[ET-VK][ez] Apply quantize op replacement to all argument nodes (pytorch#15746)

Title says it all!

With the way the pass is currently written only the first arg will be inspected for q/dq node replacement. As a consequence, the second arg for i.e. binary ops may not have the quantized op be replaced.

Differential Revision: [D86674169](https://our.internmc.facebook.com/intern/diff/D86674169/)

Author: pytorchbot

backends/vulkan/_passes/replace_qdq.py

@@ -32,24 +32,23 @@ def call(self, graph_module: torch.fx.GraphModule):
                 exir_ops.edge.et_vk.conv2d_q8ta_q8csw_q8to_dw.default,
                 exir_ops.edge.et_vk.add_q8ta_q8ta_q8to.default,
             ]:
-                # Replace quantize op feeding into conv2d (first argument is the quantized input)
-                quantized_input_node = node.args[0]
-                if isinstance(
-                    quantized_input_node, torch.fx.Node
-                ) and utils.is_quant_node(quantized_input_node):
-                    # Get the arguments from the original quantize node
-                    input_tensor = quantized_input_node.args[0]
-                    scale = quantized_input_node.args[1]
-                    zero_point = quantized_input_node.args[2]
+                for quantized_input_node in node.args:
+                    if isinstance(
+                        quantized_input_node, torch.fx.Node
+                    ) and utils.is_quant_node(quantized_input_node):
+                        # Get the arguments from the original quantize node
+                        input_tensor = quantized_input_node.args[0]
+                        scale = quantized_input_node.args[1]
+                        zero_point = quantized_input_node.args[2]
 
-                    nodes_to_replace.append(
-                        {
-                            "old_node": quantized_input_node,
-                            "new_target": exir_ops.edge.et_vk.quantize_q8ta_for_conv2d.default,
-                            "args": (input_tensor, scale, zero_point),
-                            "node_type": "quantize_input",
-                        }
-                    )
+                        nodes_to_replace.append(
+                            {
+                                "old_node": quantized_input_node,
+                                "new_target": exir_ops.edge.et_vk.quantize_q8ta_for_conv2d.default,
+                                "args": (input_tensor, scale, zero_point),
+                                "node_type": "quantize_input",
+                            }
+                        )
 
                 # Find dequantize ops that consume the output of this conv2d
                 for user in node.users: