[dynamo] equivalent conditions get different optimized code
Labels: triaged, oncall: pt2, module: dynamo

### 🐛 Describe the bug

When I run the following example code, I got three fx graphs. One is to get the result of `ta.sum() < 0`, the other two are to get  the result of `3 * ta + tb` and `ta + 3 * tb` respectively. When I change the condition to `0 > ta.sum()`, dynamo fails to get a single fx graph and keeps the original bytecode.
```
import torch
import torch._dynamo as torchdynamo
import logging

torchdynamo.config.log_level = logging.INFO
torchdynamo.config.output_code = True


@torchdynamo.optimize("eager")
def toy_example(ta, tb):
    if ta.sum() < 0:
        return ta + 3 * tb
    else:
        return 3 * ta + tb
    
x = torch.randn(4, 4)
y = torch.randn(4, 4)
 
toy_example(x, y)
```
The output bytecode when the condition is `ta.sum() < 0`.
```
  9           0 LOAD_GLOBAL              1 (__compiled_fn_0)
              2 LOAD_FAST                0 (ta)
              4 CALL_FUNCTION            1
              6 UNPACK_SEQUENCE          1
              8 POP_JUMP_IF_FALSE       20
             10 LOAD_GLOBAL              2 (__resume_at_12_1)
             12 LOAD_FAST                0 (ta)
             14 LOAD_FAST                1 (tb)
             16 CALL_FUNCTION            2
             18 RETURN_VALUE
        >>   20 LOAD_GLOBAL              3 (__resume_at_24_2)
             22 LOAD_FAST                0 (ta)
             24 LOAD_FAST                1 (tb)
             26 CALL_FUNCTION            2
             28 RETURN_VALUE
```
The output bytecode when the condition is `0 > ta.sum()`.
```
 11           0 LOAD_CONST               1 (0)
              2 LOAD_FAST                0 (ta)
              4 LOAD_ATTR                0 (sum)
              6 CALL_FUNCTION            0
              8 COMPARE_OP               4 (>)
             10 POP_JUMP_IF_FALSE       24

 12          12 LOAD_FAST                0 (ta)
             14 LOAD_CONST               2 (3)
             16 LOAD_FAST                1 (tb)
             18 BINARY_MULTIPLY
             20 BINARY_ADD
             22 RETURN_VALUE

 14     >>   24 LOAD_CONST               2 (3)
             26 LOAD_FAST                0 (ta)
             28 BINARY_MULTIPLY
             30 LOAD_FAST                1 (tb)
             32 BINARY_ADD
             34 RETURN_VALUE
```
I wonder whether it is a bug or feature, its behavior just changes though the two conditions are equivalent.

### Versions

Collecting environment information...
PyTorch version: 2.0.0.dev20230207+cu118
Is debug build: False
CUDA used to build PyTorch: 11.8
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.5 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
Clang version: Could not collect
CMake version: version 3.25.0
Libc version: glibc-2.31

Python version: 3.9.16 (main, Jan 11 2023, 16:05:54)  [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-58-generic-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: 11.8.89
GPU models and configuration: 
GPU 0: NVIDIA A100 80GB PCIe
GPU 1: NVIDIA A100 80GB PCIe
GPU 2: NVIDIA A100 80GB PCIe
GPU 3: NVIDIA A100 80GB PCIe
GPU 4: NVIDIA A100 80GB PCIe
GPU 5: NVIDIA A100 80GB PCIe
GPU 6: NVIDIA A100 80GB PCIe
GPU 7: NVIDIA A100 80GB PCIe

Nvidia driver version: 520.61.05
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] numpy==1.24.1
[pip3] pytorch-triton==2.0.0+0d7e753227
[pip3] torch==2.0.0.dev20230207+cu118
[pip3] torchaudio==2.0.0.dev20230205+cu118
[pip3] torchdynamo==1.14.0.dev0
[pip3] torchtriton==2.0.0+f16138d447
[pip3] torchvision==0.15.0.dev20230205+cu118
[conda] numpy                     1.24.1                   pypi_0    pypi
[conda] pytorch-triton            2.0.0+0d7e753227          pypi_0    pypi
[conda] torch                     2.0.0.dev20230207+cu118          pypi_0    pypi
[conda] torchaudio                2.0.0.dev20230205+cu118          pypi_0    pypi
[conda] torchdynamo               1.14.0.dev0              pypi_0    pypi
[conda] torchtriton               2.0.0+f16138d447          pypi_0    pypi
[conda] torchvision               0.15.0.dev20230205+cu118          pypi_0    pypi

cc @ezyang @soumith @msaroufim @wconstab @ngimel @bdhirsh @voznesenskym @yanboliang @penguinwu @anijain2305 @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @Xia-Weiwen @wenzhe-nrv @jiayisunx @desertfire