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--> config model
done
--> Loading model
W:tensorflow:From /home/toybrick/.local/lib/python3.7/site-packages/rknn/api/rknn.py:100: The name tf.ConfigProto is deprecated. Please use tf.compat.v1.ConfigProto instead.
W:tensorflow:From /home/toybrick/.local/lib/python3.7/site-packages/rknn/api/rknn.py:100: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.
W:tensorflow:From /home/toybrick/.local/lib/python3.7/site-packages/rknn/api/rknn.py:100: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.
done
--> Building model
W The target_platform is not set in config, using default target platform rk1808.
W The channel_mean_value filed will not be used in the future!
W:tensorflow:From /home/toybrick/.local/lib/python3.7/site-packages/rknn/api/rknn.py:249: The name tf.FIFOQueue is deprecated. Please use tf.queue.FIFOQueue instead.
W:tensorflow:From /home/toybrick/.local/lib/python3.7/site-packages/tensorflow/python/ops/control_flow_ops.py:1814: py_func (from tensorflow.python.ops.script_ops) is deprecated and will be removed in a future version.
Instructions for updating:
tf.py_func is deprecated in TF V2. Instead, there are two
options available in V2.
- tf.py_function takes a python function which manipulates tf eager
tensors instead of numpy arrays. It's easy to convert a tf eager tensor to
an ndarray (just call tensor.numpy()) but having access to eager tensors
means `tf.py_function`s can use accelerators such as GPUs as well as
being differentiable using a gradient tape.
- tf.numpy_function maintains the semantics of the deprecated tf.py_func
(it is not differentiable, and manipulates numpy arrays). It drops the
stateful argument making all functions stateful.
W:tensorflow:From /home/toybrick/.local/lib/python3.7/site-packages/tensorflow/python/ops/control_flow_ops.py:1814: The name tf.read_file is deprecated. Please use tf.io.read_file instead.
W:tensorflow:From /home/toybrick/.local/lib/python3.7/site-packages/rknn/api/rknn.py:249: The name tf.nn.avg_pool is deprecated. Please use tf.nn.avg_pool2d instead.
W:tensorflow:From /home/toybrick/.local/lib/python3.7/site-packages/rknn/api/rknn.py:249: add_dispatch_support.<locals>.wrapper (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.where in 2.0, which has the same broadcast rule as np.where
done
--> Export RKNN model
done
--> Init runtime environment
I NPUTransfer: Starting NPU Transfer Client, Transfer version 2.0.0 (8f9ebbc@2020-04-03T09:12:43)
D RKNNAPI: ==============================================
D RKNNAPI: RKNN VERSION:
D RKNNAPI: API: 1.4.0 (b4a8096 build: 2020-08-12 10:16:10)
D RKNNAPI: DRV: 1.5.0 (83d70a9 build: 2020-09-30 16:25:49)
D RKNNAPI: ==============================================
done
--> Running model
D RKNNAPI: __can_use_fixed_point: use_fixed_point = 1.
mobilenet_v1
-----TOP 5-----
[156]: 0.86474609375
[155]: 0.0838623046875
[205]: 0.012420654296875
[284]: 0.005908966064453125
[194]: 0.0020465850830078125
done
--> Begin evaluate model performance
W When performing performance evaluation, inputs can be set to None to use fake inputs.
D RKNNAPI: __can_use_fixed_point: cache use_fixed_point = 1.
========================================================================
Performance
========================================================================
Total Time(us): 5436
FPS: 183.96
========================================================================
done
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