[tvm] branch main updated: Make Autopad static when available (#7755)

[jw...@apache.org]

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jwfromm pushed a commit to branch main
in repository https://gitbox.apache.org/repos/asf/tvm.git


The following commit(s) were added to refs/heads/main by this push:
     new 34deb80  Make Autopad static when available (#7755)
34deb80 is described below

commit 34deb800bbb53bd48b9c7cd3d3fab3bc07d70d5a
Author: Matthew Brookhart <mb...@octoml.ai>
AuthorDate: Mon Mar 29 10:14:29 2021 -0600

    Make Autopad static when available (#7755)
---
 python/tvm/relay/frontend/onnx.py          | 3 +--
 tests/python/frontend/onnx/test_forward.py | 2 +-
 2 files changed, 2 insertions(+), 3 deletions(-)

diff --git a/python/tvm/relay/frontend/onnx.py b/python/tvm/relay/frontend/onnx.py
index d9fc2ff..01c22d0 100644
--- a/python/tvm/relay/frontend/onnx.py
+++ b/python/tvm/relay/frontend/onnx.py
@@ -397,7 +397,7 @@ def autopad(data, strides, kernel_shape, dilations, ndim, pad_type="constant", d
     # pad N and C with zeros
     pad = _op.concatenate([_op.const(np.zeros([2, 2], dtype="int64"), dtype="int64"), pad], axis=0)
 
-    return _op.nn.pad(data, pad, _op.const(0.0), pad_type)
+    return _op.nn.pad(data, fold_constant(pad), _op.const(0.0), pad_type)
 
 
 class Conv(OnnxOpConverter):
@@ -809,7 +809,6 @@ class Pad(OnnxOpConverter):
 
         pad_width_expr = fold_constant(_op.transpose(_op.reshape(pads, (2, -1))))
         pad_mode = attr.get("mode", b"constant").decode("utf-8")
-
         if not pad_mode in ["constant", "edge", "reflect"]:
             raise tvm.error.OpAttributeInvalid(
                 "Value " + pad_mode + ' in attribute "mode" is invalid for operator Pad.'
diff --git a/tests/python/frontend/onnx/test_forward.py b/tests/python/frontend/onnx/test_forward.py
index 9116b09..772d834 100644
--- a/tests/python/frontend/onnx/test_forward.py
+++ b/tests/python/frontend/onnx/test_forward.py
@@ -2703,7 +2703,7 @@ def verify_pooling(x_shape, kernel_shape, strides, pads, out_shape, mode, auto_p
     )
 
     model = helper.make_model(graph, producer_name="pooling_test")
-    verify_with_ort(model, [x_shape], [out_shape], use_vm=True, convert_to_static=True)
+    verify_with_ort(model, [x_shape], [out_shape], use_vm=False, convert_to_static=True)
 
 
 @tvm.testing.uses_gpu