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[ONNX] Support importing Conv with missing attributes #7899

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Apr 23, 2021
Merged

[ONNX] Support importing Conv with missing attributes #7899

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2a899c3
[ONNX] Support importing Conv with missing attributes
Apr 21, 2021
c5c195f
fix removal of attributes ONLY when they are default and for autopad
Apr 22, 2021
df69572
move comment to the right place
Apr 22, 2021
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21 changes: 16 additions & 5 deletions python/tvm/relay/frontend/onnx.py
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Original file line number Diff line number Diff line change
Expand Up @@ -368,8 +368,8 @@ def autopad(data, strides, kernel_shape, dilations, ndim, pad_type="constant", d
),
dtype="int64",
)
shape = _op.strided_slice(shape_of(data, dtype="int64"), [2], [ndim])
# get input shape
shape = _op.strided_slice(shape_of(data, dtype="int64"), [2], [ndim])

# set up integer constants
zero = _op.const(0, dtype="int64")
Expand Down Expand Up @@ -410,12 +410,24 @@ def _impl_v1(cls, inputs, attr, params):
data = inputs[0]
input_shape = infer_shape(data)
ndim = len(input_shape)

kernel_type = infer_type(inputs[1])
kernel_shapes = [get_const_tuple(kernel_type.checked_type.shape)]
if "kernel_shape" not in attr:
attr["kernel_shape"] = kernel_shapes[0][2:]

if "auto_pad" in attr:
attr["auto_pad"] = attr["auto_pad"].decode("utf-8")
if attr["auto_pad"] in ("SAME_UPPER", "SAME_LOWER"):
# Warning: Convolution does not yet support dynamic shapes,
# one will need to run dynamic_to_static on this model after import
data = autopad(data, attr["strides"], attr["kernel_shape"], attr["dilations"], ndim)
data = autopad(
data,
attr.get("strides", [1] * (ndim - 2)),
attr["kernel_shape"],
attr.get("dilations", [1] * (ndim - 2)),
ndim,
)
elif attr["auto_pad"] == "VALID":
attr["pads"] = tuple([0 for i in range(ndim - 2)])
elif attr["auto_pad"] == "NOTSET":
Expand All @@ -424,7 +436,6 @@ def _impl_v1(cls, inputs, attr, params):
msg = 'Value {} in attribute "auto_pad" of operator Conv is invalid.'
raise tvm.error.OpAttributeInvalid(msg.format(attr["auto_pad"]))
attr.pop("auto_pad")

out = AttrCvt(
op_name=dimension_picker("conv"),
transforms={
Expand Down Expand Up @@ -469,9 +480,9 @@ def _impl_v1(cls, inputs, attr, params):
# one will need to run dynamic_to_static on this model after import
data = autopad(
data,
attr["strides"],
attr.get("strides", [1] * (ndim - 2)),
attr["kernel_shape"],
attr["dilations"],
attr.get("dilations", [1] * (ndim - 2)),
ndim,
deconv=True,
)
Expand Down
5 changes: 1 addition & 4 deletions tests/python/frontend/onnx/test_forward.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2402,15 +2402,12 @@ def verify_conv(
auto_pad=auto_pad,
)
else:
## autopadding with unset attributes
node = helper.make_node(
"Conv",
inputs=["x", "W"],
outputs=["y"],
kernel_shape=kernel_shape,
# Default values for other attributes:
strides=strides,
dilations=dilations,
# groups=1
pads=padding,
)

Expand Down