Skip to content

Latest commit

 

History

History
33 lines (23 loc) · 2.04 KB

README.md

File metadata and controls

33 lines (23 loc) · 2.04 KB
Raw

ResNet50 Demo

Introduction

ResNet50 is a deep convolutional neural network architecture with 50 layers, designed to enable training of very deep networks by using residual learning to mitigate the vanishing gradient problem.

This demo is a work in progress.

Details

  • The entry point to the Metal ResNet model is ResNet in ttnn_functional_resnet50_new_conv_api.py.
  • The model picks up certain configs and weights from TorchVision pretrained model. We have used torchvision.models.ResNet50_Weights.IMAGENET1K_V1 version from TorchVision as our reference.
  • Our ImageProcessor on the other hand is based on microsoft/resnet-50 from huggingface.

Performance

Single Device

Device Performance

  • To obtain device performance, run WH_ARCH_YAML=wormhole_b0_80_arch_eth_dispatch.yaml ./tt_metal/tools/profiler/profile_this.py -c "pytest models/demos/ttnn_resnet/tests/test_ttnn_resnet50_performant.py::test_run_resnet50_inference[16z-act_dtype0-weight_dtype0-math_fidelity0-device_params0]"
  • This will generate a CSV report under <this repo dir>/generated/profiler/reports/ops/<report name>. The report file name is logged in the run output.

End-to-End Performance

  • For end-to-end performance, run WH_ARCH_YAML=wormhole_b0_80_arch_eth_dispatch.yaml pytest models/demos/ttnn_resnet/tests/test_perf_ttnn_resnet.py::test_perf_trace_2cqs_bare_metal[16-0.004-25-device_params0].
  • This will generate a CSV with the timings and throughputs.
  • Expected end-to-end perf: For batch = 16, it is about 4300 fps currently. This may vary machine to machine.

T3000

End-to-End Performance

  • For end-to-end performance, run WH_ARCH_YAML=wormhole_b0_80_arch_eth_dispatch.yaml pytest models/demos/ttnn_resnet/tests/multi_device/test_perf_ttnn_resnet.py::test_perf_trace_2cqs_t3000[wormhole_b0-True-16-True-0.0043-60-device_params0].
  • This will generate a CSV with the timings and throughputs.
  • Expected end-to-end perf: For batch = 16 per device, or batch 128 in total, it is about 31,700 fps currently. This may vary machine to machine.