From 76d4920aa8b92bda5d8f0a4e14bd9d7e3759832e Mon Sep 17 00:00:00 2001 From: Huy Do Date: Mon, 3 Feb 2025 11:37:01 -0800 Subject: [PATCH] Update TorchBench commit to main (#145455) Summary: I'm adding sam2 to TorchBench https://github.com/pytorch/benchmark/issues/2566, so, as part of that, I'm updating PyTorch CI to use latest TorchBench commit. The corresponding change from TorchBench is https://github.com/pytorch/benchmark/pull/2584 The main thing to call out that the newer transformers added by https://github.com/pytorch/benchmark/pull/2488 is regressing several models. This needs to be investigated further, and I pin the version to unblock this change. * `hf_Roberta_base` a new model added by https://github.com/pytorch/benchmark/pull/2279, not sure why it fails accuracy on A10G, but it works fine on A100 * `speech_transformer` failures are pre-existing trunk failures, i.e. https://github.com/pytorch/pytorch/actions/runs/13040114684/job/36380989702#step:22:2408 X-link: https://github.com/pytorch/pytorch/pull/145455 Approved by: https://github.com/kit1980 Reviewed By: ZainRizvi Differential Revision: D69056903 fbshipit-source-id: 6b98c246b9dc8811257ec46d4821ba6ee3363dfe --- userbenchmark/dynamo/dynamobench/common.py | 2 +- userbenchmark/dynamo/dynamobench/torchbench.yaml | 3 ++- 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/userbenchmark/dynamo/dynamobench/common.py b/userbenchmark/dynamo/dynamobench/common.py index b3a17f4f66..b88d6ca8f5 100644 --- a/userbenchmark/dynamo/dynamobench/common.py +++ b/userbenchmark/dynamo/dynamobench/common.py @@ -189,7 +189,7 @@ class CI(NamedTuple): "stable_diffusion_text_encoder", "timm_efficientdet", "timm_nfnet", - "timm_regnet", + "timm_resnest", "timm_vision_transformer", "timm_vovnet", "vgg16", diff --git a/userbenchmark/dynamo/dynamobench/torchbench.yaml b/userbenchmark/dynamo/dynamobench/torchbench.yaml index 5647ab4900..3911b2c2a2 100644 --- a/userbenchmark/dynamo/dynamobench/torchbench.yaml +++ b/userbenchmark/dynamo/dynamobench/torchbench.yaml @@ -34,7 +34,6 @@ tolerance: - vgg16 - mobilenet_v3_large - nvidia_deeprecommender - - timm_efficientdet # These models need >1e-3 tolerance even_higher: @@ -42,6 +41,7 @@ tolerance: - tacotron2 - yolov3 - timm_efficientdet + - timm_efficientnet - squeezenet1_1 higher_fp16: @@ -66,6 +66,7 @@ tolerance: require_larger_multiplier_for_smaller_tensor: - yolov3 + - timm_efficientnet # These benchmarks took >600s on an i9-11900K CPU very_slow: &VERY_SLOW_MODELS