Propagate dump_graphs to print quantization graphs. (#4167)

Summary:
Pull Request resolved: #4167

As titled. Also fixed a pyre-fixme along the way.

Differential Revision: D59438228

Reviewed By: zonglinpengmeta

Author: Matthias Cremon

backends/cadence/aot/TARGETS

@@ -28,6 +28,7 @@ python_library(
         "compiler.py",
     ],
     deps = [
+        "fbsource//third-party/pypi/pyre-extensions:pyre-extensions",
         ":passes",
         ":utils",
         "//caffe2:torch",

backends/cadence/aot/compiler.py

@@ -18,9 +18,13 @@
     ReplaceSqueezeAndUnsqueezeWithViewPass,
 )
 from executorch.backends.cadence.aot.quantizer.fusion_pass import QuantFusion
-from executorch.backends.cadence.aot.quantizer.quantizer import CadenceQuantizer
+from executorch.backends.cadence.aot.quantizer.quantizer import (
+    CadenceGenericQuantizer,
+    CadenceQuantizer,
+)
 from executorch.backends.cadence.aot.utils import model_is_quantized
 from executorch.exir import EdgeCompileConfig, EdgeProgramManager, to_edge
+from pyre_extensions import assert_is_instance
 from torch._export import capture_pre_autograd_graph
 from torch.ao.quantization.pt2e.export_utils import model_is_exported
 from torch.ao.quantization.quantize_pt2e import convert_pt2e, prepare_pt2e
@@ -53,8 +57,10 @@ def quantize_pt2(
     converted_model = convert_pt2e(prepared_model)
 
     # Get patterns and apply fusion of dq -> op -> q to qop
-    # pyre-fixme[16]: Pyre doesn't get that CadenceQuantizer has a patterns attribute
-    patterns = [q.pattern for q in quantizer.quantizers]
+    patterns = [
+        assert_is_instance(q, CadenceGenericQuantizer).pattern
+        for q in quantizer.quantizers
+    ]
     QuantFusion(patterns)(converted_model)
 
     return converted_model