converting to ONNX, need names of input and output nodes.

[I-CANT-CODE]

Hi I am trying to convert the model to onnx for deployment. To do that I need the name of the input and output

from tf2onnx repo:
"Tensorflow model's input/output names, which can be found with summarize graph tool. Those names typically end on :0, for example --inputs input0:0,input1:0. inputs and outputs are not needed for models in saved-model format."

I basically edited the saving mechanism of the repo to save the model into .pb because thats what tf summarizer graph tool requires. here is this is the output of the tf summarize graph module, but I am not sure which nodes are the input and output nodes. If anyone can help with this I'd greatly appreciate it.

bazel-bin/tensorflow/tools/graph_transforms/summarize_graph --in_graph=/home/users/user/tf_unet/tmp/tmp/my_model.pb
Found 3 possible inputs: (name=x, type=float(1), shape=[?,?,?,1]) (name=y, type=float(1), shape=[?,?,?,2]) (name=dropout_probability, type=float(1), shape=)
Found 26 variables: (name=down_conv_0/w1, type=float(1), shape=[3,3,1,32]) (name=down_conv_0/w2, type=float(1), shape=[3,3,32,32]) (name=down_conv_0/b1, type=float(1), shape=[32]) (name=down_conv_0/b2, type=float(1), shape=[32]) (name=down_conv_1/w1, type=float(1), shape=[3,3,32,64]) (name=down_conv_1/w2, type=float(1), shape=[3,3,64,64]) (name=down_conv_1/b1, type=float(1), shape=[64]) (name=down_conv_1/b2, type=float(1), shape=[64]) (name=down_conv_2/w1, type=float(1), shape=[3,3,64,128]) (name=down_conv_2/w2, type=float(1), shape=[3,3,128,128]) (name=down_conv_2/b1, type=float(1), shape=[128]) (name=down_conv_2/b2, type=float(1), shape=[128]) (name=up_conv_1/wd, type=float(1), shape=[2,2,64,128]) (name=up_conv_1/bd, type=float(1), shape=[64]) (name=up_conv_1/w1, type=float(1), shape=[3,3,128,64]) (name=up_conv_1/w2, type=float(1), shape=[3,3,64,64]) (name=up_conv_1/b1, type=float(1), shape=[64]) (name=up_conv_1/b2, type=float(1), shape=[64]) (name=up_conv_0/wd, type=float(1), shape=[2,2,32,64]) (name=up_conv_0/bd, type=float(1), shape=[32]) (name=up_conv_0/w1, type=float(1), shape=[3,3,64,32]) (name=up_conv_0/w2, type=float(1), shape=[3,3,32,32]) (name=up_conv_0/b1, type=float(1), shape=[32]) (name=up_conv_0/b2, type=float(1), shape=[32]) (name=output_map/weight, type=float(1), shape=[1,1,32,2]) (name=output_map/bias, type=float(1), shape=[2])
Found 80 possible outputs: (name=preprocessing/strided_slice_2, op=StridedSlice) (name=summaries/summary_conv_00_01, op=ImageSummary) (name=summaries/summary_conv_00_02, op=ImageSummary) (name=summaries/summary_conv_01_01, op=ImageSummary) (name=summaries/summary_conv_01_02, op=ImageSummary) (name=summaries/summary_conv_02_01, op=ImageSummary) (name=summaries/summary_conv_02_02, op=ImageSummary) (name=summaries/summary_conv_03_01, op=ImageSummary) (name=summaries/summary_conv_03_02, op=ImageSummary) (name=summaries/summary_conv_04_01, op=ImageSummary) (name=summaries/summary_conv_04_02, op=ImageSummary) (name=summaries/summary_pool_00, op=ImageSummary) (name=summaries/summary_pool_01, op=ImageSummary) (name=summaries/summary_deconv_concat_01, op=ImageSummary) (name=summaries/summary_deconv_concat_00, op=ImageSummary) (name=summaries/dw_convolution_00/activations, op=HistogramSummary) (name=summaries/dw_convolution_01/activations, op=HistogramSummary) (name=summaries/dw_convolution_02/activations, op=HistogramSummary) (name=summaries/up_convolution_1/activations, op=HistogramSummary) (name=summaries/up_convolution_0/activations, op=HistogramSummary) (name=summaries/up_convolution_out/activations, op=HistogramSummary) (name=cost/Reshape, op=Reshape) (name=cost/Reshape_1, op=Reshape) (name=cost/Mean, op=Mean) (name=gradients/cost/Mul_1_grad/Reshape_1, op=Reshape) (name=gradients/zeros_like, op=ZerosLike) (name=gradients/cost/softmax_cross_entropy_with_logits_grad/mul_1, op=Mul) (name=gradients/output_map/conv2d/BiasAdd_grad/BiasAddGrad, op=BiasAddGrad) (name=gradients/output_map/conv2d/Conv2D_grad/Conv2DBackpropFilter, op=Conv2DBackpropFilter) (name=gradients/up_conv_0/conv2d_1/dropout/mul_grad/Reshape_1, op=Reshape) (name=gradients/up_conv_0/conv2d_1/dropout/div_grad/Reshape_1, op=Reshape) (name=gradients/up_conv_0/conv2d_1/BiasAdd_grad/BiasAddGrad, op=BiasAddGrad) (name=gradients/up_conv_0/conv2d_1/Conv2D_grad/Conv2DBackpropFilter, op=Conv2DBackpropFilter) (name=gradients/up_conv_0/conv2d/dropout/mul_grad/Reshape_1, op=Reshape) (name=gradients/up_conv_0/conv2d/dropout/div_grad/Reshape_1, op=Reshape) (name=gradients/up_conv_0/conv2d/BiasAdd_grad/BiasAddGrad, op=BiasAddGrad) (name=gradients/up_conv_0/conv2d/Conv2D_grad/Conv2DBackpropFilter, op=Conv2DBackpropFilter) (name=gradients/up_conv_0/crop_and_concat/concat_grad/Shape, op=Shape) (name=gradients/up_conv_0/add_grad/Reshape_1, op=Reshape) (name=gradients/up_conv_0/deconv2d/conv2d_transpose_grad/Conv2DBackpropFilter, op=Conv2DBackpropFilter) (name=gradients/up_conv_1/conv2d_1/dropout/mul_grad/Reshape_1, op=Reshape) (name=gradients/up_conv_1/conv2d_1/dropout/div_grad/Reshape_1, op=Reshape) (name=gradients/up_conv_1/conv2d_1/BiasAdd_grad/BiasAddGrad, op=BiasAddGrad) (name=gradients/up_conv_1/conv2d_1/Conv2D_grad/Conv2DBackpropFilter, op=Conv2DBackpropFilter) (name=gradients/up_conv_1/conv2d/dropout/mul_grad/Reshape_1, op=Reshape) (name=gradients/up_conv_1/conv2d/dropout/div_grad/Reshape_1, op=Reshape) (name=gradients/up_conv_1/conv2d/BiasAdd_grad/BiasAddGrad, op=BiasAddGrad) (name=gradients/up_conv_1/conv2d/Conv2D_grad/Conv2DBackpropFilter, op=Conv2DBackpropFilter) (name=gradients/up_conv_1/crop_and_concat/concat_grad/Shape, op=Shape) (name=gradients/up_conv_1/add_grad/Reshape_1, op=Reshape) (name=gradients/up_conv_1/deconv2d/conv2d_transpose_grad/Conv2DBackpropFilter, op=Conv2DBackpropFilter) (name=gradients/down_conv_2/conv2d_1/dropout/mul_grad/Reshape_1, op=Reshape) (name=gradients/down_conv_2/conv2d_1/dropout/div_grad/Reshape_1, op=Reshape) (name=gradients/down_conv_2/conv2d_1/BiasAdd_grad/BiasAddGrad, op=BiasAddGrad) (name=gradients/down_conv_2/conv2d_1/Conv2D_grad/Conv2DBackpropFilter, op=Conv2DBackpropFilter) (name=gradients/down_conv_2/conv2d/dropout/mul_grad/Reshape_1, op=Reshape) (name=gradients/down_conv_2/conv2d/dropout/div_grad/Reshape_1, op=Reshape) (name=gradients/down_conv_2/conv2d/BiasAdd_grad/BiasAddGrad, op=BiasAddGrad) (name=gradients/down_conv_2/conv2d/Conv2D_grad/Conv2DBackpropFilter, op=Conv2DBackpropFilter) (name=gradients/down_conv_1/conv2d_1/dropout/mul_grad/Reshape_1, op=Reshape) (name=gradients/down_conv_1/conv2d_1/dropout/div_grad/Reshape_1, op=Reshape) (name=gradients/down_conv_1/conv2d_1/BiasAdd_grad/BiasAddGrad, op=BiasAddGrad) (name=gradients/down_conv_1/conv2d_1/Conv2D_grad/Conv2DBackpropFilter, op=Conv2DBackpropFilter) (name=gradients/down_conv_1/conv2d/dropout/mul_grad/Reshape_1, op=Reshape) (name=gradients/down_conv_1/conv2d/dropout/div_grad/Reshape_1, op=Reshape) (name=gradients/down_conv_1/conv2d/BiasAdd_grad/BiasAddGrad, op=BiasAddGrad) (name=gradients/down_conv_1/conv2d/Conv2D_grad/Conv2DBackpropFilter, op=Conv2DBackpropFilter) (name=gradients/down_conv_0/conv2d_1/dropout/mul_grad/Reshape_1, op=Reshape) (name=gradients/down_conv_0/conv2d_1/dropout/div_grad/Reshape_1, op=Reshape) (name=gradients/down_conv_0/conv2d_1/BiasAdd_grad/BiasAddGrad, op=BiasAddGrad) (name=gradients/down_conv_0/conv2d_1/Conv2D_grad/Conv2DBackpropFilter, op=Conv2DBackpropFilter) (name=gradients/down_conv_0/conv2d/dropout/mul_grad/Reshape_1, op=Reshape) (name=gradients/down_conv_0/conv2d/dropout/div_grad/Reshape_1, op=Reshape) (name=gradients/down_conv_0/conv2d/BiasAdd_grad/BiasAddGrad, op=BiasAddGrad) (name=gradients/down_conv_0/conv2d/Conv2D_grad/Conv2DBackpropInput, op=Conv2DBackpropInput) (name=gradients/down_conv_0/conv2d/Conv2D_grad/Conv2DBackpropFilter, op=Conv2DBackpropFilter) (name=cross_entropy/Neg, op=Neg) (name=results/Mean, op=Mean) (name=save/control_dependency, op=Identity) (name=save_1/control_dependency, op=Identity)
2019-11-08 15:06:54.139399: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodedown_conv_0/w1
2019-11-08 15:06:54.139468: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodedown_conv_0/w2
2019-11-08 15:06:54.139484: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodedown_conv_0/b1
2019-11-08 15:06:54.139496: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodedown_conv_0/b2
2019-11-08 15:06:54.139515: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodedown_conv_1/w1
2019-11-08 15:06:54.139529: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodedown_conv_1/w2
2019-11-08 15:06:54.139540: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodedown_conv_1/b1
2019-11-08 15:06:54.139552: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodedown_conv_1/b2
2019-11-08 15:06:54.139569: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodedown_conv_2/w1
2019-11-08 15:06:54.139582: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodedown_conv_2/w2
2019-11-08 15:06:54.139594: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodedown_conv_2/b1
2019-11-08 15:06:54.139605: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodedown_conv_2/b2
2019-11-08 15:06:54.139622: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodeup_conv_1/wd
2019-11-08 15:06:54.139634: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodeup_conv_1/bd
2019-11-08 15:06:54.139668: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodeup_conv_1/w1
2019-11-08 15:06:54.139682: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodeup_conv_1/w2
2019-11-08 15:06:54.139694: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodeup_conv_1/b1
2019-11-08 15:06:54.139706: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodeup_conv_1/b2
2019-11-08 15:06:54.139724: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodeup_conv_0/wd
2019-11-08 15:06:54.139736: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodeup_conv_0/bd
2019-11-08 15:06:54.139769: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodeup_conv_0/w1
2019-11-08 15:06:54.139784: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodeup_conv_0/w2
2019-11-08 15:06:54.139796: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodeup_conv_0/b1
2019-11-08 15:06:54.139807: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodeup_conv_0/b2
2019-11-08 15:06:54.139824: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodeoutput_map/weight
2019-11-08 15:06:54.139836: W tensorflow/tools/graph_transforms/summarize_graph_main.cc:225] Decoding Tensor failed for nodeoutput_map/bias
Found 1631 (1.63k) const parameters, 0 (0) variable parameters, and 80 control_edges
6 nodes assigned to device '/device:CPU:0'Op types used: 457 Const, 105 Shape, 92 Reshape, 88 Mul, 78 Assign, 57 RealDiv, 51 StridedSlice, 49 Sum, 40 Pack, 37 Sub, 35 Add, 28 Identity, 26 VariableV2, 23 BroadcastGradientArgs, 23 Slice, 16 Max, 14 Min, 14 Transpose, 14 ImageSummary, 13 ReluGrad, 13 Relu, 13 ShapeN, 13 TruncatedNormal, 13 Conv2D, 13 Conv2DBackpropInput, 13 Conv2DBackpropFilter, 12 Neg, 11 BiasAdd, 11 BiasAddGrad, 10 RandomUniform, 10 Floor, 7 FloorDiv, 6 ConcatV2, 6 HistogramSummary, 3 Mean, 3 NoOp, 3 Placeholder, 2 RestoreV2, 2 SaveV2, 2 AddN, 2 Pad, 2 Prod, 2 Maximum, 2 MaxPoolGrad, 2 MaxPool, 2 ArgMax, 2 Cast, 2 FloorMod, 2 ConcatOffset, 2 ExpandDims, 2 Exp, 1 ZerosLike, 1 Tile, 1 Equal, 1 SoftmaxCrossEntropyWithLogits, 1 Fill, 1 Log, 1 LogSoftmax, 1 Minimum
To use with tensorflow/tools/benchmark:benchmark_model try these arguments:
bazel run tensorflow/tools/benchmark:benchmark_model -- --graph=/home/users/user/tf_unet/tmp/tmp/my_model.pb --show_flops --input_layer=x,y,dropout_probability,down_conv_0/w1,down_conv_0/w2,down_conv_0/b1,down_conv_0/b2,down_conv_1/w1,down_conv_1/w2,down_conv_1/b1,down_conv_1/b2,down_conv_2/w1,down_conv_2/w2,down_conv_2/b1,down_conv_2/b2,up_conv_1/wd,up_conv_1/bd,up_conv_1/w1,up_conv_1/w2,up_conv_1/b1,up_conv_1/b2,up_conv_0/wd,up_conv_0/bd,up_conv_0/w1,up_conv_0/w2,up_conv_0/b1,up_conv_0/b2,output_map/weight,output_map/bias --input_layer_type=float,float,float,float,float,float,float,float,float,float,float,float,float,float,float,float,float,float,float,float,float,float,float,float,float,float,float,float,float --input_layer_shape=-1,-1,-1,1:-1,-1,-1,2::3,3,1,32:3,3,32,32:32:32:3,3,32,64:3,3,64,64:64:64:3,3,64,128:3,3,128,128:128:128:2,2,64,128:64:3,3,128,64:3,3,64,64:64:64:2,2,32,64:32:3,3,64,32:3,3,32,32:32:32:1,1,32,2:2 --output_layer=preprocessing/strided_slice_2,summaries/summary_conv_00_01,summaries/summary_conv_00_02,summaries/summary_conv_01_01,summaries/summary_conv_01_02,summaries/summary_conv_02_01,summaries/summary_conv_02_02,summaries/summary_conv_03_01,summaries/summary_conv_03_02,summaries/summary_conv_04_01,summaries/summary_conv_04_02,summaries/summary_pool_00,summaries/summary_pool_01,summaries/summary_deconv_concat_01,summaries/summary_deconv_concat_00,summaries/dw_convolution_00/activations,summaries/dw_convolution_01/activations,summaries/dw_convolution_02/activations,summaries/up_convolution_1/activations,summaries/up_convolution_0/activations,summaries/up_convolution_out/activations,cost/Reshape,cost/Reshape_1,cost/Mean,gradients/cost/Mul_1_grad/Reshape_1,gradients/zeros_like,gradients/cost/softmax_cross_entropy_with_logits_grad/mul_1,gradients/output_map/conv2d/BiasAdd_grad/BiasAddGrad,gradients/output_map/conv2d/Conv2D_grad/Conv2DBackpropFilter,gradients/up_conv_0/conv2d_1/dropout/mul_grad/Reshape_1,gradients/up_conv_0/conv2d_1/dropout/div_grad/Reshape_1,gradients/up_conv_0/conv2d_1/BiasAdd_grad/BiasAddGrad,gradients/up_conv_0/conv2d_1/Conv2D_grad/Conv2DBackpropFilter,gradients/up_conv_0/conv2d/dropout/mul_grad/Reshape_1,gradients/up_conv_0/conv2d/dropout/div_grad/Reshape_1,gradients/up_conv_0/conv2d/BiasAdd_grad/BiasAddGrad,gradients/up_conv_0/conv2d/Conv2D_grad/Conv2DBackpropFilter,gradients/up_conv_0/crop_and_concat/concat_grad/Shape,gradients/up_conv_0/add_grad/Reshape_1,gradients/up_conv_0/deconv2d/conv2d_transpose_grad/Conv2DBackpropFilter,gradients/up_conv_1/conv2d_1/dropout/mul_grad/Reshape_1,gradients/up_conv_1/conv2d_1/dropout/div_grad/Reshape_1,gradients/up_conv_1/conv2d_1/BiasAdd_grad/BiasAddGrad,gradients/up_conv_1/conv2d_1/Conv2D_grad/Conv2DBackpropFilter,gradients/up_conv_1/conv2d/dropout/mul_grad/Reshape_1,gradients/up_conv_1/conv2d/dropout/div_grad/Reshape_1,gradients/up_conv_1/conv2d/BiasAdd_grad/BiasAddGrad,gradients/up_conv_1/conv2d/Conv2D_grad/Conv2DBackpropFilter,gradients/up_conv_1/crop_and_concat/concat_grad/Shape,gradients/up_conv_1/add_grad/Reshape_1,gradients/up_conv_1/deconv2d/conv2d_transpose_grad/Conv2DBackpropFilter,gradients/down_conv_2/conv2d_1/dropout/mul_grad/Reshape_1,gradients/down_conv_2/conv2d_1/dropout/div_grad/Reshape_1,gradients/down_conv_2/conv2d_1/BiasAdd_grad/BiasAddGrad,gradients/down_conv_2/conv2d_1/Conv2D_grad/Conv2DBackpropFilter,gradients/down_conv_2/conv2d/dropout/mul_grad/Reshape_1,gradients/down_conv_2/conv2d/dropout/div_grad/Reshape_1,gradients/down_conv_2/conv2d/BiasAdd_grad/BiasAddGrad,gradients/down_conv_2/conv2d/Conv2D_grad/Conv2DBackpropFilter,gradients/down_conv_1/conv2d_1/dropout/mul_grad/Reshape_1,gradients/down_conv_1/conv2d_1/dropout/div_grad/Reshape_1,gradients/down_conv_1/conv2d_1/BiasAdd_grad/BiasAddGrad,gradients/down_conv_1/conv2d_1/Conv2D_grad/Conv2DBackpropFilter,gradients/down_conv_1/conv2d/dropout/mul_grad/Reshape_1,gradients/down_conv_1/conv2d/dropout/div_grad/Reshape_1,gradients/down_conv_1/conv2d/BiasAdd_grad/BiasAddGrad,gradients/down_conv_1/conv2d/Conv2D_grad/Conv2DBackpropFilter,gradients/down_conv_0/conv2d_1/dropout/mul_grad/Reshape_1,gradients/down_conv_0/conv2d_1/dropout/div_grad/Reshape_1,gradients/down_conv_0/conv2d_1/BiasAdd_grad/BiasAddGrad,gradients/down_conv_0/conv2d_1/Conv2D_grad/Conv2DBackpropFilter,gradients/down_conv_0/conv2d/dropout/mul_grad/Reshape_1,gradients/down_conv_0/conv2d/dropout/div_grad/Reshape_1,gradients/down_conv_0/conv2d/BiasAdd_grad/BiasAddGrad,gradients/down_conv_0/conv2d/Conv2D_grad/Conv2DBackpropInput,gradients/down_conv_0/conv2d/Conv2D_grad/Conv2DBackpropFilter,cross_entropy/Neg,results/Mean,save/control_dependency,save_1/control_dependency

[jakeret]

you could use tensorboard to visualize the graph of the network.
The input placeholder is defined here and the output here