quant params from static inputs (#573)

Summary:
Pull Request resolved: #573

Since we allow tensor constants to be quantized inputs, we need to adjust the from_inputs api to search if this input is static or not. If it is static, then we take the first q node in get_attr --> q --> dq. If it is not static, then we just take the dq node to create the QuantParams object.

In the past, we can take in static quant inputs only on weights and biases.

Differential Revision: D49850149

fbshipit-source-id: 48bc0d6b0bb258f555201e9f182c1276c5d9247f

Author: mcr229

backends/xnnpack/operators/quant_params.py

@@ -11,8 +11,9 @@
 import torch
 from executorch.backends.xnnpack.passes.tag_implicit_q_dq_pass import TagImplicitQDqPass
 from executorch.backends.xnnpack.utils.quant_utils import is_dequant, is_quant
-from executorch.backends.xnnpack.utils.utils import check_or_raise
+from executorch.backends.xnnpack.utils.utils import check_or_raise, is_param_node
 from executorch.exir.dialects._ops import ops as exir_ops
+from torch.export import ExportedProgram
 
 
 class QuantParams:
@@ -183,6 +184,11 @@ def from_inputs(cls, tensor_node: torch.fx.Node) -> Optional[QuantParams]:
         if is_dequant(tensor_node) and TagImplicitQDqPass.is_tagged_as_implicit_q_dq(
             tensor_node
         ):
+            dq_input = cast(torch.fx.Node, tensor_node.args[0])
+            if is_quant(dq_input):
+                q_input = cast(torch.fx.Node, dq_input.args[0])
+                if q_input.op == "placeholder":
+                    return cls.from_q_dq_node(dq_input)
             return cls.from_q_dq_node(tensor_node)
 
         return None