[Feature Request] GPU Graph optimization for Flan-T5-Large

### Describe the feature request

Would it be possible to add GPU graph optimizations for Flan-T5-Large model?

### Describe scenario use case

Actually, after having exported the model to ONNX and trying to optimize it with `ORTOptimizer` as below:

```
from optimum.onnxruntime import ORTOptimizer
from optimum.onnxruntime.configuration import OptimizationConfig

onnx_path = Path("./flan-t5-large")

# Create ORTOptimizer
optimizer = ORTOptimizer.from_pretrained(ort_model)

# Define the optimization strategy by creating the appropriate configuration
optimization_config = OptimizationConfig(optimization_level=1,
optimize_for_gpu=True,
fp16=True
)

# Optimize the model
optimizer.optimize(save_dir=onnx_path, optimization_config=optimization_config)
```

I got the following error message:
```
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
Cell In [10], line 16
10 optimization_config = OptimizationConfig(optimization_level=1,
11 optimize_for_gpu=True,
12 fp16=True
13 )
15 # Optimize the model
---> 16 optimizer.optimize(save_dir=onnx_path, optimization_config=optimization_config)

File ~/anaconda3/envs/optimum_gpu_py3.8/lib/python3.8/site-packages/optimum/onnxruntime/optimization.py:128, in ORTOptimizer.optimize(self, optimization_config, save_dir, file_suffix, use_external_data_format, one_external_file)
126 save_dir = Path(save_dir)
127 save_dir.mkdir(parents=True, exist_ok=True)
--> 128 ORTConfigManager.check_optimization_supported_model(self.model_type)
130 self.config.save_pretrained(save_dir)
131 maybe_save_preprocessors(self.onnx_model_path[0].parent, save_dir)

File ~/anaconda3/envs/optimum_gpu_py3.8/lib/python3.8/site-packages/optimum/onnxruntime/utils.py:120, in ORTConfigManager.check_optimization_supported_model(cls, model_type)
118 supported_model_types_for_optimization = ["bert", "gpt2", "bart"]
119 if (model_type not in cls._conf) or (cls._conf[model_type] not in supported_model_types_for_optimization):
--> 120 raise KeyError(
121 f"ONNX Runtime doesn't support the graph optimization of {model_type} yet. Only {supported_model_types_for_optimization} are supported. "
122 f"If you want to support {model_type} please propose a PR or open up an issue in ONNX Runtime:https://github.com/microsoft/onnxruntime."
123 )

KeyError: "ONNX Runtime doesn't support the graph optimization of t5 yet. Only ['bert', 'gpt2', 'bart'] are supported. If you want to support t5 please propose a PR or open up an issue in ONNX Runtime:https://github.com/microsoft/onnxruntime."
```

Start with ORTOptimizer.optimize and ORTConfigManager.check_optimization_supported_model in optimization.py and utils.py, then review the listed model types and the ONNX Runtime GPU graph-optimization support for t5. Done means Flan-T5-Large can be optimized with optimize_for_gpu and fp16 without the reported unsupported-model error.

Written by the indexing model from the issue text.