add elementwise max/min conversation and test case #92
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doombeaker
commented
Sep 14, 2022
| @@ -211,6 +211,8 @@ def _MakeMinOrMaxOp(ctx, op_type, inputs, outputs, output_shapes=None, output_dt | |||
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| @flow_op("broadcast_minimum", onnx_op="Min") | |||
| @flow_op("broadcast_maximum", onnx_op="Max") | |||
| @flow_op("elementwise_minimum", onnx_op="Min") | |||
| @flow_op("elementwise_maximum", onnx_op="Max") | |||
| class MinMaxOp: | |||
| @classmethod | |||
| def Version_1(cls, ctx, node, **kwargs): | |||
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这里我有个疑问，我看 https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Min-1 提到 Version 1 的 Min，是不支持 broadcast 的，所以在下面 _MakeMinOrMaxOp 里做了一些处理。
然而后面较高版本的 onnx op （比如 12 https://github.com/onnx/onnx/blob/main/docs/Changelog.md#Min-12）又支持 broadcast 了。
不过自定义的 trick 好像又够用了，这个是不是暂时就不用添加更高版本的映射了？
BBuf
reviewed
Sep 15, 2022
| @@ -34,6 +34,7 @@ def forward(self, x: flow.Tensor) -> flow.Tensor: | |||
| y3 = flow.acos(y3) | |||
| y3 = flow.pow(y3, 2.0) | |||
| y2 = y2 + y3 | |||
| flow.minimum(y2, y3) | |||
BBuf
approved these changes
Sep 15, 2022
Closed
doombeaker
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