Comments (7)
I have looked at all of the API in v2.16.1 and there does not appear to be any flags or options that you would expect. Once I remove the TODO flag, the bot will automatically close this issue after 5 days if there is no new feedback from you.
Thanks, It really seems not have that flags. I will use tf-v1.x as a solution.
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relu6 activation is fuse into conv
It is completely wrong.
No wonder.
from onnx2tf.
relu6 activation is fuse into conv
It is completely wrong.
No wonder.
Thanks for your Response~~
I don't think it was wrong. take a look at the scale and zero point formate:
The old formate compute the relu-like activation into the scale computation.
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I am posting only the reference URL for the research process as I have to be out of town for an extended period of time. I will check it when I get home.
https://stackoverflow.com/questions/62000090/how-does-tflite-fuses-relu-into-conv-layers
from onnx2tf.
I am posting only the reference URL for the research process as I have to be out of town for an extended period of time. I will check it when I get home.
https://stackoverflow.com/questions/62000090/how-does-tflite-fuses-relu-into-conv-layers
Thanks !
I found that this kind of fusion (fused_activation_function=NONE) was adopt by tensorflow<=1.12.x version, after this version, activation like relu was explicit fused_activation_function=RELU, there should be some switch button in latest tensorflow, because the type: FusedActivationFunctionType::kNone is still in main branch of tensorflow.
Thank you again for your great work.
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I am posting only the reference URL for the research process as I have to be out of town for an extended period of time. I will check it when I get home.
https://stackoverflow.com/questions/62000090/how-does-tflite-fuses-relu-into-conv-layers
I will take a look at this solution. Thanks again.
from onnx2tf.
I have looked at all of the API in v2.16.1 and there does not appear to be any flags or options that you would expect. Once I remove the TODO flag, the bot will automatically close this issue after 5 days if there is no new feedback from you.
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Related Issues (20)
- Discrepancies between Conv layer outputs of the ONNX model and converted TensorFlow models HOT 3
- Resize operation fails (['unk__0', 'unk__1', 'unk__2', 'unk__3']) and raises UnboundLocalError: local variable 'new_size' referenced before assignment HOT 20
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- [ONNX to TFLite] Cannot reshape from slice to unsqueeze. HOT 6
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- Android GPU inference falls with TRANSPOSE_CONV: Max version supported: 3. Requested version 4. HOT 2
- Conversion error for Resize layer when using flag "-nuo" HOT 2
- Incorrect arguments in tf.nn.convolution HOT 5
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