我正在frozon .pb模型文件上运行OpenVINO优化。运行优化时，它显示以下错误消息：
E0806 16:58:26.145075 140020238079808 matmul.py:52] MatMul wasn't able to infer shape because input dimensions are not compatible
E0806 16:58:26.146022 140020238079808 infer.py:152] Shape is not defined for output 0 of "lstm_27/while/MatMul_3".
E0806 16:58:26.146118 140020238079808 infer.py:180] Cannot infer shapes or values for node "lstm_27/while/MatMul_3".
E0806 16:58:26.146183 140020238079808 infer.py:181] Not all output shapes were inferred or fully defined for node "lstm_27/while/MatMul_3".
For more information please refer to Model Optimizer FAQ (https://docs.openvinotoolkit.org/latest/_docs_MO_DG_prepare_model_Model_Optimizer_FAQ.html), question #40.
E0806 16:58:26.146232 140020238079808 infer.py:182]
E0806 16:58:26.146281 140020238079808 infer.py:183] It can happen due to bug in custom shape infer function <function tf_matmul_infer at 0x7f586c514e18>.
E0806 16:58:26.146322 140020238079808 infer.py:184] Or because the node inputs have incorrect values/shapes.
E0806 16:58:26.146360 140020238079808 infer.py:185] Or because input shapes are incorrect (embedded to the model or passed via --input_shape).
model.summary（）的输出
Model: "sequential_11"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
lstm_27 (LSTM) (None, 10, 50) 10600
_________________________________________________________________
lstm_28 (LSTM) (None, 10, 40) 14560
_________________________________________________________________
lstm_29 (LSTM) (None, 30) 8520
_________________________________________________________________
dense_7 (Dense) (None, 1) 31
=================================================================
Total params: 33,711
Trainable params: 33,711
Non-trainable params: 0
我正在按照以下要求进行优化。
input_shape = [0, 10, 50]
input_shape_str = str(input_shape).replace(' ','')
input_shape_str
!python3 {mo_tf_path} --input_model {pb_file} --output_dir {output_dir} --input_shape {input_shape_str} --data_type FP32
这是什么问题？
答案 0 :(得分：0)
mo_tf需要精确的输入形状，即input_shape = [1、10、50]。使用-1、0或跳过第一维将引发错误。