Update name from xtensa to cadence

Summary: As titled.

Differential Revision: D55998135

Author: mcremon-meta

examples/xtensa/CMakeLists.txt renamed to examples/cadence/CMakeLists.txt

@@ -28,7 +28,7 @@
 logging.basicConfig(level=logging.INFO, format=FORMAT)
 
 
-def export_xtensa_model(model, example_inputs):
+def export_model(model, example_inputs):
     # Quantizer
     quantizer = XtensaBaseQuantizer()
 
@@ -46,20 +46,20 @@ def export_xtensa_model(model, example_inputs):
     patterns = [q.pattern for q in quantizer.quantizers]
     QuantFusion(patterns)(converted_model)
 
-    # Get edge program (note: the name will change to export_to_xtensa in future PRs)
+    # Get edge program (note: the name will change to export_to_cadence in future PRs)
     edge_prog_manager = export_to_edge(converted_model, example_inputs, pt2_quant=True)
 
     # Run a couple required passes for quant/dequant ops
-    xtensa_prog_manager = edge_prog_manager.transform(
+    cadence_prog_manager = edge_prog_manager.transform(
         [ReplacePT2QuantWithXtensaQuant(), ReplacePT2DequantWithXtensaDequant()],
         check_ir_validity=False,
     )
 
-    exec_prog = xtensa_prog_manager.to_executorch()
+    exec_prog = cadence_prog_manager.to_executorch()
 
     logging.info(
         f"Final exported graph module:\n{exec_prog.exported_program().graph_module}"
     )
 
-    # Save the program as XtensaDemoModel.pte
-    save_pte_program(exec_prog, "XtensaDemoModel")
+    # Save the program as CadenceDemoModel.pte
+    save_pte_program(exec_prog, "CadenceDemoModel")

examples/xtensa/aot/compiler.py renamed to examples/cadence/aot/compiler.py

@@ -437,7 +437,7 @@ def get_anchors(
         )
 
     def replacement_op(self):
-        return torch.ops.xtensa.quantized_linear.default
+        return torch.ops.cadence.quantized_linear.default
 
 
 class LinearFunctionalPattern(QuantizationPattern):
@@ -457,7 +457,7 @@ def get_anchors(
         )
 
     def replacement_op(self):
-        return torch.ops.xtensa.quantized_linear.default
+        return torch.ops.cadence.quantized_linear.default
 
 
 class LayerNormPattern(QuantizationPattern):
@@ -476,7 +476,7 @@ def get_anchors(self, gm, fused_partition) -> PartitionAnchors:
         )
 
     def replacement_op(self):
-        return torch.ops.xtensa.quantized_layer_norm.default
+        return torch.ops.cadence.quantized_layer_norm.default
 
 
 class Conv1dPattern(QuantizationPattern):
@@ -503,7 +503,7 @@ def get_anchors(
         )
 
     def replacement_op(self):
-        return torch.ops.xtensa.quantized_conv.default
+        return torch.ops.cadence.quantized_conv.default
 
 
 class Conv2dPattern(QuantizationPattern):
@@ -530,7 +530,7 @@ def get_anchors(
         )
 
     def replacement_op(self):
-        return torch.ops.xtensa.quantized_conv.default
+        return torch.ops.cadence.quantized_conv.default
 
 
 class AddmmPattern(QuantizationPattern):
@@ -550,7 +550,7 @@ def get_anchors(
         )
 
     def replacement_op(self):
-        return torch.ops.xtensa.quantized_linear.default
+        return torch.ops.cadence.quantized_linear.default
 
 
 class ReluPattern(QuantizationPattern):
@@ -573,7 +573,7 @@ def get_anchors(
         )
 
     def replacement_op(self):
-        return torch.ops.xtensa.quantized_relu.default
+        return torch.ops.cadence.quantized_relu.default
 
 
 class GenericQuantizer(Quantizer):
@@ -823,15 +823,15 @@ def mark_fused(cls, nodes) -> bool:
 
 class ReplacePT2QuantWithXtensaQuant(ExportPass):
     """
-    Replace the pt2 quantization ops with custom xtensa quantization ops.
+    Replace the pt2 quantization ops with custom cadence quantization ops.
     """
 
     def call_operator(self, op, args, kwargs, meta):
         if op not in {exir_ops.edge.quantized_decomposed.quantize_per_tensor.default}:
             return super().call_operator(op, args, kwargs, meta)
 
         return super().call_operator(
-            exir_ops.edge.xtensa.quantize_per_tensor.default,
+            exir_ops.edge.cadence.quantize_per_tensor.default,
             args,
             kwargs,
             meta,
@@ -840,15 +840,15 @@ def call_operator(self, op, args, kwargs, meta):
 
 class ReplacePT2DequantWithXtensaDequant(ExportPass):
     """
-    Replace the pt2 dequantization ops with custom xtensa dequantization ops.
+    Replace the pt2 dequantization ops with custom cadence dequantization ops.
     """
 
     def call_operator(self, op, args, kwargs, meta):
         if op not in {exir_ops.edge.quantized_decomposed.dequantize_per_tensor.default}:
             return super().call_operator(op, args, kwargs, meta)
 
         return super().call_operator(
-            exir_ops.edge.xtensa.dequantize_per_tensor.default,
+            exir_ops.edge.cadence.dequantize_per_tensor.default,
             args,
             kwargs,
             meta,