Refactor torchao and tests to use model architectures from torchao.testing.model_architectures

[jainapurva]

PR: #2036, adds standard model architectures to torchao.testing.model_architectures.py. Replace the existing model definitions from torchao and tests to reuse the model definitions from model_architectures.py. If new definitions are found, add them to model_architectures.py

Eg:
Replace

ao/test/quantization/test_quant_api.py

Lines 122 to 138 in 34421b1

	class ToyLinearModel(torch.nn.Module):
	def __init__(self, m=64, n=32, k=64, bias=False):
	super().__init__()
	self.linear1 = torch.nn.Linear(m, n, bias=bias).to(torch.float)
	self.linear2 = torch.nn.Linear(n, k, bias=bias).to(torch.float)
	def example_inputs(self, batch_size=1, dtype=torch.float, device="cpu"):
	return (
	torch.randn(
	batch_size, self.linear1.in_features, dtype=dtype, device=device
	),
	)
	def forward(self, x):
	x = self.linear1(x)
	x = self.linear2(x)
	return x

to use torchao.testing.model_architectures.ToyLinearModel

[XueSongTap]

Can I work on this ?