[RELAY]Frontend darknet

nnvm/python/nnvm/testing/__init__.py

@@ -13,5 +13,4 @@
 from . import inception_v3
 from . import dcgan
 from . import dqn
-from . import yolo_detection
 from . import check_computation

nnvm/tests/python/frontend/darknet/test_forward.py

@@ -27,8 +27,8 @@
 from tvm.contrib.download import download_testdata
 download_testdata.__test__ = False
 from nnvm import frontend
-from nnvm.testing.darknet import LAYERTYPE
-from nnvm.testing.darknet import __darknetffi__
+from tvm.relay.testing.darknet import LAYERTYPE
+from tvm.relay.testing.darknet import __darknetffi__
 import nnvm.compiler
 
 DARKNET_LIB = 'libdarknet2.0.so'

nnvm/tutorials/from_darknet.py

@@ -33,16 +33,16 @@
 
 import nnvm
 import nnvm.frontend.darknet
-import nnvm.testing.yolo_detection
-import nnvm.testing.darknet
+import tvm.relay.testing.yolo_detection
+import tvm.relay.testing.darknet
 import matplotlib.pyplot as plt
 import numpy as np
 import tvm
 import sys
 
 from ctypes import *
 from tvm.contrib.download import download_testdata
-from nnvm.testing.darknet import __darknetffi__
+from tvm.relay.testing.darknet import __darknetffi__
 
 # Model name
 MODEL_NAME = 'yolov3'
@@ -104,7 +104,7 @@
           test_image + '?raw=true'
 img_path = download_testdata(img_url, test_image, "data")
 
-data = nnvm.testing.darknet.load_image(img_path, netw, neth)
+data = tvm.relay.testing.darknet.load_image(img_path, netw, neth)
 ######################################################################
 # Execute on TVM Runtime
 # ----------------------
@@ -153,12 +153,12 @@
 # do the detection and bring up the bounding boxes
 thresh = 0.5
 nms_thresh = 0.45
-img = nnvm.testing.darknet.load_image_color(img_path)
+img = tvm.relay.testing.darknet.load_image_color(img_path)
 _, im_h, im_w = img.shape
-dets = nnvm.testing.yolo_detection.fill_network_boxes((netw, neth), (im_w, im_h), thresh,
+dets = tvm.relay.testing.yolo_detection.fill_network_boxes((netw, neth), (im_w, im_h), thresh,
                                                       1, tvm_out)
 last_layer = net.layers[net.n - 1]
-nnvm.testing.yolo_detection.do_nms_sort(dets, last_layer.classes, nms_thresh)
+tvm.relay.testing.yolo_detection.do_nms_sort(dets, last_layer.classes, nms_thresh)
 
 coco_name = 'coco.names'
 coco_url = 'https://github.com/siju-samuel/darknet/blob/master/data/' + coco_name + '?raw=true'
@@ -172,6 +172,6 @@
 
 names = [x.strip() for x in content]
 
-nnvm.testing.yolo_detection.draw_detections(font_path, img, dets, thresh, names, last_layer.classes)
+tvm.relay.testing.yolo_detection.draw_detections(font_path, img, dets, thresh, names, last_layer.classes)
 plt.imshow(img.transpose(1, 2, 0))
 plt.show()

python/tvm/relay/frontend/__init__.py

@@ -30,3 +30,4 @@
 from .coreml import from_coreml
 from .caffe2 import from_caffe2
 from .tensorflow import from_tensorflow
+from .darknet import from_darknet

python/tvm/relay/frontend/common.py

@@ -241,7 +241,7 @@ def get_relay_op(op_name):
             op = None
     else:
         # try search op in various modules
-        for candidate in (_op, _op.nn, _op.image):
+        for candidate in (_op, _op.nn, _op.image, _op.vision):
             op = getattr(candidate, op_name, None)
             if op is not None:
                 break