Bumped minor version from 1.4.0 to 1.5.0 on master, updated License f…

…ile (#13478)

* updated to v1.5.0

* Bumped minor version from 1.4.0 to 1.5.0 on master

* added Anirudh as maintainer for R package

... adding something useful and re-trigger PR check

* Updated license file for clojure, onnx-tensorrt, gtest, R-package

* Get the correct include path in pip package (#13452)

* add find_include_path API

* address reviewer comment

* change return type from list to string

* add unit test

* address reviewer comment

* address reviewer comment

* address reviewer comment

* address reviewer comment

* fix include path problem in pip package

* add comment

* fix lint error

* address reviewer comment

* address reviewer comment

* Use ~/.ccache as default ccache directory so is not cache is not erased on reboot (#13431)

* Skip flaky test #13446 (#13480)

* Rewrite dataloader with process pool, improves responsiveness and reliability (#13447)

* fix recordio.py

* rewrite dataloader with pool

* fix batch as tuple

* fix prefetching

* fix pylint

* picklable function

* use pickle

* add missing commit

* Fix errors in docstrings for subgraph op; use code directive (#13463)

* [MXNET-1158] JVM Memory Management Documentation (#13105)

* update train_mnist

* Add documentation for JVM Memory Management

* update doc

* address nit picks

* address nit picks

* Grammar and clarity edits for memory management doc

* Edits for scala memory management

* Update memory-management.md

* Update memory-management.md

* Update memory-management.md

* capitalization fix

* Update row_sparse tutorial (#13414)

Update row_sparse tutorial

* Add resiliency to onnx export code (#13426)

* Added resiliency to onnx export code

- With previous infer-shape implementation, if input shape was list instead of tuple or if extra non-existent parameters were provided, the code would still work. The fixes in this commit make sure that behavior is restored to prevent any compatibility issues with existing export code.

* Fixed name of net in unittest

* Fix pylint

* [MXNET-1185] Support large array in several operators (part 1) (#13418)

* fix a few operators with large arrays (# of elements)

* fix bug in broadcast_div and add tests

* address reviewer comment

* add unit test

* add empty line

* retrigger CI

* [MXNET-1210 ] Gluon Audio - Example (#13325)

* Initialized the example

* Addressed PR comments, about existing synset.txt file - no overwrite

* RST - docstring issues fixed

* added README

* Addressed PR comments

* Addressed PR comments, checking Divide by 0

* Raising error if format is not supported.

* changed a line for ndarray of labels

* Trigger CI

* Trigger CI

* PR comments addressed around skip_header argument

* Addressed PR comments around librosa import

* PR Comments

* Passing lazy=lazy from argument

* Added PR comments, labels to README.MD

* Trigger CI

* Addressing PR Comments in README

* Modified README.md

* Added example under audio folder

* Retrigger CI

* Retrigger CI

* ONNX export: Instance normalization, Shape (#12920)

* ONNX import/export: Make backend_rep common

* ONNX export: Instance Normalization

* ONNX export: Shape operator

* Clarify dependency on OpenCV in CNN Visualization tutorial. (#13495)

* clarify ops faq regarding docs strings (#13492)

* Add graph_compact operator. (#13436)

* add graph_compact.

* fix.

* add doc.

* add tests for graph_compact.

* address comments.

* update docs.

* trigger CI

* Deprecate Jenkinsfile (#13474)

* update github location for sampled_block.py (#13508)

Updated to https://github.com/dmlc/gluon-nlp/blob/master/src/gluonnlp/model/sampled_block.py

* #13453 [Clojure] - Add Spec Validations to the Optimizer namespace (#13499)

* ONNX export: Logical operators (#12852)

* Fix cmake options parsing in dev_menu (#13458)

Add GPU+MKLDNN unittests to dev_menu

* Revert "Manually track num_max_thread (#12380)" (#13501)

This reverts commit 7541021.

* Feature/mkldnn static 2 (#13503)

* build mkldnn as static lib

* update makefile to statically build mkldnn

* build static mkldnn

* fix static name

* fix static name

* update static for mac

* rename mkldnn dep in ci

* remove moving mkldnn dynamic lib

* remove commented code

* remove mkldnn dnaymic for unitest

* force static for mkldnn lib

* remove dynamic mkldnn bind

* only link windows

* add mkldnn.mk

* try force linking

* remove mkldnn dynanmic check

* remove test mkldnn install

* fix spacing

* fix index

* add artifacts

* add comment about windows

* remove static

* update makefile

* fix toctree Sphinx errors (#13489)

* fix toctree errors

* nudging file for CI

* Disabled flaky test test_gluon_data.test_recordimage_dataset_with_data_loader_multiworker (#13527)

* [MXNET-1234] Fix shape inference problems in Activation backward (#13409)

* Provide a failing test for ReLU activation shape inference bug

* Fix Activation backward shape inference

fixes: #13333

* Add softsign Activation to test_gluon.py

* Use activation in GPU if we are using CUDNN and not MKLDNN as it's happening right now

* Don't disable MKLDNN

CMakeLists.txt

@@ -227,6 +227,7 @@ if(USE_MKLDNN)
   include(cmake/DownloadMKLML.cmake)
   # CPU architecture (e.g., C5) can't run on another architecture (e.g., g3).
   if(NOT MSVC)
+    set(MKLDNN_LIBRARY_TYPE "STATIC" CACHE INTERNAL "" FORCE)
     set(ARCH_OPT_FLAGS "-mtune=generic")
   else()
     set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} /EHsc")

LICENSE

@@ -218,16 +218,20 @@
     1. MXNet Cpp-package - For details, /cpp-package/LICENSE
     2. MXNet rcnn - For details, see, example/rcnn/LICENSE
     3. scala-package - For details, see, scala-package/LICENSE
-    4. Warp-CTC - For details, see, src/operator/contrib/ctc_include/LICENSE
+    4. Warp-CTC - For details, see, 3rdparty/ctc_include/LICENSE
     5. 3rdparty/dlpack - For details, see, 3rdparty/dlpack/LICENSE
     6. 3rdparty/dmlc-core - For details, see, 3rdparty/dmlc-core/LICENSE
     7. 3rdparty/mshadow - For details, see, 3rdparty/mshadow/LICENSE
     8. 3rdparty/tvm - For details, see, 3rdparty/tvm/LICENSE
     9. 3rdparty/tvm/dmlc-core - For details, see, 3rdparty/tvm/dmlc-core/LICENSE
-    10. 3rdparty/tvm/nnvm - For details, see, 3rdparty/tvm/nnvm/LICENSE
-    11. 3rdparty/ps-lite - For details, see, 3rdparty/ps-lite/LICENSE
-    12. 3rdparty/mkldnn - For details, see, 3rdparty/mkldnn/LICENSE
-    13. googlemock scripts/generator - For details, see, 3rdparty/googletest/googlemock/scripts/generator/LICENSE
+    10. 3rdparty/tvm/dlpack - For details, see, 3rdparty/tvm/3rdparty/dlpack/LICENSE
+    11. 3rdparty/tvm/nnvm - For details, see, 3rdparty/tvm/nnvm/LICENSE
+    12. 3rdparty/ps-lite - For details, see, 3rdparty/ps-lite/LICENSE
+    13. 3rdparty/mkldnn - For details, see, 3rdparty/mkldnn/LICENSE
+    14. googlemock scripts/generator - For details, see, 3rdparty/googletest/googlemock/scripts/generator/LICENSE
+    15. clojure-package - For details, see, contrib/clojure-package/LICENSE
+    16. R-package - For details, see, R-package/LICENSE
+    17. ONNX-TensorRT benchmark package - For details, see, 3rdparty/onnx-tensorrt/third_party/onnx/third_party/benchmark/LICENSE
 
 
     =======================================================================================
@@ -239,14 +243,17 @@
     3. tree_lstm - For details, see example/gluon/tree_lstm/LICENSE
     4. OpenMP - For details, see 3rdparty/openmp/LICENSE.txt
     5. HalideIR - For details, see nnvm/tvm/HalideIR/LICENSE
+    6. HalideIR - For details, see 3rdparty/tvm/3rdparty/HalideIR/LICENSE
+    7. ONNX-TensorRT - For details, see 3rdparty/onnx-tensorrt/LICENSE
+    8. ONNX-TensorRT - For details, see 3rdparty/onnx-tensorrt/third_party/onnx/LICENSE
 
 
     =======================================================================================
     NVIDIA Licenses
     =======================================================================================
 
     1. Moderngpu
-    For details, see, src/operator/contrib/ctc_include/contrib/moderngpu/LICENSE
+    For details, see, 3rdparty/ctc_include/contrib/moderngpu/LICENSE
 
     /******************************************************************************
     * Redistribution and use in source and binary forms, with or without
@@ -559,4 +566,79 @@
     #  (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
     #  OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
+    =======================================================================================
+
+    12. Google tests
+        For details, ses, 3rdparty/mkldnn/tests/gtests/gtest/LICENSE
+
+    Copyright 2008, Google Inc.
+    All rights reserved.
+
+    Redistribution and use in source and binary forms, with or without
+    modification, are permitted provided that the following conditions are
+    met:
+
+        * Redistributions of source code must retain the above copyright
+    notice, this list of conditions and the following disclaimer.
+        * Redistributions in binary form must reproduce the above
+    copyright notice, this list of conditions and the following disclaimer
+    in the documentation and/or other materials provided with the
+    distribution.
+        * Neither the name of Google Inc. nor the names of its
+    contributors may be used to endorse or promote products derived from
+    this software without specific prior written permission.
+
+    THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+    "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+    LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+    A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+    OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+    SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+    LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+    DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+    THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+    (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+    OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+    =======================================================================================
+
+    13. ONNX python bindings
+    For details, see, 3rdparty/onnx-tensorrt/third_party/onnx/third_party/pybind11/LICENSE
+
+    Copyright (c) 2016 Wenzel Jakob <[email protected]>, All rights reserved.
+
+    Redistribution and use in source and binary forms, with or without
+    modification, are permitted provided that the following conditions are met:
+
+    1. Redistributions of source code must retain the above copyright notice, this
+       list of conditions and the following disclaimer.
+
+    2. Redistributions in binary form must reproduce the above copyright notice,
+       this list of conditions and the following disclaimer in the documentation
+       and/or other materials provided with the distribution.
+
+    3. Neither the name of the copyright holder nor the names of its contributors
+       may be used to endorse or promote products derived from this software
+       without specific prior written permission.
+
+    THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+    ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+    WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+    DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+    FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+    DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+    SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+    CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+    OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+    OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+    You are under no obligation whatsoever to provide any bug fixes, patches, or
+    upgrades to the features, functionality or performance of the source code
+    ("Enhancements") to anyone; however, if you choose to make your Enhancements
+    available either publicly, or directly to the author of this software, without
+    imposing a separate written license agreement for such Enhancements, then you
+    hereby grant the following license: a non-exclusive, royalty-free perpetual
+    license to install, use, modify, prepare derivative works, incorporate into
+    other computer software, distribute, and sublicense such enhancements or
+    derivative works thereof, in binary and source code form.
 

Makefile

@@ -131,8 +131,13 @@ ifeq ($(USE_MKLDNN), 1)
 		CFLAGS += -I$(MKLROOT)/include
 		LDFLAGS += -L$(MKLROOT)/lib
 	endif
-	CFLAGS += -I$(MKLDNNROOT)/include
-	LDFLAGS += -L$(MKLDNNROOT)/lib -lmkldnn -Wl,-rpath,'$${ORIGIN}'
+	# MKLDNN but to needs to be dynamically linked for windows as not all VS compilers support static linking
+	ifneq ($(UNAME_S), Windows)
+		LIB_DEP += $(MKLDNNROOT)/lib/libmkldnn.a
+	else
+		CFLAGS += -I$(MKLDNNROOT)/include
+		LDFLAGS += -L$(MKLDNNROOT)/lib -lmkldnn -Wl,-rpath,'$${ORIGIN}'
+	endif
 endif
 
 # setup opencv

R-package/DESCRIPTION

@@ -1,17 +1,17 @@
 Package: mxnet
 Type: Package
 Title: MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems
-Version: 1.4.0
+Version: 1.5.0
 Date: 2017-06-27
 Author: Tianqi Chen, Qiang Kou, Tong He
-Maintainer: Qiang Kou <[email protected]>
-Repository: DMLC
+Maintainer: Qiang Kou <[email protected]>, anirudhacharya <https://github.com/anirudhacharya>
+Repository: Apache
 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: Apache License (== 2.0)
-URL: https://github.com/dmlc/mxnet/tree/master/R-package
-BugReports: https://github.com/dmlc/mxnet/issues
+URL: https://github.com/apache/incubator-mxnet/tree/master/R-package
+BugReports: https://github.com/apache/incubator-mxnet/issues
 Imports:
     methods,
     Rcpp (>= 0.12.1),

ci/docker/runtime_functions.sh

@@ -629,9 +629,6 @@ build_ubuntu_gpu_cmake_mkldnn() {
         /work/mxnet
 
     ninja -v
-    # libmkldnn.so.0 is a link file. We need an actual binary file named libmkldnn.so.0.
-    cp 3rdparty/mkldnn/src/libmkldnn.so.0 3rdparty/mkldnn/src/libmkldnn.so.0.tmp
-    mv 3rdparty/mkldnn/src/libmkldnn.so.0.tmp 3rdparty/mkldnn/src/libmkldnn.so.0
 }
 
 build_ubuntu_gpu_cmake() {

ci/jenkins/Jenkins_steps.groovy

@@ -23,19 +23,19 @@
 utils = load('ci/Jenkinsfile_utils.groovy')
 
 // mxnet libraries
-mx_lib = 'lib/libmxnet.so, lib/libmxnet.a, 3rdparty/dmlc-core/libdmlc.a, 3rdparty/tvm/nnvm/lib/libnnvm.a'
+mx_lib = 'lib/libmxnet.so, lib/libmxnet.a, lib/libiomp5.so, lib/libmklml_intel.so, 3rdparty/dmlc-core/libdmlc.a, 3rdparty/tvm/nnvm/lib/libnnvm.a'
 
 // Python wheels
 mx_pip = 'build/*.whl'
 
 // for scala build, need to pass extra libs when run with dist_kvstore
-mx_dist_lib = 'lib/libmxnet.so, lib/libmxnet.a, 3rdparty/dmlc-core/libdmlc.a, 3rdparty/tvm/nnvm/lib/libnnvm.a, 3rdparty/ps-lite/build/libps.a, deps/lib/libprotobuf-lite.a, deps/lib/libzmq.a'
+mx_dist_lib = 'lib/libmxnet.so, lib/libmxnet.a, 3rdparty/dmlc-core/libdmlc.a, 3rdparty/tvm/nnvm/lib/libnnvm.a, 3rdparty/ps-lite/build/libps.a, deps/lib/libprotobuf-lite.a, deps/lib/libzmq.a, lib/libmkldnn.a'
 // mxnet cmake libraries, in cmake builds we do not produce a libnvvm static library by default.
 mx_cmake_lib = 'build/libmxnet.so, build/libmxnet.a, build/3rdparty/dmlc-core/libdmlc.a, build/tests/mxnet_unit_tests, build/3rdparty/openmp/runtime/src/libomp.so'
 // mxnet cmake libraries, in cmake builds we do not produce a libnvvm static library by default.
 mx_cmake_lib_debug = 'build/libmxnet.so, build/libmxnet.a, build/3rdparty/dmlc-core/libdmlc.a, build/tests/mxnet_unit_tests'
-mx_cmake_mkldnn_lib = 'build/libmxnet.so, build/libmxnet.a, build/3rdparty/dmlc-core/libdmlc.a, build/tests/mxnet_unit_tests, build/3rdparty/openmp/runtime/src/libomp.so, build/3rdparty/mkldnn/src/libmkldnn.so.0'
-mx_mkldnn_lib = 'lib/libmxnet.so, lib/libmxnet.a, lib/libiomp5.so, lib/libmkldnn.so.0, lib/libmklml_intel.so, 3rdparty/dmlc-core/libdmlc.a, 3rdparty/tvm/nnvm/lib/libnnvm.a'
+mx_cmake_mkldnn_lib = 'build/libmxnet.so, build/libmxnet.a, build/3rdparty/dmlc-core/libdmlc.a, build/tests/mxnet_unit_tests, build/3rdparty/openmp/runtime/src/libomp.so'
+mx_mkldnn_lib = 'lib/libmxnet.so, lib/libmxnet.a, lib/libiomp5.so, lib/libmklml_intel.so, 3rdparty/dmlc-core/libdmlc.a, 3rdparty/tvm/nnvm/lib/libnnvm.a'
 mx_tensorrt_lib = 'lib/libmxnet.so, lib/libnvonnxparser_runtime.so.0, lib/libnvonnxparser.so.0, lib/libonnx_proto.so, lib/libonnx.so'
 mx_lib_cpp_examples = 'lib/libmxnet.so, lib/libmxnet.a, 3rdparty/dmlc-core/libdmlc.a, 3rdparty/tvm/nnvm/lib/libnnvm.a, 3rdparty/ps-lite/build/libps.a, deps/lib/libprotobuf-lite.a, deps/lib/libzmq.a, build/cpp-package/example/*'
 mx_lib_cpp_examples_cpu = 'build/libmxnet.so, build/cpp-package/example/*'

contrib/clojure-package/README.md

@@ -105,9 +105,9 @@ brew install opencv
 - Create a new project with `lein new my-mxnet`
 - Edit your `project.clj` and add one of the following entries to `:dependencies`, based on your system and the compute device you want to use:
 
-  - `[org.apache.mxnet.contrib.clojure/clojure-mxnet-linux-cpu "1.4.0"]`
-  - `[org.apache.mxnet.contrib.clojure/clojure-mxnet-linux-gpu "1.4.0"]`
-  - `[org.apache.mxnet.contrib.clojure/clojure-mxnet-osx-cpu "1.4.0"]`
+  - `[org.apache.mxnet.contrib.clojure/clojure-mxnet-linux-cpu "1.5.0"]`
+  - `[org.apache.mxnet.contrib.clojure/clojure-mxnet-linux-gpu "1.5.0"]`
+  - `[org.apache.mxnet.contrib.clojure/clojure-mxnet-osx-cpu "1.5.0"]`
 
 After making this change and running `lein deps`, you should be able to run example code like this [NDArray Tutorial](https://github.com/apache/incubator-mxnet/blob/master/contrib/clojure-package/examples/tutorial/src/tutorial/ndarray.clj).
 
@@ -116,20 +116,20 @@ After making this change and running `lein deps`, you should be able to run exam
 With this option, you will install a Git revision of the Clojure package source and a [Scala package jar from Maven](https://search.maven.org/search?q=g:org.apache.mxnet) with native dependencies baked in.
 
 - Install additional dependencies as described in [the corresponding section for Option 1](#installing-additional-dependencies),
-- Recursively clone the MXNet repository and checkout the desired revision. Here we assume the `1.4.0` tag and a clone into the `~/mxnet` directory:
+- Recursively clone the MXNet repository and checkout the desired revision. Here we assume the `1.5.0` tag and a clone into the `~/mxnet` directory:
 
   ```bash
   git clone --recursive https://github.com/apache/incubator-mxnet.git ~/mxnet
   cd ~/mxnet
   git tag --list  # Find the tag that matches the Scala package version
-  git checkout tags/1.4.0 -b my_mxnet
+  git checkout tags/1.5.0 -b my_mxnet
   git submodule update --init --recursive
   cd contrib/clojure
   ```
 
 - Edit `project.clj` to include the desired Scala jar from Maven:
 
-      [org.apache.mxnet/mxnet-full_2.11-linux-x86_64-cpu "1.4.0”]
+      [org.apache.mxnet/mxnet-full_2.11-linux-x86_64-cpu "1.5.0”]
 
 - Run `lein test`. All the tests should run without error.
 - At this point you can run `lein install` to build and install the Clojure jar locally.
@@ -147,7 +147,7 @@ The first step is to recursively clone the MXNet repository and checkout the des
   ```bash
   git clone --recursive https://github.com/apache/incubator-mxnet.git ~/mxnet
   cd ~/mxnet
-  git checkout tags/1.4.0 -b my_mxnet  # this is optional
+  git checkout tags/1.5.0 -b my_mxnet  # this is optional
   git submodule update --init --recursive
   ```
 
@@ -176,7 +176,7 @@ The outcome of this step will be a shared library `lib/libmxnet.so` that is used
 
 #### Building the Clojure jar
  
-- Enter the `contrib/clojure` directory and edit the `project.clj` file. Add the Scala jar that was just created and installed, e.g., `[org.apache.mxnet/mxnet-full_2.11-osx-x86_64-cpu "1.4.0-SNAPSHOT"]`, to the `:dependencies`.
+- Enter the `contrib/clojure` directory and edit the `project.clj` file. Add the Scala jar that was just created and installed, e.g., `[org.apache.mxnet/mxnet-full_2.11-osx-x86_64-cpu "1.5.0-SNAPSHOT"]`, to the `:dependencies`.
 - Run `lein test`. All the tests should run without an error.
 - Run `lein install` to build and install the Clojure jar locally.
 

contrib/clojure-package/examples/cnn-text-classification/project.clj

@@ -19,6 +19,6 @@
   :description "CNN text classification with MXNet"
   :plugins [[lein-cljfmt "0.5.7"]]
   :dependencies [[org.clojure/clojure "1.9.0"]
-                 [org.apache.mxnet.contrib.clojure/clojure-mxnet "1.4.0-SNAPSHOT"]]
+                 [org.apache.mxnet.contrib.clojure/clojure-mxnet "1.5.0-SNAPSHOT"]]
   :pedantic? :skip
   :main cnn-text-classification.classifier)

contrib/clojure-package/examples/gan/project.clj

@@ -19,6 +19,6 @@
   :description "GAN MNIST with MXNet"
   :plugins [[lein-cljfmt "0.5.7"]]
   :dependencies [[org.clojure/clojure "1.9.0"]
-                 [org.apache.mxnet.contrib.clojure/clojure-mxnet "1.4.0-SNAPSHOT"]
+                 [org.apache.mxnet.contrib.clojure/clojure-mxnet "1.5.0-SNAPSHOT"]
                  [nu.pattern/opencv "2.4.9-7"]]
   :main gan.gan-mnist)

contrib/clojure-package/examples/imclassification/project.clj

@@ -19,6 +19,6 @@
   :description "Clojure examples for image classification"
   :plugins [[lein-cljfmt "0.5.7"]]
   :dependencies [[org.clojure/clojure "1.9.0"]
-                 [org.apache.mxnet.contrib.clojure/clojure-mxnet "1.4.0-SNAPSHOT"]]
+                 [org.apache.mxnet.contrib.clojure/clojure-mxnet "1.5.0-SNAPSHOT"]]
   :pedantic? :skip
   :main imclassification.train-mnist)

contrib/clojure-package/examples/module/project.clj

@@ -19,7 +19,7 @@
   :description "Clojure examples for module"
   :plugins [[lein-cljfmt "0.5.7"]]
   :dependencies [[org.clojure/clojure "1.9.0"]
-                 [org.apache.mxnet.contrib.clojure/clojure-mxnet "1.4.0-SNAPSHOT"]]
+                 [org.apache.mxnet.contrib.clojure/clojure-mxnet "1.5.0-SNAPSHOT"]]
   :pedantic? :skip
   :main mnist-mlp)
 

contrib/clojure-package/examples/multi-label/project.clj

@@ -19,5 +19,5 @@
   :description "Example of multi-label classification"
   :plugins [[lein-cljfmt "0.5.7"]]
   :dependencies [[org.clojure/clojure "1.9.0"]
-                 [org.apache.mxnet.contrib.clojure/clojure-mxnet "1.4.0-SNAPSHOT"]]
+                 [org.apache.mxnet.contrib.clojure/clojure-mxnet "1.5.0-SNAPSHOT"]]
   :main multi-label.core)

contrib/clojure-package/examples/neural-style/project.clj

@@ -19,7 +19,7 @@
   :description "Neural Style Transfer with MXNet"
   :plugins [[lein-cljfmt "0.5.7"]]
   :dependencies [[org.clojure/clojure "1.9.0"]
-                 [org.apache.mxnet.contrib.clojure/clojure-mxnet "1.4.0-SNAPSHOT"]
+                 [org.apache.mxnet.contrib.clojure/clojure-mxnet "1.5.0-SNAPSHOT"]
                  [net.mikera/imagez "0.12.0"]
                  [thinktopic/think.image "0.4.16"]]
   :main neural-style.core)

contrib/clojure-package/examples/pre-trained-models/project.clj

@@ -19,7 +19,7 @@
   :description "Example of using pre-trained models with MXNet"
   :plugins [[lein-cljfmt "0.5.7"]]
   :dependencies [[org.clojure/clojure "1.9.0"]
-                 [org.apache.mxnet.contrib.clojure/clojure-mxnet "1.4.0-SNAPSHOT"]
+                 [org.apache.mxnet.contrib.clojure/clojure-mxnet "1.5.0-SNAPSHOT"]
                  [net.mikera/imagez "0.12.0"]
                  [thinktopic/think.image "0.4.16"]]
   :main pre-trained-models.fine-tune)

contrib/clojure-package/examples/profiler/project.clj

@@ -18,5 +18,5 @@
 (defproject profiler "0.1.0-SNAPSHOT"
   :plugins [[lein-cljfmt "0.5.7"]]
   :dependencies [[org.clojure/clojure "1.9.0"]
-                 [org.apache.mxnet.contrib.clojure/clojure-mxnet "1.4.0-SNAPSHOT"]]
+                 [org.apache.mxnet.contrib.clojure/clojure-mxnet "1.5.0-SNAPSHOT"]]
   :main profiler.core)

contrib/clojure-package/examples/rnn/project.clj

@@ -19,5 +19,5 @@
   :description "RNN example"
   :plugins [[lein-cljfmt "0.5.7"]]
   :dependencies [[org.clojure/clojure "1.9.0"]
-                 [org.apache.mxnet.contrib.clojure/clojure-mxnet "1.4.0-SNAPSHOT"]]
+                 [org.apache.mxnet.contrib.clojure/clojure-mxnet "1.5.0-SNAPSHOT"]]
   :main rnn.train-char-rnn)

contrib/clojure-package/examples/tutorial/project.clj

@@ -20,6 +20,6 @@
   :plugins [[lein-cljfmt "0.5.7"]]
   :dependencies [[org.clojure/clojure "1.9.0"]
                  ;; Uncomment the one appropriate for your machine & configuration:
-                 #_[org.apache.mxnet.contrib.clojure/clojure-mxnet-linux-cpu "1.4.0"]
-                 #_[org.apache.mxnet.contrib.clojure/clojure-mxnet-linux-gpu "1.4.0"]
-                 #_[org.apache.mxnet.contrib.clojure/clojure-mxnet-osx-cpu "1.4.0"]])
+                 #_[org.apache.mxnet.contrib.clojure/clojure-mxnet-linux-cpu "1.5.0"]
+                 #_[org.apache.mxnet.contrib.clojure/clojure-mxnet-linux-gpu "1.5.0"]
+                 #_[org.apache.mxnet.contrib.clojure/clojure-mxnet-osx-cpu "1.5.0"]])

contrib/clojure-package/examples/visualization/project.clj

@@ -19,5 +19,5 @@
   :description "Visualization example"
   :plugins [[lein-cljfmt "0.5.7"]]
   :dependencies [[org.clojure/clojure "1.9.0"]
-                 [org.apache.mxnet.contrib.clojure/clojure-mxnet "1.4.0-SNAPSHOT"]]
+                 [org.apache.mxnet.contrib.clojure/clojure-mxnet "1.5.0-SNAPSHOT"]]
   :main visualization.core)