Merge remote-tracking branch 'internal/release_1.1.3'

Author: daisyden

CMakeLists.txt

@@ -10,8 +10,8 @@ endif()
 project(Caffe C CXX)
 
 # ---[ Caffe version
-set(CAFFE_TARGET_VERSION "1.1.2" CACHE STRING "Caffe logical version")
-set(CAFFE_TARGET_SOVERSION "1.1.2" CACHE STRING "Caffe soname version")
+set(CAFFE_TARGET_VERSION "1.1.3" CACHE STRING "Caffe logical version")
+set(CAFFE_TARGET_SOVERSION "1.1.3" CACHE STRING "Caffe soname version")
 add_definitions(-DCAFFE_VERSION=${CAFFE_TARGET_VERSION})
 
 # ---[ Using cmake scripts and modules

INSTALL.md

@@ -1,7 +1,9 @@
-# Installation
+#### Installation
+
 
 See http://caffe.berkeleyvision.org/installation.html for the latest
 installation instructions.
 
+
 Check the users group in case you need help:
 https://groups.google.com/forum/#!forum/caffe-users

Makefile

@@ -102,7 +102,7 @@ LIB_BUILD_DIR := $(BUILD_DIR)/lib
 STATIC_NAME := $(LIB_BUILD_DIR)/lib$(LIBRARY_NAME).a
 DYNAMIC_VERSION_MAJOR 		:= 1
 DYNAMIC_VERSION_MINOR 		:= 1
-DYNAMIC_VERSION_REVISION 	:= 2
+DYNAMIC_VERSION_REVISION 	:= 3
 DYNAMIC_NAME_SHORT := lib$(LIBRARY_NAME).so
 #DYNAMIC_SONAME_SHORT := $(DYNAMIC_NAME_SHORT).$(DYNAMIC_VERSION_MAJOR)
 DYNAMIC_VERSIONED_NAME_SHORT := $(DYNAMIC_NAME_SHORT).$(DYNAMIC_VERSION_MAJOR).$(DYNAMIC_VERSION_MINOR).$(DYNAMIC_VERSION_REVISION)

docker/README.md

@@ -17,7 +17,7 @@ docker run -ti caffe:cpu caffe --version
 ```
 which should show a message like:
 ```
-caffe version 1.1.2
+caffe version 1.1.3
 ```
 
 One can also build and run the Caffe tests in the image using:

examples/faster-rcnn/license.txt

@@ -0,0 +1,8 @@
+The MIT License
+Copyright (c) <year> <copyright holders>
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
+
+ The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

examples/pycaffe/tune_model.py

@@ -1,12 +1,14 @@
 import os
 import sys
 import argparse
+
+sys.path.insert(0, "python")
+import caffe
 from caffe.proto import caffe_pb2
 import google.protobuf.text_format as txtf
 import copy
 import utils
 
-
 def genOptimalModel(net, mkldnn_direct_time_map, mkldnn_winograd_time_map, optimal_model):
     for index in range(0, len(net.layer)):
         l = net.layer[index]
@@ -17,37 +19,21 @@ def genOptimalModel(net, mkldnn_direct_time_map, mkldnn_winograd_time_map, optim
             stride = 1
             if len(l.convolution_param.stride) != 0:
                 stride = l.convolution_param.stride[0]
-            if mkldnn_winograd_time_map[l.name] < mkldnn_direct_time_map[l.name] and kernel_size == 3 and stride == 1 and l.convolution_param.num_output % 16 == 0:
+            if kernel_size == 3 and stride == 1 and l.convolution_param.num_output % 16 ==0:
                 l.convolution_param.conv_algorithm = "winograd"
             else:
                 l.convolution_param.conv_algorithm = "direct"
-
+        
     with open(optimal_model, "w") as f:
         f.write(txtf.MessageToString(net, float_format=".17g"))
 
-
-def tuneModelDefinition(model_path, iteration, is_test_phase, core_num, socket_num):
-    working_dir = sys.path[0]
-    caffe_path = os.path.join(working_dir, "..", "..",
-                              "build", "tools", "caffe")
+def tuneModelDefinition(model_path, iteration):
+    working_dir = sys.argv[0]
+    
+    caffe_path = os.path.join(os.path.dirname(os.path.abspath(working_dir)), "../..",  "build", "tools", "caffe")
     if not os.path.exists(caffe_path):
         print "Caffe binary does not exist; please build Caffe binary first."
         sys.exit(1)
-    core_num_per_socket = int([i for i in os.popen('lscpu').readlines(
-    ) if i.startswith('Core(s) per socket:')][0].strip().split(':')[-1].strip())
-    core_num_per_socket *= socket_num
-    if is_test_phase:
-        caffe_path += ' time -phase TEST -forward_only'
-        if core_num != 0:
-            core_num = core_num_per_socket if core_num > core_num_per_socket else core_num
-            env_prefix = 'OMP_NUM_THREADS={} KMP_HW_SUBSET=1t KMP_AFFINITY=compact,granularity=fine numactl -C 0-{} -m 0 '.format(
-                core_num, core_num)
-        elif socket_num == 1:
-            env_prefix = 'OMP_NUM_THREADS={} KMP_HW_SUBSET=1t KMP_AFFINITY=compact,granularity=fine numactl -C 0-{} -m 0 '.format(
-                core_num_per_socket, core_num_per_socket)
-        else:
-            env_prefix = 'numactl -l '
-        caffe_path = env_prefix + caffe_path
 
     base_model_name = os.path.basename(model_path)
     model_dir = os.path.dirname(model_path)
@@ -83,30 +69,21 @@ def tuneModelDefinition(model_path, iteration, is_test_phase, core_num, socket_n
     mkldnn_winograd_log = "mkldnn_winograd.log"
     mkldnn_direct_log_path = os.path.join(model_dir, mkldnn_direct_log)
     mkldnn_winograd_log_path = os.path.join(model_dir, mkldnn_winograd_log)
-    mkldnn_direct_command = caffe_path + " -model " + direct_model_path + \
-        " -engine MKLDNN -iterations " + \
-        str(iteration) + " >& " + mkldnn_direct_log_path
+    mkldnn_direct_command = caffe_path + " time -model " + direct_model_path + " -engine MKLDNN -iterations " + str(iteration) + " >& " + mkldnn_direct_log_path
     os.system(mkldnn_direct_command)
-    mkldnn_winograd_command = caffe_path + " -model " + winograd_model_path + \
-        " -engine MKLDNN -iterations " + \
-        str(iteration) + " >& " + mkldnn_winograd_log_path
+    mkldnn_winograd_command = caffe_path + " time -model " + winograd_model_path + " -engine MKLDNN -iterations " + str(iteration) + " >& " + mkldnn_winograd_log_path
     os.system(mkldnn_winograd_command)
 
     (model_str, mkldnn_direct_time_lines) = utils.parseLog(mkldnn_direct_log_path)
-    mkldnn_direct_layer_time_map = utils.parseTimeLines(
-        mkldnn_direct_time_lines)
-    (model_str, mkldnn_winograd_time_lines) = utils.parseLog(
-        mkldnn_winograd_log_path)
-    mkldnn_winograd_layer_time_map = utils.parseTimeLines(
-        mkldnn_winograd_time_lines)
+    mkldnn_direct_layer_time_map = utils.parseTimeLines(mkldnn_direct_time_lines)
+    (model_str, mkldnn_winograd_time_lines) = utils.parseLog(mkldnn_winograd_log_path)
+    mkldnn_winograd_layer_time_map = utils.parseTimeLines(mkldnn_winograd_time_lines)
 
     hybrid_model_name = base_model_name.split(".")[0] + "_hybrid.prototxt"
     hybrid_model_path = os.path.join(model_dir, hybrid_model_name)
-    genOptimalModel(base_net, mkldnn_direct_layer_time_map,
-                    mkldnn_winograd_layer_time_map, hybrid_model_path)
+    genOptimalModel(base_net, mkldnn_direct_layer_time_map, mkldnn_winograd_layer_time_map, hybrid_model_path)
     print '{} has been generated.'.format(hybrid_model_path)
 
-
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
 
@@ -116,17 +93,7 @@ def tuneModelDefinition(model_path, iteration, is_test_phase, core_num, socket_n
     parser.add_argument('-i', '--iteration', action='store', dest='iterations', type=int, default=10,
                         help='require iterations number to run the model')
 
-    parser.add_argument('-t', '--phase', action='store', dest='is_test_phase', type=bool, default=False,
-                        help='Train or Test phase')
-
-    parser.add_argument('-c', '--core_num', action='store', dest='core_num', type=int, default=0,
-                        help='core number for inference')
-
-    parser.add_argument('-s', '--socket', action='store', dest='socket_num', type=int, default=2,
-                        help='socket number for inference')
-
-    parser.add_argument('-v', '--version', action='version',
-                        version='%(prog)s 1.0')
+    parser.add_argument('-v', '--version', action='version', version='%(prog)s 1.0')
 
     params = parser.parse_args()
 
@@ -135,5 +102,4 @@ def tuneModelDefinition(model_path, iteration, is_test_phase, core_num, socket_n
         print "[ERROR] Please specify the model definition file with -m"
         exit(1)
 
-    tuneModelDefinition(params.model, params.iterations,
-                        params.is_test_phase, params.core_num,  params.socket_num)
+    tuneModelDefinition(params.model, params.iterations)

examples/pycaffe/utils.py

@@ -1,5 +1,7 @@
 import os
 import sys
+sys.path.insert(0,"python")
+import caffe
 from caffe.proto import caffe_pb2
 import google.protobuf.text_format as txtf
 

examples/rfcn/license.txt

@@ -0,0 +1,8 @@
+The MIT License
+Copyright (c) <year> <copyright holders>
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
+
+ The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

external/mkl/prepare_mkl.sh

@@ -34,8 +34,8 @@
 # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
 # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
 # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
-# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-#
+# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.  
+# 
 FindLibrary()
 {
 # Find all the instances of the MKL libraries present in Caffe
@@ -74,11 +74,11 @@ echo $VERSION_LINE  # Return Version Line
 # MKL
 DST=`dirname $0`
 OMP=0 
-VERSION_MATCH=20180710
-ARCHIVE_BASENAME=mklml_lnx_2019.0.20180710.tgz
+VERSION_MATCH=20180928
+ARCHIVE_BASENAME=mklml_lnx_2019.0.1.20180928.tgz
 MKL_CONTENT_DIR=`echo $ARCHIVE_BASENAME | rev | cut -d "." -f 2- | rev`
 
-MKLURL="https://github.com/intel/mkl-dnn/releases/download/v0.16/$ARCHIVE_BASENAME"
+MKLURL="https://github.com/intel/mkl-dnn/releases/download/v0.17-rc/$ARCHIVE_BASENAME"
 # there are diffrent MKL lib to be used for GCC and for ICC
 reg='^[0-9]+$'
 VERSION_LINE=`GetVersionName $MKLROOT`

include/caffe/mkldnn_memory.hpp

@@ -64,7 +64,8 @@ class MKLDNNMemoryDescriptorBase : public PrvMemDescr
                                 , std::vector<float>scale=std::vector<float>(1,1.)
                                 , int mask=0
                                 , bool is_sum=false
-                                , bool is_wino=false);
+                                , bool is_wino=false
+                                , bool is_weight=false);
 
 
     ~MKLDNNMemoryDescriptorBase() {}
@@ -142,12 +143,12 @@ class MKLDNNMemoryDescriptorBase : public PrvMemDescr
           // TODO: may need initialize memory by 0
         }
     }
-    void set_prv_memory_pd(shared_ptr<memory::primitive_desc> memory_pd, std::vector<float> scale, int mask, bool is_wino)  {
+    void set_prv_memory_pd(shared_ptr<memory::primitive_desc> memory_pd, std::vector<float> scale, int mask, bool is_wino, bool is_weight)  {
         _prv_memory_pd = memory_pd;
         if (_prv_memory_pd && _usr_memory_pd) {
             check_usr_with_prv_descriptors();
             std::vector<float>scale_ext = std::vector<float>(1,1.);            
-            this->create_reorder_descriptors(scale, mask, scale_ext, false, is_wino);
+            this->create_reorder_descriptors(scale, mask, scale_ext, false, is_wino, is_weight);
         }
     }
 
@@ -163,7 +164,7 @@ class MKLDNNMemoryDescriptorBase : public PrvMemDescr
         _usr_memory_pd = memory_pd;
     }
 
-    void create_reorder_descriptors(std::vector<float> scale, int mask=0, std::vector<float>scale_ext=std::vector<float>(1,1.), bool is_sum=false, bool is_wino=false);
+    void create_reorder_descriptors(std::vector<float> scale, int mask=0, std::vector<float>scale_ext=std::vector<float>(1,1.), bool is_sum=false, bool is_wino=false, bool is_weight=false);
 
     shared_ptr<memory::primitive_desc> _usr_memory_pd;
     shared_ptr<memory::primitive_desc> _prv_memory_pd;
@@ -205,7 +206,8 @@ class MKLDNNMemoryDescriptor : public MKLDNNMemoryDescriptorBase<Dtype> {
                         , std::vector<float> scale=std::vector<float>(1,1.)
                         , int mask=0
                         , bool is_sum=false
-                        , bool is_wino=false);
+                        , bool is_wino=false
+                        , bool is_weight=false);
 
     virtual void convert_from_prv(void* cpu_ptr);
     virtual void convert_to_prv(void* cpu_ptr);
@@ -253,8 +255,9 @@ class MKLDNNData : public MKLDNNMemoryDescriptor<Dtype, false>
                 , std::vector<float> scale=std::vector<float>(1,1.)
                 , int mask=0
                 , bool is_sum=false
-                , bool is_wino=false)
-        : MKLDNNMemoryDescriptor<Dtype, false>(usr_memory_pd, prv_memory_pd, blob, mkldnn_layer, scale, mask, is_sum, is_wino) {}
+                , bool is_wino=false
+                , bool is_weight=false)
+        : MKLDNNMemoryDescriptor<Dtype, false>(usr_memory_pd, prv_memory_pd, blob, mkldnn_layer, scale, mask, is_sum, is_wino, is_weight) {}
 };
 
 template <typename Dtype>