This document has instructions to run a WaveNet FP32 inference using Intel® Optimizations for TensorFlow*.
Quick Start Scripts
||Runs inference with a pretrained model|
To run on bare metal, the following prerequisites must be installed in your environment:
- Python* 3
- Clone the tensorflow-wavenet repo and get pull request #352 for the CPU optimizations. The path to the cloned repo will be passed as the model source directory when running the launch script.
git clone https://github.com/ibab/tensorflow-wavenet.git cd tensorflow-wavenet/ git fetch origin pull/352/head:cpu_optimized git checkout cpu_optimized
After installing the prerequisites, download and untar the model package. Set environment variables for the path to your
TF_WAVENET_DIR and an
OUTPUT_DIR where log files will be written, then run a quickstart script.
TF_WAVENET_DIR=<tensorflow-wavenet directory> OUTPUT_DIR=<directory where log files will be written> wget https://storage.googleapis.com/intel-optimized-tensorflow/models/v2_3_0/wavenet-fp32-inference.tar.gz tar -xzf wavenet-fp32-inference.tar.gz cd wavenet-fp32-inference quickstart/fp32_inference.sh
Documentation and Sources
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Product and Performance Information
Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.