How do I compare inference performance between popular frameworks like ONNX TensorFlow and PyTorch

Question

Can you tell me how I compare inference performance between popular frameworks like ONNX, TensorFlow, and PyTorch?

Answer 1

TensorFlow, and PyTorch involves measuring latency, throughput, and memory usage on different hardware. Use tools like time, torch.cuda.Event, or tf.function for precise measurements.

Here is the code snippet you can refer to:

In the above code, we are using the following key points:

• Latency Measurement: Records time taken per inference for real-time comparison.
• Cross-Framework Benchmarking: Tests ONNX, TensorFlow, and PyTorch on the same inputs.
• Hardware Optimization: Helps decide the best framework based on performance on CPU/GPU.
• Model Compatibility: Assesses how different formats impact execution speed.
• Scalability Insights: Determines which framework scales better for deployment scenarios.

Hence, by referring to the above, you can compare inference performance between popular frameworks like ONNX TensorFlow and PyTorch.