diff --git a/frontend/Python/ops/func.py b/frontend/Python/ops/func.py
index a7dcc5e11b..b58ba92d97 100644
--- a/frontend/Python/ops/func.py
+++ b/frontend/Python/ops/func.py
@@ -104,6 +104,8 @@ def param_extract(
     dtype_mapping = {
         TensorDType.Float32: ir.F32Type.get(),
         TensorDType.Int64: ir.IntegerType.get_signless(64),
+        TensorDType.BFloat16: ir.BF16Type.get(),
+        TensorDType.Float16: ir.F16Type.get(),
     }
     memref_element_type = dtype_mapping[node.tensor_meta["dtype"]]
     if(len(node.tensor_meta['shape'])== 0):
diff --git a/frontend/Python/ops/tosa.py b/frontend/Python/ops/tosa.py
index 9562d95d83..470078509f 100644
--- a/frontend/Python/ops/tosa.py
+++ b/frontend/Python/ops/tosa.py
@@ -117,7 +117,7 @@ def _scalar_to_tensor(
     doesn't support operation between scalers and tensors."""
     element = (
         ir.FloatAttr.get(element_type, float(scalar))
-        if str(element_type) == "f32"
+        if str(element_type) in ("f32", "bf16", "f16")
         else ir.IntegerAttr.get(element_type, int(scalar))
     )
     attr = ir.DenseElementsAttr.get_splat(
@@ -804,7 +804,7 @@ def expand_op(node: ExpandOp, symbol_table) -> ir.Operation:
     ).element_type
     if result_element_type == ir.IntegerType.get_signless(1):
         element = ir.IntegerAttr.get(result_element_type, 0)
-    elif result_element_type == ir.F32Type.get():
+    elif result_element_type in (ir.F32Type.get(), ir.BF16Type.get(), ir.F16Type.get()):
         element = ir.FloatAttr.get(result_element_type, 0.0)
     else:
         raise NotImplementedError("Unsupported element type!")
diff --git a/frontend/Python/ops/utils.py b/frontend/Python/ops/utils.py
index 822cb4f535..0979822065 100644
--- a/frontend/Python/ops/utils.py
+++ b/frontend/Python/ops/utils.py
@@ -56,7 +56,7 @@ def mlir_element_attr_get(type_name, value):
             return ir.IntegerAttr.get(ir.IntegerType.get_signless(64), value)
         case TensorDType.Bool:
             return ir.IntegerAttr.get(ir.IntegerType.get_signless(1), value)
-        case TensorDType.Floaf16:
+        case TensorDType.Float16:
             return ir.FloatAttr.get(ir.F16Type.get(), value)
-        case TensorDType.BFloaf16:
+        case TensorDType.BFloat16:
             return ir.FloatAttr.get(ir.BF16Type.get(), value)