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Hello, I have a custom trained keras mobilenet model which i have converted to a tensorflow model successfully. I am now trying to convert it to movidius but I am running into this problem:
robert@atreus:~$ mvNCCheck -in input_1 -on predictions/concat dev/converter/TF_Model/tf_model.meta /usr/local/bin/ncsdk/Controllers/Parsers/TensorFlowParser/Convolution.py:47: SyntaxWarning: assertion is always true, perhaps remove parentheses? assert(False, "Layer type not supported by Convolution: " + obj.type) mvNCCheck v02.00, Copyright @ Intel Corporation 2017 ****** Info: No Weights provided. inferred path: dev/converter/TF_Model/tf_model.data-00000-of-00001****** dev/converter/TF_Model/tf_model.meta 2019-02-27 11:27:46.187790: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2019-02-27 11:27:46.209947: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2904000000 Hz 2019-02-27 11:27:46.210526: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x4a0f550 executing computations on platform Host. Devices: 2019-02-27 11:27:46.210541: I tensorflow/compiler/xla/service/service.cc:158] StreamExecutor device (0): <undefined>, <undefined> WARNING:tensorflow:From /home/robert/.local/lib/python3.5/site-packages/tensorflow/python/training/saver.py:1266: checkpoint_exists (from tensorflow.python.training.checkpoint_management) is deprecated and will be removed in a future version. Instructions for updating: Use standard file APIs to check for files with this prefix. Traceback (most recent call last): File "/usr/local/bin/mvNCCheck", line 239, in <module> quit_code = check_net(args.network, args.image, args.inputnode, args.outputnode, args.nshaves, args.inputsize, args.weights, args) File "/usr/local/bin/mvNCCheck", line 206, in check_net load_ret = load_network(args, parser, myriad_config) File "/usr/local/bin/ncsdk/Controllers/Scheduler.py", line 72, in load_network parsedLayers = p.parse(arguments) File "/usr/local/bin/ncsdk/Controllers/Parsers/TensorFlow.py", line 673, in parse parsed_op = opParser(op, operations, dummy_feed_dict) File "/usr/local/bin/ncsdk/Controllers/Parsers/TensorFlowParser/FusedBatchNorm.py", line 36, in load scale = np.reciprocal(np.sqrt(variance)) * scale_param ValueError: operands could not be broadcast together with shapes (0,) (32,)
This is the original keras model that I am using to train:
After training I am converting to a tensorflow graph like this:
input_shape = (300, 300, 3) mobilenet_model = SSD(input_shape, num_classes=1) mobilenet_model.load_weights('mobilenet_test/weights.32-3.41.hdf5', by_name=True) def keras_to_tf( ): tf_model_path = './TF_Model/tf_model' saver = tf.train.Saver() with K.get_session() as sess: K.set_learning_phase(0) saver.save(sess, tf_model_path) return True keras_to_tf( )