Merge pull request #8 from dmlc/master

merge back

.gitignore

@@ -66,3 +66,5 @@ deps
 # R
 *.Rcheck
 *.rds
+*.Rproj
+.Rproj.user

.travis.yml

@@ -1,4 +1,3 @@
-# disable sudo to use container based build
 sudo: false
 
 language: cpp
@@ -18,6 +17,7 @@ env:
   - TASK=cpp_test
   # run tests/python
   - TASK=python_test
+  #- TASK=r_test
 
   # TODO, R test, distributed test, clang, more g++ versions
 
@@ -27,6 +27,8 @@ matrix:
       env: TASK=lint
     - os: osx
       env: TASK=doc
+    - os: linux
+      env: TASK=r_test
 
 # dependent apt packages
 addons:
@@ -67,10 +69,13 @@ cache:
 
 before_cache:
   - dmlc-core/scripts/travis/travis_before_cache.sh
+
+after_failure:
+  - tests/travis/travis_after_failure.sh
 
 notifications:
 # Emails are sent to the committer's git-configured email address by default,
   email:
     on_success: change
     on_failure: always
-  slack: dmlc:NmroCzntCiWOuxUZpii40USd
+  #slack: dmlc:NmroCzntCiWOuxUZpii40USd

CMakeLists.txt

@@ -9,6 +9,9 @@ mxnet_option(USE_OPENCV  "Build with OpenCV support" ON)
 mxnet_option(USE_OPENMP  "Build with Openmp support" ON)
 mxnet_option(USE_CUDNN   "Build with cudnn support"  ON) # one could set CUDNN_ROOT for search path
 mxnet_option(USE_CUDA    "Build with CUDA support"   ON)
+mxnet_option(USE_DIST_KVSTORE    "Build with DIST_KVSTORE support"   OFF)
+
+
 
 include(mshadow/cmake/mshadow.cmake)
 include(mshadow/cmake/Utils.cmake)
@@ -65,8 +68,8 @@ if(USE_CUDNN)
 endif()
 
 add_subdirectory("dmlc-core")
-if(NOT MSVC)
-  add_subdirectory("ps-lite")
+if(USE_DIST_KVSTORE)
+	add_subdirectory("ps-lite")
 endif()
 
 mxnet_source_group("Source"   GLOB_RECURSE "src/*.cc")
@@ -91,6 +94,7 @@ if(USE_CUDA)
   list(APPEND SOURCE ${cuda_objs} ${cuda})
 endif()
 
+
 if(NOT MSVC)
   # Only add c++11 flags and definitions after cuda compiling
   add_definitions(-DDMLC_USE_CXX11)
@@ -102,12 +106,18 @@ endif()
 add_library(mxnet SHARED ${SOURCE})
 target_link_libraries(mxnet ${mshadow_LINKER_LIBS})
 target_link_libraries(mxnet dmlccore)
-if(NOT MSVC)
-  target_link_libraries(mxnet pslite)
-  target_link_libraries(mxnet ${pslite_LINKER_LIBS})
-endif()
+
+
+
 set_target_properties(mxnet PROPERTIES OUTPUT_NAME "libmxnet")
 
+if(USE_DIST_KVSTORE)
+	add_definitions(-DMXNET_USE_DIST_KVSTORE)
+	target_link_libraries(mxnet pslite)
+	target_link_libraries(mxnet ${pslite_LINKER_LIBS})
+	include_directories(SYSTEM ${pslite_INCLUDE_DIR})
+endif()
+
 # ---[ Linter target
 if(MSVC)
   find_package(PythonInterp 2)

CONTRIBUTORS.md

@@ -26,6 +26,12 @@ The committers are the granted write access to the project.
   - Mingjie is the initiator, and contributes the design of the dependency engine.
 * [Chuntao Hong](https://github.com/hjk41)
   - Chuntao is the initiator and provides the initial design of engine.
+* [Chiyuan Zhang](https://github.com/pluskid)
+  - Chiyuan is the creator of MXNet Julia Package.
+* [Qiang Kou](https://github.com/thirdwing)
+  - KK is a R ninja, he makes mxnet available for R users.
+* [Tong He](https://github.com/hetong007)
+  - Tong is the major maintainer of MXNetR, he designs the mxnet interface and wrote many of the tutorials on R.
 
 ### Become a Comitter
 MXNet is a opensource project and we are actively looking for new comitters
@@ -39,12 +45,10 @@ List of Contributors
 --------------------
 * [Full List of Contributors](https://github.com/dmlc/mxnet/graphs/contributors)
   - To contributors: please add your name to the list when you submit a patch to the project:)
-* [Qiang Kou](https://github.com/thirdwing)
-  - KK is a R ninja, he makes mxnet available for R users.
-* [Tong He](https://github.com/hetong007)
-  - Tong is the major maintainer of MXNetR, he designs the mxnet interface and wrote many of the tutorials on R.
 * [Feng Wang](https://github.com/happynear)
   - Feng makes mxnet compatible with Windows Visual Studio.
+* [Jack Deng](https://github.com/jdeng)
+  - Jack created the amalgamation script and Go bind for mxnet.
 * [Li Dong](https://github.com/donglixp)
 * [Piji Li](https://github.com/lipiji)
 * [Hu Shiwen](https://github.com/yajiedesign)
@@ -55,3 +59,8 @@ List of Contributors
 * [Xiaodong](https://github.com/XD-DENG)
 * [Nan Xiao](https://github.com/road2stat)
 * [Junyuan Xie](https://github.com/piiswrong)
+* [Wei Wu](https://github.com/tornadomeet)
+* [Yuan Tang](https://github.com/terrytangyuan)
+  - Yuan set up the R Travis environment to make development safer.
+* [Michaël Benesty](https://github.com/pommedeterresautee)
+  -Michaël contributes the R visualization module of mxnet

R-package/DESCRIPTION

@@ -5,10 +5,21 @@ Version: 0.5
 Date: 2015-10-02
 Author: Tianqi Chen, Qiang Kou, Tong He
 Maintainer: Qiang Kou <[email protected]>
-Description: MXNet is a deep learning framework designed for both efficiency and flexibility. It allows you to mix the flavours of deep learning programs together to maximize the efficiency and your productivity.
+Description: MXNet is a deep learning framework designed for both efficiency
+    and flexibility. It allows you to mix the flavours of deep learning programs
+    together to maximize the efficiency and your productivity.
 License: BSD
 URL: https://github.com/dmlc/mxnet/R-package
 BugReports: https://github.com/dmlc/mxnet/issues
-Imports: methods, Rcpp (>= 0.11.1)
-Suggests: testthat
+Imports:
+    methods,
+    Rcpp (>= 0.11.1),
+    DiagrammeR,
+    data.table,
+    jsonlite,
+    magrittr,
+    stringr
+Suggests:
+    testthat
 LinkingTo: Rcpp
+RoxygenNote: 5.0.0

R-package/NAMESPACE

@@ -1,4 +1,4 @@
-# Generated by roxygen2 (4.1.1): do not edit by hand
+# Generated by roxygen2: do not edit by hand
 
 S3method(Ops,MXNDArray)
 S3method(as.array,MXNDArray)
@@ -9,6 +9,7 @@ S3method(predict,MXFeedForwardModel)
 S3method(print,MXNDArray)
 export(arguments)
 export(ctx)
+export(graph.viz)
 export(is.mx.context)
 export(is.mx.dataiter)
 export(is.mx.ndarray)
@@ -40,11 +41,14 @@ export(mx.model.FeedForward.create)
 export(mx.model.load)
 export(mx.model.save)
 export(mx.nd.array)
-export(mx.nd.choose.element)
+export(mx.nd.choose.element.0index)
 export(mx.nd.clip)
 export(mx.nd.copyto)
 export(mx.nd.dot)
+export(mx.nd.exp)
 export(mx.nd.load)
+export(mx.nd.log)
+export(mx.nd.norm)
 export(mx.nd.ones)
 export(mx.nd.save)
 export(mx.nd.sqrt)
@@ -58,6 +62,7 @@ export(mx.set.seed)
 export(mx.simple.bind)
 export(mx.symbol.Activation)
 export(mx.symbol.BatchNorm)
+export(mx.symbol.BlockGrad)
 export(mx.symbol.Concat)
 export(mx.symbol.Convolution)
 export(mx.symbol.Dropout)
@@ -74,10 +79,26 @@ export(mx.symbol.Reshape)
 export(mx.symbol.SliceChannel)
 export(mx.symbol.Softmax)
 export(mx.symbol.Variable)
+export(mx.symbol.exp)
 export(mx.symbol.infer.shape)
 export(mx.symbol.load)
+export(mx.symbol.log)
 export(mx.symbol.save)
+export(mx.symbol.sqrt)
+export(mx.symbol.square)
 export(mxnet.export)
 export(outputs)
 import(Rcpp)
 import(methods)
+importFrom(DiagrammeR,combine_edges)
+importFrom(DiagrammeR,create_edges)
+importFrom(DiagrammeR,create_graph)
+importFrom(DiagrammeR,create_nodes)
+importFrom(DiagrammeR,render_graph)
+importFrom(data.table,":=")
+importFrom(data.table,as.data.table)
+importFrom(data.table,data.table)
+importFrom(data.table,setkey)
+importFrom(jsonlite,fromJSON)
+importFrom(magrittr,"%>%")
+importFrom(stringr,str_extract_all)

R-package/R/mxnet_generated.R

@@ -2,7 +2,7 @@
 # Generated by mxnet.export, do not edit by hand.
 ######
 
-#' Choose one element from each line(row for python, column for R/Julia) in lhs according to index indicated by rhs
+#' Choose one element from each line(row for python, column for R/Julia) in lhs according to index indicated by rhs. This function assume rhs uses 0-based index.
 #' 
 #' @param lhs  NDArray
 #'     Left operand to the function.
@@ -11,7 +11,7 @@
 #' @return out The result mx.ndarray
 #' 
 #' @export
-#' @name mx.nd.choose.element
+#' @name mx.nd.choose.element.0index
 NULL
 
 #' Clip ndarray elements to range (a_min, a_max)
@@ -40,10 +40,40 @@ NULL
 #' @name mx.nd.dot
 NULL
 
-#' Take square root of the src
+#' Take exp of the src
 #' 
 #' @param src  NDArray
-#'     Source input to the function.
+#'     Source input to the function
+#' @return out The result mx.ndarray
+#' 
+#' @export
+#' @name mx.nd.exp
+NULL
+
+#' Take log of the src
+#' 
+#' @param src  NDArray
+#'     Source input to the function
+#' @return out The result mx.ndarray
+#' 
+#' @export
+#' @name mx.nd.log
+NULL
+
+#' Take L2 norm of the src.The result will be ndarray of shape (1,) on the same device.
+#' 
+#' @param src  NDArray
+#'     Source input to the function
+#' @return out The result mx.ndarray
+#' 
+#' @export
+#' @name mx.nd.norm
+NULL
+
+#' Take sqrt of the src
+#' 
+#' @param src  NDArray
+#'     Source input to the function
 #' @return out The result mx.ndarray
 #' 
 #' @export
@@ -53,7 +83,7 @@ NULL
 #' Take square of the src
 #' 
 #' @param src  NDArray
-#'     Source input to the function.
+#'     Source input to the function
 #' @return out The result mx.ndarray
 #' 
 #' @export
@@ -208,6 +238,19 @@ mx.symbol.BatchNorm <- function(...) {
   mx.varg.symbol.BatchNorm(list(...))
 }
 
+#' Get output from a symbol and pass 0 gradient back
+#' 
+#' @param data  Symbol
+#'     Input data.
+#' @param name  string, optional
+#'     Name of the resulting symbol.
+#' @return out The result mx.symbol
+#' 
+#' @export
+mx.symbol.BlockGrad <- function(...) {
+  mx.varg.symbol.BlockGrad(list(...))
+}
+
 #' Perform an feature concat on channel dim (dim 1) over all the inputs.
 #' 
 #' @param num.args  int, required
@@ -238,7 +281,7 @@ mx.symbol.Concat <- function(...) {
 #' @param num.filter  int (non-negative), required
 #'     convolution filter(channel) number
 #' @param num.group  int (non-negative), optional, default=1
-#'     number of groups partition
+#'     Number of groups partition. This option is not supported by CuDNN, you can use SliceChannel to num_group,apply convolution and concat instead to achieve the same need.
 #' @param workspace  long (non-negative), optional, default=512
 #'     Tmp workspace for convolution (MB)
 #' @param no.bias  boolean, optional, default=False
@@ -442,6 +485,8 @@ mx.symbol.SliceChannel <- function(...) {
 #'     Input data to softmax.
 #' @param grad.scale  float, optional, default=1
 #'     Scale the gradient by a float factor
+#' @param multi.output  boolean, optional, default=False
+#'     If set to true, for a (n,k,x_1,..,x_n) dimensionalinput tensor, softmax will generate n*x_1*...*x_n output, eachhas k classes
 #' @param name  string, optional
 #'     Name of the resulting symbol.
 #' @return out The result mx.symbol
@@ -450,3 +495,55 @@ mx.symbol.SliceChannel <- function(...) {
 mx.symbol.Softmax <- function(...) {
   mx.varg.symbol.Softmax(list(...))
 }
+
+#' Take exp of the src
+#' 
+#' @param src  Symbol
+#'     Source symbolic input to the function
+#' @param name  string, optional
+#'     Name of the resulting symbol.
+#' @return out The result mx.symbol
+#' 
+#' @export
+mx.symbol.exp <- function(...) {
+  mx.varg.symbol.exp(list(...))
+}
+
+#' Take log of the src
+#' 
+#' @param src  Symbol
+#'     Source symbolic input to the function
+#' @param name  string, optional
+#'     Name of the resulting symbol.
+#' @return out The result mx.symbol
+#' 
+#' @export
+mx.symbol.log <- function(...) {
+  mx.varg.symbol.log(list(...))
+}
+
+#' Take sqrt of the src
+#' 
+#' @param src  Symbol
+#'     Source symbolic input to the function
+#' @param name  string, optional
+#'     Name of the resulting symbol.
+#' @return out The result mx.symbol
+#' 
+#' @export
+mx.symbol.sqrt <- function(...) {
+  mx.varg.symbol.sqrt(list(...))
+}
+
+#' Take square of the src
+#' 
+#' @param src  Symbol
+#'     Source symbolic input to the function
+#' @param name  string, optional
+#'     Name of the resulting symbol.
+#' @return out The result mx.symbol
+#' 
+#' @export
+mx.symbol.square <- function(...) {
+  mx.varg.symbol.square(list(...))
+}