fix quantized ic3/ic4/edsr examples (#574)

Summary:
Pull Request resolved: #574

The fix for quantized ic3/ic4/edsr requires runnign the pass

`convert_scalars_to_attrs` after capturing_pre_autograd_graph and before preparing and converting

We add using this pass in the examples to fix the quantized ic3/ic4/edsr

Reviewed By: digantdesai, guangy10

Differential Revision: D49850155

fbshipit-source-id: 359b7bbec45426292afe7d81ac1d816522c6e921

Author: mcr229

examples/quantization/utils.py

@@ -11,6 +11,9 @@
     get_symmetric_quantization_config,
     XNNPACKQuantizer,
 )
+from torch.ao.quantization.quantizer.xnnpack_quantizer_utils import (
+    convert_scalars_to_attrs,
+)
 
 
 def quantize(model, example_inputs):
@@ -20,6 +23,8 @@ def quantize(model, example_inputs):
     # if we set is_per_channel to True, we also need to add out_variant of quantize_per_channel/dequantize_per_channel
     operator_config = get_symmetric_quantization_config(is_per_channel=False)
     quantizer.set_global(operator_config)
+    # TODO(T165162973): This pass shall eventually be folded into quantizer
+    model = convert_scalars_to_attrs(model)
     m = prepare_pt2e(model, quantizer)
     # calibration
     m(*example_inputs)