use tf.shape instead of .shape for dynamic axes in InstanceNormalization#771
use tf.shape instead of .shape for dynamic axes in InstanceNormalization#771masakistan wants to merge 12 commits intoonnx:mainfrom
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Signed-off-by: masakistan <sfujimoto@gmail.com>
* Add model stepping test for Mnist Add model stepping test for Mnist using ONNX runtime. The assumption is that ONNX runtime is installed and the mnist model from ONNX model zoo is downloaded. Signed-off-by: Chin Huang <chhuang@us.ibm.com> * add tensor_dict back in TFRep Signed-off-by: Chin Huang <chhuang@us.ibm.com>
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winnietsang
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@masakistan Thanks for helping us to identify and fix this dynamic shape issue.
May you please add in a dynamic shape testcase for instance_normalization into onnx-tensorflow/test/backend/test_dynamic_shape.py
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Signed-off-by: masakistan <sfujimoto@gmail.com>
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@masakistan please add in a dynamic shape testcase for instance_normalization into onnx-tensorflow/test/backend/test_dynamic_shape.py |
Will do, sorry I haven't had time to get to it. |
Hi, I want to convert my onnx file to the tensorflow considering dynamic batch size, but it fails after lots of trial, could you help me |
InstanceNormalizationfailed to handle tensor shape with undefined/batch size dimension. This PR fixes it by querying the dynamic shape instead of creating a constant from static shape.Essentially the same as #543