tensorflow-lite

问题 I am using a .tflite model on device. The last layer is ConditionalRandomField layer, and I need weights of the layer to do prediction. How do I get weights with c++ api? related: How can I view weights in a .tflite file? Netron or flatc doesn't meet my needs. too heavy on device. It seems TfLiteNode stores weights in void* user_data or void* builtin_data. How do I read them? UPDATE: Conclusion: .tflite doesn't store CRF weights while .h5 dose. (Maybe because they do not affect output.) WHAT

问题 I have a custom neural network written in Tensorflow.Keras and apply the hard-swish function as activation (as used in the MobileNetV3 paper): Implementation: def swish(x): return x * tf.nn.relu6(x+3) / 6 I am running quantization aware training and write a protobuf file at the end. Then, I am using this code to convert to tflite (and deploy it finally on the EdgeTPU): tflite_convert --output_file test.tflite --graph_def_file=test.pb --inference_type=QUANTIZED_UINT8 --input_arrays=input_1 -

问题 I have a custom neural network written in Tensorflow.Keras and apply the hard-swish function as activation (as used in the MobileNetV3 paper): Implementation: def swish(x): return x * tf.nn.relu6(x+3) / 6 I am running quantization aware training and write a protobuf file at the end. Then, I am using this code to convert to tflite (and deploy it finally on the EdgeTPU): tflite_convert --output_file test.tflite --graph_def_file=test.pb --inference_type=QUANTIZED_UINT8 --input_arrays=input_1 -

问题 I am trying out tflite C++ API for running a model that I built. I converted the model to tflite format by following snippet: import tensorflow as tf converter = tf.lite.TFLiteConverter.from_keras_model_file('model.h5') tfmodel = converter.convert() open("model.tflite", "wb").write(tfmodel) I am following the steps provided at tflite official guide, and my code upto this point looks like this // Load the model std::unique_ptr<tflite::FlatBufferModel> model = tflite::FlatBufferModel:

问题 I had lost my dataset by a careless mistake. I have only my tflite file left in my hand. Is there any solution to reverse back h5 file. I have been done decent research in this but no solutions found. 回答1: The conversion from a TensorFlow SaveModel or tf.keras H5 model to .tflite is an irreversible process. Specifically, the original model topology is optimized during the compilation by the TFLite converter, which leads to some loss of information. Also, the original tf.keras model's loss and

来源： https://stackoverflow.com/questions/64239738/tensorflow-lite-does-not-recognize-op-varhandleop

来源： https://stackoverflow.com/questions/64239738/tensorflow-lite-does-not-recognize-op-varhandleop

来源： https://stackoverflow.com/questions/63726309/why-accuracy-of-tflite-model-is-so-different-from-keras-model

来源： https://stackoverflow.com/questions/55701663/input-images-with-dynamic-dimensions-in-tensorflow-lite

来源： https://stackoverflow.com/questions/55701663/input-images-with-dynamic-dimensions-in-tensorflow-lite