[BugFix] SSD fully supported on GPUs, updated deploy_ssd tutorial (#2510)

* nms fixed for gpu, tested on cuda and opencl devices, ssd now can run fully on the gpu

* sort updated to use virtual thread

* typo fixed

* fix lint

* fix lint

* add support when batch_size > 1

* intel graphics conv2d bugs fixed for inception_v3

* intel conv2d api updated, nn input size 4 condition added

* review addressed

* move conv_tags to attributes

* opencl ctx fixed

* nms_ir index simplified

tutorials/nnvm/deploy_ssd.py

 """
 Deploy Single Shot Multibox Detector(SSD) model
 ===============================================
-**Author**: `Yao Wang <https://github.com/kevinthesun>`_
+**Author**: `Yao Wang <https://github.com/kevinthesun>`_, \
+`Leyuan Wang <https://github.com/Laurawly>`_
 
 This article is an introductory tutorial to deploy SSD models with TVM.
 We will use mxnet pretrained SSD model with Resnet50 as body network and
@@ -32,17 +33,20 @@ from mxnet.model import load_checkpoint
 #   echo "set(USE_SORT ON)" > config.mk
 #   make -j8
 #
-# .. note::
-#
-#   Currently we support compiling SSD on CPU only.
-#   GPU support is in progress.
-#
 
 model_name = "ssd_resnet50_512"
 model_file = "%s.zip" % model_name
 test_image = "dog.jpg"
 dshape = (1, 3, 512, 512)
 dtype = "float32"
+
+# Target settings
+# Use these commented settings to build for cuda.
+#target = 'cuda'
+#ctx = tvm.gpu(0)
+# Use these commented settings to build for opencl.
+#target = 'opencl'
+#ctx = tvm.opencl(0)
 target = "llvm"
 ctx = tvm.cpu()
 
@@ -56,7 +60,8 @@ model_url = "https://github.com/zhreshold/mxnet-ssd/releases/download/v0.6/" \
             "resnet50_ssd_512_voc0712_trainval.zip"
 image_url = "https://cloud.githubusercontent.com/assets/3307514/20012567/" \
             "cbb60336-a27d-11e6-93ff-cbc3f09f5c9e.jpg"
-inference_symbol_folder = "c1904e900848df4548ce5dfb18c719c7-a28c4856c827fe766aa3da0e35bad41d44f0fb26"
+inference_symbol_folder = \
+"c1904e900848df4548ce5dfb18c719c7-a28c4856c827fe766aa3da0e35bad41d44f0fb26"
 inference_symbol_url = "https://gist.github.com/kevinthesun/c1904e900848df4548ce5dfb18c719c7/" \
                        "archive/a28c4856c827fe766aa3da0e35bad41d44f0fb26.zip"
 
@@ -92,7 +97,8 @@ parser.add_argument(
     default="nnvm")
 args = parser.parse_args()
 if args.frontend == "relay":
-    net, params = relay.frontend.from_mxnet(sym, {"data": dshape}, arg_params=arg_params, aux_params=aux_params)
+    net, params = relay.frontend.from_mxnet(sym, {"data": dshape}, arg_params=arg_params, \
+                                            aux_params=aux_params)
     with relay.build_config(opt_level=3):
         graph, lib, params = relay.build(net, target, params=params)
 elif args.frontend == "nnvm":
@@ -134,7 +140,7 @@ def display(img, out, thresh=0.5):
     import random
     import matplotlib as mpl
     import matplotlib.pyplot as plt
-    mpl.rcParams['figure.figsize'] = (10,10)
+    mpl.rcParams['figure.figsize'] = (10, 10)
     pens = dict()
     plt.clf()
     plt.imshow(img)