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Mir Akhtar Ali
4 hours ago
Using TensorFlow backend.
2018-09-05 18:27:17.202041: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: FMA
2018-09-05 18:27:17.336380: W tensorflow/stream_executor/cuda/cuda_driver.cc:513] A non-primary context 0x60fa250 for device 0 exists before initializing the StreamExecutor. The primary context is now 0x60cc960. We haven’t verified StreamExecutor works with that.
2018-09-05 18:27:17.337269: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1405] Found device 0 with properties:
name: GeForce GTX 1080 major: 6 minor: 1 memoryClockRate(GHz): 1.7335
pciBusID: 0000:01:00.0
totalMemory: 7.93GiB freeMemory: 7.70GiB
2018-09-05 18:27:17.337304: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1484] Adding visible gpu devices: 0
2018-09-05 18:27:17.991676: I tensorflow/core/common_runtime/gpu/gpu_device.cc:965] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-09-05 18:27:17.991732: I tensorflow/core/common_runtime/gpu/gpu_device.cc:971] 0
2018-09-05 18:27:17.991747: I tensorflow/core/common_runtime/gpu/gpu_device.cc:984] 0: N
2018-09-05 18:27:17.991999: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1097] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 7408 MB memory) → physical GPU (device: 0, name: GeForce GTX 1080, pci bus id: 0000:01:00.0, compute capability: 6.1)
model_data/yolo.h5 model, anchors, and classes loaded.
Using output node dense_2/Softmax
Converting to UFF graph
Traceback (most recent call last):
File “demo.py”, line 193, in
main(YOLO())
File “demo.py”, line 43, in main
uff_model = uff.from_tensorflow_frozen_model(“mars-small128.pb”, [“dense_2/Softmax”])
File “/usr/lib/python3.5/dist-packages/uff/converters/tensorflow/conversion_helpers.py”, line 149, in from_tensorflow_frozen_model
return from_tensorflow(graphdef, output_nodes, preprocessor, **kwargs)
File “/usr/lib/python3.5/dist-packages/uff/converters/tensorflow/conversion_helpers.py”, line 120, in from_tensorflow
name=“main”)
File “/usr/lib/python3.5/dist-packages/uff/converters/tensorflow/converter.py”, line 76, in convert_tf2uff_graph
uff_graph, input_replacements)
File “/usr/lib/python3.5/dist-packages/uff/converters/tensorflow/converter.py”, line 53, in convert_tf2uff_node
raise UffException(str(name) + " was not found in the graph. Please use the -l option to list nodes in the graph.")
NameError: name ‘UffException’ is not defined
Python knows the purposes of certain names (ex. built-in functions ). Other names are defined within the program (ex. variables). If Python encounters a name that it doesn’t recognize, you’ll probably get NameError: global name ‘xx’ is not defined error. In most cases, this error is triggered when Python sees a variable name (Global or Local) and doesn’t know what it’s for. These errors can happen if you forget to initialize a variable , if you misspell a variable, or if you misspell a reserved word such as “True”. Before you use the global variable in your function for reading, it must be first initialized somewhere: either outside of the function or inside it.