Support lowering 'densenet161' from 'torchvision' to 'torch` dialect

Lowering of DenseNet model fails with error.

import torch
import torch_mlir
import torchvision
mdl = torchvision.models.densenet.densenet161()
shp = torch_mlir.TensorPlaceholder([1, 3, 224, 224], torch.float32)
mlir = torch_mlir.compile(mdl, shp, "torch")

Execution of the script cause following error:

File "/pytorch_venv/lib/python3.11/site-packages/torch_mlir/__init__.py", line 458, in compile
run_pipeline_with_repro_report(
File "/pytorch_venv/lib/python3.11/site-packages/torch_mlir/compiler_utils.py", line 73, in run_pipeline_with_repro_report
raise TorchMlirCompilerError(trimmed_message) from None
torch_mlir.compiler_utils.TorchMlirCompilerError: Lowering TorchScript IR -> Torch Backend IR failed with the following diagnostics:
python exception: Failure while executing pass pipeline:
error: unknown: unsupported by backend contract: module initializers

Start by reproducing the failure with the provided densenet161 and TensorPlaceholder script, then trace the TorchScript IR to Torch Backend IR pipeline where the unsupported module initializers diagnostic is emitted. Done means the shown torchvision model compiles to the torch dialect without the module-initializer error and the regression is covered by an appropriate test.