Samediff import doc (#8301)
* first commit. Signed-off-by: Robert Altena <Rob@Ra-ai.com> * fix review items. Signed-off-by: Robert Altena <Rob@Ra-ai.com> * update reviewed items. Signed-off-by: Robert Altena <Rob@Ra-ai.com>master
Robert Altena
Alex Black
parent
0107fb10ab
commit
4cb281c01f
|
|
@ -1 +1,71 @@
|
|||
# Getting started: importing TensorFlow and ONNX models into SameDiff
|
||||
---
|
||||
title: Getting started: importing TensorFlow models into SameDiff
|
||||
short_title: Model import
|
||||
description: importing TensorFlow models into SameDiff
|
||||
category: SameDiff
|
||||
weight: 3
|
||||
---
|
||||
|
||||
# Getting started: importing TensorFlow models into SameDiff
|
||||
|
||||
## 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 [here](https://www.TensorFlow.org/guide/saved_model#the_savedmodel_format_on_disk).
|
||||
|
||||
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(inputs, 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.
|
||||
We have a TensorFlow graph analyzing utility which will report any missing operations (operations that still need to be implemented) [here](https://github.com/eclipse/deeplearning4j/blob/master/nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/imports/TensorFlow/TensorFlowImportValidator.java)
|
||||
|
||||
## Advanced: Node Skipping and Import Overrides
|
||||
It is possible to remove nodes from the network. For example TensorFlow 1.x models can have hard coded dropout layers.
|
||||
See the [BERT Graph test](https://github.com/eclipse/deeplearning4j/blob/master/nd4j/nd4j-backends/nd4j-tests/src/test/java/org/nd4j/imports/TFGraphs/BERTGraphTest.java#L114-L150) for an example.
|
||||
|
||||
## List of models known to work with SameDiff.
|
||||
|
||||
- [PorV-RNN](https://deeplearning4jblob.blob.core.windows.net/testresources/PorV-RNN_frozenmodel.pb)
|
||||
- [alexnet](https://deeplearning4jblob.blob.core.windows.net/testresources/alexnet_frozenmodel.pb)
|
||||
- [cifar10_gan_85](https://deeplearning4jblob.blob.core.windows.net/testresources/cifar10_gan_85_frozenmodel.pb)
|
||||
- [deeplab_mobilenetv2_coco_voc_trainval](http://download.tensorflow.org/models/deeplabv3_mnv2_pascal_trainval_2018_01_29.tar.gz)
|
||||
- [densenet_2018_04_27](https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/densenet_2018_04_27.tgz)
|
||||
- [inception_resnet_v2_2018_04_27](https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/inception_resnet_v2_2018_04_27.tgz)
|
||||
- [inception_v4_2018_04_27](https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/inception_v4_2018_04_27.tgz)
|
||||
- [labels](https://github.com/KonduitAI/dl4j-test-resources/tree/master/src/main/resources/tf_graphs/zoo_models/labels)
|
||||
- [mobilenet_v1_0.5_128](http://download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_0.5_128.tgz)
|
||||
- [mobilenet_v2_1.0_224](http://download.tensorflow.org/models/tflite_11_05_08/mobilenet_v2_1.0_224.tgz)
|
||||
- [nasnet_mobile_2018_04_27](https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/nasnet_mobile_2018_04_27.tgz)
|
||||
- [resnetv2_imagenet_frozen_graph](http://download.tensorflow.org/models/official/resnetv2_imagenet_frozen_graph.pb)
|
||||
- [squeezenet_2018_04_27](https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/squeezenet_2018_04_27.tgz)
|
||||
- [temperature_bidirectional_63](https://deeplearning4jblob.blob.core.windows.net/testresources/temperature_bidirectional_63_frozenmodel.pb)
|
||||
- [temperature_stacked_63](https://deeplearning4jblob.blob.core.windows.net/testresources/temperature_stacked_63_frozenmodel.pb)
|
||||
- [text_gen_81](https://deeplearning4jblob.blob.core.windows.net/testresources/text_gen_81_frozenmodel.pb)
|
||||
|
||||
## 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.
|
||||
|
||||
If you run into an operation that can't be imported, feel free to [open an issue](https://github.com/eclipse/deeplearning4j/issues).
|
||||
Loading…
Reference in New Issue