Unable to know the output notes of the PNET, ONET and RNET
Santhosh1509 opened this issue · 0 comments
I am trying to convert the tensorflow model to tensorflow tensorrt version.
I tried converting only with the PNET to tensorrt taking conv4_1/BiasAdd and conv4_2/BiasAdd as output nodes while converting guided by P/R/O output nodes
But no luck it didn't work.
Could anyone please tell me what exactly are the names of the output nodes of the PNET,ONET and RNET in this model?
When I try to print all the nodes in the model I get this output
['input_image', 'image_width', 'image_height', 'Reshape/shape/0', 'Reshape/shape/3', 'Reshape/shape', 'Reshape', 'conv1/weights/Initializer/random_uniform/shape', 'conv1/weights/Initializer/random_uniform/min', 'conv1/weights/Initializer/random_uniform/max', 'conv1/weights/Initializer/random_uniform/RandomUniform', 'conv1/weights/Initializer/random_uniform/sub', 'conv1/weights/Initializer/random_uniform/mul', 'conv1/weights/Initializer/random_uniform', 'conv1/weights', 'conv1/weights/Assign', 'conv1/weights/read', 'conv1/kernel/Regularizer/l2_regularizer/scale', 'conv1/kernel/Regularizer/l2_regularizer/L2Loss', 'conv1/kernel/Regularizer/l2_regularizer', 'conv1/biases/Initializer/zeros', 'conv1/biases', 'conv1/biases/Assign', 'conv1/biases/read', 'conv1/dilation_rate', 'conv1/Conv2D', 'conv1/BiasAdd', 'conv1/alphas/Initializer/Const', 'conv1/alphas', 'conv1/alphas/Assign', 'conv1/alphas/read', 'conv1/Relu', 'conv1/Abs', 'conv1/sub', 'conv1/mul', 'conv1/mul_1/y', 'conv1/mul_1', 'conv1/add', 'conv1/add/activations/tag', 'conv1/add/activations', 'pool1/MaxPool', 'pool1/MaxPool/activations/tag', 'pool1/MaxPool/activations', 'conv2/weights/Initializer/random_uniform/shape', 'conv2/weights/Initializer/random_uniform/min', 'conv2/weights/Initializer/random_uniform/max', 'conv2/weights/Initializer/random_uniform/RandomUniform', 'conv2/weights/Initializer/random_uniform/sub', 'conv2/weights/Initializer/random_uniform/mul', 'conv2/weights/Initializer/random_uniform', 'conv2/weights', 'conv2/weights/Assign', 'conv2/weights/read', 'conv2/kernel/Regularizer/l2_regularizer/scale', 'conv2/kernel/Regularizer/l2_regularizer/L2Loss', 'conv2/kernel/Regularizer/l2_regularizer', 'conv2/biases/Initializer/zeros', 'conv2/biases', 'conv2/biases/Assign', 'conv2/biases/read', 'conv2/dilation_rate', 'conv2/Conv2D', 'conv2/BiasAdd', 'conv2/alphas/Initializer/Const', 'conv2/alphas', 'conv2/alphas/Assign', 'conv2/alphas/read', 'conv2/Relu', 'conv2/Abs', 'conv2/sub', 'conv2/mul', 'conv2/mul_1/y', 'conv2/mul_1', 'conv2/add', 'conv2/add/activations/tag', 'conv2/add/activations', 'conv3/weights/Initializer/random_uniform/shape', 'conv3/weights/Initializer/random_uniform/min', 'conv3/weights/Initializer/random_uniform/max', 'conv3/weights/Initializer/random_uniform/RandomUniform', 'conv3/weights/Initializer/random_uniform/sub', 'conv3/weights/Initializer/random_uniform/mul', 'conv3/weights/Initializer/random_uniform', 'conv3/weights', 'conv3/weights/Assign', 'conv3/weights/read', 'conv3/kernel/Regularizer/l2_regularizer/scale', 'conv3/kernel/Regularizer/l2_regularizer/L2Loss', 'conv3/kernel/Regularizer/l2_regularizer', 'conv3/biases/Initializer/zeros', 'conv3/biases', 'conv3/biases/Assign', 'conv3/biases/read', 'conv3/dilation_rate', 'conv3/Conv2D', 'conv3/BiasAdd', 'conv3/alphas/Initializer/Const', 'conv3/alphas', 'conv3/alphas/Assign', 'conv3/alphas/read', 'conv3/Relu', 'conv3/Abs', 'conv3/sub', 'conv3/mul', 'conv3/mul_1/y', 'conv3/mul_1', 'conv3/add', 'conv3/add/activations/tag', 'conv3/add/activations', 'conv4_1/weights/Initializer/random_uniform/shape', 'conv4_1/weights/Initializer/random_uniform/min', 'conv4_1/weights/Initializer/random_uniform/max', 'conv4_1/weights/Initializer/random_uniform/RandomUniform', 'conv4_1/weights/Initializer/random_uniform/sub', 'conv4_1/weights/Initializer/random_uniform/mul', 'conv4_1/weights/Initializer/random_uniform', 'conv4_1/weights', 'conv4_1/weights/Assign', 'conv4_1/weights/read', 'conv4_1/kernel/Regularizer/l2_regularizer/scale', 'conv4_1/kernel/Regularizer/l2_regularizer/L2Loss', 'conv4_1/kernel/Regularizer/l2_regularizer', 'conv4_1/biases/Initializer/zeros', 'conv4_1/biases', 'conv4_1/biases/Assign', 'conv4_1/biases/read', 'conv4_1/dilation_rate', 'conv4_1/Conv2D', 'conv4_1/BiasAdd', 'conv4_1/Softmax', 'conv4_1/Softmax/activations/tag', 'conv4_1/Softmax/activations', 'conv4_2/weights/Initializer/random_uniform/shape', 'conv4_2/weights/Initializer/random_uniform/min', 'conv4_2/weights/Initializer/random_uniform/max', 'conv4_2/weights/Initializer/random_uniform/RandomUniform', 'conv4_2/weights/Initializer/random_uniform/sub', 'conv4_2/weights/Initializer/random_uniform/mul', 'conv4_2/weights/Initializer/random_uniform', 'conv4_2/weights', 'conv4_2/weights/Assign', 'conv4_2/weights/read', 'conv4_2/kernel/Regularizer/l2_regularizer/scale', 'conv4_2/kernel/Regularizer/l2_regularizer/L2Loss', 'conv4_2/kernel/Regularizer/l2_regularizer', 'conv4_2/biases/Initializer/zeros', 'conv4_2/biases', 'conv4_2/biases/Assign', 'conv4_2/biases/read', 'conv4_2/dilation_rate', 'conv4_2/Conv2D', 'conv4_2/BiasAdd', 'conv4_2/BiasAdd/activations/tag', 'conv4_2/BiasAdd/activations', 'conv4_3/weights/Initializer/random_uniform/shape', 'conv4_3/weights/Initializer/random_uniform/min', 'conv4_3/weights/Initializer/random_uniform/max', 'conv4_3/weights/Initializer/random_uniform/RandomUniform', 'conv4_3/weights/Initializer/random_uniform/sub', 'conv4_3/weights/Initializer/random_uniform/mul', 'conv4_3/weights/Initializer/random_uniform', 'conv4_3/weights', 'conv4_3/weights/Assign', 'conv4_3/weights/read', 'conv4_3/kernel/Regularizer/l2_regularizer/scale', 'conv4_3/kernel/Regularizer/l2_regularizer/L2Loss', 'conv4_3/kernel/Regularizer/l2_regularizer', 'conv4_3/biases/Initializer/zeros', 'conv4_3/biases', 'conv4_3/biases/Assign', 'conv4_3/biases/read', 'conv4_3/dilation_rate', 'conv4_3/Conv2D', 'conv4_3/BiasAdd', 'conv4_3/BiasAdd/activations/tag', 'conv4_3/BiasAdd/activations', 'Squeeze', 'Squeeze_1', 'Squeeze_2', 'save/filename/input', 'save/filename', 'save/Const', 'save/SaveV2/tensor_names', 'save/SaveV2/shape_and_slices', 'save/SaveV2', 'save/control_dependency', 'save/RestoreV2/tensor_names', 'save/RestoreV2/shape_and_slices', 'save/RestoreV2', 'save/Assign', 'save/Assign_1', 'save/Assign_2', 'save/Assign_3', 'save/Assign_4', 'save/Assign_5', 'save/Assign_6', 'save/Assign_7', 'save/Assign_8', 'save/Assign_9', 'save/Assign_10', 'save/Assign_11', 'save/Assign_12', 'save/Assign_13', 'save/Assign_14', 'save/restore_all']