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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2018/08/15 22:43:05 UTC
[GitHub] apeforest closed pull request #12175: Update codeowner
apeforest closed pull request #12175: Update codeowner
URL: https://github.com/apache/incubator-mxnet/pull/12175
This is a PR merged from a forked repository.
As GitHub hides the original diff on merge, it is displayed below for
the sake of provenance:
As this is a foreign pull request (from a fork), the diff is supplied
below (as it won't show otherwise due to GitHub magic):
diff --git a/CODEOWNERS b/CODEOWNERS
index 3e2e352592e..f6bf3d5aab8 100644
--- a/CODEOWNERS
+++ b/CODEOWNERS
@@ -21,14 +21,14 @@
/src/kvstore/ @rahul003 @anirudh2290
/include/ @anirudh2290
/src/c_api/ @anirudh2290
-/src/common/ @anirudh2290
-/src/engine/ @anirudh2290
-/src/executor/ @anirudh2290
-/src/imperative/ @anirudh2290
-/src/io/ @anirudh2290
-/src/ndarray/ @anirudh2290
-/src/nnvm/ @anirudh2290
-/src/operator/ @anirudh2290
+/src/common/ @anirudh2290 @apeforest
+/src/engine/ @anirudh2290 @apeforest
+/src/executor/ @anirudh2290 @apeforest
+/src/imperative/ @anirudh2290 @apeforest
+/src/io/ @anirudh2290 @apeforest
+/src/ndarray/ @anirudh2290 @apeforest
+/src/nnvm/ @anirudh2290 @apeforest
+/src/operator/ @anirudh2290 @apeforest
/src/profiler/ @anirudh2290
/src/storage/ @anirudh2290
/tests/cpp/ @anirudh2290
diff --git a/ci/docker/runtime_functions.sh b/ci/docker/runtime_functions.sh
index 24f844fdfc5..e4aac8b18bd 100755
--- a/ci/docker/runtime_functions.sh
+++ b/ci/docker/runtime_functions.sh
@@ -837,11 +837,14 @@ build_docs() {
pushd .
cd /work/mxnet/docs/build_version_doc
# Parameters are set in the Jenkins pipeline: restricted-website-build
- # $1 is the list of branches to build; $2 is the list of tags to display
+ # $1: the list of branches/tags to build
+ # $2: the list of tags to display
# So you can build from the 1.2.0 branch, but display 1.2.1 on the site
- ./build_all_version.sh $1 $2
- # $3 is the default version tag for the website; $4 is the base URL
- ./update_all_version.sh $2 $3 $4
+ # $3: the fork URL
+ ./build_all_version.sh $1 $2 $3
+ # $4: the default version tag for the website
+ # $5: the base URL
+ ./update_all_version.sh $2 $4 $5
cd VersionedWeb
tar -zcvf ../artifacts.tgz .
popd
diff --git a/docs/Jenkinsfile b/docs/Jenkinsfile
index 0e1dce2dbbe..9c7b857615b 100644
--- a/docs/Jenkinsfile
+++ b/docs/Jenkinsfile
@@ -37,7 +37,7 @@ core_logic: {
ws('workspace/docs') {
utils.init_git()
timeout(time: max_time, unit: 'MINUTES') {
- sh "ci/build.py -p ubuntu_cpu --docker-registry ${env.DOCKER_CACHE_REGISTRY} --docker-build-retries 3 /work/runtime_functions.sh build_docs ${params.tags_to_build} ${params.tag_list} ${params.tag_default} ${params.domain}"
+ sh "ci/build.py -p ubuntu_cpu --docker-registry ${env.DOCKER_CACHE_REGISTRY} --docker-build-retries 3 /work/runtime_functions.sh build_docs ${params.tags_to_build} ${params.tag_list} ${params.fork} ${params.tag_default} ${params.domain}"
archiveArtifacts 'docs/build_version_doc/artifacts.tgz'
build 'restricted-website-publish'
}
diff --git a/docs/Makefile b/docs/Makefile
index 4673d0ed1b5..90603b0875f 100644
--- a/docs/Makefile
+++ b/docs/Makefile
@@ -72,6 +72,8 @@ livehtml:
sphinx-autobuild --ignore "web-data/*" -b html $(ALLSPHINXOPTS) $(BUILDDIR)/html
html:
+ export BUILD_VER=$(BUILD_VER)
+ @echo "Env var set for BUILD_VER: $(BUILD_VER)"
$(SPHINXBUILD) -b html $(ALLSPHINXOPTS) $(BUILDDIR)/html
@echo
@echo "Build finished. The HTML pages are in $(BUILDDIR)/html."
diff --git a/docs/build_version_doc/artifacts/mxnet.css b/docs/build_version_doc/artifacts/mxnet.css
new file mode 100644
index 00000000000..cb771967b62
--- /dev/null
+++ b/docs/build_version_doc/artifacts/mxnet.css
@@ -0,0 +1,1479 @@
+/*-------------------- AmazonEmber font -----------------------------------*/
+@font-face {
+ font-family: AmazonEmber;
+ src: url(https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/font/AmazonEmber_Rg.ttf);
+ font-weight: normal;
+}
+
+@font-face {
+ font-family: AmazonEmber;
+ src: url(https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/font/AmazonEmber_Bd.ttf);
+ font-weight: bold;
+}
+
+@font-face {
+ font-family: AmazonEmber;
+ src: url(https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/font/AmazonEmber_Th.ttf);
+ font-weight: 300;
+}
+
+
+/*-------------------- basic html elements and classes --------------------*/
+html, body {
+ margin: 0;
+ padding: 0;
+ background-color: #ffffff;
+}
+
+body {
+ display: block;
+ visibility: hidden;
+ background-size: cover;
+ background-attachment: fixed;
+}
+
+body, div {
+ font-family: AmazonEmber;
+ font-size: 16px;
+ color: #000;
+}
+
+p {
+ font-family: AmazonEmber;
+ color: #000;
+ font-size: 16px;
+ line-height: 1.5em;
+}
+
+#language-filter {
+ float: right;
+ margin-top: 5px;
+}
+
+li, dt a, dt span {
+ font-size: 16px;
+ line-height: 1.5em;
+}
+
+.footer {
+ z-index: 10;
+ position: relative;
+ bottom: 0;
+ width: 100%;
+}
+
+/* /\*Content paragraph space*\/ */
+/* div.content p { */
+/* margin-top: 20px; */
+/* } */
+
+/*------------------ Headings -------------------*/
+h1, h2, h3, h4 {
+ font-family: AmazonEmber;
+ margin-top: 18px;
+ color: #444;
+}
+
+h1 {
+ margin-top: 5px;
+ margin-bottom: 25px;
+ font-size: 28px;
+ font-weight: bold;
+}
+
+h2 {
+ font-size: 24px;
+ font-weight: bold;
+ margin-bottom: 15px;
+}
+
+h3 {
+ font-size: 20px;
+ font-weight: bold;
+ margin-bottom: 10px;
+}
+
+h4 {
+ font-size: 16px;
+ font-weight: bold;
+ margin-bottom: 10px;
+}
+
+img {
+ border-style: hidden;
+ border-width: 0px 0px 0px 0px;
+ border-color: #ffffff;
+ /* white */
+ padding: 0px 0px 0px 0px;
+ margin: 0px 0px 0px 0px;
+}
+
+.topictitle {
+ font-size: 24px;
+ font-weight: bold;
+ color: #e47911;
+ padding: 0 0 14px 0;
+}
+
+.section:before {
+ content: " ";
+ display: block;
+ height: 60px; /* fixed header height*/
+ margin: -60px 0 0; /* negative fixed header height */
+}
+
+/*-----------------------nav bar-----------------------*/
+.navbar {
+ opacity: 0.9;
+ border: 0px;
+ height: 60px;
+ margin-bottom: 0px;
+ border-bottom: 0.01em solid #fff;
+ background-image: url("https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/image/mxnet-navbar.png");
+ background-size: cover;
+ background-attachment: scroll;
+}
+
+.navbar .container {
+ position: relative;
+ width: 100%;
+}
+
+@media screen and (max-width: 510px) {
+ .navbar {
+ height: 60px;
+ }
+}
+
+#header-inner {
+ display: -webkit-box;
+ display: -webkit-flex;
+ display: -ms-flexbox;
+ display: box;
+ display: flex;
+ -webkit-box-orient: horizontal;
+ -moz-box-orient: horizontal;
+ -webkit-box-lines: single;
+ -moz-box-lines: single;
+ -webkit-flex-flow: row nowrap;
+ -ms-flex-flow: row nowrap;
+ flex-flow: row;
+ -webkit-box-align: center;
+ -ms-flex-align: center;
+ -webkit-align-items: center;
+ align-items: center;
+ padding-left: 10px;
+}
+
+@media screen and(max-width: 768 px) {
+ #header-inner {
+ -webkit-box-pack: center;
+ -ms-flex-pack: center;
+ -webkit-justify-content: center;
+ justify-content: center
+ }
+}
+
+#logo-wrap {
+ -webkit-box-flex: 1;
+ padding-top: 0;
+ margin-top: 0;
+ width: 125px;
+ padding-left: 25px;
+ padding-right: 200px;
+}
+
+#logo {
+ color: #fff;
+ width: 150px;
+ display: block;
+ float: left;
+ height: 60px;
+ padding: 15px 0 0 0;
+ text-decoration: none;
+}
+
+#logo > img {
+ display: block;
+ width: 110px;
+}
+
+.nav-bar {
+ display: block;
+ -webkit-box-flex: 1;
+ flex: 1 auto;
+ position: relative;
+ top: -12px;
+ white-space: nowrap;
+}
+
+.main-nav-link {
+ color: #fff;
+ text-decoration: none;
+ line-height: 50px;
+ font-family: AmazonEmber;
+ display: inline-block;
+ padding: 0 15px;
+ font-weight: 500;
+}
+
+.main-nav-link:hover {
+ opacity: 1;
+ color: #fff;
+ text-decoration: none;
+}
+
+#dropdown-menu-position-anchor,
+#dropdown-menu-position-anchor-docs,
+#dropdown-menu-position-anchor-community,
+#dropdown-menu-position-anchor-version,
+#dropdown-menu-position-anchor-version-mobile {
+ position: relative;
+}
+
+.navbar-menu {
+ top: 36px;
+ border-radius: 4px;
+ padding: 0;
+}
+
+.navbar-menu > li > a {
+ color: #0079b2;
+ padding: 6px 16px;
+
+}
+
+#search-input-wrap {
+ display: block;
+ position: absolute;
+ top: 15px;
+ right: 20px;
+ width: 200px;
+ -webkit-transition: width 0.5s;
+ transition: width 0.5s;
+}
+
+#search-input-wrap ul {
+ list-style-type: none;
+}
+
+#searchIcon {
+ display: none;
+ position: fixed;
+ top: 20px;
+ right: 35px;
+ color: white;
+}
+
+.searchBox {
+ position: absolute;
+ top: 0;
+ left: 0;
+ width: 200px;
+ background: transparent;
+ border-radius: 5px;
+ -webkit-transition: width 0.5s;
+ transition: width 0.5s;
+}
+
+.searchBox input {
+ background: transparent;
+}
+
+.searchBox input::placeholder {
+ font-weight: 200;
+}
+
+.searchBoxNorm input::placeholder {
+ color: white;
+}
+
+.searchBoxExp input::placeholder {
+ color: dimgray;
+}
+
+.searchBtn {
+ display: none;
+ position: absolute;
+ top: 0;
+ right: 0;
+ width: 40px;
+}
+
+@media screen and (max-width: 510px) {
+ #search-input-wrap {
+ width: 120px;
+ margin-right: 10px;
+ }
+
+ .searchBox {
+ width: 120px;
+ }
+}
+
+#lang-select-wrap {
+ display: block;
+ position: fixed;
+ right: 120px;
+ top: 5px
+}
+
+#lang-select-label {
+ color: #fff;
+ opacity: .7;
+ font-family: AmazonEmber;
+ line-height: 50px
+}
+
+#lang-select-label span {
+ padding-left: 8px
+}
+
+#lang-select-label i {
+ opacity: .7
+}
+
+#lang-select {
+ opacity: 0;
+ position: absolute;
+ top: 0;
+ left: 0;
+ width: 100%;
+ height: 100%;
+ -webkit-appearance: menulist-button;
+ font-size: inherit
+}
+
+.github-btn { border: 0; overflow: hidden }
+
+.boxed {
+ border: 1px solid rgb(57, 144, 211);
+ background: #0079b2;
+ color: white;
+ font-weight: bold
+}
+
+.boxed-bordered {
+ border: 3px solid rgba(0,0,0,.05);
+ background: #0079b2;
+ font-weight: bold;
+ color: white;
+}
+
+/*burger icon*/
+div .burgerIcon {
+ font-size: 25px;
+ position: fixed;
+ right: 155px;
+ top: 11px;
+ display: none;
+ width: 30px;
+}
+
+div .burgerIcon a {
+ color: white;
+}
+
+/*burger menu*/
+#burgerMenu, #plusMenu {
+ list-style-type: none;
+ margin-top: 10px;
+ padding: 0;
+ background-color: white;
+ list-style-position: inside;
+ min-width: 100px;
+}
+
+#burgerMenu a, #plusMenu a {
+ display: table-cell;
+ font-size: 15px;
+ color: #0079b2;
+ vertical-align: middle;
+ height: 30px;
+ padding-left: 5px;
+ width: 108px;
+ max-width: 250px;
+}
+
+#plusMenu .dropdown-submenu>.dropdown-menu {
+ left: 127px;
+ top: 0;
+ background: #fff;
+}
+
+#burgerMenu li, #plusMenu li {
+ height: 30px;
+ list-style-position: inside;
+}
+
+li.dropdown-submenu ul.dropdown-menu {
+ min-width: 75px;
+}
+
+li.dropdown-submenu ul.dropdown-menu li {
+ border-style: none !important;
+}
+
+li.dropdown-submenu ul.dropdown-menu a {
+ padding-left: 20px !important;
+}
+
+@media screen and (max-width: 420px) {
+ li.dropdown-submenu ul.dropdown-menu a {
+ font-size: 12px !important;
+ }
+}
+
+/*dropdown submenu*/
+.dropdown-submenu {
+ position: relative;
+}
+
+.dropdown-submenu>.dropdown-menu {
+ top: -8px;
+ left: 250px;
+ -webkit-border-radius: 0 6px 6px 6px;
+ -moz-border-radius: 0 6px 6px;
+ border-radius: 0 6px 6px 6px;
+ background: transparent;
+}
+
+.dropdown-submenu:hover>.dropdown-menu {
+ display: block;
+}
+
+.dropdown-submenu>a:after {
+ display: block;
+ content: " ";
+ float: right;
+ width: 0;
+ height: 0;
+ border-color: transparent;
+ border-style: solid;
+ border-width: 5px 0 5px 5px;
+ border-left-color: #ccc;
+ margin-top: 10px;
+ margin-right: -10px;
+}
+
+.dropdown-submenu:hover>a:after {
+ border-left-color: #fff;
+}
+
+.dropdown-submenu.pull-left {
+ float: none;
+}
+
+.dropdown-submenu.pull-left>.dropdown-menu {
+ left: -100%;
+ margin-left: 10px;
+ -webkit-border-radius: 6px 0 6px 6px;
+ -moz-border-radius: 6px 0 6px 6px;
+ border-radius: 6px 0 6px 6px
+}
+
+/*Plus icon*/
+.plusIcon {
+ display: none;
+ position: absolute;
+ top: 20px;
+ right: 210px;
+ width: 30px;
+}
+
+.glyphicon-plus {
+ color: white;
+}
+
+@media screen and (max-width:600px) {
+ div .plusIcon, .nav-bar {
+ display: none !important;
+ }
+
+ div.burgerIcon {
+ display: block;
+ position: fixed;
+ left: 45px;
+ }
+
+ #burgerMenu {
+ position: fixed;
+ left: 0;
+ top: 49px;
+ width: 100%;
+ height: 100%;
+ background: url(https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/image/mxnet-background-compressed.jpeg);
+ background-attachment: initial;
+ background-size: cover;
+ }
+
+ #burgerMenu a {
+ display: block;
+ font-size: 19px;
+ width: auto;
+ padding-left: 75px;
+ padding-top: 10px;
+ color: #fff;
+ text-decoration: none;
+ }
+
+ #burgerMenu a:hover {
+ color: initial;
+ background-color: inherit;
+ }
+
+ #burgerMenu li {
+ border-bottom: 1px solid lightgray;
+ height: 50px;
+ }
+
+ #logo-wrap {
+ margin-left: 30px;
+ }
+}
+/*--------------------------banner---------------------------*/
+#splash{
+ padding:60px 0 0 0;
+ background-size:cover;
+ background-attachment:fixed;
+ color:#fff;
+ text-align:center
+}
+
+#splash #banner {
+ text-align: center
+}
+
+#banner-title span {
+ font-family: AmazonEmber;
+ font-weight: bold;
+}
+
+#banner-title {
+ padding: 60px 0 10px 0;
+ font-size: 40px;
+ line-height: 55px;
+ font-weight: 500;
+ font-family: AmazonEmber;
+ color: #fff;
+ max-width: 600px;
+ text-align: left;
+ margin-left: 30px;
+}
+
+#landing-title {
+ margin-right: 40px;
+ font-size: 35px;
+ color: #fff;
+ font-family: AmazonEmber;
+ font-weight: 300;
+}
+
+#intro {
+ font-size: 16px;
+ color: #fff;
+ font-family: AmazonEmber;
+ font-weight: 300;
+}
+
+@media screen and (max-width:768px) {
+ #banner-title {
+ font-size: 30px;
+ padding: 60px 30px 10px 30px;
+ margin-left: 0;
+ }
+}
+
+#splash h1{
+ font-size: 40px;
+ margin-bottom: 20px;
+}
+
+#splash #social{
+ margin:2em 0 4em 0;
+}
+
+#landing-btn-blk {
+ margin-top: 2em;
+}
+
+#why_mxnet, #install_blk {
+ margin:2em 0;
+ display: inline;
+}
+
+#why_mxnet {
+ padding-left: 20px;
+}
+
+@media screen and (max-width:400px) {
+ #install_blk, #install_blk{
+ display: block;
+ }
+
+ #install_blk {
+ padding-left: 0;
+ margin-top: 0;
+ }
+}
+
+#why_mxnet_btn {
+ border: 1.8px solid #FFFFFF;
+ color: #FFFFFF;
+ display: inline;
+ font-size: 18px;
+ font-family: AmazonEmber;
+ padding: 8px 20px;
+ -webkit-transition: .2s;
+ transition: .2s;
+}
+
+#install_btn {
+ border: 1.8px solid #FFFFFF;
+ color: #fff;
+ display: inline;
+ font-size: 18px;
+ font-family: AmazonEmber;
+ padding: 8px 40px;
+ -webkit-transition: .2s;
+ transition: .2s;
+}
+
+#release_btn {
+ width: auto;
+ border: none;
+}
+
+#why_mxnet_btn:hover, #install_btn:hover {
+ background-color: #FFFFFF;
+ color: #0079b2;
+ opacity: 0.9;
+ text-decoration: none;
+}
+
+/*------------------------index page section----------------------------*/
+.section-tout {
+ padding:3em 0 1em;
+}
+
+.section-tout .container {
+ height: 220px;
+}
+
+.section-tout .row {
+ height: 100%;
+}
+
+.section-tout .row div {
+ height: 110%;
+ padding-left: 50px;
+ background-color:#fff;
+ box-shadow: 0px 2px 4px 0px rgba(0, 28, 36, 0.5);
+}
+
+.section-tout .row a {
+ font-family: AmazonEmber;
+ position: absolute;
+ bottom: 20px;
+ border: solid 1px;
+ padding: 5px 10px;
+ color: #111;
+}
+
+.section-tout h3{
+ font-family: AmazonEmber;
+ font-size:20px;
+ color: #007dbc;
+ padding-top: 10px
+}
+
+.section-tout p {
+ font-family: AmazonEmber;
+ margin-bottom:2em;
+}
+
+@media (max-width: 1199px) {
+ .section-tout .container {
+ height: auto;
+ }
+
+ .section-tout .row a {
+ position: inherit;
+ }
+
+ .section-tout .row div {
+ padding-left: 45px;
+ }
+
+ .section-tout .row p {
+ padding-bottom: 10px;
+ }
+}
+
+@media (max-width: 767px) {
+ .section-tout .row div {
+ margin-bottom: -20px;
+ }
+}
+
+.section-util {
+ padding:3em 0 3em;
+ text-align: left;
+ margin-bottom: 50px;
+}
+
+.section-util .row > div {
+ height: 320px;
+ padding-left: 50px;
+ padding-top: 40px;
+}
+
+.section-util .row div h2 {
+ font-family: AmazonEmber;
+ color: #fff;
+}
+
+#model-zoo-blk {
+ background-color: #00446e;
+ box-shadow: 0px 2px 4px 0px rgba(0, 28, 36, 0.5);
+}
+
+#example-blk {
+ background-color: #006ea7;
+ box-shadow: 0px 2px 4px 0px rgba(0, 28, 36, 0.5);
+}
+
+#tutorial-blk {
+ background-color: #00a1c9;
+ box-shadow: 0px 2px 4px 0px rgba(0, 28, 36, 0.5);
+}
+
+@media (min-width: 1200px) {
+ #model-zoo-blk {
+ width: 370px;
+ margin-right: 20px;
+ }
+
+ #example-blk {
+ width: 370px;
+ margin-right: 20px;
+ }
+}
+
+.section-util p {
+ font-family: AmazonEmber;
+ color: #fff;
+ position: absolute;
+ width: 70%;
+ font-size: 14px;
+ font-weight: 300;
+}
+
+.section-util .util-btn {
+ position: absolute;
+ bottom: 30px;
+}
+
+@media (max-width: 600px) {
+ .section-util .util-btn {
+ margin-top: 100px;
+ }
+}
+
+.section-util .glyphicon {
+ font-size: 50px;
+ color: #b3ffff;
+}
+
+.util-btn a {
+ font-family: AmazonEmber;
+ display: inline-block;
+ border: 1.8px solid;
+ -webkit-transition: .2s;
+ transition: .2s;
+ padding: 5px 30px;
+ color: #fff;
+}
+
+.util-btn a:hover {
+ background-color: #0079b2;
+ color: #FFFFFF;
+ opacity: 0.9;
+ text-decoration: none;
+}
+
+.section-util .container {
+ height: 250px;
+}
+
+@media (max-width: 1199px) {
+ .section-util .container {
+ height: auto
+ }
+}
+
+.section-inst {
+ padding:3em 0 3em;
+ border-bottom:1px solid rgba(0,0,0,.05);
+ text-align: left;
+ background-color: #fff;
+}
+
+.section-inst .row div {
+ text-align: center;
+ margin-bottom: 30px;
+ height: 80px;
+}
+
+.section-inst p {
+ font-family: AmazonEmber;
+ font-weight: 300;
+ margin-bottom:2em;
+ padding-left: 50px;
+ color: #111;
+}
+
+.section-inst h2 {
+ font-family: AmazonEmber;
+ margin-top: -20px;
+ margin-bottom: 50px;
+ color: dimgray;
+ padding-left: 40px;
+}
+
+@media (min-width: 1200px) {
+ .section-inst .row div.clear {
+ clear: both;
+ }
+}
+
+@media (max-width: 1199px) {
+ .section-inst .row div.smallClear {
+ clear: both;
+ }
+}
+
+.section-inst img {
+ -webkit-filter: grayscale(90%); /* Chrome, Safari, Opera */
+ filter: grayscale(90%);
+ margin-bottom:2em
+}
+.section-inst img:hover {
+ -webkit-filter: grayscale(0%); /* Chrome, Safari, Opera */
+ filter: grayscale(0%);
+}
+
+.section-disclaimer {
+ padding: 3em 0 3em;
+ background-color: #f2f2f2;
+}
+
+.section-disclaimer .container div {
+ padding-left: 50px;
+}
+
+.section-disclaimer p {
+ padding-top: 2em;
+}
+
+.footer li{
+ float:right;
+ margin-right:1.5em;
+ margin-bottom:1.5em
+}
+.footer p{
+ font-family: AmazonEmber;
+ font-weight: 300;
+ font-size: 12px;
+ clear:right;
+ margin-bottom:0;
+}
+
+/*------------------content----------------------*/
+div.navbar + div.container {
+ padding-top: 65px;
+}
+
+div.content {
+ padding: 80px 40px 40px 45px;
+ background: #fff;
+ width: calc(100% - 300px);
+ float: right;
+ overflow-x: hidden;
+ z-index: -1;
+}
+
+@media (max-width: 999px) {
+ div.content {
+ overflow-x: auto;
+ width: 100%;
+ }
+}
+
+div.page-tracker {
+ margin-bottom: 30px;
+ font-family: AmazonEmber;
+}
+
+div.page-tracker ul {
+ padding-left: 0;
+}
+
+div.page-tracker ul li {
+ text-transform: capitalize;
+ display: inline;
+}
+
+div.page-tracker a {
+ text-transform: capitalize;
+ color: #337ab7;
+}
+
+div.page-tracker li:last-child {
+ color: #aab7b8;
+}
+
+div.page-tracker i {
+ margin: 0 10px;
+}
+
+/*------------------sidebar-----------------------*/
+div.sphinxsidebar {
+ position: fixed;
+ padding-top: 40px;
+ height: 100%;
+ display: none;
+ visibility: hidden;
+ overflow: auto;
+}
+
+div.leftsidebar {
+ width: 300px;
+ margin-left: 25px;
+ background: #f2f2f2;
+}
+
+div.rightsidebar {
+ right: 20px;
+ width: 200px;
+ padding: 40px 0 15px 0;
+}
+
+div.sphinxsidebar ul {
+ padding: 0;
+ list-style-type: none !important;
+}
+
+div.sphinxsidebar a {
+ font-family: AmazonEmber;
+ font-size: 13px;
+}
+
+div.rightsidebar div.sphinxsidebarwrapper > ul {
+ padding-left: 15px;
+}
+
+div.sphinxsidebar li {
+ padding-top: 5px;
+ margin-bottom: 5px;
+ margin-left: -10px;
+}
+
+div.leftsidebar > div.sphinxsidebarwrapper {
+ padding: 40px 20px 10px 20px;
+ background: #f2f2f2;
+}
+
+div.leftsidebar > div.sphinxsidebarwrapper > ul > li {
+ margin-left: 20px;
+}
+
+div.rightsidebar > div.sphinxsidebarwrapper > ul {
+ margin-left: 2px;
+ border-left: 4px solid #337ab7;
+}
+
+div.rightsidebar > div.sphinxsidebarwrapper > ul > li {
+ margin-left: 5px;
+}
+
+div.sphinxsidebar li.opened .tocToggle:before {
+ font-family: 'FontAwesome';
+ content: "\f0d7";
+ margin: 0 5px 0 -15px;
+ color: #999999;
+}
+
+div.sphinxsidebar li.closed .tocToggle:before {
+ font-family: 'FontAwesome';
+ content: "\f0da";
+ margin: 0 5px 0 -15px;
+ color: #999999;
+}
+
+div.sphinxsidebar li.leaf .tocToggle:before {
+ /*font-family: 'FontAwesome';*/
+ content: " ";
+ margin: 0 5px 0 -15px;
+ color: #f2f2f2;
+}
+
+@media (min-width:1015px) {
+ div.sphinxsidebar {display: block}
+}
+
+div.sphinxsidebarwrapper h3 {
+ padding-top: 0;
+}
+
+/*-------------------- table styles --------------------*/
+table {
+ margin-bottom: 10px;
+ border-collapse: collapse; }
+
+table p {
+ font-size: 16px; }
+
+td p:first-child {
+ margin-top: 0px; }
+
+td p:last-child {
+ margin-bottom: 0px; }
+
+td ul:first-child {
+ margin-top: 0px;
+ /* new 8/22/07 */ }
+
+td ol:first-child {
+ margin-top: 0px;
+ /* new 8/22/07 */ }
+
+div.table {
+ position: relative; }
+
+div.informaltable {
+ position: relative; }
+
+.table-expand-icon {
+ position: absolute;
+ right: -20px;
+ font-size: 24px;
+ background: #cccccc;
+ float: right;
+ bottom: 0;
+ cursor: pointer; }
+
+.table-contents table {
+ border-top: 1px solid #cccccc;
+ /* medium gray */
+ border-left: 1px solid #cccccc;
+ /* medium gray */
+ border-bottom: 0px;
+ border-right: 0px;
+ border-spacing: 0px; }
+
+.table-contents td {
+ font-size: 16px;
+ padding: 5px 5px 5px 5px;
+ border-bottom: 1px solid #cccccc;
+ /* medium gray */
+ border-right: 1px solid #cccccc;
+ /* medium gray */
+ border-left: 0px;
+ border-top: 0px;
+ vertical-align: top; }
+
+.table-contents th {
+ font-size: 16px;
+ padding: 5px 5px 5px 5px;
+ border-bottom: 1px solid #cccccc;
+ /* medium gray */
+ border-right: 1px solid #cccccc;
+ /* medium gray */
+ border-left: 0px;
+ border-top: 0px;
+ vertical-align: top;
+ background-color: #eeeeee;
+ /* light gray */
+ color: #333333;
+ /* Dark gray */
+ font-size: 16px;
+ font-weight: bold;
+ text-align: left; }
+
+/*----------------API class and function formatting---------------------*/
+p.rubric {
+ margin-top: 10px;
+}
+
+dl {
+ padding-top: 20px;
+}
+
+dt:target, .highlighted {
+ background-color: #e7f2fa;
+ border-bottom: 3px solid #c7254e;
+ margin-bottom: -3px;
+}
+
+dt:target:before {
+ background-color: white;
+ content: '';
+ display: block;
+ height: 60px;
+}
+
+dt {
+ background: #e7f2fa;
+ border-bottom: solid #0079b2;
+}
+
+dl.method dt {
+ background: #f0f0f0;
+ border-bottom: solid #ccc;
+}
+
+dl.method dt code.descname {
+ color:#555;
+}
+
+dl.attribute dt {
+ background: #f0f0f0;
+ border-bottom: solid #ccc;
+}
+
+dl.attribute dt code.descname {
+ color:#555;
+}
+
+dt em {
+ font-weight: normal;
+ font-style: normal;
+ font-size: 90%;
+}
+
+code {
+ color: #337ab7;
+ background-color: #f5f5f5;
+}
+
+code.docutils.literal {
+ color: #111;
+ font-weight: bold;
+}
+
+a code.docutils.literal {
+ color: #337ab7;
+}
+
+dt code {
+ color: #555;
+}
+
+dl.last.docutils dt{
+ background-color: transparent;
+ border-bottom: none;
+}
+
+dl.docutils dt {
+ color: #555;
+ background-color: #f0f0f0;
+ border-bottom: solid #ccc;
+}
+
+/*----------------Model zoo page style------------------*/
+#mxnet-model-zoo table, #mxnet-model-zoo td, #mxnet-model-zoo th {
+ border: 1px solid lightgray;
+}
+
+#mxnet-model-zoo table {
+ margin-top: 30px;
+ border-collapse: collapse;
+}
+
+#mxnet-model-zoo th {
+ vertical-align: middle;
+ text-align: center;
+ height: 50px;
+}
+
+#mxnet-model-zoo td {
+ vertical-align: middle;
+ height: 50px;
+ padding: 10px;
+}
+
+#mxnet-model-zoo tr:nth-child(even) {
+ background-color: #f2f2f2;
+}
+
+/*--------- note block -----------*/
+div.admonition {
+ padding: 15px;
+ background-color: #f6f8fa;
+ border: 1px solid rgb(204, 204, 204);
+ border-radius: 4px;
+}
+
+p.admonition-title {
+ color: #187dbb;
+}
+
+/*------------ code block ------------*/
+pre {
+ background-color: #f6f8fa;
+}
+
+/*-------------API table---------------------*/
+table.docutils {
+ margin-top: 15px;
+}
+
+table.docutils td, table.docutils th {
+ padding-top: 5px;
+ padding-bottom: 5px;
+ padding-left: 10px;
+ padding-right: 10px;
+ /* border-top: 0; */
+ /* border-left: 0; */
+ /* border-right: 0; */
+ border: 1px solid rgb(223, 226, 229);
+}
+
+table.docutils tr:nth-child(even) {
+ background-color: #f6f8fa;
+}
+
+/*---------------getting started homepage---------*/
+
+#lang-demo ul {
+ margin-top: 20px;
+ margin-bottom: 15px;
+}
+
+.option-title {
+ width: 100px;
+ float: left;
+ clear: none;
+ text-align: right;
+ font-size: 14px;
+ padding-top: 7px;
+ padding-bottom: 8px;
+ padding-right: 10px;
+ font-weight: bold;
+}
+.option-row {
+ padding-bottom: 8px;
+}
+
+.install-inst {
+}
+
+.btn-default:hover, .btn-default:focus, .btn-default:active,
+.btn-default.active.focus, .btn-default.active:focus, .btn-default.active:hover,
+.btn-default:active.focus, .btn-default:active:focus, .btn-default:active:hover,
+.btn-default.active, .open>.dropdown-toggle.btn-default,
+.btn-default:active:focus {
+ color: #fff;
+ background-color: #0079b2;
+ border-color: #0079b2;
+}
+
+.btn-default:hover a {
+ color: #fff;
+}
+
+#setup-options {
+ margin-top: 15px;
+ margin-bottom: 15px;
+ margin-left: 30px;
+}
+
+.opt-group {
+ margin-top: 10px;
+ margin-bottom: 10px;
+}
+
+/*----------------Copy code button------------------------*/
+.copy-btn {
+ display: none;
+ position: absolute;
+ right: 0;
+ width: 40px;
+ height: 38px;
+}
+
+/*----------------Search function style------------------*/
+#searchPage {
+ width: 60%;
+ margin-left: 20%;
+}
+
+#search-preview {
+ display: none;
+ background-color: white;
+ margin-top: -10px;
+ border: solid;
+ border-width: 1px;
+ border-color: #87CEFA;
+ width: 100%;
+}
+
+
+#search-preview p {
+ color: dimgray;
+ padding: 5px 20px 0 20px;
+}
+
+#search-preview li {
+ padding-top: 10px;
+}
+
+#search-preview ul {
+ padding-left: 20px;
+ padding-right: 20px;
+}
+
+#search-preview hr {
+ margin: 10px 0 10px 0;
+ border-top: 1px solid dimgray;
+}
+
+#search-results ul {
+ list-style-type: none;
+}
+
+@media screen and (max-width: 510px) {
+ #search-preview {
+ position: fixed;
+ left: 0;
+ width: 100vw;
+ }
+
+ #search-preview li {
+ font-size: 12px;
+ }
+}
+
+/* enable absolute positioning */
+.inner-addon {
+ position: relative;
+}
+
+/* style icon */
+.inner-addon .glyphicon {
+ position: absolute;
+ padding: 10px;
+ pointer-events: none;
+}
+
+/* align icon */
+.left-addon .glyphicon {
+ right: 0px;
+}
+.right-addon .glyphicon {
+ right: 0px;
+}
+
+/* add padding */
+.left-addon input {
+ font-family: AmazonEmber;
+ font-style: italic;
+}
+.right-addon input {
+ padding-right: 40px;
+}
+
+.form-group .glyphicon-search {
+ color: white;
+}
+
+/*----------------------Get started page----------------------------*/
+#why-mxnet img {
+ position: relative;
+ width: 60%;
+ left: 50%;
+ margin-right: -50%;
+ transform: translate(-50%);
+}
+
+button.download {
+ color: #0079b2;
+}
+
+/*----------------------Download button------------------------*/
+div.download-btn {
+
+ border: solid 1px #000;
+ border-radius: 3px;
+ font-size: 90%;
+ height: 40px;
+ display: table;
+ float: left;
+}
+
+div.download-btn a {
+ padding: 0 10px;
+ display: table-cell;
+ vertical-align: middle;
+ color: #000;
+}
+
+div.download-btn a:hover {
+ background-color: #0079b2;
+ color: white;
+ text-decoration: none;
+}
+
+div.download-btn.download-btn-top {
+ border-color: #ec7211;
+ background: #ec7211;
+ float: right;
+}
+
+div.download-btn.download-btn-top a {
+ color: #fff;
+}
+
+/*-------------output blocks----------------*/
+
+.highlight-results .highlight pre {
+ background-color: #eeffcc;
+}
+
+.cell-results-header {
+ color: #888;
+ padding-bottom: 3px;
+ font-style: italic;
+}
+
+/*------------Download source-----------------*/
+#download-source-package {
+ display: none;
+ padding-top: 40px;
+}
+
+/*------------Mobile dropdown menu smooth transition---------------*/
+@keyframes slide {
+ 0% {
+ left: -100%;
+ }
+ 25% {
+ left: -75%;
+ }
+ 50% {
+ left: -50%;
+ }
+ 75% {
+ left: -25%;
+ }
+ 100% {
+ left: 0;
+ }
+}
+
+#burgerMenu {
+ animation-name: slide;
+ animation-duration: 0.3s;
+ animation-timing-function: ease-in-out;
+}
diff --git a/docs/build_version_doc/build_all_version.sh b/docs/build_version_doc/build_all_version.sh
index 44cd540fda0..d36f1f5edc6 100755
--- a/docs/build_version_doc/build_all_version.sh
+++ b/docs/build_version_doc/build_all_version.sh
@@ -19,20 +19,31 @@
# This script is for locally building website for all versions
# Built files are stored in $built
-
-# Takes two arguments:
-# tag list - semicolon delimited list of Github tags
+# Default repo is mxnet_url="https://github.com/apache/incubator-mxnet.git"
+# Default build directory is mxnet_folder="apache-mxnet"
+# Takes two required arguments and one optional:
+# tag list (required)- semicolon delimited list of Github tags
# Example: "1.2.0;1.1.0;master"
-# display list - semicolon delimited list of what to display on website
+# display list (required) - semicolon delimited list of what to display on website
# Example: "1.2.1;1.1.0;master"
-# The number of tags for the two arguments must be the same.
+# NOTE: The number of tags for the two arguments must be the same.
+# Repo URL (optional) - a GitHub URL that is a fork of the MXNet project
+# When this is used the build directory will be {github_username}-mxnet
+
# Example Usage:
-# ./build_all_version.sh "1.2.0;1.1.0;master" "1.2.1;1.1.0;master"
+# Build the content of the 1.2.0 branch in the main repo to the 1.2.1 folder.
# ./build_all_version.sh "1.2.0" "1.2.1"
+# Using the main project repo, map the 1.2.0 branch to output to a 1.2.1 directory; others as is:
+# ./build_all_version.sh "1.2.0;1.1.0;master" "1.2.1;1.1.0;master"
+# Using a custom branch and fork of the repo, map the branch to master,
+# map 1.2.0 branch to 1.2.1 and leave 1.1.0 in 1.1.0:
+# ./build_all_version.sh "sphinx_error_reduction;1.2.0;1.1.0" \
+# "master;1.2.1;1.1.0" https://github.com/aaronmarkham/incubator-mxnet.git
set -e
set -x
+# $1 is the list of branches/tags to build
if [ -z "$1" ]
then
echo "Please provide a list of branches or tags you wish to build."
@@ -44,6 +55,7 @@ if [ -z "$1" ]
build_arr=($tag_list)
fi
+# $2 is the list of output folders which will be displayed on the site
if [ -z "$2" ]
then
echo "Please provide a list of version tags you wish to display on the site."
@@ -58,13 +70,61 @@ if [ -z "$2" ]
done
fi
-mxnet_url="https://github.com/apache/incubator-mxnet.git"
-mxnet_folder="apache_mxnet"
+# $3 is the GitHub project URL or fork
+if [ -z "$3" ]
+ then
+ echo "Using the main project URL."
+ mxnet_url="https://github.com/apache/incubator-mxnet.git"
+ mxnet_folder="apache-mxnet"
+ else
+ mxnet_url=$3
+ fork=${mxnet_url##"https://github.com/"}
+ fork_user=${fork%%"/incubator-mxnet.git"}
+ mxnet_folder=$fork_user"-mxnet"
+ echo "Building with a user supplied fork: $mxnet_url"
+fi
+
+# This is the output folder
built="VersionedWeb"
+
+function create_repo () {
+ repo_folder=$1
+ mxnet_url=$2
+ git clone $mxnet_url $repo_folder --recursive
+ echo "Adding MXNet upstream repo..."
+ cd $repo_folder
+ git remote add upstream https://github.com/apache/incubator-mxnet
+ cd ..
+}
+
+
+function refresh_branches () {
+ repo_folder=$1
+ cd $repo_folder
+ git fetch
+ git fetch upstream
+ cd ..
+}
+
+
+function checkout () {
+ repo_folder=$1
+ cd $repo_folder
+ # Overriding configs later will cause a conflict here, so stashing...
+ git stash
+ # Fails to checkout if not available locally, so try upstream
+ git checkout "$repo_folder" || git branch $repo_folder "upstream/$repo_folder"
+ if [ $tag == 'master' ]; then
+ git pull
+ fi
+ git submodule update --init --recursive
+ cd ..
+}
+
+
if [ ! -d "$mxnet_folder" ]; then
mkdir $mxnet_folder
- git clone $mxnet_url $mxnet_folder --recursive
fi
if [ ! -d "$built" ]; then
@@ -81,25 +141,27 @@ fi
for key in ${!build_arr[@]}; do
tag=${build_arr[${key}]}
cd "$mxnet_folder"
- git fetch
- if [ $tag == 'master' ]
- then
- git checkout master
- git pull
- echo "Building master..."
- else
- # Use "v$tag" for branches or pass that in from jenkins
- git checkout "$tag"
- echo "Building $tag..."
+
+ # Each tag will get its own subfolder
+ if [ ! -d "$tag" ]; then
+ create_repo "$tag" "$mxnet_url"
fi
- git submodule update --init --recursive || exit 1
+ refresh_branches $tag
+
+ checkout $tag
+
+ # Bring over the current configurations, so we can anticipate results.
+ cp ../../mxdoc.py $tag/docs/
+ cp ../../settings.ini $tag/docs/
+ cp ../../conf.py $tag/docs/
+ cp ../../Doxyfile $tag/docs/
- make clean
- cd docs
- make clean
- make html USE_OPENMP=1 || exit 1
- cd ../../
+ echo "Building $tag..."
+ cd $tag/docs
+ make html USE_OPENMP=1 BUILD_VER=$tag || exit 1
+ # Navigate back to build_version_doc folder
+ cd ../../../
# Use the display tag name for the folder name
file_loc="$built/versions/${display_arr[${key}]}"
if [ -d "$file_loc" ] ; then
@@ -107,7 +169,9 @@ for key in ${!build_arr[@]}; do
fi
mkdir "$file_loc"
echo "Storing artifacts for $tag in $file_loc folder..."
- cp -a "$mxnet_folder/docs/_build/html/." "$file_loc"
+ cp -a "$mxnet_folder/$tag/docs/_build/html/." "$file_loc"
done
echo "Now you may want to run update_all_version.sh to create the production layout with the versions dropdown and other per-version corrections."
+echo "The following pattern is recommended (tags, default tag, url base):"
+echo "./update_all_version.sh "$tags_to_display " master http://mxnet.incubator.apache.org/"
diff --git a/docs/build_version_doc/update_all_version.sh b/docs/build_version_doc/update_all_version.sh
index e39b0a50341..0c91973bd19 100755
--- a/docs/build_version_doc/update_all_version.sh
+++ b/docs/build_version_doc/update_all_version.sh
@@ -22,21 +22,22 @@
# It assumes you have already run build_all_version.sh for
# the tags you want to update.
-# Takes three arguments:
-# * tag list - semicolon delimited list of tags to display on site; Example: "1.1.0;1.0.0;master"
-# * default tag - which version should the site default to; Example: 1.0.0
-# * root URL - for the versions dropdown to change to production or dev server; Example: http://mxnet.incubator.apache.org/
+# Takes three required arguments:
+# * tag list (required) - semicolon delimited list of tags to display on site
+# Example: "1.1.0;1.0.0;master"
+# * default tag (required) - which version should the site default to
+# Example: 1.0.0
+# * root URL (required) - for the versions dropdown to change to production or
+# dev server.
+# Example: http://mxnet.incubator.apache.org/
# Example Usage:
-# ./update_all_version.sh "1.1.0;1.0.0;master" 1.0.0 http://mxnet.incubator.apache.org/
+# ./update_all_version.sh "1.2.1;1.1.0;1.0.0;master" master \
+# http://mxnet.incubator.apache.org/
set -e
set -x
-MASTER_SOURCE_DIR="../../docs"
-STATIC_FILES_DIR="_static"
-MXNET_THEME_DIR="_static/mxnet-theme"
-
if [ -z "$1" ]
then
echo "Please provide a list of version tags you wish to run."
@@ -64,7 +65,6 @@ if [ -z "$3" ]
root_url=$3
fi
-mxnet_folder="apache_mxnet"
built="VersionedWeb"
tag_file="tag_list.txt"
@@ -85,8 +85,8 @@ function update_mxnet_css {
# During a nightly build, these fixes will be patched to all the versions in the asf-site repository including the master folder under versions directory.
# copy <master folder location> <version folder location>
- echo "Copying mxnet.css from master branch to all versions...."
- cp "$MASTER_SOURCE_DIR/$STATIC_FILES_DIR/mxnet.css" "$built/versions/$tag/_static"
+ echo "Copying mxnet.css from artifacts folder..."
+ cp "artifacts/mxnet.css" "$built/versions/$tag/_static"
echo "Update fixes complete.."
}
@@ -121,12 +121,9 @@ for tag in $tag_list; do
file_loc="$built/versions/$tag"
fi
- # Copy the latest README.md from master
+ # Copy the latest README.md; needs to come from local branch
if [ $tag == 'master' ]; then
- cd $mxnet_folder
- git checkout master
- cp README.md ../$built
- cd ..
+ cp ../../README.md $built
fi
done
diff --git a/docs/conf.py b/docs/conf.py
index d018408d455..656a1da96d6 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -33,13 +33,13 @@
# -- General configuration -----------------------------------------------------
# If your documentation needs a minimal Sphinx version, state it here.
-needs_sphinx = '1.2'
+needs_sphinx = '1.5.6'
# General information about the project.
project = u'mxnet'
author = u'%s developers' % project
-copyright = u'2015-2017, %s' % author
-github_doc_root = 'https://github.com/dmlc/mxnet/tree/master/docs/'
+copyright = u'2015-2018, %s' % author
+github_doc_root = 'https://github.com/apache/incubator-mxnet/tree/master/docs/'
doc_root = 'http://mxnet.io/'
# add markdown parser
@@ -107,7 +107,7 @@
# List of patterns, relative to source directory, that match files and
# directories to ignore when looking for source files.
-exclude_patterns = ['virtualenv']
+exclude_patterns = ['3rdparty', 'build_version_doc', 'virtualenv', 'api/python/model.md', 'README.md']
# The reST default role (used for this markup: `text`) to use for all documents.
#default_role = None
diff --git a/docs/mxdoc.py b/docs/mxdoc.py
index 8332ae22d48..dabfd3bbb64 100644
--- a/docs/mxdoc.py
+++ b/docs/mxdoc.py
@@ -26,6 +26,29 @@
# import StringIO from io for python3 compatibility
from io import StringIO
import contextlib
+from ConfigParser import SafeConfigParser
+
+_BUILD_VER = os.getenv('BUILD_VER', 'default')
+print("Building version {}".format(_BUILD_VER))
+_DOC_SET = 'document_sets_' + _BUILD_VER
+
+parser = SafeConfigParser()
+parser.read('settings.ini')
+
+if _DOC_SET not in parser.sections():
+ _DOC_SET = 'document_sets_default'
+
+for section in [ _DOC_SET ]:
+ print("Document sets to generate:")
+ for candidate in [ 'scala_docs', 'clojure_docs', 'doxygen_docs', 'r_docs' ]:
+ print '%-12s : %s' % (candidate, parser.get(section, candidate))
+ print
+
+_MXNET_DOCS_BUILD_MXNET = parser.getboolean('mxnet', 'build_mxnet')
+_SCALA_DOCS = parser.getboolean(_DOC_SET, 'scala_docs')
+_CLOJURE_DOCS = parser.getboolean(_DOC_SET, 'clojure_docs')
+_DOXYGEN_DOCS = parser.getboolean(_DOC_SET, 'doxygen_docs')
+_R_DOCS = parser.getboolean(_DOC_SET, 'r_docs')
# white list to evaluate the code block output, such as ['tutorials/gluon']
_EVAL_WHILTELIST = []
@@ -72,7 +95,7 @@ def build_mxnet(app):
def build_r_docs(app):
"""build r pdf"""
r_root = app.builder.srcdir + '/../R-package'
- pdf_path = root_path + '/docs/api/r/mxnet-r-reference-manual.pdf'
+ pdf_path = app.builder.srcdir + '/api/r/mxnet-r-reference-manual.pdf'
_run_cmd('cd ' + r_root +
'; R -e "roxygen2::roxygenize()"; R CMD Rd2pdf . --no-preview -o ' + pdf_path)
dest_path = app.builder.outdir + '/api/r/'
@@ -383,13 +406,21 @@ def setup(app):
# If MXNET_DOCS_BUILD_MXNET is set something different than 1
# Skip the build step
- if os.getenv('MXNET_DOCS_BUILD_MXNET', '1') == '1':
+ if os.getenv('MXNET_DOCS_BUILD_MXNET', '1') == '1' or _MXNET_DOCS_BUILD_MXNET:
+ print("Building MXNet!")
app.connect("builder-inited", build_mxnet)
- app.connect("builder-inited", generate_doxygen)
- app.connect("builder-inited", build_scala_docs)
- app.connect("builder-inited", build_clojure_docs)
- # skipped to build r, it requires to install latex, which is kinds of too heavy
- # app.connect("builder-inited", build_r_docs)
+ if _DOXYGEN_DOCS:
+ print("Building Doxygen!")
+ app.connect("builder-inited", generate_doxygen)
+ if _SCALA_DOCS:
+ print("Building Scala Docs!")
+ app.connect("builder-inited", build_scala_docs)
+ if _CLOJURE_DOCS:
+ print("Building Clojure Docs!")
+ app.connect("builder-inited", build_clojure_docs)
+ if _R_DOCS:
+ print("Building R Docs!")
+ app.connect("builder-inited", build_r_docs)
app.connect('source-read', convert_table)
app.connect('source-read', add_buttons)
app.add_config_value('recommonmark_config', {
diff --git a/docs/settings.ini b/docs/settings.ini
new file mode 100644
index 00000000000..b438a071f70
--- /dev/null
+++ b/docs/settings.ini
@@ -0,0 +1,38 @@
+[mxnet]
+build_mxnet = 0
+
+[document_sets_default]
+clojure_docs = 1
+doxygen_docs = 1
+r_docs = 0
+scala_docs = 1
+
+[document_sets_1.2.0]
+clojure_docs = 0
+doxygen_docs = 1
+r_docs = 0
+scala_docs = 1
+
+[document_sets_1.1.0]
+clojure_docs = 0
+doxygen_docs = 1
+r_docs = 0
+scala_docs = 0
+
+[document_sets_1.0.0]
+clojure_docs = 0
+doxygen_docs = 1
+r_docs = 0
+scala_docs = 0
+
+[document_sets_0.12.0]
+clojure_docs = 0
+doxygen_docs = 1
+r_docs = 0
+scala_docs = 0
+
+[document_sets_0.11.0]
+clojure_docs = 0
+doxygen_docs = 1
+r_docs = 0
+scala_docs = 0
diff --git a/docs/tutorials/basic/symbol.md b/docs/tutorials/basic/symbol.md
index 3a40e597846..aafaa1fa9b1 100644
--- a/docs/tutorials/basic/symbol.md
+++ b/docs/tutorials/basic/symbol.md
@@ -94,7 +94,7 @@ mx.viz.plot_network(symbol=g)
The computations declared in the above examples can be bound to the input data
for evaluation by using `bind` method. We discuss this further in the
-[symbol manipulation](#Symbol Manipulation) section.
+[Symbol Manipulation](#symbol-manipulation) section.
### Basic Neural Networks
diff --git a/example/deep-embedded-clustering/model.py b/example/deep-embedded-clustering/model.py
index 777634e3cf8..9b6185c9fd1 100644
--- a/example/deep-embedded-clustering/model.py
+++ b/example/deep-embedded-clustering/model.py
@@ -22,7 +22,7 @@
import numpy as np
try:
import cPickle as pickle
-except ModuleNotFoundError:
+except ImportError:
import pickle
@@ -75,4 +75,4 @@ def load(self, fname):
self.args[key][:] = v
def setup(self, *args, **kwargs):
- raise NotImplementedError("must override this")
\ No newline at end of file
+ raise NotImplementedError("must override this")
diff --git a/example/neural-style/end_to_end/model_vgg19.py b/example/neural-style/end_to_end/model_vgg19.py
index 0d369ae08f5..1bc38766beb 100644
--- a/example/neural-style/end_to_end/model_vgg19.py
+++ b/example/neural-style/end_to_end/model_vgg19.py
@@ -90,6 +90,7 @@ def get_executor_with_style(style, content, input_size, ctx):
arg_dict=arg_dict)
def get_executor_content(content, input_size, ctx):
+ out = mx.sym.Group([content])
arg_shapes, output_shapes, aux_shapes = content.infer_shape(data=(1, 3, input_size[0], input_size[1]))
arg_names = out.list_arguments()
arg_dict = dict(zip(arg_names, [mx.nd.zeros(shape, ctx=ctx) for shape in arg_shapes]))
diff --git a/example/profiler/README.md b/example/profiler/README.md
index 7d3c42b629d..1b9279ccf22 100644
--- a/example/profiler/README.md
+++ b/example/profiler/README.md
@@ -5,8 +5,12 @@ Please refer to [this link](http://mxnet.incubator.apache.org/faq/perf.html?high
for visualizing profiling results and make sure that you have installed a version of MXNet compiled
with `USE_PROFILER=1`.
-- profiler_executor.py. To run this example, simply type `python profiler_executor.py` in terminal.
-It will generate a json file named `profile_executor_5iter.json`.
+- profiler_executor.py. To run this example,
+ - clone mxnet-memonger (git clone https://github.com/dmlc/mxnet-memonger.git).
+ - Add mxnet-memonger folder to PYTHONPATH.
+ export PYTHONPATH=$PYTHONPATH:/path/to/mxnet-memonger
+ - type python profiler_executor.py in terminal.
+ It will generate a json file named `profile_executor_5iter.json`.
- profiler_imageiter.py. You first need to create a file named `test.rec`,
which is an image dataset file before running this example.
@@ -20,4 +24,4 @@ that you have installed a GPU enabled version of MXNet before running this examp
`python profiler_matmul.py` and it will generate `profile_matmul_20iter.json`.
- profiler_ndarray.py. This examples profiles a series of `NDArray` operations. Simply type
-`python profiler_ndarray.py` in terminal and it will generate `profile_ndarray.json`.
\ No newline at end of file
+`python profiler_ndarray.py` in terminal and it will generate `profile_ndarray.json`.
diff --git a/example/profiler/profiler_executor.py b/example/profiler/profiler_executor.py
index 8ab417a9744..91532535bd0 100644
--- a/example/profiler/profiler_executor.py
+++ b/example/profiler/profiler_executor.py
@@ -21,6 +21,7 @@
import time
import numpy as np
from mxnet import profiler
+import memonger
def parse_args():
@@ -86,7 +87,8 @@ def get_symbol():
def get_module(ctx, sym, provide_data, provide_label, batch_size=None, is_train=True, use_memonger=False):
if use_memonger:
- sym = search_plan(sym, data=data_shapes)
+ name, data_shapes = provide_data[0]
+ sym = memonger.search_plan(sym, data=data_shapes)
mod = mx.mod.Module(symbol=sym,
data_names=[name for name, _ in provide_data],
label_names=[name for name, _ in provide_label],
diff --git a/example/reinforcement-learning/a3c/a3c.py b/example/reinforcement-learning/a3c/a3c.py
index f74ce77b652..c100f61304d 100644
--- a/example/reinforcement-learning/a3c/a3c.py
+++ b/example/reinforcement-learning/a3c/a3c.py
@@ -203,7 +203,7 @@ def test():
mx.gpu(int(i)) for i in args.gpus.split(',')]
# module
- dataiter = robo_data.RobosimsDataIter('scenes', args.batch_size, args.input_length, web_viz=True)
+ dataiter = rl_data.GymDataIter('scenes', args.batch_size, args.input_length, web_viz=True)
print(dataiter.provide_data)
net = sym.get_symbol_thor(dataiter.act_dim)
module = mx.mod.Module(net, data_names=[d[0] for d in dataiter.provide_data], label_names=('policy_label', 'value_label'), context=devs)
diff --git a/example/sparse/factorization_machine/metric.py b/example/sparse/factorization_machine/metric.py
index 05ef04a0c48..a8c52c781c0 100644
--- a/example/sparse/factorization_machine/metric.py
+++ b/example/sparse/factorization_machine/metric.py
@@ -107,7 +107,9 @@ def update(self, labels, preds):
label_sum = label_weight.sum()
if label_sum == 0 or label_sum == label_weight.size:
raise Exception("AUC with one class is undefined")
-
+
+ label_one_num = np.count_nonzero(label_weight)
+ label_zero_num = len(label_weight) - label_one_num
total_area = label_zero_num * label_one_num
height = 0
width = 0
diff --git a/python/mxnet/gluon/data/dataloader.py b/python/mxnet/gluon/data/dataloader.py
index e0b6aec294a..412d3134476 100644
--- a/python/mxnet/gluon/data/dataloader.py
+++ b/python/mxnet/gluon/data/dataloader.py
@@ -183,7 +183,8 @@ def fetcher_loop(data_queue, data_buffer, pin_memory=False):
class _MultiWorkerIter(object):
"""Interal multi-worker iterator for DataLoader."""
- def __init__(self, num_workers, dataset, batchify_fn, batch_sampler, pin_memory=False):
+ def __init__(self, num_workers, dataset, batchify_fn, batch_sampler, pin_memory=False,
+ worker_fn=worker_loop):
assert num_workers > 0, "_MultiWorkerIter is not for {} workers".format(num_workers)
self._num_workers = num_workers
self._dataset = dataset
@@ -200,7 +201,7 @@ def __init__(self, num_workers, dataset, batchify_fn, batch_sampler, pin_memory=
workers = []
for _ in range(self._num_workers):
worker = multiprocessing.Process(
- target=worker_loop,
+ target=worker_fn,
args=(self._dataset, self._key_queue, self._data_queue, self._batchify_fn))
worker.daemon = True
worker.start()
diff --git a/python/mxnet/module/base_module.py b/python/mxnet/module/base_module.py
index 654e41bf365..08ab8fa89e4 100644
--- a/python/mxnet/module/base_module.py
+++ b/python/mxnet/module/base_module.py
@@ -22,6 +22,7 @@
import time
import logging
import warnings
+import numpy as np
from .. import metric
from .. import ndarray
@@ -29,7 +30,7 @@
from ..context import cpu
from ..model import BatchEndParam
from ..initializer import Uniform
-from ..io import DataDesc
+from ..io import DataDesc, DataIter, DataBatch
from ..base import _as_list
@@ -333,7 +334,7 @@ def predict(self, eval_data, num_batch=None, merge_batches=True, reset=True,
Parameters
----------
- eval_data : DataIter
+ eval_data : DataIter or NDArray or numpy array
Evaluation data to run prediction on.
num_batch : int
Defaults to ``None``, indicates running all the batches in the data iterator.
@@ -363,6 +364,15 @@ def predict(self, eval_data, num_batch=None, merge_batches=True, reset=True,
"""
assert self.binded and self.params_initialized
+ if isinstance(eval_data, (ndarray.NDArray, np.ndarray)):
+ if isinstance(eval_data, np.ndarray):
+ eval_data = ndarray.array(eval_data)
+ self.forward(DataBatch([eval_data]))
+ return self.get_outputs()[0]
+
+ if not isinstance(eval_data, DataIter):
+ raise ValueError('eval_data must be of type NDArray or DataIter')
+
if reset:
eval_data.reset()
diff --git a/python/mxnet/ndarray_doc.py b/python/mxnet/ndarray_doc.py
index 0c51036d820..9d6258a89a3 100644
--- a/python/mxnet/ndarray_doc.py
+++ b/python/mxnet/ndarray_doc.py
@@ -105,6 +105,21 @@ class BroadcastToDoc(NDArrayDoc):
(2L, 2L, 2L, 3L)
"""
+class StackDoc(NDArrayDoc):
+ """
+ Example
+ --------
+ Join a sequence of arrays along a new axis.
+ >>> x = mx.nd.array([1, 2])
+ >>> y = mx.nd.array([3, 4])
+ >>> stack(x, y)
+ [[1, 2],
+ [3, 4]]
+ >>> stack(x, y, axis=1)
+ [[1, 3],
+ [2, 4]]
+ """
+
class CustomDoc(NDArrayDoc):
"""
Example
diff --git a/python/mxnet/optimizer.py b/python/mxnet/optimizer.py
index ab7dadb17a5..b69d0c9af0d 100644
--- a/python/mxnet/optimizer.py
+++ b/python/mxnet/optimizer.py
@@ -1,3 +1,4 @@
+# coding: utf-8
# 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
@@ -15,7 +16,6 @@
# specific language governing permissions and limitations
# under the License.
-# coding: utf-8
# pylint: disable=too-many-lines
"""Weight updating functions."""
import logging
@@ -548,7 +548,7 @@ def update_multi_precision(self, index, weight, grad, state):
@register
class Signum(Optimizer):
- """The Signum optimizer that takes the sign of gradient or momentum.
+ r"""The Signum optimizer that takes the sign of gradient or momentum.
The optimizer updates the weight by::
@@ -556,7 +556,11 @@ class Signum(Optimizer):
state = momentum * state + (1-momentum)*rescaled_grad
weight = (1 - lr * wd_lh) * weight - lr * sign(state)
- See the original paper at: https://jeremybernste.in/projects/amazon/signum.pdf
+ Reference:
+ Jeremy Bernstein, Yu-Xiang Wang, Kamyar Azizzadenesheli & Anima Anandkumar. (2018).
+ signSGD: Compressed Optimisation for Non-Convex Problems. In ICML'18.
+
+ See: https://arxiv.org/abs/1802.04434
For details of the update algorithm see
:class:`~mxnet.ndarray.signsgd_update` and :class:`~mxnet.ndarray.signum_update`.
diff --git a/src/operator/tensor/indexing_op.cc b/src/operator/tensor/indexing_op.cc
index ef59145bb4a..b663ef0179d 100644
--- a/src/operator/tensor/indexing_op.cc
+++ b/src/operator/tensor/indexing_op.cc
@@ -570,6 +570,10 @@ Examples::
indices = [[1, 1, 0], [0, 1, 0]]
gather_nd(data, indices) = [2, 3, 0]
+ data = [[[1, 2], [3, 4]], [[5, 6], [7, 8]]]
+ indices = [[0, 1], [1, 0]]
+ gather_nd(data, indices) = [[3, 4], [5, 6]]
+
)code")
.set_num_outputs(1)
.set_num_inputs(2)
@@ -629,6 +633,21 @@ Examples::
shape = (2, 2)
scatter_nd(data, indices, shape) = [[0, 0], [2, 3]]
+ data = [[[1, 2], [3, 4]], [[5, 6], [7, 8]]]
+ indices = [[0, 1], [1, 1]]
+ shape = (2, 2, 2, 2)
+ scatter_nd(data, indices, shape) = [[[[0, 0],
+ [0, 0]],
+
+ [[1, 2],
+ [3, 4]]],
+
+ [[[0, 0],
+ [0, 0]],
+
+ [[5, 6],
+ [7, 8]]]]
+
)code")
.set_num_outputs(1)
.set_num_inputs(2)
diff --git a/src/operator/tensor/indexing_op.h b/src/operator/tensor/indexing_op.h
index edaf9397303..1daf0a2cb18 100644
--- a/src/operator/tensor/indexing_op.h
+++ b/src/operator/tensor/indexing_op.h
@@ -1034,8 +1034,8 @@ void TakeOpBackward(const nnvm::NodeAttrs& attrs,
using namespace mshadow::expr;
CHECK_EQ(inputs.size(), 2U);
CHECK_EQ(outputs.size(), 2U);
- CHECK_EQ(req[take_::kIdx], kNullOp)
- << "take layer doesn't support gradient into index";
+ CHECK_NE(req[take_::kIdx], kAddTo)
+ << "take layer doesn't support gradient of req type kAddTo to index";
const TakeParam& param = nnvm::get<TakeParam>(attrs.parsed);
@@ -1052,6 +1052,11 @@ void TakeOpBackward(const nnvm::NodeAttrs& attrs,
const TShape& arrshape = outputs[0].shape_;
const TShape& oshape = inputs[0].shape_;
+ if (req[take_::kIdx] != kNullOp) {
+ mxnet_op::Kernel<mxnet_op::set_zero, xpu>::Launch(
+ s, idxshape.Size(), outputs[take_::kIdx].dptr<IType>());
+ }
+
const int actual_axis = param.axis + ((param.axis < 0) ? arrshape.ndim() : 0);
int idxndim = idxshape.ndim();
diff --git a/tests/nightly/apache_rat_license_check/README.md b/tests/nightly/apache_rat_license_check/README.md
index 04def917636..e8578a85722 100755
--- a/tests/nightly/apache_rat_license_check/README.md
+++ b/tests/nightly/apache_rat_license_check/README.md
@@ -14,7 +14,7 @@ The following commands can be used to run a Apache RAT check locally -
Docker based 1-click-method:
```
-ci/build.py --platform ubuntu_rat /work/runtime_functions.sh nightly_test_rat_check
+ci/build.py -p ubuntu_rat nightly_test_rat_check
```
Manual method:
@@ -25,8 +25,8 @@ sudo apt-get install maven -y #>/dev/null
#install svn
sudo apt-get install subversion -y #>/dev/null
-#download RAT
-svn co http://svn.apache.org/repos/asf/creadur/rat/trunk/ #>/dev/null
+#download RAT 0.12 version
+svn co http://svn.apache.org/repos/asf/creadur/rat/tags/apache-rat-project-0.12-RC3/ #>/dev/null
#cd into correct directory
cd trunk
@@ -38,5 +38,5 @@ mvn install #>/dev/null
cd apache-rat/target
#run Apache RAT check on the src
-java -jar apache-rat-0.13-SNAPSHOT.jar -E <path-to-.rat-excludes-file> -d <path-to-mxnet-source>
+java -jar apache-rat-0.12.jar -E <path-to-.rat-excludes-file> -d <path-to-mxnet-source>
```
diff --git a/tests/python/unittest/test_loss.py b/tests/python/unittest/test_loss.py
index 2cdc2909ffc..24cc747a308 100644
--- a/tests/python/unittest/test_loss.py
+++ b/tests/python/unittest/test_loss.py
@@ -274,7 +274,7 @@ def test_saveload():
eval_metric=mx.metric.Loss())
assert mod.score(data_iter, eval_metric=mx.metric.Loss())[0][1] < 0.05
-@with_seed(1234)
+@with_seed()
def test_huber_loss():
N = 20
data = mx.random.uniform(-1, 1, shape=(N, 10))
diff --git a/tests/python/unittest/test_module.py b/tests/python/unittest/test_module.py
index a21527a5a4a..5e60989489f 100644
--- a/tests/python/unittest/test_module.py
+++ b/tests/python/unittest/test_module.py
@@ -772,6 +772,8 @@ def test_forward_reshape():
for_training=False, force_rebind=True)
assert mod.predict(pred_dataiter).shape == tuple([10, num_class])
+@with_seed()
+def test_forward_types():
#Test forward with other data batch API
Batch = namedtuple('Batch', ['data'])
data = mx.sym.Variable('data')
@@ -786,6 +788,18 @@ def test_forward_reshape():
mod.forward(Batch(data2))
assert mod.get_outputs()[0].shape == (3, 5)
+ #Test forward with other NDArray and np.ndarray inputs
+ data = mx.sym.Variable('data')
+ out = data * 2
+ mod = mx.mod.Module(symbol=out, label_names=None)
+ mod.bind(data_shapes=[('data', (1, 10))])
+ mod.init_params()
+ data1 = mx.nd.ones((1, 10))
+ assert mod.predict(data1).shape == (1, 10)
+ data2 = np.ones((1, 10))
+ assert mod.predict(data1).shape == (1, 10)
+
+
if __name__ == '__main__':
import nose
diff --git a/tests/python/unittest/test_operator.py b/tests/python/unittest/test_operator.py
index c395199e8ea..f1aec12ccc3 100644
--- a/tests/python/unittest/test_operator.py
+++ b/tests/python/unittest/test_operator.py
@@ -3190,7 +3190,7 @@ def l2norm(input_data, axis=0, keepdims=True):
for order in [1, 2]:
for dtype in [np.float16, np.float32, np.float64]:
in_data = np.random.uniform(-1, 1, in_shape).astype(dtype)
- in_data[abs(in_data) < epsilon] = epsilon
+ in_data[abs(in_data) < epsilon] = 2 * epsilon
for i in range(in_data_dim):
norm_sym = mx.symbol.norm(data=data, ord=order, axis=i, keepdims=True)
npy_out = l1norm(in_data, i) if order is 1 else l2norm(in_data, i)
@@ -3204,20 +3204,22 @@ def l2norm(input_data, axis=0, keepdims=True):
atol=1e-2 if dtype is np.float16 else 1e-5, ctx=ctx)
# Disable numeric gradient https://github.com/apache/incubator-mxnet/issues/11509
# # check gradient
- # check_numeric_gradient(norm_sym, [in_data], numeric_eps=epsilon, rtol=1e-2, atol=1e-3)
- # if i < in_data_dim-1:
- # norm_sym = mx.symbol.norm(data=data, ord=order, axis=(i, i+1), keepdims=True)
- # npy_out = l1norm(in_data, (i, i+1)) if order is 1 else l2norm(in_data, (i, i+1))
- # npy_out_backward = np.sign(in_data) if order is 1 else in_data/npy_out
- # check_symbolic_forward(norm_sym, [in_data], [npy_out],
- # rtol=1e-2 if dtype is np.float16 else 1e-5,
- # atol=1e-2 if dtype is np.float16 else 1e-5, ctx=ctx)
- # check_symbolic_backward(norm_sym, [in_data], [np.ones(npy_out.shape)],
- # [npy_out_backward],
- # rtol=1e-2 if dtype is np.float16 else 1e-5,
- # atol=1e-2 if dtype is np.float16 else 1e-5, ctx=ctx)
- # # check gradient
- # check_numeric_gradient(norm_sym, [in_data], numeric_eps=epsilon, rtol=1e-2, atol=1e-3)
+ # if dtype is not np.float16:
+ # check_numeric_gradient(norm_sym, [in_data], numeric_eps=epsilon, rtol=1e-1, atol=1e-3)
+ if i < in_data_dim-1:
+ norm_sym = mx.symbol.norm(data=data, ord=order, axis=(i, i+1), keepdims=True)
+ npy_out = l1norm(in_data, (i, i+1)) if order is 1 else l2norm(in_data, (i, i+1))
+ npy_out_backward = np.sign(in_data) if order is 1 else in_data/npy_out
+ check_symbolic_forward(norm_sym, [in_data], [npy_out],
+ rtol=1e-2 if dtype is np.float16 else 1e-5,
+ atol=1e-2 if dtype is np.float16 else 1e-5, ctx=ctx)
+ check_symbolic_backward(norm_sym, [in_data], [np.ones(npy_out.shape)],
+ [npy_out_backward],
+ rtol=1e-2 if dtype is np.float16 else 1e-5,
+ atol=1e-2 if dtype is np.float16 else 1e-5, ctx=ctx)
+ # # check gradient
+ # if dtype is not np.float16:
+ # check_numeric_gradient(norm_sym, [in_data], numeric_eps=epsilon, rtol=1e-1, atol=1e-3)
def test_layer_norm():
@@ -3810,6 +3812,31 @@ def check_output_n_grad(data_shape, idx_shape, axis, mode):
exe.backward([mx.nd.array(grad_out)])
assert_almost_equal(exe.grad_dict['a'].asnumpy(), grad_in)
+ def check_autograd_req():
+ row_len = 2
+ col_len = 8
+ shape = (row_len, col_len)
+ sc = mx.nd.random.uniform(-1.0, 1.0, shape=shape, dtype="float32")
+ sc.attach_grad()
+ i = mx.nd.array([0], dtype="int64")
+ j = mx.nd.array([0], dtype="int64")
+ with mx.autograd.record(train_mode=True):
+ xs = []
+ for _ in range(row_len):
+ x_i = []
+ for _ in range(col_len):
+ x_ij = sc.take(i).squeeze(axis=0).take(j).squeeze(axis=0)
+ x_i.append(x_ij)
+ j = j + 1
+ i = i + 1
+ j = j - col_len # reset j
+ xs.append(mx.nd.stack(*x_i))
+ x = mx.nd.stack(*xs)
+ x = x.sum()
+
+ x.backward()
+ assert_almost_equal(np.ones(sc.grad.shape), sc.grad.asnumpy())
+
for mode in ['clip', 'wrap']:
for data_ndim in range(1, 5):
for idx_ndim in range(1, 4):
@@ -3822,6 +3849,8 @@ def check_output_n_grad(data_shape, idx_shape, axis, mode):
idx_shape += (np.random.randint(low=1, high=5), )
check_output_n_grad(data_shape, idx_shape, axis, mode)
+ check_autograd_req()
+
@with_seed()
def test_grid_generator():
diff --git a/tests/python/unittest/test_optimizer.py b/tests/python/unittest/test_optimizer.py
index bdd71eef81a..449cdb42346 100644
--- a/tests/python/unittest/test_optimizer.py
+++ b/tests/python/unittest/test_optimizer.py
@@ -943,7 +943,7 @@ def test_ftrl():
compare_optimizer(opt1(lazy_update=True, **kwarg), opt2(**kwarg), shape,
np.float32, w_stype='row_sparse', g_stype='row_sparse')
-@with_seed(1234)
+@with_seed()
def test_nadam():
def get_net(num_hidden, flatten=True):
@@ -965,10 +965,10 @@ def get_net(num_hidden, flatten=True):
loss = Loss(output, l)
loss = mx.sym.make_loss(loss)
mod = mx.mod.Module(loss, data_names=('data',), label_names=('label',))
- mod.fit(data_iter, num_epoch=60, optimizer_params={'learning_rate': 0.0005, 'wd': 0.0005},
+ mod.fit(data_iter, num_epoch=60, optimizer_params={'learning_rate': 0.001, 'wd': 0.0005},
initializer=mx.init.Xavier(magnitude=2), eval_metric=mx.metric.Loss(),
optimizer='nadam')
- assert mod.score(data_iter, eval_metric=mx.metric.Loss())[0][1] < 0.1
+ assert mod.score(data_iter, eval_metric=mx.metric.Loss())[0][1] < 0.11
# AdaGrad
class PyAdaGrad(mx.optimizer.Optimizer):
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