Revert D48588121: Add support for mul and mul_relu

Differential Revision:
D48588121

Original commit changeset: 04f9930effa1

Original Phabricator Diff: D48588121

fbshipit-source-id: afcc4c5a81222e1e1d02845d72c4c8fc87fa43cb

Author: ZainRizvi

examples/models/models.py

@@ -155,5 +155,4 @@ class OptimizationOptions(object):
     "add": OptimizationOptions(True, True),
     "add_mul": OptimizationOptions(True, True),
     "mv2": OptimizationOptions(True, True),
-    "mv3": OptimizationOptions(True, False),
 }

examples/quantization/example.py

@@ -46,7 +46,6 @@ def verify_xnnpack_quantizer_matching_fx_quant_model(model_name, model, example_
     m = prepare_pt2e(m, quantizer)
     # calibration
     after_prepare_result = m(*example_inputs)
-    print("pt2e prepare:", m)
     m = convert_pt2e(m)
     after_quant_result = m(*example_inputs)
 
@@ -58,7 +57,6 @@ def verify_xnnpack_quantizer_matching_fx_quant_model(model_name, model, example_
         m_copy, qconfig_mapping, example_inputs, backend_config=backend_config
     )
     after_prepare_result_fx = m_fx(*example_inputs)
-    print("fx prepare:", m_fx)
     m_fx = _convert_to_reference_decomposed_fx(m_fx, backend_config=backend_config)
     after_quant_result_fx = m_fx(*example_inputs)
 
@@ -71,10 +69,10 @@ def verify_xnnpack_quantizer_matching_fx_quant_model(model_name, model, example_
     print("m_fx:", m_fx)
     print("prepare sqnr:", compute_sqnr(after_prepare_result, after_prepare_result_fx))
     assert compute_sqnr(after_prepare_result, after_prepare_result_fx) > 100
-    print("diff max:", torch.max(after_quant_result - after_quant_result_fx))
-    print("sqnr:", compute_sqnr(after_quant_result, after_quant_result_fx))
+    print("quant diff max:", torch.max(after_quant_result - after_quant_result_fx))
     assert torch.max(after_quant_result - after_quant_result_fx) < 1e-1
-    assert compute_sqnr(after_quant_result, after_quant_result_fx) > 35
+    print("quant sqnr:", compute_sqnr(after_quant_result, after_quant_result_fx))
+    assert compute_sqnr(after_quant_result, after_quant_result_fx) > 30
 
 
 if __name__ == "__main__":
@@ -123,7 +121,7 @@ def verify_xnnpack_quantizer_matching_fx_quant_model(model_name, model, example_
         raise RuntimeError(
             f"Model {args.model_name} is not a valid name. or not quantizable right now, "
             "please contact executorch team if you want to learn why or how to support "
-            "quantization for the requested model "
+            "quantization for the requested model"
             f"Available models are {list(MODEL_NAME_TO_OPTIONS.keys())}."
         )