#4312 broke Huggingface BERT ONNX import

[mbrookhart]

Hi @yongwww @kevinthesun @lixiaoquan,

I haven't been running this model recently, but one of the models I was targeting in my recent dynamic shapes work is a BERT Model from HuggingFace, imported via the ONNX importer. It's written in a dynamic fashion, but it's actually a complex static model, so I'm testing my ONNX refactor against it before starting on fully dynamic models. I was testing it again this week after a break, and noticed the model is broken on master.

The basic issue is that before #4312, I get strided slices that look like this:

%40 = strided_slice(%39, begin=[0, 0, 0, 0], end=[9223372036854775807, 2147483647, 2147483647, 9223372036854775807]);

And after #4312, I get strided slices that look like this:

%40 = strided_slice(%39, meta[relay.Constant][2], meta[relay.Constant][3], meta[relay.Constant][4], begin=[0, 0, 0, 0], end=[-1, 2147483647, 2147483647, -1], strides=[1]);

The -1 is a problem, becuase the shape of the input tensor is (1, 1, 1, 128), so I end up with an empty array.

I can reproduce this with a change to the onnx importer tests:

diff --git a/tests/python/frontend/onnx/test_forward.py b/tests/python/frontend/onnx/test_forward.py
index 14b827c79..c376c9aa7 100644
--- a/tests/python/frontend/onnx/test_forward.py
+++ b/tests/python/frontend/onnx/test_forward.py
@@ -478,15 +478,15 @@ def _test_slice_iteration_v10(indata, outdata, starts, ends, axes=None):
     inputs = [
         helper.make_tensor_value_info("data", TensorProto.FLOAT,
                                       list(indata.shape)),
-        helper.make_tensor_value_info("starts", TensorProto.INT32,
+        helper.make_tensor_value_info("starts", TensorProto.INT64,
                                       list(starts.shape)),
-        helper.make_tensor_value_info("ends", TensorProto.INT32,
+        helper.make_tensor_value_info("ends", TensorProto.INT64,
                                       list(ends.shape))
     ]
     initializer = [
-        helper.make_tensor("starts", TensorProto.INT32, list(starts.shape),
+        helper.make_tensor("starts", TensorProto.INT64, list(starts.shape),
                            starts),
-        helper.make_tensor("ends", TensorProto.INT32, list(ends.shape), ends)
+        helper.make_tensor("ends", TensorProto.INT64, list(ends.shape), ends)
     ]
 
     if axes:
@@ -534,7 +534,8 @@ def test_slice():
     _test_slice_iteration_v10(x, x[0:3, 0:10], (0, 0), (3, 10), (0, 1))
     _test_slice_iteration_v10(x, x[:, :, 3:4], (0, 0, 3), (20, 10, 4))
     _test_slice_iteration_v10(x, x[:, 1:1000], (1), (1000), (1))
-    _test_slice_iteration_v10(x, x[:, 0:-1], (0), (-1), (1))
+    x = np.random.randn(1, 1, 1, 128).astype(np.float32)
+    _test_slice_iteration_v10(x, x, (0, 0), (9223372036854775807, 9223372036854775807), (0, 3))
 
 
 def _test_onnx_op_elementwise(inshape, outfunc, npargs, dtype, opname, kwargs):

Which passes before #4312 but fails after with this error:

E       (shapes (1, 1, 1, 128), (0, 1, 1, 127) mismatch)
E        x: array([[[[ 0.857093,  0.894232,  1.201452, -0.637382, -0.028272,
E                  0.989941, -0.312949,  1.000041, -0.895313, -0.075969,
E                  1.994201, -0.617561, -0.712636,  0.255715,  2.050107,...
E        y: array([], shape=(0, 1, 1, 127), dtype=float32)

I haven't figured out which change in #4312 is causing the problem, but if you guys have any ideas, I'd love to hear them.

Thanks!

Matthew

[kevinthesun]

What is the original end? Usually -1 means the end of that dimension.

[mbrookhart]

The original end was the max of int64. In numpy, onnx, and tvm's default mode, -1 means take everything but the last element of the axis.

Turned out to be a precision/rounding issue, that PR fixes it