Fix TypeError bug in static quantization tutorial

[Ashutosh0x]

Summary

Fix a TypeError bug in the static quantization tutorial. QuantizedLinear.from_observed() passes target_dtype to __init__() which doesn't accept it:

# __init__ takes 6 positional args:
def __init__(self, in_features, out_features, act_obs, weight_obs, weight, bias):

# from_observed passes 7 args (extra target_dtype):
quantized_linear = cls(in_features, out_features, act_obs, weight_obs, weight, bias, target_dtype)
# TypeError: __init__() takes 7 positional arguments but 8 were given

Anyone copying this tutorial code would hit TypeError immediately. The target_dtype was unused since QuantizedLinear hardcodes int8 behavior via Int8Tensor.

Fix

• Removed target_dtype from from_observed()
• Removed target_dtype field from StaticQuantConfig (now empty dataclass)
• Updated quantize_() call to match: StaticQuantConfig() instead of StaticQuantConfig(torch.uint8)

Partial fix for #3637

Test Plan

Documentation-only change. Verified argument counts match between __init__ (6 params) and from_observed's cls() call (6 args).

This change was authored with the assistance of an AI coding assistant.

[pytorch-bot]

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