Support for Dynamic Data Dependent Tensor Slicing

import torch

from executorch.exir import EdgeCompileConfig, ExecutorchBackendConfig, to_edge
from executorch.backends.xnnpack.partition.xnnpack_partitioner import XnnpackPartitioner

from torch.export import export_for_training
from torch.export.experimental import _export_forward_backward

class DynamicTestModel(torch.nn.Module):
      
    def __init__(self,):
        super(DynamicTestModel, self).__init__()
    
    def forward(self, tensor_to_slice: torch.Tensor,
        slice_conditional_tensor: torch.Tensor,
    ) -> torch.Tensor:

        mask_tensor_bool = (slice_conditional_tensor.squeeze() != -100).bool()
        tensor_to_slice = tensor_to_slice[:, mask_tensor_bool, :]

        return tensor_to_slice.mean()

def _export(model, tensor_to_slice, slice_conditional_tensor):

        exp = export_for_training(model, (tensor_to_slice, slice_conditional_tensor))

        exp = _export_forward_backward(exp)

        edge = to_edge(
            exp,
            compile_config=EdgeCompileConfig()
        )
        edge = edge.to_backend(
            XnnpackPartitioner(force_fp32_dynamic_linear=True)
        )
        edge = edge.to_executorch(config=ExecutorchBackendConfig(
            external_mutable_weights=False
        ))


if __name__ == "__main__":
    tensor_to_slice = torch.randn((1, 10, 20))
    slice_conditional_tensor = torch.randint(0, 100, (1, 10))
    slice_conditional_tensor[:, : 5] = -100

    tensor_to_slice.requires_grad_(True)
    _export(DynamicTestModel(), tensor_to_slice, slice_conditional_tensor.contiguous())

`Traceback (most recent call last):`
...
raise self._make_data_dependent_error(
torch.fx.experimental.symbolic_shapes.GuardOnDataDependentSymNode: Could not guard on data-dependent expression Eq(20*u21, 0) (unhinted: Eq(20*u21, 0)).  (Size-like symbols: u21)

ATTENTION: guard_size_oblivious would fix the error, evaluating expression to False.
Maybe you need to add guard_size_oblivious to framework code, see doc below for more guidance.

Caused by: (executorch/exir/tensor.py:71 in dim_order_from_stride)
For more information, run with TORCH_LOGS="dynamic"
For extended logs when we create symbols, also add TORCHDYNAMO_EXTENDED_DEBUG_CREATE_SYMBOL="u21"
If you suspect the guard was triggered from C++, add TORCHDYNAMO_EXTENDED_DEBUG_CPP=1
For more debugging help, see https://docs.google.com/document/d/1HSuTTVvYH1pTew89Rtpeu84Ht3nQEFTYhAX3Ypa_xJs/edit?usp=sharing

For C++ stack trace, run with TORCHDYNAMO_EXTENDED_DEBUG_CPP=1

While executing %aten_index_tensor : [num_users=2] = call_function[target=executorch.exir.dialects.edge._ops.aten.index.Tensor](args = (%tensor_to_slice, [None, %aten_ne_scalar]), kwargs = {})
GraphModule: class GraphModule(torch.nn.Module):
...