This document has instructions for running ResNet101* FP32 inference using Intel® Optimization for TensorFlow*.
Download and preprocess the ImageNet dataset using the instructions here. After running the conversion script you should have a directory with the ImageNet dataset in the TF records format.
DATASET_DIR to point to this directory when running ResNet101*.
Quick Start Scripts
||Runs online inference (batch_size=1).|
||Runs batch inference (batch_size=128).|
||Measures the model accuracy (batch_size=100).|
To run on bare metal, the following prerequisites must be installed in your environment:
- Python* 3
- Intel® Optimization for TensorFlow*
Download and untar the model package. Set environment variables for the path to your
DATASET_DIR and an
OUTPUT_DIR where log files will be written, then run a quick start script.
DATASET_DIR=<path to the dataset> OUTPUT_DIR=<directory where log files will be written> wget https://storage.googleapis.com/intel-optimized-tensorflow/models/v2_3_0/resnet101-fp32-inference.tar.gz tar -xzf resnet101-fp32-inference.tar.gz cd resnet101-fp32-inference quickstart/<script name>.sh
Documentation and Sources
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Product and Performance Information
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