Testcases and CI to include TVM as dependency

tests/ci_build/Dockerfile.gpu

@@ -12,3 +12,9 @@ COPY install/ubuntu_install_r.sh /install/
 RUN /install/ubuntu_install_r.sh
 COPY install/ubuntu_install_perl.sh /install/
 RUN /install/ubuntu_install_perl.sh
+
+COPY install/ubuntu_install_llvm.sh /install/
+RUN /install/ubuntu_install_llvm.sh
+
+COPY install/ubuntu_install_tvm.sh /install/
+RUN /install/ubuntu_install_tvm.sh

tests/ci_build/install/ubuntu_install_llvm.sh

@@ -0,0 +1,28 @@
+#!/usr/bin/env bash
+
+# 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
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+
+
+echo deb http://apt.llvm.org/xenial/ llvm-toolchain-xenial-5.0 main\
+     >> /etc/apt/sources.list.d/llvm.list
+echo deb-src http://apt.llvm.org/xenial/ llvm-toolchain-xenial-5.0 main\
+     >> /etc/apt/sources.list.d/llvm.list
+
+wget -O - http://apt.llvm.org/llvm-snapshot.gpg.key|sudo apt-key add -
+apt-get update && apt-get install -y --force-yes llvm-5.0

tests/ci_build/install/ubuntu_install_tvm.sh

@@ -0,0 +1,38 @@
+#!/usr/bin/env bash
+
+# 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
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+# Build and install TVM
+cd /tmp
+git clone https://github.com/dmlc/tvm/ --recursive
+cd tvm
+cp make/config.mk
+echo USE_CUDA=1 >> config.mk
+echo LLVM_CONFIG=llvm-config-5.0 >> config.mk
+echo USE_RPC=1 >> config.mk
+echo USE_GRAPH_RUNTIME=1 >> config.mk
+echo CUDA_PATH=/usr/local/cuda >> config.mk
+make -j10
+
+cd python
+python setup.py install
+cd -
+
+cd topi/python
+python setup.py install
+cd -

tests/python/gpu/test_tvm_bridge.py

@@ -0,0 +1,57 @@
+# 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
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+"""Test TVM bridge, only enable this when TVM is available"""
+import mxnet as mx
+import numpy as np
+
+def test_tvm_bridge():
+    # only enable test if TVM is available
+    try:
+        import tvm
+        import tvm.contrib.mxnet
+        import topi
+    except ImportError:
+        return
+
+    shape = (20,)
+    scale = tvm.var("scale", dtype="float32")
+    x = tvm.placeholder(shape)
+    y = tvm.placeholder(shape)
+    z = tvm.compute(shape, lambda i: x[i] + y[i])
+    zz = tvm.compute(shape, lambda *i: z(*i) * scale)
+
+    target = tvm.target.cuda()
+    # build the function
+    with target:
+        s = topi.generic.schedule_injective(zz)
+        f = tvm.build(s, [x, y, zz, scale])
+
+    # get a mxnet version
+    mxf = tvm.contrib.mxnet.to_mxnet_func(f, const_loc=[0, 1])
+    ctx = mx.gpu(0)
+    xx = mx.nd.uniform(shape=shape, ctx=ctx)
+    yy = mx.nd.uniform(shape=shape, ctx=ctx)
+    zz = mx.nd.empty(shape=shape, ctx=ctx)
+    # invoke myf: this runs in mxnet engine
+    mxf(xx, yy, zz, 10.0)
+    np.testing.assert_allclose(
+        zz.asnumpy(), (xx.asnumpy() + yy.asnumpy()) * 10)
+
+
+if __name__ == "__main__":
+    test_tvm_bridge()