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Posted to commits@tvm.apache.org by GitBox <gi...@apache.org> on 2021/10/12 19:58:06 UTC
[GitHub] [tvm] CircleSpin opened a new pull request #9265: [ONNX] [Relay] Resize Opset 13
CircleSpin opened a new pull request #9265:
URL: https://github.com/apache/tvm/pull/9265
@mbrookhart @AndrewZhaoLuo @anwang2009
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[GitHub] [tvm] emijiayw commented on a change in pull request #9265: [ONNX] [Relay] Resize Opset 13
Posted by GitBox <gi...@apache.org>.
emijiayw commented on a change in pull request #9265:
URL: https://github.com/apache/tvm/pull/9265#discussion_r727677663
##########
File path: python/tvm/relay/frontend/onnx.py
##########
@@ -2697,6 +2697,40 @@ def _impl_v10(cls, inputs, attr, params):
@classmethod
def _impl_v11(cls, inputs, attr, params):
+ scale = inputs[2]
+ scale_shape = infer_shape(scale)
+ if len(inputs) == 4:
+ assert (
+ len(scale_shape) == 0 or scale_shape[0] == 0
+ ), "One of scale or size should be passed, not both."
+ size = inputs[3]
+ else:
+ assert len(scale_shape) != 0, "One of scale or size should be passed."
+ size = _op.cast(shape_of(inputs[0]), infer_type(scale).checked_type.dtype) * scale
+ return cls.v11_13_common(inputs, size, attr, params)
+
+ @classmethod
+ def _impl_v13(cls, inputs, attr, params):
+ scale = inputs[2]
+ size = inputs[3]
+ if size is not None:
+ assert scale is None, "One of scale or size should be passed, not both."
+ else:
+ scale_type = infer_type(scale)
+ scale_shape = scale_type.checked_type.shape
+ scale_dtype = scale_type.checked_type.dtype
+ assert len(scale_shape) != 0, "One of scale or size should be passed."
+ size = _op.cast(shape_of(inputs[0]), scale_dtype) * scale
+
+ return cls.v11_13_common(inputs, size, attr, params)
+
+ @classmethod
+ def v11_13_common(cls, inputs, size, attr, params):
+ """
+ Resize v11 and Resize v13 are identical except in how
Review comment:
Resize v11 and resize
##########
File path: python/tvm/relay/frontend/onnx.py
##########
@@ -2697,6 +2697,40 @@ def _impl_v10(cls, inputs, attr, params):
@classmethod
def _impl_v11(cls, inputs, attr, params):
+ scale = inputs[2]
+ scale_shape = infer_shape(scale)
+ if len(inputs) == 4:
+ assert (
+ len(scale_shape) == 0 or scale_shape[0] == 0
+ ), "One of scale or size should be passed, not both."
+ size = inputs[3]
+ else:
+ assert len(scale_shape) != 0, "One of scale or size should be passed."
+ size = _op.cast(shape_of(inputs[0]), infer_type(scale).checked_type.dtype) * scale
+ return cls.v11_13_common(inputs, size, attr, params)
+
+ @classmethod
+ def _impl_v13(cls, inputs, attr, params):
+ scale = inputs[2]
+ size = inputs[3]
+ if size is not None:
+ assert scale is None, "One of scale or size should be passed, not both."
Review comment:
One of the scales or sizes
##########
File path: python/tvm/relay/frontend/onnx.py
##########
@@ -2697,6 +2697,40 @@ def _impl_v10(cls, inputs, attr, params):
@classmethod
def _impl_v11(cls, inputs, attr, params):
+ scale = inputs[2]
+ scale_shape = infer_shape(scale)
+ if len(inputs) == 4:
+ assert (
+ len(scale_shape) == 0 or scale_shape[0] == 0
+ ), "One of scale or size should be passed, not both."
+ size = inputs[3]
+ else:
+ assert len(scale_shape) != 0, "One of scale or size should be passed."
+ size = _op.cast(shape_of(inputs[0]), infer_type(scale).checked_type.dtype) * scale
+ return cls.v11_13_common(inputs, size, attr, params)
+
+ @classmethod
+ def _impl_v13(cls, inputs, attr, params):
+ scale = inputs[2]
+ size = inputs[3]
+ if size is not None:
+ assert scale is None, "One of scale or size should be passed, not both."
+ else:
+ scale_type = infer_type(scale)
+ scale_shape = scale_type.checked_type.shape
+ scale_dtype = scale_type.checked_type.dtype
+ assert len(scale_shape) != 0, "One of scale or size should be passed."
+ size = _op.cast(shape_of(inputs[0]), scale_dtype) * scale
+
+ return cls.v11_13_common(inputs, size, attr, params)
+
+ @classmethod
+ def v11_13_common(cls, inputs, size, attr, params):
+ """
+ Resize v11 and Resize v13 are identical except in how
+ they handle passing in scale and size. This utility
Review comment:
they handle the passing
##########
File path: python/tvm/relay/frontend/onnx.py
##########
@@ -2697,6 +2697,40 @@ def _impl_v10(cls, inputs, attr, params):
@classmethod
def _impl_v11(cls, inputs, attr, params):
+ scale = inputs[2]
+ scale_shape = infer_shape(scale)
+ if len(inputs) == 4:
+ assert (
+ len(scale_shape) == 0 or scale_shape[0] == 0
+ ), "One of scale or size should be passed, not both."
+ size = inputs[3]
+ else:
+ assert len(scale_shape) != 0, "One of scale or size should be passed."
Review comment:
One of the scales or sizes
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[GitHub] [tvm] AndrewZhaoLuo commented on a change in pull request #9265: [ONNX] [Relay] Resize Opset 13
Posted by GitBox <gi...@apache.org>.
AndrewZhaoLuo commented on a change in pull request #9265:
URL: https://github.com/apache/tvm/pull/9265#discussion_r727459057
##########
File path: tests/python/frontend/onnx/test_forward.py
##########
@@ -3970,6 +3970,12 @@ def verify(ishape, oshape, scales, mode, coord_trans="asymmetric", alpha=0.5, ex
make_constant_node("scales", onnx.TensorProto.FLOAT, (len(scales),), scales),
]
input_names = ["X", "roi", "scales"]
+
+ # if scales == []:
Review comment:
Just remove this if you don't need it.
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[GitHub] [tvm] CircleSpin commented on a change in pull request #9265: [ONNX] [Relay] Resize Opset 13
Posted by GitBox <gi...@apache.org>.
CircleSpin commented on a change in pull request #9265:
URL: https://github.com/apache/tvm/pull/9265#discussion_r728242091
##########
File path: python/tvm/relay/frontend/onnx.py
##########
@@ -2697,6 +2697,40 @@ def _impl_v10(cls, inputs, attr, params):
@classmethod
def _impl_v11(cls, inputs, attr, params):
+ scale = inputs[2]
+ scale_shape = infer_shape(scale)
+ if len(inputs) == 4:
+ assert (
+ len(scale_shape) == 0 or scale_shape[0] == 0
+ ), "One of scale or size should be passed, not both."
+ size = inputs[3]
+ else:
+ assert len(scale_shape) != 0, "One of scale or size should be passed."
+ size = _op.cast(shape_of(inputs[0]), infer_type(scale).checked_type.dtype) * scale
+ return cls.v11_13_common(inputs, size, attr, params)
+
+ @classmethod
+ def _impl_v13(cls, inputs, attr, params):
+ scale = inputs[2]
+ size = inputs[3]
+ if size is not None:
+ assert scale is None, "One of scale or size should be passed, not both."
+ else:
+ scale_type = infer_type(scale)
+ scale_shape = scale_type.checked_type.shape
+ scale_dtype = scale_type.checked_type.dtype
+ assert len(scale_shape) != 0, "One of scale or size should be passed."
+ size = _op.cast(shape_of(inputs[0]), scale_dtype) * scale
+
+ return cls.v11_13_common(inputs, size, attr, params)
+
+ @classmethod
+ def v11_13_common(cls, inputs, size, attr, params):
+ """
+ Resize v11 and Resize v13 are identical except in how
Review comment:
Hi emijiayw, Thanks for your feedback! Resize v13 is specified for clarity since just resize could be misleading. :)
##########
File path: python/tvm/relay/frontend/onnx.py
##########
@@ -2697,6 +2697,40 @@ def _impl_v10(cls, inputs, attr, params):
@classmethod
def _impl_v11(cls, inputs, attr, params):
+ scale = inputs[2]
+ scale_shape = infer_shape(scale)
+ if len(inputs) == 4:
+ assert (
+ len(scale_shape) == 0 or scale_shape[0] == 0
+ ), "One of scale or size should be passed, not both."
+ size = inputs[3]
+ else:
+ assert len(scale_shape) != 0, "One of scale or size should be passed."
+ size = _op.cast(shape_of(inputs[0]), infer_type(scale).checked_type.dtype) * scale
+ return cls.v11_13_common(inputs, size, attr, params)
+
+ @classmethod
+ def _impl_v13(cls, inputs, attr, params):
+ scale = inputs[2]
+ size = inputs[3]
+ if size is not None:
+ assert scale is None, "One of scale or size should be passed, not both."
Review comment:
both scale and size are singular (there is only one of them) and adding an 's' makes them plural. It's only one dog or cat, not dogs or cats :dog: :cat2: vs :dog: :dog: :dog: :cat2: :cat2: :cat2:
##########
File path: python/tvm/relay/frontend/onnx.py
##########
@@ -2697,6 +2697,40 @@ def _impl_v10(cls, inputs, attr, params):
@classmethod
def _impl_v11(cls, inputs, attr, params):
+ scale = inputs[2]
+ scale_shape = infer_shape(scale)
+ if len(inputs) == 4:
+ assert (
+ len(scale_shape) == 0 or scale_shape[0] == 0
+ ), "One of scale or size should be passed, not both."
+ size = inputs[3]
+ else:
+ assert len(scale_shape) != 0, "One of scale or size should be passed."
Review comment:
Same as above!
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[GitHub] [tvm] CircleSpin commented on a change in pull request #9265: [ONNX] [Relay] Resize Opset 13
Posted by GitBox <gi...@apache.org>.
CircleSpin commented on a change in pull request #9265:
URL: https://github.com/apache/tvm/pull/9265#discussion_r728243879
##########
File path: python/tvm/relay/frontend/onnx.py
##########
@@ -2697,6 +2697,40 @@ def _impl_v10(cls, inputs, attr, params):
@classmethod
def _impl_v11(cls, inputs, attr, params):
+ scale = inputs[2]
+ scale_shape = infer_shape(scale)
+ if len(inputs) == 4:
+ assert (
+ len(scale_shape) == 0 or scale_shape[0] == 0
+ ), "One of scale or size should be passed, not both."
+ size = inputs[3]
+ else:
+ assert len(scale_shape) != 0, "One of scale or size should be passed."
+ size = _op.cast(shape_of(inputs[0]), infer_type(scale).checked_type.dtype) * scale
+ return cls.v11_13_common(inputs, size, attr, params)
+
+ @classmethod
+ def _impl_v13(cls, inputs, attr, params):
+ scale = inputs[2]
+ size = inputs[3]
+ if size is not None:
+ assert scale is None, "One of scale or size should be passed, not both."
Review comment:
both scale and size are singular (there is only one of them) and adding an 's' makes them plural. It's only one dog or cat, not dogs or cats :dog: :cat2: vs :dog: :dog: :dog: :cat2: :cat2: :cat2:
--
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[GitHub] [tvm] AndrewZhaoLuo commented on a change in pull request #9265: [ONNX] [Relay] Resize Opset 13
Posted by GitBox <gi...@apache.org>.
AndrewZhaoLuo commented on a change in pull request #9265:
URL: https://github.com/apache/tvm/pull/9265#discussion_r727459057
##########
File path: tests/python/frontend/onnx/test_forward.py
##########
@@ -3970,6 +3970,12 @@ def verify(ishape, oshape, scales, mode, coord_trans="asymmetric", alpha=0.5, ex
make_constant_node("scales", onnx.TensorProto.FLOAT, (len(scales),), scales),
]
input_names = ["X", "roi", "scales"]
+
+ # if scales == []:
Review comment:
Just remove this if you don't need it.
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[GitHub] [tvm] masahi merged pull request #9265: [ONNX] [Relay] Resize Opset 13
Posted by GitBox <gi...@apache.org>.
masahi merged pull request #9265:
URL: https://github.com/apache/tvm/pull/9265
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[GitHub] [tvm] emijiayw commented on a change in pull request #9265: [ONNX] [Relay] Resize Opset 13
Posted by GitBox <gi...@apache.org>.
emijiayw commented on a change in pull request #9265:
URL: https://github.com/apache/tvm/pull/9265#discussion_r727677663
##########
File path: python/tvm/relay/frontend/onnx.py
##########
@@ -2697,6 +2697,40 @@ def _impl_v10(cls, inputs, attr, params):
@classmethod
def _impl_v11(cls, inputs, attr, params):
+ scale = inputs[2]
+ scale_shape = infer_shape(scale)
+ if len(inputs) == 4:
+ assert (
+ len(scale_shape) == 0 or scale_shape[0] == 0
+ ), "One of scale or size should be passed, not both."
+ size = inputs[3]
+ else:
+ assert len(scale_shape) != 0, "One of scale or size should be passed."
+ size = _op.cast(shape_of(inputs[0]), infer_type(scale).checked_type.dtype) * scale
+ return cls.v11_13_common(inputs, size, attr, params)
+
+ @classmethod
+ def _impl_v13(cls, inputs, attr, params):
+ scale = inputs[2]
+ size = inputs[3]
+ if size is not None:
+ assert scale is None, "One of scale or size should be passed, not both."
+ else:
+ scale_type = infer_type(scale)
+ scale_shape = scale_type.checked_type.shape
+ scale_dtype = scale_type.checked_type.dtype
+ assert len(scale_shape) != 0, "One of scale or size should be passed."
+ size = _op.cast(shape_of(inputs[0]), scale_dtype) * scale
+
+ return cls.v11_13_common(inputs, size, attr, params)
+
+ @classmethod
+ def v11_13_common(cls, inputs, size, attr, params):
+ """
+ Resize v11 and Resize v13 are identical except in how
Review comment:
Resize v11 and resize
##########
File path: python/tvm/relay/frontend/onnx.py
##########
@@ -2697,6 +2697,40 @@ def _impl_v10(cls, inputs, attr, params):
@classmethod
def _impl_v11(cls, inputs, attr, params):
+ scale = inputs[2]
+ scale_shape = infer_shape(scale)
+ if len(inputs) == 4:
+ assert (
+ len(scale_shape) == 0 or scale_shape[0] == 0
+ ), "One of scale or size should be passed, not both."
+ size = inputs[3]
+ else:
+ assert len(scale_shape) != 0, "One of scale or size should be passed."
+ size = _op.cast(shape_of(inputs[0]), infer_type(scale).checked_type.dtype) * scale
+ return cls.v11_13_common(inputs, size, attr, params)
+
+ @classmethod
+ def _impl_v13(cls, inputs, attr, params):
+ scale = inputs[2]
+ size = inputs[3]
+ if size is not None:
+ assert scale is None, "One of scale or size should be passed, not both."
Review comment:
One of the scales or sizes
##########
File path: python/tvm/relay/frontend/onnx.py
##########
@@ -2697,6 +2697,40 @@ def _impl_v10(cls, inputs, attr, params):
@classmethod
def _impl_v11(cls, inputs, attr, params):
+ scale = inputs[2]
+ scale_shape = infer_shape(scale)
+ if len(inputs) == 4:
+ assert (
+ len(scale_shape) == 0 or scale_shape[0] == 0
+ ), "One of scale or size should be passed, not both."
+ size = inputs[3]
+ else:
+ assert len(scale_shape) != 0, "One of scale or size should be passed."
+ size = _op.cast(shape_of(inputs[0]), infer_type(scale).checked_type.dtype) * scale
+ return cls.v11_13_common(inputs, size, attr, params)
+
+ @classmethod
+ def _impl_v13(cls, inputs, attr, params):
+ scale = inputs[2]
+ size = inputs[3]
+ if size is not None:
+ assert scale is None, "One of scale or size should be passed, not both."
+ else:
+ scale_type = infer_type(scale)
+ scale_shape = scale_type.checked_type.shape
+ scale_dtype = scale_type.checked_type.dtype
+ assert len(scale_shape) != 0, "One of scale or size should be passed."
+ size = _op.cast(shape_of(inputs[0]), scale_dtype) * scale
+
+ return cls.v11_13_common(inputs, size, attr, params)
+
+ @classmethod
+ def v11_13_common(cls, inputs, size, attr, params):
+ """
+ Resize v11 and Resize v13 are identical except in how
+ they handle passing in scale and size. This utility
Review comment:
they handle the passing
##########
File path: python/tvm/relay/frontend/onnx.py
##########
@@ -2697,6 +2697,40 @@ def _impl_v10(cls, inputs, attr, params):
@classmethod
def _impl_v11(cls, inputs, attr, params):
+ scale = inputs[2]
+ scale_shape = infer_shape(scale)
+ if len(inputs) == 4:
+ assert (
+ len(scale_shape) == 0 or scale_shape[0] == 0
+ ), "One of scale or size should be passed, not both."
+ size = inputs[3]
+ else:
+ assert len(scale_shape) != 0, "One of scale or size should be passed."
Review comment:
One of the scales or sizes
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[GitHub] [tvm] CircleSpin commented on a change in pull request #9265: [ONNX] [Relay] Resize Opset 13
Posted by GitBox <gi...@apache.org>.
CircleSpin commented on a change in pull request #9265:
URL: https://github.com/apache/tvm/pull/9265#discussion_r728244270
##########
File path: python/tvm/relay/frontend/onnx.py
##########
@@ -2697,6 +2697,40 @@ def _impl_v10(cls, inputs, attr, params):
@classmethod
def _impl_v11(cls, inputs, attr, params):
+ scale = inputs[2]
+ scale_shape = infer_shape(scale)
+ if len(inputs) == 4:
+ assert (
+ len(scale_shape) == 0 or scale_shape[0] == 0
+ ), "One of scale or size should be passed, not both."
+ size = inputs[3]
+ else:
+ assert len(scale_shape) != 0, "One of scale or size should be passed."
Review comment:
Same as above!
--
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[GitHub] [tvm] CircleSpin commented on a change in pull request #9265: [ONNX] [Relay] Resize Opset 13
Posted by GitBox <gi...@apache.org>.
CircleSpin commented on a change in pull request #9265:
URL: https://github.com/apache/tvm/pull/9265#discussion_r728242091
##########
File path: python/tvm/relay/frontend/onnx.py
##########
@@ -2697,6 +2697,40 @@ def _impl_v10(cls, inputs, attr, params):
@classmethod
def _impl_v11(cls, inputs, attr, params):
+ scale = inputs[2]
+ scale_shape = infer_shape(scale)
+ if len(inputs) == 4:
+ assert (
+ len(scale_shape) == 0 or scale_shape[0] == 0
+ ), "One of scale or size should be passed, not both."
+ size = inputs[3]
+ else:
+ assert len(scale_shape) != 0, "One of scale or size should be passed."
+ size = _op.cast(shape_of(inputs[0]), infer_type(scale).checked_type.dtype) * scale
+ return cls.v11_13_common(inputs, size, attr, params)
+
+ @classmethod
+ def _impl_v13(cls, inputs, attr, params):
+ scale = inputs[2]
+ size = inputs[3]
+ if size is not None:
+ assert scale is None, "One of scale or size should be passed, not both."
+ else:
+ scale_type = infer_type(scale)
+ scale_shape = scale_type.checked_type.shape
+ scale_dtype = scale_type.checked_type.dtype
+ assert len(scale_shape) != 0, "One of scale or size should be passed."
+ size = _op.cast(shape_of(inputs[0]), scale_dtype) * scale
+
+ return cls.v11_13_common(inputs, size, attr, params)
+
+ @classmethod
+ def v11_13_common(cls, inputs, size, attr, params):
+ """
+ Resize v11 and Resize v13 are identical except in how
Review comment:
Hi emijiayw, Thanks for your feedback! Resize v13 is specified for clarity since just resize could be misleading. :)
--
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