You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Has a TFLite model ever been exported for the TF model in this repo? If there is one, can you upload it or a step-by-step guide is appreciated.
I run TF2.1.0 Python3.7 Linux and am trying to export one using python3 export_tflite_ssd_graph.py --pipeline_config_path=/PATH_TO/pipeline.config --trained_checkpoint_prefix=/PATH_TO/model.ckpt.data-00000-of-00001 --output_directory=/my_tflite --add_postprocessing_op=true
and get error File "../.local/lib/python3.7/site-packages/tensorflow_core/python/ops/array_ops.py", line 2715, in placeholder raise RuntimeError("tf.placeholder() is not compatible with " RuntimeError: tf.placeholder() is not compatible with eager execution.
The text was updated successfully, but these errors were encountered:
File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/lite/python/tflite_convert.py", line 235, in _convert_tf2_model tflite_model = converter.convert() File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/lite/python/lite.py", line 446, in convert "invalid shape '{1}'.".format(_get_tensor_name(tensor), shape_list)) ValueError: None is only supported in the 1st dimension. Tensor 'image_tensor' has invalid shape '[None, None, None, 3]'.
Did you resolve the problem or develop a work-around?
Has a TFLite model ever been exported for the TF model in this repo? If there is one, can you upload it or a step-by-step guide is appreciated.
I run TF2.1.0 Python3.7 Linux and am trying to export one using
python3 export_tflite_ssd_graph.py --pipeline_config_path=/PATH_TO/pipeline.config --trained_checkpoint_prefix=/PATH_TO/model.ckpt.data-00000-of-00001 --output_directory=/my_tflite --add_postprocessing_op=true
and get error
File "../.local/lib/python3.7/site-packages/tensorflow_core/python/ops/array_ops.py", line 2715, in placeholder raise RuntimeError("tf.placeholder() is not compatible with " RuntimeError: tf.placeholder() is not compatible with eager execution.
The text was updated successfully, but these errors were encountered: