pytorch

a1343394 - allow loading model from a path in torchbench (#89028)

allow loading model from a path in torchbench (#89028) Sometimes it's really convenient to run simple models thru the torchbench.py script rather than those from pytorch/benchmark. This PR add the ability to run any model from a specified path by overloading the --only argument. This PR is split out from #88904 Here is the usage: Specify the path and class name of the model in format like: --only=path:<MODEL_FILE_PATH>,class:<CLASS_NAME> Due to the fact that dynamo changes current working directory, the path should be an absolute path. The class should have a method get_example_inputs to return the inputs for the model. An example looks like ``` class LinearModel(nn.Module): def __init__(self): super().__init__() self.linear = nn.Linear(10, 10) def forward(self, x): return self.linear(x) def get_example_inputs(self): return (torch.randn(2, 10),) ``` Test command: ``` # python benchmarks/dynamo/torchbench.py --performance --only=path:/pytorch/myscripts/model_collection.py,class:LinearModel --backend=eager WARNING:common:torch.cuda.is_available() == False, using CPU cpu eval LinearModel 0.824x p=0.00 ``` Content of model_collection.py ``` from torch import nn import torch class LinearModel(nn.Module): """ AotAutogradStrategy.compile_fn ignore graph with at most 1 call nodes. Make sure this model calls 2 linear layers to avoid being skipped. """ def __init__(self, nlayer=2): super().__init__() layers = [] for _ in range(nlayer): layers.append(nn.Linear(10, 10)) self.layers = nn.Sequential(*layers) def forward(self, x): return self.layers(x) def get_example_inputs(self): return (torch.randn(2, 10),) ``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/89028 Approved by: https://github.com/jansel