Add doctr recognition and detection models (#1315)
Summary:
This PR adds the [doctr](https://github.com/mindee/doctr) recognition and detection models to TorchBench.
This is an inference only model so no train test is added.
Pull Request resolved: https://github.com/pytorch/benchmark/pull/1315
Test Plan:
```
$ python run.py doctr_det_predictor -d cuda
Running eval method from doctr_det_predictor on cuda in eager mode with input batch size 4.
GPU Time: 47.578 milliseconds
CPU Total Wall Time: 47.624 milliseconds
$ python run.py doctr_det_predictor -d cuda --torchdynamo eager
Running eval method from doctr_det_predictor on cuda in eager mode with input batch size 4.
GPU Time: 53.928 milliseconds
CPU Total Wall Time: 53.975 milliseconds
Correctness: True
$ python run.py doctr_det_predictor -d cuda --torchdynamo inductor
self.output.compile_subgraph(self)
File "/data/home/xzhao9/cluster/miniconda3/envs/py310/lib/python3.10/site-packages/torch/_dynamo/output_graph.py", line 352, in compile_subgraph
self.compile_and_call_fx_graph(tx, pass2.graph_output_vars(), root)
File "/data/home/xzhao9/cluster/miniconda3/envs/py310/lib/python3.10/site-packages/torch/_dynamo/output_graph.py", line 397, in compile_and_call_fx_graph
compiled_fn = self.call_user_compiler(gm)
File "/data/home/xzhao9/cluster/miniconda3/envs/py310/lib/python3.10/site-packages/torch/_dynamo/output_graph.py", line 437, in call_user_compiler
raise BackendCompilerFailed(self.compiler_fn, e) from e
torch._dynamo.exc.BackendCompilerFailed: compile_fx raised RuntimeError: Inference tensors do not track version counter.
While executing %self_conv1 : [#users=1] = call_module[target=self_conv1](args = (%x,), kwargs = {})
Original traceback:
Module stack: {'self_conv1': <class 'torch.nn.modules.conv.Conv2d'>}
File "/data/home/xzhao9/cluster/miniconda3/envs/py310/lib/python3.10/site-packages/torchvision/models/_utils.py", line 69, in <graph break in forward>
x = module(x)
```
```
$ python run.py doctr_reco_predictor -d cuda
Running eval method from doctr_reco_predictor on cuda in eager mode with input batch size 64.
GPU Time: 8.284 milliseconds
CPU Total Wall Time: 8.312 milliseconds
$ python run.py doctr_reco_predictor -d cuda --torchdynamo eager
Running eval method from doctr_reco_predictor on cuda in eager mode with input batch size 64.
GPU Time: 8.334 milliseconds
CPU Total Wall Time: 8.373 milliseconds
Correctness: True
# torchinductor doesn't work on this model
$ python run.py doctr_reco_predictor -d cuda --torchdynamo inductor
File "/data/home/xzhao9/cluster/miniconda3/envs/py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 1447, in run
super().run()
File "/data/home/xzhao9/cluster/miniconda3/envs/py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 349, in run
and self.step()
File "/data/home/xzhao9/cluster/miniconda3/envs/py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 322, in step
getattr(self, inst.opname)(inst)
File "/data/home/xzhao9/cluster/miniconda3/envs/py310/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 196, in wrapper
self.output.compile_subgraph(self, reason=reason)
File "/data/home/xzhao9/cluster/miniconda3/envs/py310/lib/python3.10/site-packages/torch/_dynamo/output_graph.py", line 352, in compile_subgraph
self.compile_and_call_fx_graph(tx, pass2.graph_output_vars(), root)
File "/data/home/xzhao9/cluster/miniconda3/envs/py310/lib/python3.10/site-packages/torch/_dynamo/output_graph.py", line 397, in compile_and_call_fx_graph
compiled_fn = self.call_user_compiler(gm)
File "/data/home/xzhao9/cluster/miniconda3/envs/py310/lib/python3.10/site-packages/torch/_dynamo/output_graph.py", line 437, in call_user_compiler
raise BackendCompilerFailed(self.compiler_fn, e) from e
torch._dynamo.exc.BackendCompilerFailed: compile_fx raised RuntimeError: Inference tensors do not track version counter.
```
Fixes https://github.com/pytorch/benchmark/issues/1305
Reviewed By: FindHao
Differential Revision: D41593159
Pulled By: xuzhao9
fbshipit-source-id: 5c186fbd40fdf47ab182d5df278af84c0e824ac9
