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楼主 |
发表于 2022-6-22 10:42:29
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Using TensorFlow backend.
W __init__: rknn-toolkit2 version: 1.3.0-11912b58
W config: 'target_platform' is None, use rk3566 as default, Please set according to the actual platform!
--> Loading model
W load_tensorflow: inputs name should be a tensor name instead of node name
W:tensorflow:From /usr/local/lib/python3.6/dist-packages/rknn/api/rknn.py:108: convert_variables_to_constants (from tensorflow.python.framework.graph_util_impl) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.compat.v1.graph_util.convert_variables_to_constants`
W:tensorflow:From /home/nine/.local/lib/python3.6/site-packages/tensorflow/python/framework/graph_util_impl.py:270: extract_sub_graph (from tensorflow.python.framework.graph_util_impl) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.compat.v1.graph_util.extract_sub_graph`
2022-06-22 10:40:37.996405: W tensorflow/compiler/jit/mark_for_compilation_pass.cc:1412] (One-time warning): Not using XLA:CPU for cluster because envvar TF_XLA_FLAGS=--tf_xla_cpu_global_jit was not set. If you want XLA:CPU, either set that envvar, or use experimental_jit_scope to enable XLA:CPU. To confirm that XLA is active, pass --vmodule=xla_compilation_cache=1 (as a proper command-line flag, not via TF_XLA_FLAGS) or set the envvar XLA_FLAGS=--xla_hlo_profile.
Scaling constant 1.000000 for dropout pattern rooted at dropout/mul is inconsistent with dropout ratio 1.000000. The pattern will not be replaced with an ONNX dropout node.
W load_tensorflow: The config.mean_values is None, zeros will be set for input 0!
W load_tensorflow: The config.std_values is None, ones will be set for input 0!
done
--> Building model
Fatal: Meet unsupported operator: RandomUniformLike(name="RandomUniform__8"). |
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