Error running Model Optimizer TensorFlow for inception-resnet-v1

Error running Model Optimizer TensorFlow for inception-resnet-v1

Hi,

I am trying to run mo tensorflow for a variant of inception-resnet-v1. The pb has gone through strip_unused_nodes and fold_batch_norms using tensorflow's transform_graph.

I tried two different command, but both has errors.

$ python3.5 modeloptimizer/scripts/model_optimizer.py --input_model=facenet_1.pb --input='Facenet/ResizeBilinear' --output='Facenet/embeddings' --transforms=' calc_shapes(input_types=float32; input_shapes=1,160,160,3)   create_ir(model_name=facenet; output_dir=facenet_mobile;input_format=RGB)'

List is:  [('calc_shapes', {'input_types': 'float32', 'input_shapes': '1,160,160,3'}), ('create_ir', {'output_dir': 'facenet_mobile', 'input_format': 'RGB', 'model_name': 'facenet'})]

Xml file is /host/opt/intel/computer_vision_sdk_2017.0.113/mo/ModelOptimizerForTensorFlow/config.xml

Run command is: /host/opt/intel/computer_vision_sdk_2017.0.113/mo/ModelOptimizerForTensorFlow/bin/new_transform_graph --in_graph=/tmp/graph_transphorm_calc_shapes_input.pb --out_graph=/tmp/graph_transphorm_calc_shapes_output.pb --inputs=Facenet/ResizeBilinear --outputs=Facenet/embeddings --transforms="calc_shapes(input_types=\"float32\", input_shapes=\"1,160,160,3\")"

2017-08-25 19:11:26.227361: I tensorflow/tools/graph_transforms/transform_graph.cc:262] Applying calc_shapes

2017-08-25 19:11:27.481185: E tensorflow/core/kernels/remote_fused_graph_execute_utils.cc:196] Error during inference: Invalid argument: Retval[9] does not have value

2017-08-25 19:11:27.596962: E tensorflow/tools/graph_transforms/transform_graph.cc:208] Retval[9] does not have value

 

 

 

$ python3.5 modeloptimizer/scripts/model_optimizer.py --input_model=facenet_1.pb --input='Facenet/ResizeBilinear' --output='Facenet/embeddings' --transforms='create_ir(model_name=facenet; output_dir=facenet_mobile;input_format=RGB)'List is:  [('create_ir', {'input_format': 'RGB', 'output_dir': 'facenet_mobile', 'model_name': 'facenet'})]

Xml file is /host/opt/intel/computer_vision_sdk_2017.0.113/mo/ModelOptimizerForTensorFlow/config.xml

Convert_to_IR transform uses FP32 precision as default

Convert_to_IR transform uses scale to be 1 as default

Convert_to_IR transform uses 1.0 norm_factor as default

Convert_to_IR transform uses 1 batch_size as default

Loading facenet model from file... Done (0.000 sec)

 

Deploying facenet model into IR format

Target precision : FP32

Batch size       : 1

Artifacts path   : facenet_mobile

 

Restoring shapes and sizes... Something went wrong. Please check the error and try again:

<class 'ValueError'>

Error: Shapes (3, 3, 3, 32) and () are not compatible

Failed to run transform  create_ir

Failed to run transforms!!!

 

Best regards,

Dong

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It looks like there is a problem in the graph (or the combination with the inputs/outputs) that causes calc_shapes transform to fail.

Did you view the graph in Tensorboard?

I'll appreciate it if you attach the pb file.

Thanks

Hello, 

I've also encountered this kind of issue. 

My Command is: 

... --input=X_Content --output=gradients/add_29_grad/tuple/control_dependency_1 --transforms="strip_unused_nodes(type=float;shape=4,256,256,3) remove_nodes(op=Identity) remove_nodes(op=CheckNumerics) fold_constants(ignore_errors=true) fold_batch_norms strip_unused_nodes(type=float; shape=4,256,256,3) remove_nodes(op=Identity) remove_nodes(op=CheckNumerics) fold_constants(ignore_errors=true) fold_batch_norms strip_unused_nodes(type=float; shape=4,256,256,3) remove_nodes(op=Identity) remove_nodes(op=CheckNumerics) fold_constants(ignore_errors=true) fold_batch_norms calc_shapes(input_types=float; input_shapes=4,256,256,3) create_ir(model_name=xxx_v1; output_dir=gen)"
 

And the result is: 

 Error during inference: Not found: FeedInputs: unable to find feed output X_Content
2017-11-28 08:03:09.574728: E tensorflow/tools/graph_transforms/transform_graph.cc:208] FeedInputs: unable to find feed output X_Content
2017-11-28 08:03:09.574789: E tensorflow/tools/graph_transforms/transform_graph.cc:209] usage: /home/rdds/workspace/intel/deeplearning_deploymenttoolkit_2017.1.0.4463/deployment_tools/model_optimizer/ModelOptimizerForTensorFlow/bin/new_transform_graph
Flags:
        --in_graph=""                           string  input graph file name
        --out_graph=""                          string  output graph file name
        --inputs=""                             string  inputs
        --outputs=""                            string  outputs
        --transforms=""                         string  list of transforms
        --output_as_text=false                  bool    whether to write the graph in text protobuf format

Transforms are:
add_default_attributes
backport_concatv2
backport_tensor_array_v3
calc_shapes
fold_batch_norms
fold_constants
fold_old_batch_norms
freeze_requantization_ranges
fuse_pad_and_conv
fuse_resize_and_conv
fuse_resize_pad_and_conv
insert_logging
merge_duplicate_nodes
obfuscate_names
quantize_nodes
quantize_weights
remove_attribute
remove_device
remove_nodes
rename_attribute
rename_op
rewrite_quantized_stripped_model_for_hexagon
round_weights
set_device
sort_by_execution_order
sparsify_gather
strip_unused_nodes

Failed to run Graph Transform
Failed to run transform  calc_shapes
Failed to run transforms!!!

Is there any method to solve this?

PS: The attached file is the .pb I've used.  

Thanks!

 

Attachments: 

AttachmentSize
Downloadapplication/rar Binary_Protobuf.rar145.18 MB

Also getting this problem using https://github.com/davidsandberg/facenet example - which is largely just inception resnet-v1.

PB file: https://drive.google.com/file/d/0B5MzpY9kBtDVZ2RpVDYwWmxoSUk (though I had to force the phase_train placeholder to be a constant as the model optimizer wasn't liking two inputs as far as I could tell)

 

Hi Kodonnel, 

According to the release notes, Model Optimizer for Tensorflow supports very limited list of topologies: VGG-16/19, Inception v1/v3/v4, ResNet v1 50/101/152. Facenet you shared has a lot of unsupported primitives like fifo_queue, phase_train placeholder, etc.

Best wishes, 

Anna 

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