tiny-cnn -> tiny-dnn

all file names, cmake paths, namespaces are renamed into tiny-dnn

.travis.yml

@@ -89,4 +89,4 @@ before_script:
             -DBUILD_TESTS=$BUILD_TESTS .;
     fi
 
-script: make -j2 && ./test/tiny_cnn_test
+script: make -j2 && ./test/tiny_dnn_test

CMakeLists.txt

@@ -8,7 +8,7 @@ cmake_minimum_required(VERSION 3.2 FATAL_ERROR)
 # Set variables:
 #   * PROJECT_NAME
 #   * PROJECT_VERSION
-project(tiny_cnn VERSION 0.1.0 LANGUAGES C CXX)
+project(tiny_dnn VERSION 0.1.0 LANGUAGES C CXX)
 
 #####
 # Enables link_directories() treat paths relative
@@ -39,14 +39,14 @@ endif(NOT CMAKE_BUILD_TYPE)
 
 ####
 # Define user options
-option(USE_SSE    "Build tiny-cnn with SSE library support"     ON)
-option(USE_AVX    "Build tiny-cnn with AVX library support"     ON)
-option(USE_AVX2   "Build tiny-cnn with AVX2 library support"   OFF)
-option(USE_TBB    "Build tiny-cnn with TBB library support"    OFF)
-option(USE_OMP    "Build tiny-cnn with OMP library support"    OFF)
-option(USE_NNPACK "Build tiny-cnn with NNPACK library support" OFF)
-option(USE_OPENCV "Build tiny-cnn with OpenCV library support" OFF)
-option(USE_OPENCL "Build tiny-cnn with OpenCL library support" OFF) 
+option(USE_SSE    "Build tiny-dnn with SSE library support"     ON)
+option(USE_AVX    "Build tiny-dnn with AVX library support"     ON)
+option(USE_AVX2   "Build tiny-dnn with AVX2 library support"   OFF)
+option(USE_TBB    "Build tiny-dnn with TBB library support"    OFF)
+option(USE_OMP    "Build tiny-dnn with OMP library support"    OFF)
+option(USE_NNPACK "Build tiny-dnn with NNPACK library support" OFF)
+option(USE_OPENCV "Build tiny-dnn with OpenCV library support" OFF)
+option(USE_OPENCL "Build tiny-dnn with OpenCL library support" OFF) 
 
 option(BUILD_TESTS    "Set to ON to build tests"         OFF)
 option(BUILD_EXAMPLES "Set to ON to build examples"      OFF)
@@ -56,7 +56,7 @@ option(BUILD_DOCS     "Set to ON to build documentation" OFF)
 # Create the library target
 
 set(project_library_target_name ${PROJECT_NAME})
-set(PACKAGE_NAME TinyCNN)
+set(PACKAGE_NAME TinyDNN)
 
 add_library(${project_library_target_name} INTERFACE)
 
@@ -66,18 +66,18 @@ add_library(${project_library_target_name} INTERFACE)
 # Using cmake scripts and modules
 list(APPEND CMAKE_MODULE_PATH ${PROJECT_SOURCE_DIR}/cmake/Modules)
 
-# Tiny-cnn provides a couple of multithreading solutions.
+# Tiny-dnn provides a couple of multithreading solutions.
 # The user can specify to use Intel Threading Building Blocks (TBB)
 # or Open Multi-Processing (OpenMP) as a backend for multi threading
-# processing. In case that none of this libraries are required, tiny-cnn
+# processing. In case that none of this libraries are required, tiny-dnn
 # will use the standard C++11 Thread support library.
 
 # Find Intel Threading Building Blocks (TBB)
 find_package(TBB QUIET)
 if(USE_TBB AND TBB_FOUND)
     message(STATUS "Found Intel TBB: ${TBB_INCLUDE_DIR}")
     # In case that TBB is found we force to disable OpenMP since
-    # tiny-cnn does not support mutiple multithreading backends.
+    # tiny-dnn does not support mutiple multithreading backends.
     set(USE_OMP OFF)
     #TODO: add definitions in configure
     add_definitions(-DCNN_USE_TBB)
@@ -97,7 +97,7 @@ find_package(OpenMP QUIET)
 if(USE_OMP AND OPENMP_FOUND)
     message(STATUS "Found OpenMP")
     # In case that OMP is found we force to disable Intel TBB since
-    # tiny-cnn does not support mutiple multithreading backends.
+    # tiny-dnn does not support mutiple multithreading backends.
     set(USE_TBB OFF)
     add_definitions(-DCNN_USE_OMP)
     set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} ${OpenMP_C_FLAGS}")
@@ -216,9 +216,9 @@ set(CMAKE_CXX_FLAGS_DEBUG   "${EXTRA_C_FLAGS_DEBUG}")
 
 ####
 # Write the config.h
-# TODO: replace for tiny_cnn/config.h
-# configure_file(cmake/Templates/tinycnn_config.h.in
-#               "${PROJECT_BINARY_DIR}/tinycnn_config.h")
+# TODO: replace for tiny_dnn/config.h
+# configure_file(cmake/Templates/tinydnn_config.h.in
+#               "${PROJECT_BINARY_DIR}/tinydnn_config.h")
 
 ####
 # Setup the cmake config files

Dockerfile

@@ -37,8 +37,8 @@ RUN apt-get install ninja-build && \
     python ./configure.py && \
     ninja
 
-# Download tiny-cnn
+# Download tiny-dnn
 RUN cd /software && \
-    git clone https://github.com/nyanp/tiny-cnn.git && \
-    cd /software/tiny-cnn && \
+    git clone https://github.com/tiny-dnn/tiny-dnn.git && \
+    cd /software/tiny-dnn && \
     git submodule update --init

LICENSE

@@ -26,7 +26,7 @@ modification, are permitted provided that the following conditions are met:
   this list of conditions and the following disclaimer in the documentation
   and/or other materials provided with the distribution.
 
-* Neither the name of tiny-cnn nor the names of its
+* Neither the name of tiny-dnn nor the names of its
   contributors may be used to endorse or promote products derived from
   this software without specific prior written permission.
 

README.md

@@ -21,16 +21,16 @@ tiny-dnn is a C++11 implementation of deep learning. It is suitable for deep lea
 Check out the [documentation](doc/readme.md) for more info.
 
 ## What's New
-- 2016/8/7  tiny-cnn is now moved to organization account, and rename into tiny-dnn :)
-- 2016/7/27 [tiny-cnn v0.1.1 released!](https://github.com/tiny-dnn/tiny-dnn/releases/tag/v0.1.1)
+- 2016/8/7  tiny-dnn is now moved to organization account, and rename into tiny-dnn :)
+- 2016/7/27 [tiny-dnn v0.1.1 released!](https://github.com/tiny-dnn/tiny-dnn/releases/tag/v0.1.1)
 
 ## Features
 - reasonably fast, without GPU
     - with TBB threading and SSE/AVX vectorization
     - 98.8% accuracy on MNIST in 13 minutes training (@Core i7-3520M)
 - portable & header-only
     - Run anywhere as long as you have a compiler which supports C++11
-    - Just include tiny_cnn.h and write your model in C++. There is nothing to install.
+    - Just include tiny_dnn.h and write your model in C++. There is nothing to install.
 - easy to integrate with real applications
     - no output to stdout/stderr
     - a constant throughput (simple parallelization model, no garbage collection)
@@ -139,13 +139,13 @@ You can edit include/config.h to customize default behavior.
 construct convolutional neural networks
 
 ```cpp
-#include "tiny_cnn/tiny_cnn.h"
-using namespace tiny_cnn;
-using namespace tiny_cnn::activation;
-using namespace tiny_cnn::layers;
+#include "tiny_dnn/tiny_dnn.h"
+using namespace tiny_dnn;
+using namespace tiny_dnn::activation;
+using namespace tiny_dnn::layers;
 
 void construct_cnn() {
-    using namespace tiny_cnn;
+    using namespace tiny_dnn;
 
     network<sequential> net;
 
@@ -183,10 +183,10 @@ void construct_cnn() {
 construct multi-layer perceptron(mlp)
 
 ```cpp
-#include "tiny_cnn/tiny_cnn.h"
-using namespace tiny_cnn;
-using namespace tiny_cnn::activation;
-using namespace tiny_cnn::layers;
+#include "tiny_dnn/tiny_dnn.h"
+using namespace tiny_dnn;
+using namespace tiny_dnn::activation;
+using namespace tiny_dnn::layers;
 
 void construct_mlp() {
     network<sequential> net;
@@ -202,9 +202,9 @@ void construct_mlp() {
 another way to construct mlp
 
 ```cpp
-#include "tiny_cnn/tiny_cnn.h"
-using namespace tiny_cnn;
-using namespace tiny_cnn::activation;
+#include "tiny_dnn/tiny_dnn.h"
+using namespace tiny_dnn;
+using namespace tiny_dnn::activation;
 
 void construct_mlp() {
     auto mynet = make_mlp<tan_h>({ 32 * 32, 300, 10 });
@@ -237,4 +237,4 @@ The BSD 3-Clause License
 ## Mailing list
 google group for questions and discussions:
 
-https://groups.google.com/forum/#!forum/tiny-cnn-users
+https://groups.google.com/forum/#!forum/tiny-dnn-users

appveyor.yml

@@ -28,7 +28,7 @@ before_build:
 
 after_build:
   - cmd: 'cd C:\projects\build\test\Release'
-  - cmd: tiny_cnn_test.exe
+  - cmd: tiny_dnn_test.exe
 
 build:
-  project: C:\projects\build\tiny_cnn.sln
+  project: C:\projects\build\tiny_dnn.sln

cmake/Templates/tinycnn-config-version.cmake.in → cmake/Templates/tinydnn-config-version.cmake.in

@@ -1,4 +1,4 @@
-set(PACKAGE_VERSION "@TINYCNN_VERSION@")
+set(PACKAGE_VERSION "@TINYDNN_VERSION@")
 
 # Check whether the requested PACKAGE_FIND_VERSION is compatible
 if("${PACKAGE_VERSION}" VERSION_LESS "${PACKAGE_FIND_VERSION}")

cmake/Templates/tinycnn-config.cmake.in → cmake/Templates/tinydnn-config.cmake.in

@@ -1,67 +1,67 @@
-# FindTinyCNN
+# FindTinyDNN
 # -----------
 #
-# Find TinyCNN include dirs and libraries
+# Find TinyDNN include dirs and libraries
 #
 # Use this module by invoking find_package with the form:
 #
-#   find_package(TinyCNN
+#   find_package(TinyDNN
 #     [version] [EXACT]      # Minimum or EXACT version e.g. 0.1.0
-#     [REQUIRED]             # Fail with error if TinyCNN is not found
+#     [REQUIRED]             # Fail with error if TinyDNN is not found
 #     ) 
 #
 # This module finds headers and requested component libraries OR a CMake
-# package configuration file provided by a "TinyCNN CMake" build. For the
-# latter case skip to the "TinyCNN CMake" section below. For the former
+# package configuration file provided by a "TinyDNN CMake" build. For the
+# latter case skip to the "TinyDNN CMake" section below. For the former
 # case results are reported in variables::
 #
-#   TinyCNN_FOUND            - True if headers and requested libraries were found
-#   TinyCNN_INCLUDE_DIRS     - TinyCNN include directories
-#   TinyCNN_LIBRARY_DIRS     - Link directories for TinyCNN libraries
-#   TinyCNN_LIBRARIES        - TinyCNN third-party libraries to be linked
-#   TinyCNN_VERSION          - Version string appended to library filenames
-#   TinyCNN_MAJOR_VERSION    - TinyCNN major version number (X in X.y.z)
-#   TinyCNN_MINOR_VERSION    - TinyCNN minor version number (Y in x.Y.z)
-#   TinyCNN_SUBMINOR_VERSION - TinyCNN subminor version number (Z in x.y.Z)
+#   TinyDNN_FOUND            - True if headers and requested libraries were found
+#   TinyDNN_INCLUDE_DIRS     - TinyDNN include directories
+#   TinyDNN_LIBRARY_DIRS     - Link directories for TinyDNN libraries
+#   TinyDNN_LIBRARIES        - TinyDNN third-party libraries to be linked
+#   TinyDNN_VERSION          - Version string appended to library filenames
+#   TinyDNN_MAJOR_VERSION    - TinyDNN major version number (X in X.y.z)
+#   TinyDNN_MINOR_VERSION    - TinyDNN minor version number (Y in x.Y.z)
+#   TinyDNN_SUBMINOR_VERSION - TinyDNN subminor version number (Z in x.y.Z)
 #
 # The following :prop_tgt:`IMPORTED` targets are also defined::
 #
-#   TinyCNN::tiny_cnn        - Target for header-only dependencies
-#                              (TinyCNN include directory)
+#   TinyDNN::tiny_cnn        - Target for header-only dependencies
+#                              (TinyDNN include directory)
 #
-# TinyCNN comes in many variants encoded in their file name.
+# TinyDNN comes in many variants encoded in their file name.
 # Users or projects may tell this module which variant to find by
 # setting variables::
 #
-#   TinyCNN_USE_TBB    - Set to ON to use the Intel Threading Building 
+#   TinyDNN_USE_TBB    - Set to ON to use the Intel Threading Building 
 #                        Blocks (TBB) libraries. Default is OFF.
-#   TinyCNN_USE_OMP    - Set to ON to use of the Open Multi-Processing
+#   TinyDNN_USE_OMP    - Set to ON to use of the Open Multi-Processing
 #                        (OpenMP) libraries. Default is OFF.
-#   TinyCNN_USE_SSE    - Set to OFF to use the Streaming SIMD Extension
+#   TinyDNN_USE_SSE    - Set to OFF to use the Streaming SIMD Extension
 #                        (SSE) instructions libraries. Default is ON.
-#   TinyCNN_USE_AVX    - Set to OFF to use the Advanced Vector Extensions
+#   TinyDNN_USE_AVX    - Set to OFF to use the Advanced Vector Extensions
 #                        (AVX) libraries). Default is ON.
-#   TinyCNN_USE_AVX2   - Set to ON to use the Advanced Vector Extensions 2
+#   TinyDNN_USE_AVX2   - Set to ON to use the Advanced Vector Extensions 2
 #                        (AVX2) libraries). Default is OFF.
-#   TinyCNN_USE_NNPACK - Set to ON to use the Acceleration package
+#   TinyDNN_USE_NNPACK - Set to ON to use the Acceleration package
 #                        for neural networks on multi-core CPUs.
 #
-# Example to find TinyCNN headers only::
+# Example to find TinyDNN headers only::
 #
-#   find_package(TinyCNN 0.1.0)
-#   if(TinyCNN_FOUND)
+#   find_package(TinyDNN 0.1.0)
+#   if(TinyDNN_FOUND)
 #     add_executable(foo foo.cc)
-#     target_link_libraries(foo TinyCNN::tiny_cnn)
+#     target_link_libraries(foo TinyDNN::tiny_cnn)
 #   endif()
 #
-# Example to find TinyCNN headers and some *static* libraries::
+# Example to find TinyDNN headers and some *static* libraries::
 #
-#   set(TinyCNN_USE_TBB              ON) # only find static libs
+#   set(TinyDNN_USE_TBB              ON) # only find static libs
 #   set(TInyCNN_USE_AVX2             ON)
-#   find_package(TinyCNN 0.1.0)
-#   if(TinyCNN_FOUND)
+#   find_package(TinyDNN 0.1.0)
+#   if(TinyDNN_FOUND)
 #     add_executable(foo foo.cc)
-#     target_link_libraries(foo TinyCNN::tiny_cnn ${TinyCNN_LIBRARIES})
+#     target_link_libraries(foo TinyDNN::tiny_cnn ${TinyDNN_LIBRARIES})
 #   endif()
 #
 ##################################################################
@@ -100,7 +100,7 @@ find_package(TBB QUIET)
 if(@PACKAGE_NAME@_USE_TBB AND TBB_FOUND)
     message(STATUS "Found Intel TBB: ${TBB_INCLUDE_DIR}")
     # In case that TBB is found we force to disable OpenMP since
-    # tiny-cnn does not support mutiple multithreading backends.
+    # tiny-dnn does not support mutiple multithreading backends.
     set(@PACKAGE_NAME@_USE_OMP OFF)
     #TODO: add definitions in configure
     add_definitions(-DCNN_USE_TBB)
@@ -120,7 +120,7 @@ find_package(OpenMP QUIET)
 if(@PACKAGE_NAME@_USE_OMP AND OPENMP_FOUND)
     message(STATUS "Found OpenMP")
     # In case that OMP is found we force to disable Intel TBB since
-    # tiny-cnn does not support mutiple multithreading backends.
+    # tiny-dnn does not support mutiple multithreading backends.
     set(@PACKAGE_NAME@_USE_TBB OFF)
     add_definitions(-DCNN_USE_OMP)
     set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} ${OpenMP_C_FLAGS}")

cmake/Templates/tinycnn_config.h.in → cmake/Templates/tinydnn_config.h.in

@@ -1,5 +1,5 @@
-#ifndef TINYCNN_CONFIG_HPP_
-#define TINYCNN_CONFIG_HPP_
+#ifndef TINYDNN_CONFIG_HPP_
+#define TINYDNN_CONFIG_HPP_
 
 /* Define if you want to use intel TBB library */
 #cmakedefine CNN_USE_TBB
@@ -16,4 +16,4 @@
 /* Define to enable avx vectorization */
 #cmakedefine CNN_USE_AVX
 
-#endif  // TINYCNN_CONFIG_HPP_
+#endif  // TINYDNN_CONFIG_HPP_

examples/CMakeLists.txt

@@ -44,7 +44,7 @@ target_link_libraries(example_cifar_train
 
 find_package(Protobuf QUIET)
 if(PROTOBUF_FOUND)
-    set(proto_file "${CMAKE_CURRENT_SOURCE_DIR}/tiny_cnn/io/caffe/caffe.pb.cc")
+    set(proto_file "${CMAKE_CURRENT_SOURCE_DIR}/tiny_dnn/io/caffe/caffe.pb.cc")
     if(EXISTS ${proto_file})
         add_executable(example_caffe_converter
                        caffe_converter/caffe_converter.cpp ${proto_file})
@@ -55,12 +55,12 @@ if(PROTOBUF_FOUND)
 # and should be installed separately as in: sudo apt-get install protobuf-compiler
     elseif(EXISTS ${PROTOBUF_PROTOC_EXECUTABLE})
         message(STATUS "Found PROTOBUF Compiler: ${PROTOBUF_PROTOC_EXECUTABLE}")
-        if(EXISTS ${CMAKE_CURRENT_SOURCE_DIR}/tiny_cnn/io/caffe/caffe.proto)
+        if(EXISTS ${CMAKE_CURRENT_SOURCE_DIR}/tiny_dnn/io/caffe/caffe.proto)
             PROTOBUF_GENERATE_CPP(PROTO_SRCS PROTO_HDRS
-                ${CMAKE_CURRENT_SOURCE_DIR}/tiny_cnn/io/caffe/caffe.proto)
+                ${CMAKE_CURRENT_SOURCE_DIR}/tiny_dnn/io/caffe/caffe.proto)
             if(EXISTS ${PROTO_HDRS})
-                file(COPY ${PROTO_SRCS} DESTINATION "${CMAKE_CURRENT_SOURCE_DIR}/tiny_cnn/io/caffe")
-                file(COPY ${PROTO_HDRS} DESTINATION "${CMAKE_CURRENT_SOURCE_DIR}/tiny_cnn/io/caffe")
+                file(COPY ${PROTO_SRCS} DESTINATION "${CMAKE_CURRENT_SOURCE_DIR}/tiny_dnn/io/caffe")
+                file(COPY ${PROTO_HDRS} DESTINATION "${CMAKE_CURRENT_SOURCE_DIR}/tiny_dnn/io/caffe")
             endif()
             add_executable(example_caffe_converter
                            caffe_converter/caffe_converter.cpp

examples/benchmarks/main.cpp

@@ -28,9 +28,9 @@
 
 #include <iostream>
 
-#include "tiny_cnn/tiny_cnn.h"
+#include "tiny_dnn/tiny_dnn.h"
 
-using namespace tiny_cnn;
+using namespace tiny_dnn;
 using namespace std;
 
 int  main(int argc, char** argv) {

examples/caffe_converter/readme.md

@@ -1,5 +1,5 @@
-# Import Caffe Model to tiny-cnn
-tiny-cnn can import Caffe's trained models.
+# Import Caffe Model to tiny-dnn
+tiny-dnn can import Caffe's trained models.
 
 ## Prerequisites for this example
 - Google protobuf
@@ -31,4 +31,4 @@ In the [pre-trained CaffeNet](https://github.com/BVLC/caffe/tree/master/examples
 ```
 
 ## Restrictions
-- tiny-cnn's converter only supports single input/single output network without branch.
+- tiny-dnn's converter only supports single input/single output network without branch.