如何从保存的模型生成 tflite？
How to generate tflite from saved model?
我想创建一个基于重新训练的 ssd_mobilenet 模型的对象检测应用程序我已经像 youtube 上的那个人一样重新训练了。
我从 Tensorflow Model Zoo 中选择了型号 ssd_mobilenet_v2_coco。在重新训练过程之后，我得到了具有以下结构的模型：
- saved_model
- variables (empty folder)
- saved_model.pb
- checkpoint
- frozen_inverence_graph.pb
- model.ckpt.data-00000-of-00001
- model.ckpt.index
- model.ckpt.meta
- pipeline.config
在同一个文件夹中，我有 python 脚本，代码如下：
import tensorflow as tf
converter = tf.lite.TFLiteConverter.from_saved_model("saved_model", input_shapes={"image_tensor":[1,300,300,3]})
tflite_model = converter.convert()
open("converted_model.tflite", "wb").write(tflite_model)
在运行这段代码之后，我得到了以下错误：
...
2019-05-24 18:46:59.811289: I tensorflow/lite/toco/import_tensorflow.cc:1324] Converting unsupported operation: TensorArrayGatherV3
2019-05-24 18:46:59.811864: I tensorflow/lite/toco/import_tensorflow.cc:1373] Unable to determine output type for op: TensorArrayGatherV3
2019-05-24 18:46:59.908207: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] Before Removing unused ops: 1792 operators, 3033 arrays (0 quantized)
2019-05-24 18:47:00.089034: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] After Removing unused ops pass 1: 1771 operators, 2979 arrays (0 quantized)
2019-05-24 18:47:00.314681: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] Before general graph transformations: 1771 operators, 2979 arrays (0 quantized)
2019-05-24 18:47:00.453570: F tensorflow/lite/toco/graph_transformations/resolve_constant_slice.cc:59] Check failed: dim_size >= 1 (0 vs. 1)
"Check failed: dim_size >= 1 (0 vs. 1)"有解决办法吗？
由于图中需要一些自定义操作，MobileNet SSD 的转换略有不同。
看看这个 Medium post for the end-to-end process of training and exporting the model as a TFLite graph. For conversion, you would need to use the export_tflite_ssd_graph 脚本。
我想创建一个基于重新训练的 ssd_mobilenet 模型的对象检测应用程序我已经像 youtube 上的那个人一样重新训练了。
我从 Tensorflow Model Zoo 中选择了型号 ssd_mobilenet_v2_coco。在重新训练过程之后，我得到了具有以下结构的模型：
- saved_model
- variables (empty folder)
- saved_model.pb
- checkpoint
- frozen_inverence_graph.pb
- model.ckpt.data-00000-of-00001
- model.ckpt.index
- model.ckpt.meta
- pipeline.config
在同一个文件夹中，我有 python 脚本，代码如下：
import tensorflow as tf
converter = tf.lite.TFLiteConverter.from_saved_model("saved_model", input_shapes={"image_tensor":[1,300,300,3]})
tflite_model = converter.convert()
open("converted_model.tflite", "wb").write(tflite_model)
在运行这段代码之后，我得到了以下错误：
...
2019-05-24 18:46:59.811289: I tensorflow/lite/toco/import_tensorflow.cc:1324] Converting unsupported operation: TensorArrayGatherV3
2019-05-24 18:46:59.811864: I tensorflow/lite/toco/import_tensorflow.cc:1373] Unable to determine output type for op: TensorArrayGatherV3
2019-05-24 18:46:59.908207: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] Before Removing unused ops: 1792 operators, 3033 arrays (0 quantized)
2019-05-24 18:47:00.089034: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] After Removing unused ops pass 1: 1771 operators, 2979 arrays (0 quantized)
2019-05-24 18:47:00.314681: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] Before general graph transformations: 1771 operators, 2979 arrays (0 quantized)
2019-05-24 18:47:00.453570: F tensorflow/lite/toco/graph_transformations/resolve_constant_slice.cc:59] Check failed: dim_size >= 1 (0 vs. 1)
"Check failed: dim_size >= 1 (0 vs. 1)"有解决办法吗？
由于图中需要一些自定义操作，MobileNet SSD 的转换略有不同。
看看这个 Medium post for the end-to-end process of training and exporting the model as a TFLite graph. For conversion, you would need to use the export_tflite_ssd_graph 脚本。