fix op benchmark OOM issue (#29794)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/29794
Before this diff, all tests of an operator are created at once before testing. Once an operator is benchmarked, the same process will move to the next operator and so on. The issue is that the number of tests of a single operator could be > 100 which can cause OOM issues. This diff avoids creating all the tests of an operator at once by using generators which creates/runs test one by one.
Test Plan:
```
buck run //caffe2/benchmarks/operator_benchmark:benchmark_all_quantized_test -- --iterations 1
# ----------------------------------------
# PyTorch/Caffe2 Operator Micro-benchmarks
# ----------------------------------------
# Tag : short
# Benchmarking PyTorch: relu
# Mode: Eager
# Name: relu_dims(3,4,5)_contigFalse_inplaceFalse_dtypetorch.quint8
# Input: dims: (3, 4, 5), contig: False, inplace: False, dtype: torch.quint8
Forward Execution Time (us) : 52.493
# Benchmarking PyTorch: relu
# Mode: Eager
# Name: relu_dims(3,4,5)_contigFalse_inplaceFalse_dtypetorch.qint8
# Input: dims: (3, 4, 5), contig: False, inplace: False, dtype: torch.qint8
Forward Execution Time (us) : 44.945
...
Reviewed By: hl475
Differential Revision: D18500103
fbshipit-source-id: 747c0ad0d302177da04da36e112c67f154115b6e
