[Frontend][Relay][Parser] fix unparsable yolo formals

python/tvm/relay/frontend/darknet.py

@@ -40,7 +40,7 @@ def _darknet_not_support(attr, op="relay"):
 
 def _get_params_prefix(opname, layer_num):
     """Makes the params prefix name from opname and layer number."""
-    return str(opname) + str(layer_num)
+    return str(opname).replace(".", "_") + str(layer_num)
 
 
 def _get_params_name(prefix, item):

tests/python/relay/test_ir_text_printer.py

@@ -21,6 +21,8 @@
 import numpy as np
 from tvm.relay import Expr
 from tvm.relay.analysis import free_vars
+import pytest
+import sys
 
 DEBUG_PRINT = False
 
@@ -46,6 +48,46 @@ def show(text):
         print(text)
 
 
+def get_darknet(model_name):
+    from tvm.contrib.download import download_testdata
+    from tvm.relay.testing.darknet import __darknetffi__
+    import tvm.relay.testing.yolo_detection
+    import tvm.relay.testing.darknet
+
+    CFG_NAME = model_name + ".cfg"
+    WEIGHTS_NAME = model_name + ".weights"
+    REPO_URL = "https://github.com/dmlc/web-data/blob/main/darknet/"
+    CFG_URL = REPO_URL + "cfg/" + CFG_NAME + "?raw=true"
+    WEIGHTS_URL = "https://pjreddie.com/media/files/" + WEIGHTS_NAME
+
+    cfg_path = download_testdata(CFG_URL, CFG_NAME, module="darknet")
+    weights_path = download_testdata(WEIGHTS_URL, WEIGHTS_NAME, module="darknet")
+
+    # Download and Load darknet library
+    if sys.platform in ["linux", "linux2"]:
+        DARKNET_LIB = "libdarknet2.0.so"
+        DARKNET_URL = REPO_URL + "lib/" + DARKNET_LIB + "?raw=true"
+    elif sys.platform == "darwin":
+        DARKNET_LIB = "libdarknet_mac2.0.so"
+        DARKNET_URL = REPO_URL + "lib_osx/" + DARKNET_LIB + "?raw=true"
+    else:
+        err = "Darknet lib is not supported on {} platform".format(sys.platform)
+        raise NotImplementedError(err)
+
+    lib_path = download_testdata(DARKNET_URL, DARKNET_LIB, module="darknet")
+
+    DARKNET_LIB = __darknetffi__.dlopen(lib_path)
+    net = DARKNET_LIB.load_network(cfg_path.encode("utf-8"), weights_path.encode("utf-8"), 0)
+    dtype = "float32"
+    batch_size = 1
+
+    data = np.empty([batch_size, net.c, net.h, net.w], dtype)
+    shape_dict = {"data": data.shape}
+    mod, params = relay.frontend.from_darknet(net, dtype=dtype, shape=data.shape)
+    mod = relay.transform.InferType()(mod)
+    return mod, params
+
+
 def test_func():
     x = relay.var("x", shape=(3, 2))
     y = relay.var("y")
@@ -190,6 +232,11 @@ def test_densenet():
     astext(net)
 
 
+def test_yolov3():
+    net, _ = get_darknet("yolov3")
+    astext(net)
+
+
 def test_call_node_order():
     x = relay.var("x")
     y = relay.var("y")
@@ -269,6 +316,4 @@ def test_span():
 
 
 if __name__ == "__main__":
-    import sys
-
-    pytext.argv(sys.argv)
+    pytest.main(sys.argv)