[v1.9.x]Update git repo reference (#20496)

* update git repo url

* remove incubator

* fix typo

Co-authored-by: Wei Chu <weichu@amazon.com>

Author: waytrue17

3rdparty/mshadow/README.md

@@ -50,5 +50,5 @@ Version
 
 Projects Using MShadow
 ----------------------
-* [MXNet: Efficient and Flexible Distributed Deep Learning Framework](https://github.com/dmlc/mxnet)
+* [MXNet: Efficient and Flexible Distributed Deep Learning Framework](https://github.com/apache/mxnet)
 * [CXXNet: A lightweight  C++ based deep learnig framework](https://github.com/dmlc/cxxnet)

NEWS.md

@@ -3572,7 +3572,7 @@ For more information and examples, see [full release notes](https://cwiki.apache
   - ImageRecordIter now stores data in pinned memory to improve GPU memcopy speed.
 ### Bugfixes
   - Cython interface is fixed. `make cython` and `python setup.py install --with-cython` should install the cython interface and reduce overhead in applications that use imperative/bucketing.
-  - Fixed various bugs in Faster-RCNN example: https://github.com/dmlc/mxnet/pull/6486
+  - Fixed various bugs in Faster-RCNN example: https://github.com/apache/mxnet/pull/6486
   - Fixed various bugs in SSD example.
   - Fixed `out` argument not working for `zeros`, `ones`, `full`, etc.
   - `expand_dims` now supports backward shape inference.
@@ -3648,9 +3648,9 @@ This is the last release before the NNVM refactor.
 - Support CuDNN v5 by @antinucleon
 - More applications
   - Speech recognition by @yzhang87
-  - [Neural art](https://github.com/dmlc/mxnet/tree/master/example/neural-style) by @antinucleon
-  - [Detection](https://github.com/dmlc/mxnet/tree/master/example/rcnn), RCNN bt @precedenceguo
-  - [Segmentation](https://github.com/dmlc/mxnet/tree/master/example/fcn-xs), FCN by @tornadomeet
+  - [Neural art](https://github.com/apache/mxnet/tree/v0.7.0/example/neural-style) by @antinucleon
+  - [Detection](https://github.com/apache/mxnet/tree/v0.7.0/example/rcnn), RCNN bt @precedenceguo
+  - [Segmentation](https://github.com/apache/mxnet/tree/v0.7.0/example/fcn-xs), FCN by @tornadomeet
   - [Face identification](https://github.com/tornadomeet/mxnet-face) by @tornadomeet
   - More on the example
 

R-package/R/zzz.R

@@ -63,7 +63,7 @@ NULL
   if (!interactive() || stats::runif(1) > 0.1) return()
 
   tips <- c(
-    "Need help? Feel free to open an issue on https://github.com/dmlc/mxnet/issues",
+    "Need help? Feel free to open an issue on https://github.com/apache/mxnet/issues",
     "For more documents, please visit https://mxnet.io",
     "Use suppressPackageStartupMessages() to eliminate package startup messages."
   )

R-package/vignettes/CallbackFunction.Rmd

@@ -75,7 +75,7 @@ head(logger$eval)
 ## How to write your own callback functions
 
 
-You can find the source code for two callback functions from [here](https://github.com/dmlc/mxnet/blob/master/R-package/R/callback.R) and they can be used as your template:
+You can find the source code for two callback functions from [here](https://github.com/apache/mxnet/blob/v1.x/R-package/R/callback.R) and they can be used as your template:
 
 Basically, all callback functions follow the structure below:
 

R-package/vignettes/CustomIterator.Rmd

@@ -19,7 +19,7 @@ You'll get two files, `mnist_train.csv` that contains 60.000 examples of hand wr
 
 ## Custom CSV Iterator
 
-Next we are going to create a custom CSV Iterator based on the [C++ CSVIterator class](https://github.com/dmlc/mxnet/blob/master/src/io/iter_csv.cc).
+Next we are going to create a custom CSV Iterator based on the [C++ CSVIterator class](https://github.com/apache/mxnet/blob/master/src/io/iter_csv.cc).
 
 For that we are going to use the R function `mx.io.CSVIter` as a base class. This class has as parameters `data.csv, data.shape, batch.size` and two main functions, `iter.next()` that calls the iterator in the next batch of data and `value()` that returns the train data and the label.
 

R-package/vignettes/mnistCompetition.Rmd

@@ -1,7 +1,7 @@
 # Handwritten Digits Classification Competition
 
 [MNIST](http://yann.lecun.com/exdb/mnist/) is a handwritten digits image data set created by Yann LeCun. Every digit is represented by a 28x28 image. It has become a standard data set to test classifiers on simple image input. Neural network is no doubt a strong model for image classification tasks. There's a [long-term hosted competition](https://www.kaggle.com/c/digit-recognizer) on Kaggle using this data set.
-We will present the basic usage of [mxnet](https://github.com/dmlc/mxnet/tree/master/R-package) to compete in this challenge.
+We will present the basic usage of [mxnet](https://github.com/apache/mxnet/tree/v1.x/R-package) to compete in this challenge.
 
 ## Data Loading
 

README.md

@@ -81,10 +81,10 @@ What's New
 * [0.12.0 Release](https://github.com/apache/incubator-mxnet/releases/tag/0.12.0) - MXNet 0.12.0 Release.
 * [0.11.0 Release](https://github.com/apache/incubator-mxnet/releases/tag/0.11.0) - MXNet 0.11.0 Release.
 * [Apache Incubator](http://incubator.apache.org/projects/mxnet.html) - We are now an Apache Incubator project.
-* [0.10.0 Release](https://github.com/dmlc/mxnet/releases/tag/v0.10.0) - MXNet 0.10.0 Release.
+* [0.10.0 Release](https://github.com/apache/mxnet/releases/tag/v0.10.0) - MXNet 0.10.0 Release.
 * [0.9.3 Release](./docs/architecture/release_note_0_9.md) - First 0.9 official release.
 * [0.9.1 Release (NNVM refactor)](./docs/architecture/release_note_0_9.md) - NNVM branch is merged into master now. An official release will be made soon.
-* [0.8.0 Release](https://github.com/dmlc/mxnet/releases/tag/v0.8.0)
+* [0.8.0 Release](https://github.com/apache/mxnet/releases/tag/v0.8.0)
 
 ### Ecosystem News
 

docker/Dockerfiles/Dockerfile.in.lib.cpu

@@ -24,6 +24,6 @@ FROM ubuntu:14.04
 COPY install/cpp.sh install/
 RUN install/cpp.sh
 
-RUN git clone --recursive https://github.com/dmlc/mxnet && cd mxnet && \
+RUN git clone --recursive https://github.com/apache/mxnet && cd mxnet && \
     make -j$(nproc) && \
     rm -r build

docker/Dockerfiles/Dockerfile.in.lib.gpu

@@ -25,5 +25,5 @@ COPY install/cpp.sh install/
 RUN install/cpp.sh
 
 ENV BUILD_OPTS "USE_CUDA=1 USE_CUDA_PATH=/usr/local/cuda USE_CUDNN=1"
-RUN git clone --recursive https://github.com/dmlc/mxnet && cd mxnet && \
+RUN git clone --recursive https://github.com/apache/mxnet && cd mxnet && \
     make -j$(nproc) $BUILD_OPTS

docs/static_site/src/pages/api/faq/caffe.md

@@ -32,7 +32,7 @@ Key topics covered include the following:
 ## Converting Caffe trained models to MXNet
 
 The converting tool is available at
-[tools/caffe_converter](https://github.com/dmlc/mxnet/tree/master/tools/caffe_converter). On
+[tools/caffe_converter](https://github.com/apache/mxnet/tree/v1.x/tools/caffe_converter). On
 the remaining of this section, we assume we are on the `tools/caffe_converter`
 directory.
 
@@ -205,4 +205,4 @@ train = mx.io.CaffeDataIter(
 ### Put it all together
 
 The complete example is available at
-[example/caffe](https://github.com/dmlc/mxnet/blob/master/example/caffe/)
+[example/caffe](https://github.com/apache/mxnet/blob/v1.x/example/caffe/)