onnx2keras
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Convert ONNX model graph to Keras model format.
**Pull Request: Small Correction to convert_clip Function** This pull request addresses a small correction in the `convert_clip` function, as suggested in [comment #1129549436](https://github.com/gmalivenko/onnx2keras/issues/79#issuecomment-1129549436) of [issue #79](https://github.com/gmalivenko/onnx2keras/issues/79). ### Why: The convert_clip()...
Hey, I cannot convert a model which uses BatchNormalization Layers, because of dimension mismatches.. Assume the input tensor for BN is 48x112x112 (CHW) the parameters (e.g. gamma) has a size...
I am trying to convert an ONNX model to Keras, but when I call the conversion function I receive the following error message "TypeError: unhashable type: 'google._upb._message.RepeatedScalarContainer'" ``` import onnx...
Trying to load and use onnx exported from pytorch - (1, 3, 28, 28). onnx_model = onnx.load('data/export-torch.onnx') k_model = onnx_to_keras(onnx_model, ['actual_input']) DEBUG:onnx2keras:... DEBUG:onnx2keras:Check if all inputs are available: DEBUG:onnx2keras:Check input...
Converting a model that has Relu6 operation fails; it seems to be converted into a `clip` where the min and max is not set. I hacked together a temporary fix...
I trained my model using yolov5 and with ultralitics/yolov5 github repository converted it to a onnx model. I want to convert it to a h5 keras model but the code...
There are two similar LeNet5 models. But when using onnx2keras, their node information is different. As a result, an error is reported when converting the second model. VGG16 met the...
I am trying to convert an onnx model with dynamic input shape : ['p2o.DynamicDimension.0', 3, 'p2o.DynamicDimension.1', 'p2o.DynamicDimension.2'] . > Traceback (most recent call last): > File "/home/dockerpaddle/Desktop/onnx/test.py", line 11, in...
_**i was trying to export .onnx file to .h5 file i don't konw how to solve this error**_ DEBUG:onnx2keras:Output TF Layer -> KerasTensor(type_spec=TensorSpec(shape=(None, 128, 42), dtype=tf.float32, name=None), name='input.1/transpose_1:0', description="created by...
In the original implementation, when converting Conv1d layers from ONNX to Keras, bias terms of conv1d was ignored. Fixed this issue by adding back bias terms to the output.