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Create Release 1.7.0 (#817)
Signed-off-by: Winnie Tsang <wtsang@us.ibm.com>
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‎.travis.yml

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# at the time of the ONNX-TensorFlow release.
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env:
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- ONNX_PIP=onnx==1.6.0 TF_PIP=tensorflow==2.0.2 TFA_PIP=tensorflow-addons==0.6.0
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- ONNX_PIP=onnx==1.7.0 TF_PIP=tensorflow-cpu==2.3.1 TFA_PIP=tensorflow-addons==0.11.2
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- ONNX_PIP=onnx==1.8.0 TF_PIP=tensorflow-cpu==2.3.1 TFA_PIP=tensorflow-addons==0.11.2
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- ONNX_PIP=git+https://github.com/onnx/onnx.git@master TF_PIP=tensorflow-cpu TFA_PIP=tensorflow-addons
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jobs:

‎ONNX_VERSION_NUMBER

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1.6.0
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1.7.0

‎README.md

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# Tensorflow Backend for ONNX
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[![Build Status](https://travis-ci.org/onnx/onnx-tensorflow.svg?branch=master)](https://travis-ci.org/onnx/onnx-tensorflow)
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[![Build Status](https://travis-ci.com/onnx/onnx-tensorflow.svg?branch=master)](https://travis-ci.com/github/onnx/onnx-tensorflow)
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## To convert models from ONNX to Tensorflow:
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### Use CLI:
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[Command Line Interface Documentation](https://github.com/onnx/onnx-tensorflow/blob/master/doc/CLI.md)
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From ONNX to Tensorflow: `onnx-tf convert -i /path/to/input.onnx -o /path/to/output.pb`
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From ONNX to Tensorflow: `onnx-tf convert -i /path/to/input.onnx -o /path/to/output`
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### Convert programmatically:
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The specific ONNX release version that we support in the master branch of ONNX-TF can be found [here](https://github.com/onnx/onnx-tensorflow/blob/master/ONNX_VERSION_NUMBER). This information about ONNX version requirement is automatically encoded in `setup.py`, therefore users needn't worry about ONNX version requirement when installing ONNX-TF.
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To install the latest version of ONNX-TF via pip, run `pip install onnx-tf`.
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As of November 24, 2020, we are unable to publish release 1.7.0 to PyPi due to problem described in issue #738.\
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Once the issue is resolved you should install the latest version of ONNX-TF via pip, by running `pip install onnx-tf`\
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In the mean time please get release 1.7.0 by running the following commands to checkout v1.7.0 tag and install it from source via pip.\
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`git clone https://github.com/onnx/onnx-tensorflow.git && cd onnx-tensorflow`\
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`git checkout v1.7.0`\
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`pip install -e .`
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Because users often have their own preferences for which variant of Tensorflow to install (i.e., a GPU version instead of a CPU version), we do not explicitly require tensorflow in the installation script. It is therefore users' responsibility to ensure that the proper variant of Tensorflow is available to ONNX-TF. Moreover, we require Tensorflow version == 2.2.0.
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Because users often have their own preferences for which variant of Tensorflow to install (i.e., a GPU version instead of a CPU version), we do not explicitly require tensorflow in the installation script. It is therefore users' responsibility to ensure that the proper variant of Tensorflow is available to ONNX-TF. Moreover, we require Tensorflow version == 2.3.1.
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## Development:
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### Installation:
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- Install ONNX master branch from source.
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- Install Tensorflow >= 2.2.0 and tensorflow-addons. (Note for Tensorflow 1.x please refer the [tf-1.x branch](https://github.com/onnx/onnx-tensorflow/tree/tf-1.x))
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- Install Tensorflow >= 2.3.1 and tensorflow-addons. (Note for Tensorflow 1.x please refer the [tf-1.x branch](https://github.com/onnx/onnx-tensorflow/tree/tf-1.x))
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- Run `git clone https://github.com/onnx/onnx-tensorflow.git && cd onnx-tensorflow`.
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- Run `pip install -e .`.
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To perfom unit tests, run `python -m unittest discover test`.
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Testing requires significant hardware resources, but nonetheless, we highly recommend that users run through the complete test suite before deploying onnx-tf. The complete test suite typically takes between 15 and 45 minutes to complete, depending on hardware configurations.
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PS. Please ensure your code is backward compatible with older version of ONNX. You can easily test it by running the following [docker container](https://hub.docker.com/r/winnietsang/onnx-tensorflow) with your code. If you don't have Docker installed yet, please follow this link to install [Docker](https://docs.docker.com/install/) on your environment.
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```
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sudo docker pull winnietsang/onnx-tensorflow:onnx1.7.0-tf2.2
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sudo docker run -it --name=YOUR-CONTAINER-NAME winnietsang/onnx-tensorflow:onnx1.7.0-tf2.2 /bin/bash
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git clone https://github.com/YOUR-USERNAME/onnx-tensorflow.git
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cd onnx-tensorflow
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git checkout -b YOUR-BRANCH --track remotes/origin/YOUR-BRANCH
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pip3 install -e .
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python3 -m unittest discover test
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```
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#### Test Help:
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https://docs.python.org/2/library/unittest.html

‎VERSION_NUMBER

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1.6.0
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1.7.0

‎Versioning.md

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1.3.0|1.3.0 (opset 8)|1.13.1
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1.5.0|1.5.0 (opset 10)|1.15.0
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1.6.0|1.6.0 (opset 11)|2.2.0
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1.7.0|1.7.0 (opset 12)|2.3.1

‎doc/support_status.md

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# ONNX-Tensorflow Support Status
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|||
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|-:|:-|
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|ONNX-Tensorflow Version|Master ( commit id: fb3b6758903516d80ad4cc506bc4f589be8a7231 )|
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|ONNX-Tensorflow Version|Master ( commit id: 9871ba020edac2d7122b38391c9f3a0a906a148d )|
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|ONNX Version|Master ( commit id: 274e8b54e4c11c40a8c0a89599196f5311088b64 )|
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|Tensorflow Version|v2.3.1|
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‎doc/support_status_v1_7_0.md

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# ONNX-Tensorflow Support Status
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|-:|:-|
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|ONNX-Tensorflow Version|v1.7.0|
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|ONNX Version|1.7.0|
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|Tensorflow Version|v2.3.1|
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Notes:
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* Values that are new or updated from a previous opset version are in bold.
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* -: not defined in corresponding ONNX opset version
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* \*: the operator is deprecated
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* :small_red_triangle:: not supported yet
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* :small_orange_diamond:: partially supported
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* the rest are all supported
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|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|
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|**ONNX Operator**|**Opset 1**|**Opset 2**|**Opset 3**|**Opset 4**|**Opset 5**|**Opset 6**|**Opset 7**|**Opset 8**|**Opset 9**|**Opset 10**|**Opset 11**|**Opset 12**|**ONNX Operator**|
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|Abs|**1**|1|1|1|1|**6**|6|6|6|6|6|6|Abs|
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|Acos|-|-|-|-|-|-|**7**|7|7|7|7|7|Acos|
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|Acosh|-|-|-|-|-|-|-|-|**9**|9|9|9|Acosh|
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|Add|**1**|1|1|1|1|**6**|**7**|7|7|7|7|7|Add|
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|And|**1**|1|1|1|1|1|**7**|7|7|7|7|7|And|
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|ArgMax|**1**|1|1|1|1|1|1|1|1|1|**11**|**12**|ArgMax|
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|ArgMin|**1**|1|1|1|1|1|1|1|1|1|**11**|**12**|ArgMin|
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|Asin|-|-|-|-|-|-|**7**|7|7|7|7|7|Asin|
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|Asinh|-|-|-|-|-|-|-|-|**9**|9|9|9|Asinh|
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|Atan|-|-|-|-|-|-|**7**|7|7|7|7|7|Atan|
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|Atanh|-|-|-|-|-|-|-|-|**9**|9|9|9|Atanh|
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|AveragePool|**1**|1|1|1|1|1|**7**|7|7|**10**|**11**|11|AveragePool|
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|BatchNormalization|**1**|1|1|1|1|**6**|**7**|7|**9**|9|9|9|BatchNormalization|
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|BitShift|-|-|-|-|-|-|-|-|-|-|**11**|11|BitShift|
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|Cast|**1**:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|**6**:small_orange_diamond:|6:small_orange_diamond:|6:small_orange_diamond:|**9**:small_orange_diamond:|9:small_orange_diamond:|9:small_orange_diamond:|9:small_orange_diamond:|Cast|
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|Ceil|**1**|1|1|1|1|**6**|6|6|6|6|6|6|Ceil|
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|Celu|-|-|-|-|-|-|-|-|-|-|-|**12**|Celu|
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|Clip|**1**|1|1|1|1|**6**|6|6|6|6|**11**|**12**|Clip|
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|Compress|-|-|-|-|-|-|-|-|**9**|9|**11**|11|Compress|
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|Concat|**1**|1|1|**4**|4|4|4|4|4|4|**11**|11|Concat|
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|ConcatFromSequence|-|-|-|-|-|-|-|-|-|-|**11**:small_orange_diamond:|11:small_orange_diamond:|ConcatFromSequence|
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|Constant|**1**|1|1|1|1|1|1|1|**9**|9|**11**|**12**|Constant|
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|ConstantOfShape|-|-|-|-|-|-|-|-|**9**|9|9|9|ConstantOfShape|
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|Conv|**1**|1|1|1|1|1|1|1|1|1|**11**|11|Conv|
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|ConvInteger|-|-|-|-|-|-|-|-|-|**10**|10|10|ConvInteger|
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|ConvTranspose|**1**:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|**11**:small_orange_diamond:|11:small_orange_diamond:|ConvTranspose|
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|Cos|-|-|-|-|-|-|**7**|7|7|7|7|7|Cos|
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|Cosh|-|-|-|-|-|-|-|-|**9**|9|9|9|Cosh|
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|CumSum|-|-|-|-|-|-|-|-|-|-|**11**|11|CumSum|
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|DepthToSpace|**1**|1|1|1|1|1|1|1|1|1|**11**|11|DepthToSpace|
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|DequantizeLinear|-|-|-|-|-|-|-|-|-|**10**|10|10|DequantizeLinear|
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|Det|-|-|-|-|-|-|-|-|-|-|**11**|11|Det|
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|Div|**1**|1|1|1|1|**6**|**7**|7|7|7|7|7|Div|
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|Dropout|**1**|1|1|1|1|**6**|**7**|7|7|**10**|10|**12**|Dropout|
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|DynamicQuantizeLinear|-|-|-|-|-|-|-|-|-|-|**11**|11|DynamicQuantizeLinear|
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|Einsum|-|-|-|-|-|-|-|-|-|-|-|**12**|Einsum|
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|Elu|**1**|1|1|1|1|**6**|6|6|6|6|6|6|Elu|
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|Equal|**1**|1|1|1|1|1|**7**|7|7|7|**11**|11|Equal|
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|Erf|-|-|-|-|-|-|-|-|**9**|9|9|9|Erf|
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|Exp|**1**|1|1|1|1|**6**|6|6|6|6|6|6|Exp|
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|Expand|-|-|-|-|-|-|-|**8**|8|8|8|8|Expand|
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|EyeLike|-|-|-|-|-|-|-|-|**9**|9|9|9|EyeLike|
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|Flatten|**1**|1|1|1|1|1|1|1|**9**|9|**11**|11|Flatten|
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|Floor|**1**|1|1|1|1|**6**|6|6|6|6|6|6|Floor|
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|GRU|**1**:small_orange_diamond:|1:small_orange_diamond:|**3**:small_orange_diamond:|3:small_orange_diamond:|3:small_orange_diamond:|3:small_orange_diamond:|**7**:small_orange_diamond:|7:small_orange_diamond:|7:small_orange_diamond:|7:small_orange_diamond:|7:small_orange_diamond:|7:small_orange_diamond:|GRU|
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|Gather|**1**|1|1|1|1|1|1|1|1|1|**11**|11|Gather|
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|GatherElements|-|-|-|-|-|-|-|-|-|-|**11**|11|GatherElements|
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|GatherND|-|-|-|-|-|-|-|-|-|-|**11**|**12**|GatherND|
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|Gemm|**1**|1|1|1|1|**6**|**7**|7|**9**|9|**11**|11|Gemm|
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|GlobalAveragePool|**1**|1|1|1|1|1|1|1|1|1|1|1|GlobalAveragePool|
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|GlobalLpPool|**1**|**2**|2|2|2|2|2|2|2|2|2|2|GlobalLpPool|
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|GlobalMaxPool|**1**|1|1|1|1|1|1|1|1|1|1|1|GlobalMaxPool|
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|Greater|**1**|1|1|1|1|1|**7**|7|**9**|9|9|9|Greater|
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|GreaterOrEqual|-|-|-|-|-|-|-|-|-|-|-|**12**|GreaterOrEqual|
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|HardSigmoid|**1**|1|1|1|1|**6**|6|6|6|6|6|6|HardSigmoid|
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|Hardmax|**1**|1|1|1|1|1|1|1|1|1|**11**|11|Hardmax|
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|Identity|**1**|1|1|1|1|1|1|1|1|1|1|1|Identity|
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|If|**1**|1|1|1|1|1|1|1|1|1|**11**|11|If|
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|InstanceNormalization|**1**|1|1|1|1|**6**|6|6|6|6|6|6|InstanceNormalization|
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|IsInf|-|-|-|-|-|-|-|-|-|**10**|10|10|IsInf|
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|IsNaN|-|-|-|-|-|-|-|-|**9**|9|9|9|IsNaN|
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|LRN|**1**|1|1|1|1|1|1|1|1|1|1|1|LRN|
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|LSTM|**1**:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|**7**:small_orange_diamond:|7:small_orange_diamond:|7:small_orange_diamond:|7:small_orange_diamond:|7:small_orange_diamond:|7:small_orange_diamond:|LSTM|
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|LeakyRelu|**1**|1|1|1|1|**6**|6|6|6|6|6|6|LeakyRelu|
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|Less|**1**|1|1|1|1|1|**7**|7|**9**|9|9|9|Less|
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|LessOrEqual|-|-|-|-|-|-|-|-|-|-|-|**12**|LessOrEqual|
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|Log|**1**|1|1|1|1|**6**|6|6|6|6|6|6|Log|
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|LogSoftmax|**1**|1|1|1|1|1|1|1|1|1|**11**|11|LogSoftmax|
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|Loop|**1**|1|1|1|1|1|1|1|1|1|**11**|11|Loop|
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|LpNormalization|**1**|1|1|1|1|1|1|1|1|1|1|1|LpNormalization|
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|LpPool|**1**|**2**|2|2|2|2|2|2|2|2|**11**|11|LpPool|
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|MatMul|**1**|1|1|1|1|1|1|1|**9**|9|9|9|MatMul|
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|MatMulInteger|-|-|-|-|-|-|-|-|-|**10**|10|10|MatMulInteger|
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|Max|**1**|1|1|1|1|**6**|6|**8**|8|8|8|**12**|Max|
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|MaxPool|**1**:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|**8**:small_orange_diamond:|8:small_orange_diamond:|**10**:small_orange_diamond:|**11**:small_orange_diamond:|**12**:small_orange_diamond:|MaxPool|
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|MaxRoiPool|**1**:small_red_triangle:|1:small_red_triangle:|1:small_red_triangle:|1:small_red_triangle:|1:small_red_triangle:|1:small_red_triangle:|1:small_red_triangle:|1:small_red_triangle:|1:small_red_triangle:|1:small_red_triangle:|1:small_red_triangle:|1:small_red_triangle:|MaxRoiPool|
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|MaxUnpool|-|-|-|-|-|-|-|-|**9**|9|**11**|11|MaxUnpool|
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|Mean|**1**|1|1|1|1|**6**|6|**8**|8|8|8|8|Mean|
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|MeanVarianceNormalization|-|-|-|-|-|-|-|-|**9**|9|9|9|MeanVarianceNormalization|
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|Min|**1**|1|1|1|1|**6**|6|**8**|8|8|8|**12**|Min|
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|Mod|-|-|-|-|-|-|-|-|-|**10**|10|10|Mod|
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|Mul|**1**|1|1|1|1|**6**|**7**|7|7|7|7|7|Mul|
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|Multinomial|-|-|-|-|-|-|**7**:small_red_triangle:|7:small_red_triangle:|7:small_red_triangle:|7:small_red_triangle:|7:small_red_triangle:|7:small_red_triangle:|Multinomial|
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|Neg|**1**|1|1|1|1|**6**|6|6|6|6|6|6|Neg|
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|NegativeLogLikelihoodLoss|-|-|-|-|-|-|-|-|-|-|-|**12**:small_red_triangle:|NegativeLogLikelihoodLoss|
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|NonMaxSuppression|-|-|-|-|-|-|-|-|-|**10**|**11**|11|NonMaxSuppression|
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|NonZero|-|-|-|-|-|-|-|-|**9**|9|9|9|NonZero|
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|Not|**1**|1|1|1|1|1|1|1|1|1|1|1|Not|
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|OneHot|-|-|-|-|-|-|-|-|**9**|9|**11**|11|OneHot|
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|Or|**1**|1|1|1|1|1|**7**|7|7|7|7|7|Or|
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|PRelu|**1**|1|1|1|1|**6**|**7**|7|**9**|9|9|9|PRelu|
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|Pad|**1**|**2**|2|2|2|2|2|2|2|2|**11**|11|Pad|
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|Pow|**1**|1|1|1|1|1|**7**|7|7|7|7|**12**|Pow|
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|QLinearConv|-|-|-|-|-|-|-|-|-|**10**|10|10|QLinearConv|
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|QLinearMatMul|-|-|-|-|-|-|-|-|-|**10**|10|10|QLinearMatMul|
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|QuantizeLinear|-|-|-|-|-|-|-|-|-|**10**|10|10|QuantizeLinear|
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|RNN|**1**:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|1:small_orange_diamond:|**7**:small_orange_diamond:|7:small_orange_diamond:|7:small_orange_diamond:|7:small_orange_diamond:|7:small_orange_diamond:|7:small_orange_diamond:|RNN|
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|RandomNormal|**1**|1|1|1|1|1|1|1|1|1|1|1|RandomNormal|
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|RandomNormalLike|**1**|1|1|1|1|1|1|1|1|1|1|1|RandomNormalLike|
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|RandomUniform|**1**|1|1|1|1|1|1|1|1|1|1|1|RandomUniform|
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|RandomUniformLike|**1**|1|1|1|1|1|1|1|1|1|1|1|RandomUniformLike|
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|Range|-|-|-|-|-|-|-|-|-|-|**11**|11|Range|
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|Reciprocal|**1**|1|1|1|1|**6**|6|6|6|6|6|6|Reciprocal|
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|ReduceL1|**1**|1|1|1|1|1|1|1|1|1|**11**|11|ReduceL1|
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|ReduceL2|**1**|1|1|1|1|1|1|1|1|1|**11**|11|ReduceL2|
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|ReduceLogSum|**1**|1|1|1|1|1|1|1|1|1|**11**|11|ReduceLogSum|
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|ReduceLogSumExp|**1**|1|1|1|1|1|1|1|1|1|**11**|11|ReduceLogSumExp|
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|ReduceMax|**1**|1|1|1|1|1|1|1|1|1|**11**|**12**|ReduceMax|
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|ReduceMean|**1**|1|1|1|1|1|1|1|1|1|**11**|11|ReduceMean|
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|ReduceMin|**1**|1|1|1|1|1|1|1|1|1|**11**|**12**|ReduceMin|
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|ReduceProd|**1**|1|1|1|1|1|1|1|1|1|**11**|11|ReduceProd|
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|ReduceSum|**1**|1|1|1|1|1|1|1|1|1|**11**|11|ReduceSum|
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|ReduceSumSquare|**1**|1|1|1|1|1|1|1|1|1|**11**|11|ReduceSumSquare|
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|Relu|**1**|1|1|1|1|**6**|6|6|6|6|6|6|Relu|
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|Reshape|**1**|1|1|1|**5**|5|5|5|5|5|5|5|Reshape|
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|Resize|-|-|-|-|-|-|-|-|-|**10**:small_orange_diamond:|**11**:small_orange_diamond:|11:small_orange_diamond:|Resize|
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|ReverseSequence|-|-|-|-|-|-|-|-|-|**10**|10|10|ReverseSequence|
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|RoiAlign|-|-|-|-|-|-|-|-|-|**10**:small_orange_diamond:|10:small_orange_diamond:|10:small_orange_diamond:|RoiAlign|
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|Round|-|-|-|-|-|-|-|-|-|-|**11**|11|Round|
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|Scan|-|-|-|-|-|-|-|**8**|**9**|9|**11**|11|Scan|
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|Scatter|-|-|-|-|-|-|-|-|**9**|9|**11**\*|11\*|Scatter|
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|ScatterElements|-|-|-|-|-|-|-|-|-|-|**11**|11|ScatterElements|
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|ScatterND|-|-|-|-|-|-|-|-|-|-|**11**|11|ScatterND|
142+
|Selu|**1**|1|1|1|1|**6**|6|6|6|6|6|6|Selu|
143+
|SequenceAt|-|-|-|-|-|-|-|-|-|-|**11**|11|SequenceAt|
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|SequenceConstruct|-|-|-|-|-|-|-|-|-|-|**11**|11|SequenceConstruct|
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|SequenceEmpty|-|-|-|-|-|-|-|-|-|-|**11**|11|SequenceEmpty|
146+
|SequenceErase|-|-|-|-|-|-|-|-|-|-|**11**|11|SequenceErase|
147+
|SequenceInsert|-|-|-|-|-|-|-|-|-|-|**11**|11|SequenceInsert|
148+
|SequenceLength|-|-|-|-|-|-|-|-|-|-|**11**|11|SequenceLength|
149+
|Shape|**1**|1|1|1|1|1|1|1|1|1|1|1|Shape|
150+
|Shrink|-|-|-|-|-|-|-|-|**9**|9|9|9|Shrink|
151+
|Sigmoid|**1**|1|1|1|1|**6**|6|6|6|6|6|6|Sigmoid|
152+
|Sign|-|-|-|-|-|-|-|-|**9**|9|9|9|Sign|
153+
|Sin|-|-|-|-|-|-|**7**|7|7|7|7|7|Sin|
154+
|Sinh|-|-|-|-|-|-|-|-|**9**|9|9|9|Sinh|
155+
|Size|**1**|1|1|1|1|1|1|1|1|1|1|1|Size|
156+
|Slice|**1**|1|1|1|1|1|1|1|1|**10**|**11**|11|Slice|
157+
|Softmax|**1**|1|1|1|1|1|1|1|1|1|**11**|11|Softmax|
158+
|SoftmaxCrossEntropyLoss|-|-|-|-|-|-|-|-|-|-|-|**12**:small_red_triangle:|SoftmaxCrossEntropyLoss|
159+
|Softplus|**1**|1|1|1|1|1|1|1|1|1|1|1|Softplus|
160+
|Softsign|**1**|1|1|1|1|1|1|1|1|1|1|1|Softsign|
161+
|SpaceToDepth|**1**|1|1|1|1|1|1|1|1|1|1|1|SpaceToDepth|
162+
|Split|**1**|**2**|2|2|2|2|2|2|2|2|**11**|11|Split|
163+
|SplitToSequence|-|-|-|-|-|-|-|-|-|-|**11**:small_orange_diamond:|11:small_orange_diamond:|SplitToSequence|
164+
|Sqrt|**1**|1|1|1|1|**6**|6|6|6|6|6|6|Sqrt|
165+
|Squeeze|**1**|1|1|1|1|1|1|1|1|1|**11**|11|Squeeze|
166+
|StringNormalizer|-|-|-|-|-|-|-|-|-|**10**:small_red_triangle:|10:small_red_triangle:|10:small_red_triangle:|StringNormalizer|
167+
|Sub|**1**|1|1|1|1|**6**|**7**|7|7|7|7|7|Sub|
168+
|Sum|**1**|1|1|1|1|**6**|6|**8**|8|8|8|8|Sum|
169+
|Tan|-|-|-|-|-|-|**7**|7|7|7|7|7|Tan|
170+
|Tanh|**1**|1|1|1|1|**6**|6|6|6|6|6|6|Tanh|
171+
|TfIdfVectorizer|-|-|-|-|-|-|-|-|**9**|9|9|9|TfIdfVectorizer|
172+
|ThresholdedRelu|-|-|-|-|-|-|-|-|-|**10**|10|10|ThresholdedRelu|
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|Tile|**1**|1|1|1|1|**6**|6|6|6|6|6|6|Tile|
174+
|TopK|**1**|1|1|1|1|1|1|1|1|**10**|**11**|11|TopK|
175+
|Transpose|**1**|1|1|1|1|1|1|1|1|1|1|1|Transpose|
176+
|Unique|-|-|-|-|-|-|-|-|-|-|**11**:small_red_triangle:|11:small_red_triangle:|Unique|
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|Unsqueeze|**1**|1|1|1|1|1|1|1|1|1|**11**|11|Unsqueeze|
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|Upsample|**1**:small_red_triangle:|1:small_red_triangle:|1:small_red_triangle:|1:small_red_triangle:|1:small_red_triangle:|1:small_red_triangle:|**7**:small_orange_diamond:|7:small_orange_diamond:|**9**:small_orange_diamond:|**10**\*|10\*|10\*|Upsample|
179+
|Where|-|-|-|-|-|-|-|-|**9**|9|9|9|Where|
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|Xor|**1**|1|1|1|1|1|**7**|7|7|7|7|7|Xor|
181+
182+
ONNX-TF Supported Operators / ONNX Operators: 156 / 162
183+
184+
Notes:
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1. Cast: Cast string to data types other than float32/float64/int32/int64 is not supported in Tensorflow
186+
2. ConcatFromSequence: new_axis=1 not supported in Tensorflow.
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3. ConvTranspose: ConvTranspose with dilations != 1, or transposed convolution for 4D or higher are not supported in Tensorflow.
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4. GRU: GRU with clip or GRU with linear_before_reset, or GRU not using sigmoid for z and r, or GRU using Elu as the activation function with alpha != 1, or GRU using HardSigmoid as the activation function with alpha != 0.2 or beta != 0.5 are not supported in TensorFlow.
189+
5. LSTM: LSTM not using sigmoid for `f`, or LSTM not using the same activation for `g` and `h` are not supported in Tensorflow.
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6. MaxPool: MaxPoolWithArgmax with pad is None or incompatible mode, or MaxPoolWithArgmax with 4D or higher input, or MaxPoolWithArgmax with column major are not supported in Tensorflow.
191+
7. RNN: RNN with clip is not supported in Tensorflow.
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8. Resize: Resize required 4D input in Tensorflow. For opset 11, only the following attributes and inputs conbination are supported in Tensorflow:
193+
1. mode=nearest, coordinate_transformation_mode=align_corners, nearest_mode=round_prefer_ceil, can use scales(*) or sizes.
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2. mode=nearest, coordinate_transformation_mode=asymmetric, nearest_mode=floor, can use scales(*) or sizes.
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3. mode=nearest, coordinate_transformation_mode=tf_half_pixel_for_nn, nearest_mode=floor, can use scales(*) or sizes.
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4. mode=linear, coordinate_transformation_mode=align_corners, can use scales(*) or sizes.
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5. mode=linear, coordinate_transformation_mode=asymmetric, can use scales(*) or sizes.
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6. mode=linear, coordinate_transformation_mode=half_pixel, can use scales(*) or sizes.
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7. mode=cubic, coordinate_transformation_mode=align_corners, cubic_coeff_a=-0.5, exclude_outside=1, can use scales(*) or sizes.
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8. mode=cubic, coordinate_transformation_mode=asymmetric, cubic_coeff_a=-0.5, exclude_outside=1, can use scales(*) or sizes.
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9. mode=cubic, coordinate_transformation_mode=half_pixel, cubic_coeff_a=-0.5, exclude_outside=1, can use scales(*) or sizes.
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10. mode=nearest, coordinate_transformation_mode=tf_crop_and_resize, extrapolation_value=any_float_value, nearest_mode=round_prefer_ceil, can use scales or sizes.
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11. mode=linear, coordinate_transformation_mode=tf_crop_and_resize, extrapolation_value=any_float_value, can use scales or sizes.
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- Note (*): The accuracy of your model will go down, if the height and the width of the new sizes(scales * origial sizes) are not in whole numbers.
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9. RoiAlign: sampling_ratio <= 0 is not fully supported.
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10. SplitToSequence: Scalar as the split input not supported.
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11. Upsample: Upsample required 4D input in Tensorflow.

‎setup.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -42,7 +42,7 @@
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version=version,
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description=
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'Tensorflow backend for ONNX (Open Neural Network Exchange).',
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install_requires=[onnx_dep, "PyYAML"],
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install_requires=[onnx_dep, "PyYAML", "tensorflow_addons"],
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entry_points={
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"console_scripts": [
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"onnx-tf=onnx_tf.cli:main",

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