skip hf_T5_generate in dynamic shape test (#121129)

Summary:
As reported in pytorch/pytorch#119434, `hf_T5_generate` failed with dynamic shape testing, we propose to skip the dynamic batch size testing of this model in this PR.

* Error msg is
```
  File "/home/jiayisun/pytorch/torch/_dynamo/guards.py", line 705, in SHAPE_ENV
    guards = output_graph.shape_env.produce_guards(
  File "/home/jiayisun/pytorch/torch/fx/experimental/symbolic_shapes.py", line 3253, in produce_guards
    raise ConstraintViolationError(
torch.fx.experimental.symbolic_shapes.ConstraintViolationError: Constraints violated (L['inputs_tensor'].size()[0])! For more information, run with TORCH_LOGS="+dynamic".
  - Not all values of RelaxedUnspecConstraint(L['inputs_tensor'].size()[0]) are valid because L['inputs_tensor'].size()[0] was inferred to be a constant (4).
```

* Root Cause is
This error happens while creating guard for this [model script line](https://github.com/huggingface/transformers/blob/main/src/transformers/models/t5/modeling_t5.py#L561): `scores += position_bias_masked`
I run it with TORCH_LOGS="+dynamic" and got the key line : `I0305 00:21:00.849974 140376923287424 torch/fx/experimental/symbolic_shapes.py:3963] [6/0_1] eval Eq(s0, 4) [guard added] at miniconda3/envs/pt2/lib/python3.9/site-packages/transformers/models/t5/modeling_t5.py:561 in forward (_refs/__init__.py:403 in _broadcast_shapes)`
The reason for this error is that the batch dimension of `inputs_tensor` in the dynamic batch size test is marked as dynamic shape `s0`, so the batch dimension of `scores` generated by a series of operations with `inputs_tensor` is also `s0`. However, because the function of creating `attention_mask` is not in Dynamo but in python. The batch dimension of `attention_mask` is the real shape `4`, and the batch dimension of `position_bias_masked` generated by a series of operations with `attention_mask` is also the real shape `4`, not the dynamic shape `s0`. The current line of `scores += position_bias_masked` requires creating a guard and check whether the batch dimension of `scores` is always equal to the batch dimension of `position_bias_masked`, Eq(s0, 4), the error happens.
So the root cause of this error is that the function of creating `attention_mask` not in Dynamo but in python. The reason why the function of `attention_mask` not in Dynamo is that Dynamo has a graph break on this function (happened in the [model script line](https://github.com/huggingface/transformers/blob/main/src/transformers/generation/utils.py#L476): `is_pad_token_in_inputs = (pad_token_id is not None) and (pad_token_id in inputs)`) due to the following error:
`torch._dynamo.exc.Unsupported: Tensor.item`

X-link: pytorch/pytorch#121129
Approved by: https://github.com/leslie-fang-intel, https://github.com/ezyang

Reviewed By: atalman

Differential Revision: D58296337

fbshipit-source-id: b081713ccfc5689bba23f57fc6fbc3cfe79bf99a

userbenchmark/dynamo/dynamobench/common.py

@@ -143,6 +143,7 @@ class CI(NamedTuple):
     "pyhpc_equation_of_state",
     "pyhpc_turbulent_kinetic_energy",
     "detectron2_fcos_r_50_fpn",
+    "hf_T5_generate",
 }
 
 # These models currently fail accuracy with eager Adam optimizer