https://github.com/mlperf/training/tree/master/image_classification
https://github.com/tensorflow/models/tree/master/official/resnet
2019-01-08
<ul>
<li><strong>Application: </strong>Image Classification</li>
<li><strong>ML Task:</strong> ResNet-50</li>
<li><strong>Framework:</strong> tensorflow</li>
<li><strong>Training Information: </strong></li>
<li><strong>Quality:</strong> 76.53%</li>
<li><strong>Precision:</strong> fp32</li>
<li><strong>Is Quantized: </strong>no</li>
<li><strong>Is ONNX: </strong>no</li>
<li><strong>Dataset: </strong>http://www.image-net.org/challenges/LSVRC/2012/</li>
</ul>
To re-create the model, train https://github.com/mlperf/training/tree/master/image_classification or https://github.com/tensorflow/models/tree/master/official/resnet.
Make sure the data format is NHWC.
That re-export the model with batch_size=-1 (there is a script in https://github.com/mlperf/inference/cloud/image_classification/tools).
Create a frozen model tensorflow model from the exported saved_model.
https://doi.org/10.5281/zenodo.2535873
oai:zenodo.org:2535873
Zenodo
https://zenodo.org/communities/mlperf
https://doi.org/10.5281/zenodo.2535872
info:eu-repo/semantics/openAccess
Apache License 2.0
http://www.apache.org/licenses/LICENSE-2.0
Image Classification, resnet50, tensorflow, Inference, Imagenet2012, Inference, Pretrained Model
resnet50.tensorflow model
info:eu-repo/semantics/other