diff --git a/extra/onnx.py b/extra/onnx.py
index 52e33150fd..1cbd93b40c 100644
--- a/extra/onnx.py
+++ b/extra/onnx.py
@@ -74,6 +74,8 @@ def get_run_onnx(onnx_model):
   attribute_dict = {}
   for num,n in enumerate(onnx_model.graph.node):
     attribute_dict[num] = attribute_to_dict(n.attribute)
+  
+  onnx_version = onnx_model.opset_import[0].version
 
   def run_onnx(inputs={}, debug=False):
     if getenv("DEBUGONNX"): debug = True
@@ -156,7 +158,7 @@ def get_run_onnx(onnx_model):
           i = i+s
         continue
       elif n.op_type == "Slice":
-        assert onnx_model.opset_import[0].version == 10
+        assert onnx_version == 10
         arg = [(0,x) for x in inp[0].shape]
         starts, ends, axes = inp[1:4]
         assert axes.shape == (1,)
@@ -166,7 +168,14 @@ def get_run_onnx(onnx_model):
         arg[axis] = (starts, ends)
         ret = inp[0].slice(arg=arg)
       elif hasattr(onnx_ops, n.op_type):
-        ret = getattr(onnx_ops, n.op_type)(*inp, **opt)
+        fxn = getattr(onnx_ops, n.op_type)
+        if isinstance(fxn, dict):
+          for k in sorted(fxn.keys()):
+            if k < onnx_version:
+              real_fxn = fxn[k]
+        else:
+          real_fxn = fxn
+        ret = real_fxn(*inp, **opt)
       else:
         print("UNSUPPORTED", n.op_type, n.input, n.output)
         raise Exception(f"op_type {n.op_type} not supported")
@@ -174,7 +183,7 @@ def get_run_onnx(onnx_model):
       assert len(n.output) <= len(ret), f"expected output size must be less than {len(ret)}, it's {n.output}"
       if debug: print([x.shape if isinstance(x, Tensor) else None for x in ret])
       for i in range(len(n.output)): intermediate_tensors[n.output[i]] = ret[i]
-      #print(ret.numpy().mean())
+      #print(ret[0].numpy().mean())
       if num == ONNXLIMIT:
         output_tensor_names = n.output
         break
diff --git a/extra/onnx_ops.py b/extra/onnx_ops.py
index 2f3dfb3a16..29428b7941 100644
--- a/extra/onnx_ops.py
+++ b/extra/onnx_ops.py
@@ -116,7 +116,9 @@ def Softplus(X): return X.softplus()
 def PRelu(X, slope): return X.leakyrelu(slope)
 def LeakyRelu(X, alpha=0.01): return X.leakyrelu(alpha)
 def ThresholdedRelu(X, alpha=1.0): return (X-alpha).relu() + (X-alpha).relu().sign() * alpha
-def Softmax(input, axis=-1): return input.softmax(axis)
+def Softmax_1(input, axis=1): return input.softmax(axis)
+def Softmax_13(input, axis=-1): return input.softmax(axis)
+Softmax = {1: Softmax_1, 13: Softmax_13}   # Softmax default axis changed
 def LogSoftmax(input, axis=-1): return input.log_softmax(axis)
 def Clip(input, min=-3.4e38, max=3.4e38): return input.clip(min, max)
 
diff --git a/test/external_test_onnx_backend.py b/test/external_test_onnx_backend.py
index 7da2a241ae..4cd2144036 100644
--- a/test/external_test_onnx_backend.py
+++ b/test/external_test_onnx_backend.py
@@ -152,89 +152,21 @@ backend_test.exclude('test_stft_*')
 backend_test.exclude('test_melweightmatrix_*')
 
 # disable model tests for now since they are slow
-for x in backend_test.test_suite:
-  if 'OnnxBackendRealModelTest' in str(type(x)):
-    backend_test.exclude(str(x).split(" ")[0])
-
-# passing node tests
-"""
-backend_test.include('test_unsqueeze_*')
-backend_test.include('test_gemm_*')
-backend_test.include('test_batchnorm_*')
-backend_test.include('test_transpose_*')
-backend_test.include('test_shape_*')
-backend_test.include('test_flatten_*')
-backend_test.include('test_sum_*')
-backend_test.include('test_global*')
-backend_test.include('test_log_softmax*')
-backend_test.include('test_softplus*')
-"""
-
-# requires Less, which would be a new llop
-#backend_test.include('test_clip_*')
-
-# broken empty tensor
-#backend_test.include('test_reduce_sum_*')
-#backend_test.include('test_reduce_l1_')
-
-# requires cast
-#backend_test.include('test_reduce_log_sum*')
-#backend_test.include('test_pow_*')
-
-# almost passing node tests
-#backend_test.include('test_PReLU*')
-#backend_test.include('test_expand_*')
-#backend_test.include('test_conv_.*')
-#backend_test.include('test_dropout_*')
-#backend_test.include('test_reshape_*')
-
-# good to investigate
-#backend_test.include('test_slice_*')
-
-# failing for real reasons
-#backend_test.include('test_averagepool_2d_*')
-#backend_test.include('test_maxpool_2d_*')
-
-"""
-backend_test.include('test_tanh_*')
-
-# should be passing (good place to start!)
-"""
-
-# requires CastLike?
-#backend_test.include('test_relu_*')
-#backend_test.include('test_elu_*')
-#backend_test.include('test_leakyrelu_*')
-#backend_test.include('test_hardsigmoid_*')
-
-# failing for lack of type support
-#backend_test.include('test_add_*')
-#backend_test.include('test_sub_*')
-#backend_test.include('test_div_*')
-
-
-# the node tests, slowly
-#backend_test.include('test_softmax_*')
-#backend_test.include('test_lrn_*')
-
-# working big model tests
-#backend_test.include('test_resnet50')
-#backend_test.include('test_densenet121')
-#backend_test.include('test_vgg19')
-
-"""
-# wrong big model tests
-backend_test.include('test_shufflenet')
-backend_test.include('test_inception_v2')
-backend_test.include('test_squeezenet')
-"""
-
-"""
-# unsupported big model tests : LRN
-backend_test.include('test_bvlc_alexnet')
-backend_test.include('test_inception_v1')
-backend_test.include('test_zfnet512')
-"""
+if True:
+  for x in backend_test.test_suite:
+    if 'OnnxBackendRealModelTest' in str(type(x)):
+      backend_test.exclude(str(x).split(" ")[0])
+else:
+  # model tests all pass!
+  backend_test.include('test_resnet50')
+  backend_test.include('test_inception_v1')
+  backend_test.include('test_inception_v2')
+  backend_test.include('test_densenet121')
+  backend_test.include('test_shufflenet')
+  backend_test.include('test_squeezenet')
+  backend_test.include('test_bvlc_alexnet')
+  backend_test.include('test_zfnet512')
+  backend_test.include('test_vgg19')
 
 globals().update(backend_test.enable_report().test_cases)