fx quant: enable qconfig_dict to target function invocations by order (#59605)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/59605
Enables targeting of individual function invocations by execution order.
For example, given a module such as
```
class M1(torch.nn.Module):
def forward(self, x):
x = torch.add(x, x)
x = torch.add(x, x)
return x
class M2(torch.nn.Module):
def __init__(self):
self.m1 = M1()
def forward(self, x):
x = self.m1(x)
return x
```
We can now target the first add of `m1` with
```
qconfig_dict = {
"module_name_function_order": ("m1", torch.add, 0, custom_qconfig),
}
```
Test Plan:
```
python test/test_quantization.py TestQuantizeFx.test_qconfig_module_name_function_order
```
Imported from OSS
Reviewed By: hx89
Differential Revision: D28951077
fbshipit-source-id: 311d423724a31193d4fa4bbf3a712b46464b5a29
