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On this page
  • What models can be imported into SameDiff
  • Finding the model input/outputs and running inference
  • Import Validation
  • Advanced: Node Skipping and Import Overrides
  • List of models known to work with SameDiff.
  • Operations Coverage

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  1. Samediff
  2. How To Guides

Importing Tensorflow

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Last updated 3 years ago

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What models can be imported into SameDiff

Currently SameDiff supports the import of TensorFlow frozen graphs through the various SameDiff.importFrozenTF methods. TensorFlow documentation on frozen models can be found .

import org.nd4j.autodiff.SameDiff.SameDiff;
SameDiff sd = SameDiff.importFrozenTF(modelFile);

Finding the model input/outputs and running inference

After you import the TensorFlow model there are 2 ways to find the inputs and outputs. The first method is to look at the output of

 sd.summary();

Where the input variables are the output of no ops, and the output variables are the input of no ops. Another way to find the inputs is

List<String> inputs = sd.inputs();

To run inference use:

INDArray out = sd.batchOutput()
    .input(inputName, inputArray)
    .output(outputs)
    .execSingle();

For multiple outputs, use exec() instead of execSingle(), to return a Map<String,INDArray> of outputs instead. Alternatively, you can use methods such as SameDiff.output(Map<String, INDArray> placeholders, String... outputs) to get the same output.

Import Validation

Advanced: Node Skipping and Import Overrides

List of models known to work with SameDiff.

Operations Coverage

SameDiff’s TensorFlow import is still being developed, and does not yet have support for every single operation and datatype in TensorFlow. Almost all of the common/standard operations are importable and tested, however - including almost everything in the tf, tf.math, tf.layers, tf.losses, tf.bitwise and tf.nn namespaces. The majority of existing pretrained models out there should be importable into SameDiff.

We have a TensorFlow graph analyzing utility which will report any missing operations (operations that still need to be implemented)

It is possible to remove nodes from the network. For example TensorFlow 1.x models can have hard coded dropout layers. See the for an example.

If you run into an operation that can’t be imported, feel free to .

here
here
BERT Graph test
PorV-RNN
alexnet
cifar10_gan_85
deeplab_mobilenetv2_coco_voc_trainval
densenet_2018_04_27
inception_resnet_v2_2018_04_27
inception_v4_2018_04_27
labels
mobilenet_v1_0.5_128
mobilenet_v2_1.0_224
nasnet_mobile_2018_04_27
resnetv2_imagenet_frozen_graph
squeezenet_2018_04_27
temperature_bidirectional_63
temperature_stacked_63
text_gen_81
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