOOLS/caffe train --solver=alexnet_solver.prototxt
+./build/tools/caffe train --solver=examples/imagenet/alexnet_solver.prototxt
 
 echo "Done."
diff --git a/examples/imagenet/train_imagenet.sh b/examples/imagenet/train_imagenet.sh
index 008b96c01a1..cba2ad59581 100755
--- a/examples/imagenet/train_imagenet.sh
+++ b/examples/imagenet/train_imagenet.sh
@@ -1,7 +1,5 @@
 #!/usr/bin/env sh
 
-TOOLS=../../build/tools
-
-$TOOLS/caffe train --solver=imagenet_solver.prototxt
+./build/tools/caffe train --solver=examples/imagenet/imagenet_solver.prototxt
 
 echo "Done."
diff --git a/examples/mnist/create_mnist.sh b/examples/mnist/create_mnist.sh
index ae75bec2ab2..ed6e36903c2 100755
--- a/examples/mnist/create_mnist.sh
+++ b/examples/mnist/create_mnist.sh
@@ -1,15 +1,18 @@
 #!/usr/bin/env sh
 # This script converts the mnist data into leveldb format.
 
-EXAMPLES=../../build/examples/mnist
-DATA=../../data/mnist
+EXAMPLE=examples/mnist
+DATA=data/mnist
+BUILD=build/examples/mnist
 
 echo "Creating leveldb..."
 
-rm -rf mnist-train-leveldb
-rm -rf mnist-test-leveldb
+rm -rf mnist_train_leveldb
+rm -rf mnist_test_leveldb
 
-$EXAMPLES/convert_mnist_data.bin $DATA/train-images-idx3-ubyte $DATA/train-labels-idx1-ubyte mnist-train-leveldb
-$EXAMPLES/convert_mnist_data.bin $DATA/t10k-images-idx3-ubyte $DATA/t10k-labels-idx1-ubyte mnist-test-leveldb
+$BUILD/convert_mnist_data.bin $DATA/train-images-idx3-ubyte \
+  $DATA/train-labels-idx1-ubyte $EXAMPLE/mnist_train_leveldb
+$BUILD/convert_mnist_data.bin $DATA/t10k-images-idx3-ubyte \
+  $DATA/t10k-labels-idx1-ubyte $EXAMPLE/mnist_test_leveldb
 
 echo "Done."
diff --git a/examples/mnist/lenet_consolidated_solver.prototxt b/examples/mnist/lenet_consolidated_solver.prototxt
index 2e69589c67f..8ff593f2781 100644
--- a/examples/mnist/lenet_consolidated_solver.prototxt
+++ b/examples/mnist/lenet_consolidated_solver.prototxt
@@ -22,7 +22,7 @@ display: 100
 max_iter: 10000
 # snapshot intermediate results
 snapshot: 5000
-snapshot_prefix: "lenet"
+snapshot_prefix: "examples/mnist/lenet"
 # Set a random_seed for repeatable results.
 # (For results that vary due to random initialization, comment out the below
 # line, or set to a negative integer -- e.g. "random_seed: -1")
@@ -50,7 +50,7 @@ net_param {
     top: "data"
     top: "label"
     data_param {
-      source: "mnist-train-leveldb"
+      source: "examples/mnist/mnist_train_leveldb"
       batch_size: 64
       transform_param {
         scale: 0.00390625
@@ -64,7 +64,7 @@ net_param {
     top: "data"
     top: "label"
     data_param {
-      source: "mnist-test-leveldb"
+      source: "examples/mnist/mnist_test_leveldb"
       batch_size: 100
       transform_param {
         scale: 0.00390625
@@ -81,7 +81,7 @@ net_param {
     top: "data"
     top: "label"
     data_param {
-      source: "mnist-train-leveldb"
+      source: "examples/mnist/mnist_train_leveldb"
       batch_size: 100
       transform_param {
         scale: 0.00390625
diff --git a/examples/mnist/lenet_solver.prototxt b/examples/mnist/lenet_solver.prototxt
index a3b33090472..2dfbc834f41 100644
--- a/examples/mnist/lenet_solver.prototxt
+++ b/examples/mnist/lenet_solver.prototxt
@@ -1,5 +1,5 @@
 # The train/test net protocol buffer definition
-net: "lenet_train_test.prototxt"
+net: "examples/mnist/lenet_train_test.prototxt"
 # test_iter specifies how many forward passes the test should carry out.
 # In the case of MNIST, we have test batch size 100 and 100 test iterations,
 # covering the full 10,000 testing images.
@@ -20,6 +20,6 @@ display: 100
 max_iter: 10000
 # snapshot intermediate results
 snapshot: 5000
-snapshot_prefix: "lenet"
+snapshot_prefix: "examples/mnist/lenet"
 # solver mode: CPU or GPU
 solver_mode: GPU
diff --git a/examples/mnist/lenet_train_test.prototxt b/examples/mnist/lenet_train_test.prototxt
index 578641d5b2d..8369af1daa0 100644
--- a/examples/mnist/lenet_train_test.prototxt
+++ b/examples/mnist/lenet_train_test.prototxt
@@ -5,7 +5,7 @@ layers {
   top: "data"
   top: "label"
   data_param {
-    source: "mnist-train-leveldb"
+    source: "examples/mnist/mnist_train_leveldb"
     batch_size: 64
     transform_param {
       scale: 0.00390625
@@ -19,7 +19,7 @@ layers {
   top: "data"
   top: "label"
   data_param {
-    source: "mnist-test-leveldb"
+    source: "examples/mnist/mnist_test_leveldb"
     batch_size: 100
     transform_param {
       scale: 0.00390625
diff --git a/examples/mnist/mnist_autoencoder.prototxt b/examples/mnist/mnist_autoencoder.prototxt
index 3af6b7afcb3..d0abc685f0b 100644
--- a/examples/mnist/mnist_autoencoder.prototxt
+++ b/examples/mnist/mnist_autoencoder.prototxt
@@ -4,7 +4,7 @@ layers {
   name: "data"
   type: DATA
   data_param {
-    source: "mnist-train-leveldb"
+    source: "examples/mnist/mnist_train_leveldb"
     batch_size: 100
     transform_param {
       scale: 0.0039215684
@@ -17,7 +17,7 @@ layers {
   name: "data"
   type: DATA
   data_param {
-    source: "mnist-test-leveldb"
+    source: "examples/mnist/mnist_test_leveldb"
     batch_size: 100
     transform_param {
       scale: 0.0039215684
diff --git a/examples/mnist/mnist_autoencoder_solver.prototxt b/examples/mnist/mnist_autoencoder_solver.prototxt
index ae1ddebccd2..af1202fc1fd 100644
--- a/examples/mnist/mnist_autoencoder_solver.prototxt
+++ b/examples/mnist/mnist_autoencoder_solver.prototxt
@@ -1,4 +1,4 @@
-net: "mnist_autoencoder.prototxt"
+net: "examples/mnist/mnist_autoencoder.prototxt"
 test_iter: 50
 test_interval: 100
 test_compute_loss: true
@@ -8,7 +8,7 @@ display: 20
 max_iter: 4000000
 weight_decay: 0.0005
 snapshot: 10000
-snapshot_prefix: "mnist_autoencoder_train"
+snapshot_prefix: "examples/mnist/mnist_autoencoder"
 momentum: 0.9
 # solver mode: CPU or GPU
 solver_mode: GPU
diff --git a/examples/mnist/train_lenet.sh b/examples/mnist/train_lenet.sh
index b93e48fb629..1b6bf7d978d 100755
--- a/examples/mnist/train_lenet.sh
+++ b/examples/mnist/train_lenet.sh
@@ -1,5 +1,3 @@
 #!/usr/bin/env sh
 
-TOOLS=../../build/tools
-
-$TOOLS/caffe train --solver=lenet_solver.prototxt
+./build/tools/caffe train --solver=examples/mnist/lenet_solver.prototxt
diff --git a/examples/mnist/train_lenet_consolidated.sh b/examples/mnist/train_lenet_consolidated.sh
index 83fe895ba0b..c855467897e 100755
--- a/examples/mnist/train_lenet_consolidated.sh
+++ b/examples/mnist/train_lenet_consolidated.sh
@@ -1,5 +1,4 @@
 #!/usr/bin/env sh
 
-TOOLS=../../build/tools
-
-$TOOLS/caffe train --solver=lenet_consolidated_solver.prototxt
+./build/tools/caffe train \
+  --solver=examples/mnist/lenet_consolidated_solver.prototxt
diff --git a/examples/mnist/train_mnist_autoencoder.sh b/examples/mnist/train_mnist_autoencoder.sh
index 628c74b969a..cfd67e82fda 100755
--- a/examples/mnist/train_mnist_autoencoder.sh
+++ b/examples/mnist/train_mnist_autoencoder.sh
@@ -1,4 +1,4 @@
-#!/bin/bash
-TOOLS=../../build/tools
+#!/usr/bin/env sh
 
-$TOOLS/caffe.bin train --solver=mnist_autoencoder_solver.prototxt
+./build/tools/caffe train \
+  --solver=examples/mnist/mnist_autoencoder_solver.prototxt
diff --git a/examples/pascal-finetuning/pascal_finetune_solver.prototxt b/examples/pascal-finetuning/pascal_finetune_solver.prototxt
deleted file mode 100644
index f2b80111e2f..00000000000
--- a/examples/pascal-finetuning/pascal_finetune_solver.prototxt
+++ /dev/null
@@ -1,14 +0,0 @@
-train_net: "pascal_finetune_train.prototxt"
-test_net: "pascal_finetune_val.prototxt"
-test_iter: 100
-test_interval: 1000
-base_lr: 0.001
-lr_policy: "step"
-gamma: 0.1
-stepsize: 20000
-display: 20
-max_iter: 100000
-momentum: 0.9
-weight_decay: 0.0005
-snapshot: 10000
-snapshot_prefix: "pascal_finetune_train"