我有一个训练过的rnn,我试着用在手机上。问题是,当我使用toco将我的.pb文件转换为.tflite时,它会失败,出现以下错误消息:
WARNING: Config values are not defined in any .rc file: opt.
INFO: Found 1 target...
Target //tensorflow/contrib/lite/toco:toco up-to-date:
bazel-bin/tensorflow/contrib/lite/toco/toco
INFO: Elapsed time: 0.287s, Critical Path: 0.0
我已经从MLKit创建了.tflite文件,并在张量应用程序中使用,但应用程序崩溃并出现以下错误。 java.lang.IllegalArgumentException: Cannot convert between a TensorFlowLite buffer with 150528 bytes and a ByteBuffer with 786432 bytes.
at org.tensorflow.lite.Tensor.throwIfShapeIsIncompatible(Tensor.java:281)
at org.tenso
我在gradle android项目的build.gradle模块中有下面这行代码 dependencies {
// a lot of dependencies
implementation 'org.tensorflow:tensorflow-lite-select-tf-ops:0.0.0-nightly-SNAPSHOT'
} 它会导致gradle构建失败,并显示以下错误 Null extracted folder for artifact: ResolvedArtifact(componentIdentifier=org.tensorflow:tensorflo
更新org.tensorflow:tensorflow-lite-metadata后,org.tensorflow:tensorflow-lite-task-vision和org.tensorflow:tensorflow-lite-support应用程序出现错误:
java.lang.NoSuchMethodError: No static method create(Ljava/nio/ByteBuffer;Lorg/tensorflow/lite/InterpreterApi$Options;)Lorg/tensorflow/lite/InterpreterApi; in class L
我对Tensorflow训练后量化过程感到困惑。官方网站提到了Tensorflow Lite量化。不幸的是,这在我的例子中不起作用,也就是说,TFLiteConverter为我的Mask RCNN模型返回错误:
Some of the operators in the model are not supported by the standard TensorFlow Lite runtime and are not recognized by TensorFlow. If you have a custom implementation for them you can disable th
我正在处理来自tensorflow存储库的一个相当大的Makefile,我需要添加一个文件链接。 在对链接错误进行了相当多的调试之后,我发现如果我的文件以.cc结尾,那么链接错误就会消失,而当链接.c文件时,错误就会出现(文件内容保持不变)。 我将文件链接到一个Makefile.inc文件中: .
.
.
FL_SRCS := \
tensorflow/lite/vis_mi/main.cc \
myFunctions.c \ -->>>>IF I CHANGE THE FILENAME TO myFunctions.cc and link to this .cc f
我正在尝试使用Tensorflow Lite Python解释器来检测raspberry pi 3B+中的对象,如下所示
from tensorflow.contrib.lite.python import interpreter as interpreter_wrapper
但是当我运行这一行interpreter=interpreter_wrapper.Interpreter(model_path="mobilenet.tflite")
我得到了这个错误:
Traceback (most recent call last):
File "<pyshell#
我已经通过以下方式将我的模型导出到ONNX:
# Export the model
torch_out = torch.onnx._export(learn.model, # model being run
x, # model input (or a tuple for multiple inputs)
EXPORT_PATH + "mnist.onnx", # where to save the mod
我想在android studio中使用我的keras训练模型。我在互联网上得到了这段代码,将我的代码从keras转换为tensorflow-lite。但是当我尝试编写代码时,我得到了这个错误: OSError: SavedModel file does not exist at: C:\Users\Munib\New folder/{saved_model.pbtxt|saved_model.pb} 我使用的代码是从keras转换到tensorflow-lite: import tensorflow as tf
# Converting a SavedModel to a TensorFl