diff --git a/tripy/docs/conf.py b/tripy/docs/conf.py
index 8b30df9a1..dfb827d9c 100644
--- a/tripy/docs/conf.py
+++ b/tripy/docs/conf.py
@@ -28,7 +28,7 @@
 
 import tripy as tp
 from tripy.common.datatype import DATA_TYPES
-from tripy.constraints import TYPE_VERIFICATION
+from tripy.wrappers import TYPE_VERIFICATION
 
 PARAM_PAT = re.compile(":param .*?:")
 
diff --git a/tripy/docs/post0_developer_guides/how-to-add-new-ops.md b/tripy/docs/post0_developer_guides/how-to-add-new-ops.md
index 632345571..43accc2c0 100644
--- a/tripy/docs/post0_developer_guides/how-to-add-new-ops.md
+++ b/tripy/docs/post0_developer_guides/how-to-add-new-ops.md
@@ -176,7 +176,7 @@ it as a `tripy.Module` under [`frontend/module`](source:/tripy/frontend/module).
 
 ```py
 # doc: no-eval
-from tripy import constraints, export
+from tripy import export, wrappers
 from tripy.types import ShapeLike
 
 # We can use the `export.public_api()` decorator to automatically export this
@@ -191,12 +191,12 @@ from tripy.types import ShapeLike
 # `autodoc_options` parameter.
 @export.public_api(document_under="tensor_operations")
 
-# We can use the `constraints.interface` decorator to specify constraints on
+# We can use the `wrappers.interface` decorator to specify constraints on
 # inputs and perform transformations on them, like automatically converting
 # compatible arguments (e.g., `TensorLike` or `ShapeLike`s) into tensors.
 # We will aim to include most constraints and transformations in this decorator
 # so as to avoid layering too many decorators.
-@constraints.interface(convert_tensor_and_shape_likes=True)
+@wrappers.interface(convert_to_tensors=True)
 def theta(shape: ShapeLike, dim: int = 0, dtype: datatype.dtype = datatype.float32) -> "tripy.Tensor":
     # For any public facing interfaces, we have documentation requirements which
     # you can read about in the 'Docs README' (linked below). The docstring
diff --git a/tripy/tests/common/test_exception.py b/tripy/tests/common/test_exception.py
index a006025c3..09b04782b 100644
--- a/tripy/tests/common/test_exception.py
+++ b/tripy/tests/common/test_exception.py
@@ -124,14 +124,14 @@ def test_can_determine_column_range(self):
             in dedent(error_msg).strip()
         )
 
-    def test_constraints_is_excluded(self):
-        from tripy import constraints
+    def test_wrappers_is_excluded(self):
+        from tripy import wrappers
 
         tensor = tp.ones((2, 3))
 
         stack_info = tensor.stack_info
 
-        assert any(frame.module == constraints.__name__ for frame in stack_info)
+        assert any(frame.module == wrappers.__name__ for frame in stack_info)
 
         # Make sure that no extraneous wrapper code is included
         expected = dedent(
@@ -146,7 +146,7 @@ def test_constraints_is_excluded(self):
                 [0-9]+ |     return full\(shape, 1, dtype\)
                     |            ^^^^^^^^^^^^^^^^^^^^^ --- required from here
 
-                --> [a-z_/\.]+:[0-9]+ in test_constraints_is_excluded\(\)
+                --> [a-z_/\.]+:[0-9]+ in test_wrappers_is_excluded\(\)
                     |
                 [0-9]+ |         tensor = tp.ones\(\(2, 3\)\)
                     |                  ^^^^^^^^^^^^^^^ --- required from here
diff --git a/tripy/tests/constraints/object_builders.py b/tripy/tests/wrappers/object_builders.py
similarity index 100%
rename from tripy/tests/constraints/object_builders.py
rename to tripy/tests/wrappers/object_builders.py
diff --git a/tripy/tests/constraints/test_interface.py b/tripy/tests/wrappers/test_interface.py
similarity index 91%
rename from tripy/tests/constraints/test_interface.py
rename to tripy/tests/wrappers/test_interface.py
index bbb1d178b..8d089ed76 100755
--- a/tripy/tests/constraints/test_interface.py
+++ b/tripy/tests/wrappers/test_interface.py
@@ -24,12 +24,12 @@
 import pytest
 from tests import helper
 from tests.conftest import skip_if_older_than_sm89
-from tests.constraints.object_builders import create_obj
+from tests.wrappers.object_builders import create_obj
 
 import tripy as tp
-from tripy import constraints
+from tripy import wrappers
 from tripy.common.datatype import DATA_TYPES
-from tripy.constraints import TYPE_VERIFICATION
+from tripy.wrappers import TYPE_VERIFICATION
 from tripy.export import PUBLIC_APIS
 
 # Get all functions/methods which have tensors in the type signature
@@ -239,7 +239,7 @@ def test_dtype_constraints(test_data):
                     assert ret_val.dtype == namespace[return_dtype]
 
 
-@constraints.interface(dtype_constraints={"tensors": "T1"}, variables={"T1": ["float32"]})
+@wrappers.interface(dtype_constraints={"tensors": "T1"}, dtype_variables={"T1": ["float32"]})
 def sequence_func(tensors: List[tp.Tensor]):
     return
 
@@ -255,7 +255,7 @@ def test_raises_on_mismatched_sequence_dtypes(self):
 
 class TestTensorConversion:
     def test_no_effect_on_non_tensor_likes(self):
-        @constraints.interface(convert_tensor_and_shape_likes=True)
+        @wrappers.interface(convert_to_tensors=True)
         def func(a: tp.Tensor, b: int):
             return a, b
 
@@ -266,7 +266,7 @@ def func(a: tp.Tensor, b: int):
         assert b is 4
 
     def test_tensor_likes(self):
-        @constraints.interface(convert_tensor_and_shape_likes=True)
+        @wrappers.interface(convert_to_tensors=True)
         def func(a: tp.types.TensorLike):
             return a
 
@@ -277,7 +277,7 @@ def func(a: tp.types.TensorLike):
 
     def test_converts_to_dimension_size(self):
         # The decorator should convert to DimensionSizes when possible.
-        @constraints.interface(convert_tensor_and_shape_likes=True)
+        @wrappers.interface(convert_to_tensors=True)
         def func(a: tp.types.TensorLike):
             return a
 
@@ -289,7 +289,7 @@ def func(a: tp.types.TensorLike):
         assert type(a) is tp.Tensor
 
     def test_shape_likes(self):
-        @constraints.interface(convert_tensor_and_shape_likes=True)
+        @wrappers.interface(convert_to_tensors=True)
         def func(a: tp.types.ShapeLike):
             return a
 
@@ -310,7 +310,7 @@ def func(a: tp.types.ShapeLike):
         assert bool(tp.all(a == tp.Tensor([2, 2, 3, 5])))
 
     def test_keyword_args(self):
-        @constraints.interface(convert_tensor_and_shape_likes=True)
+        @wrappers.interface(convert_to_tensors=True)
         def func(a: tp.types.TensorLike):
             return a
 
@@ -320,7 +320,7 @@ def func(a: tp.types.TensorLike):
         assert a.stack_info[4].column_range == (17, 22)
 
     def test_multiple_args(self):
-        @constraints.interface(convert_tensor_and_shape_likes=True)
+        @wrappers.interface(convert_to_tensors=True)
         def func(a: tp.types.TensorLike, b: tp.types.TensorLike):
             return a, b
 
@@ -333,7 +333,7 @@ def func(a: tp.types.TensorLike, b: tp.types.TensorLike):
         assert b.stack_info[4].column_range == (25, 28)
 
     def test_args_out_of_order(self):
-        @constraints.interface(convert_tensor_and_shape_likes=True)
+        @wrappers.interface(convert_to_tensors=True)
         def func(a: tp.types.TensorLike, b: tp.types.TensorLike):
             return a, b
 
@@ -349,10 +349,10 @@ def func(a: tp.types.TensorLike, b: tp.types.TensorLike):
 
     def test_cast_dtype(self):
         # When type constraints are included, the decorator should automatically cast when possible.
-        @constraints.interface(
-            dtype_constraints={"a": "T1", "b": "T1", constraints.RETURN_VALUE: "T1"},
-            variables={"T1": ["float16"]},
-            convert_tensor_and_shape_likes=True,
+        @wrappers.interface(
+            dtype_constraints={"a": "T1", "b": "T1", wrappers.RETURN_VALUE: "T1"},
+            dtype_variables={"T1": ["float16"]},
+            convert_to_tensors=True,
         )
         def func(a: tp.Tensor, b: tp.types.TensorLike):
             return a, b
@@ -369,10 +369,10 @@ def func(a: tp.Tensor, b: tp.types.TensorLike):
 
     @pytest.mark.parametrize("arg, dtype", [(1.0, tp.int32), (1.0, tp.int64), (2, tp.bool)])
     def test_refuse_unsafe_cast(self, arg, dtype):
-        @constraints.interface(
-            dtype_constraints={"a": "T1", "b": "T1", constraints.RETURN_VALUE: "T1"},
-            variables={"T1": ["int32", "int64"]},
-            convert_tensor_and_shape_likes=True,
+        @wrappers.interface(
+            dtype_constraints={"a": "T1", "b": "T1", wrappers.RETURN_VALUE: "T1"},
+            dtype_variables={"T1": ["int32", "int64"]},
+            convert_to_tensors=True,
         )
         def func(a: tp.Tensor, b: tp.types.TensorLike):
             return a, b
@@ -385,7 +385,7 @@ def test_preprocess_func(self):
         def add_a_to_b(a, b):
             return {"b": a + b}
 
-        @constraints.interface(convert_tensor_and_shape_likes=True, conversion_preprocess_func=add_a_to_b)
+        @wrappers.interface(convert_to_tensors=True, conversion_preprocess_func=add_a_to_b)
         def func(a: tp.types.TensorLike, b: tp.types.TensorLike):
             return a, b
 
@@ -398,7 +398,7 @@ def test_variadic_args(self):
         def increment(a, *args):
             return {"a": a + 1, "args": list(map(lambda arg: arg + 1, args))}
 
-        @constraints.interface(convert_tensor_and_shape_likes=True, conversion_preprocess_func=increment)
+        @wrappers.interface(convert_to_tensors=True, conversion_preprocess_func=increment)
         def func(a: tp.Tensor, *args):
             return [a] + list(args)
 
diff --git a/tripy/tripy/frontend/ops/allclose.py b/tripy/tripy/frontend/ops/allclose.py
index 95933370c..fd7f1b5c0 100644
--- a/tripy/tripy/frontend/ops/allclose.py
+++ b/tripy/tripy/frontend/ops/allclose.py
@@ -15,12 +15,12 @@
 # limitations under the License.
 #
 
-from tripy import constraints, export
+from tripy import export, wrappers
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", "other": "T1"}, variables={"T1": ["float32", "float16", "bfloat16"]}
+@wrappers.interface(
+    dtype_constraints={"input": "T1", "other": "T1"}, dtype_variables={"T1": ["float32", "float16", "bfloat16"]}
 )
 def allclose(input: "tripy.Tensor", other: "tripy.Tensor", rtol: float = 1e-05, atol: float = 1e-08) -> bool:
     r"""
diff --git a/tripy/tripy/frontend/ops/cumsum.py b/tripy/tripy/frontend/ops/cumsum.py
index b3db535ee..fc9fa888a 100644
--- a/tripy/tripy/frontend/ops/cumsum.py
+++ b/tripy/tripy/frontend/ops/cumsum.py
@@ -12,15 +12,15 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from tripy import constraints, export
+from tripy import export, wrappers
 
 from tripy.frontend import utils as frontend_utils
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "int32"],
     },
 )
diff --git a/tripy/tripy/frontend/ops/equal.py b/tripy/tripy/frontend/ops/equal.py
index 0c4ddd693..5590c387e 100644
--- a/tripy/tripy/frontend/ops/equal.py
+++ b/tripy/tripy/frontend/ops/equal.py
@@ -12,12 +12,12 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from tripy import constraints, export
+from tripy import export, wrappers
 from tripy.common.datatype import DATA_TYPES
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(dtype_constraints={"input": "T1", "other": "T1"}, variables={"T1": list(DATA_TYPES.keys())})
+@wrappers.interface(dtype_constraints={"input": "T1", "other": "T1"}, dtype_variables={"T1": list(DATA_TYPES.keys())})
 def equal(input: "tripy.Tensor", other: "tripy.Tensor") -> bool:
     r"""
     Returns ``True`` if ``input`` and ``other`` have the same shape and elements.
diff --git a/tripy/tripy/frontend/ops/flatten.py b/tripy/tripy/frontend/ops/flatten.py
index e2407b5a0..930a69d70 100644
--- a/tripy/tripy/frontend/ops/flatten.py
+++ b/tripy/tripy/frontend/ops/flatten.py
@@ -14,14 +14,14 @@
 # limitations under the License.
 import math
 
-from tripy import constraints, export
+from tripy import export, wrappers
 from tripy.common.exception import raise_error
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"]},
 )
 def flatten(input: "tripy.Tensor", start_dim: int = 0, end_dim: int = -1) -> "tripy.Tensor":
     """
diff --git a/tripy/tripy/frontend/ops/gelu.py b/tripy/tripy/frontend/ops/gelu.py
index ccf88fe45..19e62d7fc 100644
--- a/tripy/tripy/frontend/ops/gelu.py
+++ b/tripy/tripy/frontend/ops/gelu.py
@@ -17,13 +17,13 @@
 
 import math
 
-from tripy import export, constraints
+from tripy import export, wrappers
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16"],
     },
 )
diff --git a/tripy/tripy/frontend/ops/outer.py b/tripy/tripy/frontend/ops/outer.py
index 023a0726a..ce229ebc9 100644
--- a/tripy/tripy/frontend/ops/outer.py
+++ b/tripy/tripy/frontend/ops/outer.py
@@ -15,13 +15,13 @@
 # limitations under the License.
 #
 
-from tripy import constraints, export
+from tripy import export, wrappers
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"vec1": "T1", "vec2": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "int32"]},
+@wrappers.interface(
+    dtype_constraints={"vec1": "T1", "vec2": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "int32"]},
 )
 def outer(vec1: "tripy.Tensor", vec2: "tripy.Tensor") -> "tripy.Tensor":
     r"""
diff --git a/tripy/tripy/frontend/ops/relu.py b/tripy/tripy/frontend/ops/relu.py
index d0ea28bbf..990397a51 100644
--- a/tripy/tripy/frontend/ops/relu.py
+++ b/tripy/tripy/frontend/ops/relu.py
@@ -15,13 +15,13 @@
 # limitations under the License.
 #
 
-from tripy import export, constraints
+from tripy import export, wrappers
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "int4", "int32", "int64", "bool", "int8"],
     },
 )
diff --git a/tripy/tripy/frontend/ops/repeat.py b/tripy/tripy/frontend/ops/repeat.py
index 01d295a27..898804334 100644
--- a/tripy/tripy/frontend/ops/repeat.py
+++ b/tripy/tripy/frontend/ops/repeat.py
@@ -15,15 +15,15 @@
 #
 from typing import Union
 
-from tripy import constraints, export
+from tripy import export, wrappers
 from tripy.common.exception import raise_error
 from tripy.frontend import utils as frontend_utils
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "int4", "float8", "int8", "int32", "int64", "bool"],
     },
 )
diff --git a/tripy/tripy/frontend/ops/sigmoid.py b/tripy/tripy/frontend/ops/sigmoid.py
index b6c3dc227..45469dcdd 100644
--- a/tripy/tripy/frontend/ops/sigmoid.py
+++ b/tripy/tripy/frontend/ops/sigmoid.py
@@ -15,13 +15,13 @@
 # limitations under the License.
 #
 
-from tripy import export, constraints
+from tripy import export, wrappers
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16"],
     },
 )
diff --git a/tripy/tripy/frontend/ops/silu.py b/tripy/tripy/frontend/ops/silu.py
index cbe9f0ff2..9b3228a55 100644
--- a/tripy/tripy/frontend/ops/silu.py
+++ b/tripy/tripy/frontend/ops/silu.py
@@ -15,13 +15,13 @@
 # limitations under the License.
 #
 
-from tripy import export, constraints
+from tripy import export, wrappers
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16"],
     },
 )
diff --git a/tripy/tripy/frontend/ops/softmax.py b/tripy/tripy/frontend/ops/softmax.py
index f994d2f3d..1d7c045da 100644
--- a/tripy/tripy/frontend/ops/softmax.py
+++ b/tripy/tripy/frontend/ops/softmax.py
@@ -15,13 +15,13 @@
 # limitations under the License.
 #
 
-from tripy import export, constraints
+from tripy import export, wrappers
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16"],
     },
 )
diff --git a/tripy/tripy/frontend/ops/stack.py b/tripy/tripy/frontend/ops/stack.py
index 8ba51895a..558dfae63 100644
--- a/tripy/tripy/frontend/ops/stack.py
+++ b/tripy/tripy/frontend/ops/stack.py
@@ -15,14 +15,14 @@
 
 from typing import Sequence
 
-from tripy import constraints, export
+from tripy import export, wrappers
 from tripy.common.exception import raise_error
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"tensors": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"tensors": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"],
     },
 )
diff --git a/tripy/tripy/frontend/ops/tensor_initializers.py b/tripy/tripy/frontend/ops/tensor_initializers.py
index 3021503f8..244822f29 100644
--- a/tripy/tripy/frontend/ops/tensor_initializers.py
+++ b/tripy/tripy/frontend/ops/tensor_initializers.py
@@ -18,7 +18,7 @@
 import numbers
 from typing import Optional, Union
 
-from tripy import constraints, export
+from tripy import export, wrappers
 from tripy.common import datatype
 from tripy.common.exception import raise_error
 from tripy.frontend.trace.ops.fill import full, full_like
@@ -27,9 +27,9 @@
 
 
 @export.public_api(document_under="operations/initializers")
-@constraints.interface(
-    dtype_constraints={"dtype": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"dtype": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "float8", "int8", "int4", "int32", "int64", "bool"],
     },
 )
@@ -61,9 +61,9 @@ def ones(
 
 
 @export.public_api(document_under="operations/initializers")
-@constraints.interface(
-    dtype_constraints={"dtype": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"dtype": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "float8", "int8", "int4", "int32", "int64", "bool"],
     },
 )
@@ -95,9 +95,9 @@ def zeros(
 
 
 @export.public_api(document_under="operations/initializers")
-@constraints.interface(
-    dtype_constraints={"input": "T1", "dtype": "T2", constraints.RETURN_VALUE: "T2"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"input": "T1", "dtype": "T2", wrappers.RETURN_VALUE: "T2"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"],
         "T2": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"],
     },
@@ -128,9 +128,9 @@ def ones_like(input: "tripy.Tensor", dtype: Optional[datatype.dtype] = None) ->
 
 
 @export.public_api(document_under="operations/initializers")
-@constraints.interface(
-    dtype_constraints={"input": "T1", "dtype": "T2", constraints.RETURN_VALUE: "T2"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"input": "T1", "dtype": "T2", wrappers.RETURN_VALUE: "T2"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"],
         "T2": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"],
     },
@@ -162,9 +162,9 @@ def zeros_like(input: "tripy.Tensor", dtype: Optional[datatype.dtype] = None) ->
 
 
 @export.public_api(document_under="operations/initializers")
-@constraints.interface(
-    dtype_constraints={"tensor": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"tensor": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "int32", "int64", "bool"],
     },
 )
@@ -220,9 +220,9 @@ def tril(tensor: "tripy.Tensor", diagonal: int = 0) -> "tripy.Tensor":
 
 
 @export.public_api(document_under="operations/initializers")
-@constraints.interface(
-    dtype_constraints={"tensor": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"tensor": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "int32", "int64", "bool"],
     },
 )
@@ -278,9 +278,9 @@ def triu(tensor: "tripy.Tensor", diagonal: int = 0) -> "tripy.Tensor":
 
 
 @export.public_api(document_under="operations/initializers")
-@constraints.interface(
-    dtype_constraints={"dtype": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"dtype": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "int8", "int32", "int64", "bool"],
     },
 )
@@ -343,9 +343,9 @@ def arange(
 
 
 @export.public_api(document_under="operations/initializers")
-@constraints.interface(
-    dtype_constraints={"dtype": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"dtype": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "int8", "int32", "int64", "bool"],
     },
 )
diff --git a/tripy/tripy/frontend/ops/transpose.py b/tripy/tripy/frontend/ops/transpose.py
index 91e321920..9d37ed39e 100644
--- a/tripy/tripy/frontend/ops/transpose.py
+++ b/tripy/tripy/frontend/ops/transpose.py
@@ -12,16 +12,14 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from dataclasses import dataclass
-
-from tripy import constraints, export
+from tripy import export, wrappers
 from tripy.common.exception import raise_error
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"]},
 )
 def transpose(input: "tripy.Tensor", dim0: int, dim1: int) -> "tripy.Tensor":
     """
diff --git a/tripy/tripy/frontend/ops/unsqueeze.py b/tripy/tripy/frontend/ops/unsqueeze.py
index 72eca82f7..8fce4bc3e 100644
--- a/tripy/tripy/frontend/ops/unsqueeze.py
+++ b/tripy/tripy/frontend/ops/unsqueeze.py
@@ -15,13 +15,13 @@
 # limitations under the License.
 #
 
-from tripy import constraints, export
+from tripy import export, wrappers
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"]},
 )
 def unsqueeze(input: "tripy.Tensor", dim: int) -> "tripy.Tensor":
     """
diff --git a/tripy/tripy/frontend/trace/ops/binary_elementwise.py b/tripy/tripy/frontend/trace/ops/binary_elementwise.py
index 038c69e90..2e62e07bc 100644
--- a/tripy/tripy/frontend/trace/ops/binary_elementwise.py
+++ b/tripy/tripy/frontend/trace/ops/binary_elementwise.py
@@ -18,8 +18,7 @@
 from dataclasses import dataclass
 
 import tripy.frontend.trace.ops.utils as op_utils
-import tripy.frontend.utils as frontend_utils
-from tripy import constraints, export
+from tripy import export, wrappers
 from tripy.common import datatype
 from tripy.frontend.ops.registry import register_tensor_method
 from tripy.frontend.trace.ops.base import BaseTraceOp
@@ -186,11 +185,11 @@ def to_flat_ir(self, inputs, outputs):
 
 @register_tensor_method("__add__")
 @register_tensor_method("__radd__")
-@constraints.interface(
-    dtype_constraints={"self": "T1", "other": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "int8", "int32", "int64", "bool"]},
+@wrappers.interface(
+    dtype_constraints={"self": "T1", "other": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "int8", "int32", "int64", "bool"]},
     aliases=["__radd__"],
-    convert_tensor_and_shape_likes=True,
+    convert_to_tensors=True,
 )
 def __add__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
     """
@@ -218,10 +217,10 @@ def __add__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
 
 
 @register_tensor_method("__sub__")
-@constraints.interface(
-    dtype_constraints={"self": "T1", "other": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "int8", "int32", "int64"]},
-    convert_tensor_and_shape_likes=True,
+@wrappers.interface(
+    dtype_constraints={"self": "T1", "other": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "int8", "int32", "int64"]},
+    convert_to_tensors=True,
 )
 def __sub__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
     """
@@ -249,10 +248,10 @@ def __sub__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
 
 
 @register_tensor_method("__rsub__")
-@constraints.interface(
-    dtype_constraints={"self": "T1", "other": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "int8", "int32", "int64"]},
-    convert_tensor_and_shape_likes=True,
+@wrappers.interface(
+    dtype_constraints={"self": "T1", "other": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "int8", "int32", "int64"]},
+    convert_to_tensors=True,
 )
 def __rsub__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
     """
@@ -280,10 +279,10 @@ def __rsub__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
 
 
 @register_tensor_method("__pow__")
-@constraints.interface(
-    dtype_constraints={"self": "T1", "other": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "int8"]},
-    convert_tensor_and_shape_likes=True,
+@wrappers.interface(
+    dtype_constraints={"self": "T1", "other": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "int8"]},
+    convert_to_tensors=True,
 )
 def __pow__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
     """
@@ -311,10 +310,10 @@ def __pow__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
 
 
 @register_tensor_method("__rpow__")
-@constraints.interface(
-    dtype_constraints={"self": "T1", "other": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "int8"]},
-    convert_tensor_and_shape_likes=True,
+@wrappers.interface(
+    dtype_constraints={"self": "T1", "other": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "int8"]},
+    convert_to_tensors=True,
 )
 def __rpow__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
     """
@@ -343,11 +342,11 @@ def __rpow__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
 
 @register_tensor_method("__mul__")
 @register_tensor_method("__rmul__")
-@constraints.interface(
-    dtype_constraints={"self": "T1", "other": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "int8", "int32", "int64", "bool"]},
+@wrappers.interface(
+    dtype_constraints={"self": "T1", "other": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "int8", "int32", "int64", "bool"]},
     aliases=["__rmul__"],
-    convert_tensor_and_shape_likes=True,
+    convert_to_tensors=True,
 )
 def __mul__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
     """
@@ -375,10 +374,10 @@ def __mul__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
 
 
 @register_tensor_method("__truediv__")
-@constraints.interface(
-    dtype_constraints={"self": "T1", "other": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "int8", "int32", "int64"]},
-    convert_tensor_and_shape_likes=True,
+@wrappers.interface(
+    dtype_constraints={"self": "T1", "other": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "int8", "int32", "int64"]},
+    convert_to_tensors=True,
 )
 def __truediv__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
     """
@@ -406,10 +405,10 @@ def __truediv__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
 
 
 @register_tensor_method("__rtruediv__")
-@constraints.interface(
-    dtype_constraints={"self": "T1", "other": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "int8", "int32", "int64"]},
-    convert_tensor_and_shape_likes=True,
+@wrappers.interface(
+    dtype_constraints={"self": "T1", "other": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "int8", "int32", "int64"]},
+    convert_to_tensors=True,
 )
 def __rtruediv__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
     """
@@ -437,10 +436,10 @@ def __rtruediv__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
 
 
 @register_tensor_method("__floordiv__")
-@constraints.interface(
-    dtype_constraints={"self": "T1", "other": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64"]},
-    convert_tensor_and_shape_likes=True,
+@wrappers.interface(
+    dtype_constraints={"self": "T1", "other": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64"]},
+    convert_to_tensors=True,
 )
 def __floordiv__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
     """
@@ -473,10 +472,10 @@ def __floordiv__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
 
 
 @register_tensor_method("__rfloordiv__")
-@constraints.interface(
-    dtype_constraints={"self": "T1", "other": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64"]},
-    convert_tensor_and_shape_likes=True,
+@wrappers.interface(
+    dtype_constraints={"self": "T1", "other": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64"]},
+    convert_to_tensors=True,
 )
 def __rfloordiv__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
     """
@@ -509,10 +508,10 @@ def __rfloordiv__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
 
 
 @register_tensor_method("__mod__")
-@constraints.interface(
-    dtype_constraints={"self": "T1", "other": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "float8"]},
-    convert_tensor_and_shape_likes=True,
+@wrappers.interface(
+    dtype_constraints={"self": "T1", "other": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "float8"]},
+    convert_to_tensors=True,
 )
 def __mod__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
     """
@@ -540,10 +539,10 @@ def __mod__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
 
 
 @register_tensor_method("__rmod__")
-@constraints.interface(
-    dtype_constraints={"self": "T1", "other": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "float8"]},
-    convert_tensor_and_shape_likes=True,
+@wrappers.interface(
+    dtype_constraints={"self": "T1", "other": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "float8"]},
+    convert_to_tensors=True,
 )
 def __rmod__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
     """
@@ -570,9 +569,9 @@ def __rmod__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"lhs": "T1", "rhs": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"]},
+@wrappers.interface(
+    dtype_constraints={"lhs": "T1", "rhs": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"]},
 )
 def maximum(lhs: "tripy.Tensor", rhs: "tripy.Tensor") -> "tripy.Tensor":
     """
@@ -600,9 +599,9 @@ def maximum(lhs: "tripy.Tensor", rhs: "tripy.Tensor") -> "tripy.Tensor":
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"lhs": "T1", "rhs": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"]},
+@wrappers.interface(
+    dtype_constraints={"lhs": "T1", "rhs": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"]},
 )
 def minimum(lhs: "tripy.Tensor", rhs: "tripy.Tensor") -> "tripy.Tensor":
     """
@@ -630,13 +629,13 @@ def minimum(lhs: "tripy.Tensor", rhs: "tripy.Tensor") -> "tripy.Tensor":
 
 
 @register_tensor_method("__lt__")
-@constraints.interface(
-    dtype_constraints={"self": "T1", "other": "T1", constraints.RETURN_VALUE: "T2"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"self": "T1", "other": "T1", wrappers.RETURN_VALUE: "T2"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"],
         "T2": ["bool"],
     },
-    convert_tensor_and_shape_likes=True,
+    convert_to_tensors=True,
 )
 def __lt__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
     """
@@ -664,13 +663,13 @@ def __lt__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
 
 
 @register_tensor_method("__le__")
-@constraints.interface(
-    dtype_constraints={"self": "T1", "other": "T1", constraints.RETURN_VALUE: "T2"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"self": "T1", "other": "T1", wrappers.RETURN_VALUE: "T2"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"],
         "T2": ["bool"],
     },
-    convert_tensor_and_shape_likes=True,
+    convert_to_tensors=True,
 )
 def __le__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
     """
@@ -698,13 +697,13 @@ def __le__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
 
 
 @register_tensor_method("__eq__")
-@constraints.interface(
-    dtype_constraints={"self": "T1", "other": "T1", constraints.RETURN_VALUE: "T2"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"self": "T1", "other": "T1", wrappers.RETURN_VALUE: "T2"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"],
         "T2": ["bool"],
     },
-    convert_tensor_and_shape_likes=True,
+    convert_to_tensors=True,
 )
 def __eq__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
     """
@@ -732,13 +731,13 @@ def __eq__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
 
 
 @register_tensor_method("__ne__")
-@constraints.interface(
-    dtype_constraints={"self": "T1", "other": "T1", constraints.RETURN_VALUE: "T2"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"self": "T1", "other": "T1", wrappers.RETURN_VALUE: "T2"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"],
         "T2": ["bool"],
     },
-    convert_tensor_and_shape_likes=True,
+    convert_to_tensors=True,
 )
 def __ne__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
     """
@@ -766,13 +765,13 @@ def __ne__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
 
 
 @register_tensor_method("__ge__")
-@constraints.interface(
-    dtype_constraints={"self": "T1", "other": "T1", constraints.RETURN_VALUE: "T2"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"self": "T1", "other": "T1", wrappers.RETURN_VALUE: "T2"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"],
         "T2": ["bool"],
     },
-    convert_tensor_and_shape_likes=True,
+    convert_to_tensors=True,
 )
 def __ge__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
     """
@@ -800,13 +799,13 @@ def __ge__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
 
 
 @register_tensor_method("__gt__")
-@constraints.interface(
-    dtype_constraints={"self": "T1", "other": "T1", constraints.RETURN_VALUE: "T2"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"self": "T1", "other": "T1", wrappers.RETURN_VALUE: "T2"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"],
         "T2": ["bool"],
     },
-    convert_tensor_and_shape_likes=True,
+    convert_to_tensors=True,
 )
 def __gt__(self: "tripy.Tensor", other: TensorLike) -> "tripy.Tensor":
     """
diff --git a/tripy/tripy/frontend/trace/ops/cast.py b/tripy/tripy/frontend/trace/ops/cast.py
index 1cb5a3c74..7d45c198a 100644
--- a/tripy/tripy/frontend/trace/ops/cast.py
+++ b/tripy/tripy/frontend/trace/ops/cast.py
@@ -17,7 +17,7 @@
 
 from dataclasses import dataclass
 
-from tripy import constraints, export
+from tripy import export, wrappers
 from tripy.frontend.trace.ops import utils as op_utils
 from tripy.frontend.trace.ops.base import BaseTraceOp
 
@@ -91,9 +91,9 @@ def to_flat_ir(self, inputs, outputs):
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", "dtype": "T2", constraints.RETURN_VALUE: "T2"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"input": "T1", "dtype": "T2", wrappers.RETURN_VALUE: "T2"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"],
         "T2": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"],
     },
diff --git a/tripy/tripy/frontend/trace/ops/concatenate.py b/tripy/tripy/frontend/trace/ops/concatenate.py
index 2f917a7e9..04d1dfe22 100644
--- a/tripy/tripy/frontend/trace/ops/concatenate.py
+++ b/tripy/tripy/frontend/trace/ops/concatenate.py
@@ -18,7 +18,7 @@
 from dataclasses import dataclass
 from typing import Sequence
 
-from tripy import constraints, export
+from tripy import export, wrappers
 from tripy.common.exception import raise_error
 from tripy.frontend.trace.ops.base import BaseTraceOp
 import tripy.frontend.trace.ops.utils as op_utils
@@ -42,9 +42,9 @@ def to_flat_ir(self, inputs, outputs):
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"tensors": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"tensors": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"],
     },
 )
diff --git a/tripy/tripy/frontend/trace/ops/convolution.py b/tripy/tripy/frontend/trace/ops/convolution.py
index 4582d096e..f40a70880 100644
--- a/tripy/tripy/frontend/trace/ops/convolution.py
+++ b/tripy/tripy/frontend/trace/ops/convolution.py
@@ -19,7 +19,7 @@
 from dataclasses import dataclass
 
 import tripy.frontend.trace.ops.utils as op_utils
-from tripy import constraints
+from tripy import wrappers
 from tripy.frontend.trace.ops.base import BaseTraceOp
 
 
@@ -50,9 +50,9 @@ def to_flat_ir(self, inputs, outputs):
         )
 
 
-@constraints.interface(
-    dtype_constraints={"input": "T1", "weight": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"input": "T1", "weight": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16"],
     },
 )
diff --git a/tripy/tripy/frontend/trace/ops/copy.py b/tripy/tripy/frontend/trace/ops/copy.py
index 83435101f..bb26202d0 100644
--- a/tripy/tripy/frontend/trace/ops/copy.py
+++ b/tripy/tripy/frontend/trace/ops/copy.py
@@ -18,7 +18,7 @@
 from dataclasses import dataclass
 
 import tripy.frontend.trace.ops.utils as op_utils
-from tripy import constraints, export
+from tripy import export, wrappers
 from tripy.common.device import device
 from tripy.frontend.trace.ops.base import BaseTraceOp
 
@@ -39,9 +39,9 @@ def to_flat_ir(self, inputs, outputs):
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"],
     },
 )
diff --git a/tripy/tripy/frontend/trace/ops/dequantize.py b/tripy/tripy/frontend/trace/ops/dequantize.py
index e22dfb5ca..9f379703b 100644
--- a/tripy/tripy/frontend/trace/ops/dequantize.py
+++ b/tripy/tripy/frontend/trace/ops/dequantize.py
@@ -20,9 +20,8 @@
 from typing import Any, Sequence, Union
 
 import tripy.frontend.trace.ops.utils as op_utils
-from tripy import constraints, export
+from tripy import export, wrappers
 from tripy.common import datatype
-from tripy.frontend import utils as frontend_utils
 from tripy.frontend.trace.ops import utils as op_utils
 from tripy.frontend.trace.ops.base import BaseTraceOp
 import tripy.frontend.trace.ops.utils as op_utils
@@ -104,10 +103,10 @@ def to_flat_ir(self, inputs, outputs):
 
 
 @export.public_api(document_under="operations/quantization")
-@constraints.interface(
-    dtype_constraints={"input": "T1", "scale": "T2", "dtype": "T2", constraints.RETURN_VALUE: "T2"},
-    variables={"T1": ["int4", "int8", "float8"], "T2": ["float32", "float16", "bfloat16"]},
-    convert_tensor_and_shape_likes={"scale"},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", "scale": "T2", "dtype": "T2", wrappers.RETURN_VALUE: "T2"},
+    dtype_variables={"T1": ["int4", "int8", "float8"], "T2": ["float32", "float16", "bfloat16"]},
+    convert_to_tensors={"scale"},
 )
 def dequantize(
     input: "tripy.Tensor",
diff --git a/tripy/tripy/frontend/trace/ops/expand.py b/tripy/tripy/frontend/trace/ops/expand.py
index f43dff075..87adae404 100644
--- a/tripy/tripy/frontend/trace/ops/expand.py
+++ b/tripy/tripy/frontend/trace/ops/expand.py
@@ -16,11 +16,9 @@
 #
 
 from dataclasses import dataclass
-from typing import Optional
 
-from tripy import constraints, export
+from tripy import export, wrappers
 from tripy.common.exception import raise_error
-from tripy.frontend import utils as frontend_utils
 from tripy.frontend.trace.ops import utils as op_utils
 from tripy.frontend.trace.ops.base import BaseTraceOp
 from tripy.types import ShapeLike
@@ -73,12 +71,12 @@ def process_sizes(input: "tripy.Tensor", sizes: ShapeLike):
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "float8", "int8", "int32", "int64", "bool"],
     },
-    convert_tensor_and_shape_likes=True,
+    convert_to_tensors=True,
     conversion_preprocess_func=process_sizes,
 )
 def expand(input: "tripy.Tensor", sizes: ShapeLike) -> "tripy.Tensor":
diff --git a/tripy/tripy/frontend/trace/ops/fill.py b/tripy/tripy/frontend/trace/ops/fill.py
index f142f5d43..b4a92d856 100644
--- a/tripy/tripy/frontend/trace/ops/fill.py
+++ b/tripy/tripy/frontend/trace/ops/fill.py
@@ -20,7 +20,7 @@
 
 import tripy.frontend.trace.ops.utils as op_utils
 import tripy.frontend.utils as frontend_utils
-from tripy import constraints, export, utils
+from tripy import export, utils, wrappers
 from tripy.common import datatype
 from tripy.frontend.trace.ops import utils as op_utils
 from tripy.frontend.trace.ops.base import BaseTraceOp
@@ -69,12 +69,12 @@ def to_flat_ir(self, inputs, outputs):
 
 
 @export.public_api(document_under="operations/initializers")
-@constraints.interface(
-    dtype_constraints={"dtype": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"dtype": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"],
     },
-    convert_tensor_and_shape_likes=True,
+    convert_to_tensors=True,
 )
 def full(shape: ShapeLike, value: TensorLike, dtype: "tripy.dtype" = datatype.float32) -> "tripy.Tensor":
     """
@@ -100,13 +100,13 @@ def full(shape: ShapeLike, value: TensorLike, dtype: "tripy.dtype" = datatype.fl
 
 
 @export.public_api(document_under="operations/initializers")
-@constraints.interface(
-    dtype_constraints={"input": "T1", "dtype": "T2", constraints.RETURN_VALUE: "T2"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"input": "T1", "dtype": "T2", wrappers.RETURN_VALUE: "T2"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"],
         "T2": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"],
     },
-    convert_tensor_and_shape_likes=True,
+    convert_to_tensors=True,
 )
 def full_like(input: "tripy.Tensor", value: TensorLike, dtype: Optional["tripy.dtype"] = None) -> "tripy.Tensor":
     """
diff --git a/tripy/tripy/frontend/trace/ops/flip.py b/tripy/tripy/frontend/trace/ops/flip.py
index 264bcf2fc..0bc85d9f4 100644
--- a/tripy/tripy/frontend/trace/ops/flip.py
+++ b/tripy/tripy/frontend/trace/ops/flip.py
@@ -18,7 +18,7 @@
 from dataclasses import dataclass
 from typing import Optional, Sequence, Union
 
-from tripy import export, utils, constraints
+from tripy import export, utils, wrappers
 from tripy.common.exception import raise_error
 from tripy.frontend.trace.ops.base import BaseTraceOp
 from tripy.frontend.trace.ops import utils as op_utils
@@ -37,9 +37,9 @@ def to_flat_ir(self, inputs, outputs):
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "int32", "int64", "bool"],
     },
 )
diff --git a/tripy/tripy/frontend/trace/ops/gather.py b/tripy/tripy/frontend/trace/ops/gather.py
index 302de7ea7..0e8529ac9 100644
--- a/tripy/tripy/frontend/trace/ops/gather.py
+++ b/tripy/tripy/frontend/trace/ops/gather.py
@@ -18,7 +18,7 @@
 from dataclasses import dataclass
 
 import tripy.frontend.trace.ops.utils as op_utils
-from tripy import constraints, export, utils
+from tripy import export, utils, wrappers
 from tripy.frontend.trace.ops.base import BaseTraceOp
 
 
@@ -88,9 +88,9 @@ def to_flat_ir(self, inputs, outputs):
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", "index": "T2", constraints.RETURN_VALUE: "T1"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"input": "T1", "index": "T2", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={
         "T1": ["float8", "float32", "float16", "bfloat16", "int4", "int8", "int32", "int64", "bool"],
         "T2": ["int32"],
     },
diff --git a/tripy/tripy/frontend/trace/ops/iota.py b/tripy/tripy/frontend/trace/ops/iota.py
index 14a99ac6a..41e104df1 100644
--- a/tripy/tripy/frontend/trace/ops/iota.py
+++ b/tripy/tripy/frontend/trace/ops/iota.py
@@ -19,7 +19,7 @@
 from typing import Optional
 
 import tripy.frontend.trace.ops.utils as op_utils
-from tripy import constraints, export, utils
+from tripy import export, utils, wrappers
 from tripy.common import datatype
 from tripy.frontend import utils as frontend_utils
 from tripy.frontend.trace.ops.base import BaseTraceOp
@@ -61,12 +61,12 @@ def iota_impl(shape: "tripy.Tensor", dim: int, dtype: datatype.dtype, output_ran
 
 
 @export.public_api(document_under="operations/initializers")
-@constraints.interface(
-    dtype_constraints={"dtype": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"dtype": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"],
     },
-    convert_tensor_and_shape_likes=True,
+    convert_to_tensors=True,
     conversion_preprocess_func=lambda shape, dim=None, dtype=None: (
         {"dim": frontend_utils.process_dim(dim, len(shape))} if dim is not None else {}
     ),
@@ -96,9 +96,9 @@ def iota(shape: ShapeLike, dim: int = 0, dtype: datatype.dtype = datatype.float3
 
 
 @export.public_api(document_under="operations/initializers")
-@constraints.interface(
-    dtype_constraints={"input": "T1", "dtype": "T2", constraints.RETURN_VALUE: "T2"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"input": "T1", "dtype": "T2", wrappers.RETURN_VALUE: "T2"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"],
         "T2": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"],
     },
diff --git a/tripy/tripy/frontend/trace/ops/matmul.py b/tripy/tripy/frontend/trace/ops/matmul.py
index de7b37b44..321998d85 100644
--- a/tripy/tripy/frontend/trace/ops/matmul.py
+++ b/tripy/tripy/frontend/trace/ops/matmul.py
@@ -19,7 +19,7 @@
 from typing import Dict, List
 
 import tripy.frontend.trace.ops.utils as op_utils
-from tripy import constraints
+from tripy import wrappers
 from tripy.common.exception import raise_error
 from tripy.frontend.ops.registry import register_tensor_method
 from tripy.frontend.trace.ops.base import BaseTraceOp
@@ -149,9 +149,9 @@ def append_ones_data_tensor(input, nb_ones):
 
 
 @register_tensor_method("__matmul__")
-@constraints.interface(
-    dtype_constraints={"self": "T1", "other": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "int32"]},
+@wrappers.interface(
+    dtype_constraints={"self": "T1", "other": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "int32"]},
 )
 def __matmul__(self: "tripy.Tensor", other: "tripy.Tensor") -> "tripy.Tensor":
     """
diff --git a/tripy/tripy/frontend/trace/ops/pad.py b/tripy/tripy/frontend/trace/ops/pad.py
index f15d3ae8a..feb14caba 100644
--- a/tripy/tripy/frontend/trace/ops/pad.py
+++ b/tripy/tripy/frontend/trace/ops/pad.py
@@ -18,7 +18,7 @@
 from dataclasses import dataclass
 from typing import Sequence, Union
 
-from tripy import constraints, export
+from tripy import export, wrappers
 from tripy.common.exception import raise_error
 from tripy.frontend import utils as frontend_utils
 from tripy.frontend.trace.ops.base import BaseTraceOp
@@ -73,9 +73,9 @@ def to_flat_ir(self, inputs, outputs):
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bool", "int32"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bool", "int32"]},
 )
 def pad(
     input: "tripy.Tensor", pad: Sequence[ShapeLike], mode: str = "constant", value: Union[int, float] = 0
diff --git a/tripy/tripy/frontend/trace/ops/permute.py b/tripy/tripy/frontend/trace/ops/permute.py
index b2ffe2971..120175858 100644
--- a/tripy/tripy/frontend/trace/ops/permute.py
+++ b/tripy/tripy/frontend/trace/ops/permute.py
@@ -18,7 +18,7 @@
 from dataclasses import dataclass
 from typing import Sequence
 
-from tripy import constraints, export
+from tripy import export, wrappers
 from tripy.common.exception import raise_error
 from tripy.frontend.trace.ops import utils as op_utils
 from tripy.frontend.trace.ops.base import BaseTraceOp
@@ -37,9 +37,9 @@ def to_flat_ir(self, inputs, outputs):
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"]},
 )
 def permute(input: "tripy.Tensor", perm: Sequence[int]) -> "tripy.Tensor":
     """
diff --git a/tripy/tripy/frontend/trace/ops/pooling.py b/tripy/tripy/frontend/trace/ops/pooling.py
index d88c7199c..efecee59c 100644
--- a/tripy/tripy/frontend/trace/ops/pooling.py
+++ b/tripy/tripy/frontend/trace/ops/pooling.py
@@ -19,7 +19,7 @@
 from dataclasses import dataclass
 from typing import Optional, Sequence, Tuple
 
-from tripy import constraints, export, utils
+from tripy import export, utils, wrappers
 from tripy.common.exception import raise_error
 from tripy.frontend.trace.ops import utils as op_utils
 from tripy.frontend.trace.ops.base import BaseTraceOp
@@ -139,9 +139,9 @@ def to_flat_ir(self, inputs, outputs):
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "int8"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "int8"]},
 )
 def maxpool(
     input: "tripy.Tensor",
@@ -198,9 +198,9 @@ def maxpool(
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "int8"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "int8"]},
 )
 def avgpool(
     input: "tripy.Tensor",
diff --git a/tripy/tripy/frontend/trace/ops/quantize.py b/tripy/tripy/frontend/trace/ops/quantize.py
index 0c1a846b6..2467ea3c5 100644
--- a/tripy/tripy/frontend/trace/ops/quantize.py
+++ b/tripy/tripy/frontend/trace/ops/quantize.py
@@ -19,9 +19,8 @@
 from dataclasses import dataclass
 from typing import Any, Sequence, Union
 
-from tripy import constraints, export
+from tripy import export, wrappers
 from tripy.common import datatype
-from tripy.frontend import utils as frontend_utils
 from tripy.frontend.trace.ops import utils as op_utils
 from tripy.frontend.trace.ops.base import BaseTraceOp
 
@@ -131,10 +130,10 @@ def to_flat_ir(self, inputs, outputs):
 
 
 @export.public_api(document_under="operations/quantization")
-@constraints.interface(
-    dtype_constraints={"input": "T1", "scale": "T1", "dtype": "T2", constraints.RETURN_VALUE: "T2"},
-    variables={"T1": ["float32", "float16", "bfloat16"], "T2": ["int4", "int8", "float8"]},
-    convert_tensor_and_shape_likes={"scale"},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", "scale": "T1", "dtype": "T2", wrappers.RETURN_VALUE: "T2"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16"], "T2": ["int4", "int8", "float8"]},
+    convert_to_tensors={"scale"},
 )
 def quantize(
     input: "tripy.Tensor",
diff --git a/tripy/tripy/frontend/trace/ops/reduce.py b/tripy/tripy/frontend/trace/ops/reduce.py
index 490370814..d5f2144de 100644
--- a/tripy/tripy/frontend/trace/ops/reduce.py
+++ b/tripy/tripy/frontend/trace/ops/reduce.py
@@ -20,8 +20,7 @@
 from dataclasses import dataclass
 from typing import Optional, Sequence, Union
 
-import tripy.frontend.trace.ops.utils as op_utils
-from tripy import constraints, export
+from tripy import export, wrappers
 from tripy.common import datatype
 from tripy.frontend.trace.ops.base import BaseTraceOp
 from tripy.utils import make_list
@@ -133,9 +132,9 @@ def _reduce_impl(input: "tripy.Tensor", kind: Reduce.Kind, dim: Union[int, Seque
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "int32", "int64", "float16", "bfloat16"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "int32", "int64", "float16", "bfloat16"]},
 )
 def sum(
     input: "tripy.Tensor", dim: Optional[Union[int, Sequence[int]]] = None, keepdim: bool = False
@@ -166,9 +165,9 @@ def sum(
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["bool"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["bool"]},
 )
 def all(
     input: "tripy.Tensor", dim: Optional[Union[int, Sequence[int]]] = None, keepdim: bool = False
@@ -198,9 +197,9 @@ def all(
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["bool"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["bool"]},
 )
 def any(
     input: "tripy.Tensor", dim: Optional[Union[int, Sequence[int]]] = None, keepdim: bool = False
@@ -230,9 +229,9 @@ def any(
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "int32", "int64", "float16", "bfloat16"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "int32", "int64", "float16", "bfloat16"]},
 )
 def max(
     input: "tripy.Tensor", dim: Optional[Union[int, Sequence[int]]] = None, keepdim: bool = False
@@ -263,9 +262,9 @@ def max(
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "int32", "int64", "float16", "bfloat16"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "int32", "int64", "float16", "bfloat16"]},
 )
 def prod(
     input: "tripy.Tensor", dim: Optional[Union[int, Sequence[int]]] = None, keepdim: bool = False
@@ -317,9 +316,9 @@ def mean_impl(tensor: "tripy.Tensor", dim: Union[int, Sequence] = None, keepdim:
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "int32", "int64", "float16", "bfloat16"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "int32", "int64", "float16", "bfloat16"]},
 )
 def mean(
     input: "tripy.Tensor", dim: Optional[Union[int, Sequence[int]]] = None, keepdim: bool = False
@@ -350,9 +349,9 @@ def mean(
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16"]},
 )
 def var(
     input: "tripy.Tensor", dim: Optional[Union[int, Sequence[int]]] = None, keepdim: bool = False, correction: int = 1
@@ -417,9 +416,9 @@ def _arg_min_max_impl(tensor: "tripy.Tensor", kind: ArgMinMax.Kind, dim: Optiona
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T2"},
-    variables={"T1": ["float32", "float16", "bfloat16", "int32"], "T2": ["int32"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T2"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "int32"], "T2": ["int32"]},
 )
 def argmax(input: "tripy.Tensor", dim: Optional[int] = None, keepdim: bool = False) -> "tripy.Tensor":
     """
@@ -449,9 +448,9 @@ def argmax(input: "tripy.Tensor", dim: Optional[int] = None, keepdim: bool = Fal
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T2"},
-    variables={"T1": ["float32", "float16", "bfloat16", "int32"], "T2": ["int32"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T2"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "int32"], "T2": ["int32"]},
 )
 def argmin(input: "tripy.Tensor", dim: Optional[int] = None, keepdim: bool = False) -> "tripy.Tensor":
     """
diff --git a/tripy/tripy/frontend/trace/ops/reshape.py b/tripy/tripy/frontend/trace/ops/reshape.py
index bd4b6caac..4061adff7 100644
--- a/tripy/tripy/frontend/trace/ops/reshape.py
+++ b/tripy/tripy/frontend/trace/ops/reshape.py
@@ -18,9 +18,8 @@
 import math
 from dataclasses import dataclass
 
-from tripy import constraints, export
+from tripy import export, wrappers
 from tripy.common.exception import raise_error
-from tripy.frontend import utils as frontend_utils
 from tripy.frontend.trace.ops import utils as op_utils
 from tripy.frontend.trace.ops.base import BaseTraceOp
 from tripy.types import ShapeLike
@@ -61,10 +60,10 @@ def infer_dimensions(input: "tripy.Tensor", shape: ShapeLike) -> ShapeLike:
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"]},
-    convert_tensor_and_shape_likes=True,
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"]},
+    convert_to_tensors=True,
     conversion_preprocess_func=infer_dimensions,
 )
 def reshape(input: "tripy.Tensor", shape: ShapeLike) -> "tripy.Tensor":
diff --git a/tripy/tripy/frontend/trace/ops/resize.py b/tripy/tripy/frontend/trace/ops/resize.py
index 90ca64753..0e7317241 100644
--- a/tripy/tripy/frontend/trace/ops/resize.py
+++ b/tripy/tripy/frontend/trace/ops/resize.py
@@ -19,7 +19,7 @@
 from dataclasses import dataclass
 from typing import Optional, Sequence
 
-from tripy import constraints, export
+from tripy import export, wrappers
 from tripy.common.exception import raise_error
 from tripy.frontend import utils as frontend_utils
 from tripy.frontend.trace.ops.base import BaseTraceOp
@@ -105,10 +105,10 @@ def _check_mode(mode: str, align_corners: bool):
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "int8"]},
-    convert_tensor_and_shape_likes=True,
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "int8"]},
+    convert_to_tensors=True,
 )
 def resize(input: "tripy.Tensor", mode: str, output_shape: ShapeLike, align_corners: bool = False) -> "tripy.Tensor":
     r"""
@@ -143,9 +143,9 @@ def resize(input: "tripy.Tensor", mode: str, output_shape: ShapeLike, align_corn
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "int8"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "int8"]},
 )
 def resize(
     input: "tripy.Tensor", mode: str, scales: Sequence[numbers.Number], align_corners: bool = False
diff --git a/tripy/tripy/frontend/trace/ops/shape.py b/tripy/tripy/frontend/trace/ops/shape.py
index 90edc4c40..2e86ce469 100644
--- a/tripy/tripy/frontend/trace/ops/shape.py
+++ b/tripy/tripy/frontend/trace/ops/shape.py
@@ -17,7 +17,7 @@
 
 from dataclasses import dataclass
 
-from tripy import constraints
+from tripy import wrappers
 from tripy.common.datatype import DATA_TYPES
 from tripy.frontend.ops.registry import register_tensor_method
 from tripy.frontend.trace.ops.base import BaseTraceOp
@@ -44,7 +44,7 @@ def to_flat_ir(self, inputs, outputs):
 
 @register_tensor_method("shape")
 @property
-@constraints.interface(dtype_constraints={"self": "T1"}, variables={"T1": list(DATA_TYPES.keys())})
+@wrappers.interface(dtype_constraints={"self": "T1"}, dtype_variables={"T1": list(DATA_TYPES.keys())})
 def shape(self: "tripy.Tensor") -> ShapeLike:
     """
     Represents the shape of the tensor.
diff --git a/tripy/tripy/frontend/trace/ops/slice.py b/tripy/tripy/frontend/trace/ops/slice.py
index 95066f5a4..67a09830c 100644
--- a/tripy/tripy/frontend/trace/ops/slice.py
+++ b/tripy/tripy/frontend/trace/ops/slice.py
@@ -18,9 +18,8 @@
 from dataclasses import dataclass
 from typing import Sequence, Union
 
-from tripy import constraints, utils
+from tripy import utils, wrappers
 from tripy.common.exception import raise_error
-from tripy.frontend import utils as frontend_utils
 from tripy.frontend.ops.registry import register_tensor_method
 from tripy.frontend.trace.ops import utils as op_utils
 from tripy.frontend.trace.ops.base import BaseTraceOp
@@ -130,9 +129,9 @@ def adjust_start(start_bound, end_bound):
 
 
 @register_tensor_method("__getitem__")
-@constraints.interface(
-    dtype_constraints={"self": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"]},
+@wrappers.interface(
+    dtype_constraints={"self": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"]},
 )
 def __getitem__(
     self: "tripy.Tensor", index: Union[slice, int, "tripy.Tensor", Sequence[Union[slice, int, "tripy.Tensor"]]]
@@ -259,7 +258,7 @@ def clamp_bound(bound: Union[int, Tensor]) -> Union[int, Tensor]:
     return out
 
 
-@constraints.interface(convert_tensor_and_shape_likes=True)
+@wrappers.interface(convert_to_tensors=True)
 def slice_helper(tensor, *slice_params: TensorLike):
     from tripy import function_registry
     from tripy.utils import get_arg_candidate_column_offsets
diff --git a/tripy/tripy/frontend/trace/ops/split.py b/tripy/tripy/frontend/trace/ops/split.py
index b1cb2f706..136a5dfdb 100644
--- a/tripy/tripy/frontend/trace/ops/split.py
+++ b/tripy/tripy/frontend/trace/ops/split.py
@@ -18,7 +18,7 @@
 from dataclasses import dataclass
 from typing import Sequence, Union
 
-from tripy import constraints, export, utils
+from tripy import export, utils, wrappers
 from tripy.common.exception import raise_error
 from tripy.frontend.trace.ops import utils as op_utils
 from tripy.frontend.trace.ops.base import BaseTraceOp
@@ -174,9 +174,9 @@ def __str__(self) -> str:
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"],
     },
 )
diff --git a/tripy/tripy/frontend/trace/ops/squeeze.py b/tripy/tripy/frontend/trace/ops/squeeze.py
index 03a14c489..9d8cdaefe 100644
--- a/tripy/tripy/frontend/trace/ops/squeeze.py
+++ b/tripy/tripy/frontend/trace/ops/squeeze.py
@@ -15,7 +15,7 @@
 from dataclasses import dataclass
 from typing import Tuple, Union
 
-from tripy import constraints, export, utils
+from tripy import export, utils, wrappers
 from tripy.frontend.trace.ops import utils as op_utils
 from tripy.frontend.trace.ops.base import BaseTraceOp
 
@@ -50,9 +50,9 @@ def to_flat_ir(self, inputs, outputs):
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "float8", "int8", "int32", "int64", "bool"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "float8", "int8", "int32", "int64", "bool"]},
 )
 def squeeze(input: "tripy.Tensor", dims: Union[Tuple, int]) -> "tripy.Tensor":
     """
diff --git a/tripy/tripy/frontend/trace/ops/unary_elementwise.py b/tripy/tripy/frontend/trace/ops/unary_elementwise.py
index bdc0c6bf0..fc334b35f 100644
--- a/tripy/tripy/frontend/trace/ops/unary_elementwise.py
+++ b/tripy/tripy/frontend/trace/ops/unary_elementwise.py
@@ -18,7 +18,7 @@
 import enum
 from dataclasses import dataclass
 
-from tripy import export, constraints
+from tripy import export, wrappers
 from tripy.frontend.trace.ops.base import BaseTraceOp
 import tripy.frontend.trace.ops.utils as op_utils
 
@@ -59,9 +59,9 @@ def to_flat_ir(self, inputs, outputs):
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16"]},
 )
 def exp(input: "tripy.Tensor") -> "tripy.Tensor":
     r"""
@@ -88,9 +88,9 @@ def exp(input: "tripy.Tensor") -> "tripy.Tensor":
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16"]},
 )
 def tanh(input: "tripy.Tensor") -> "tripy.Tensor":
     """
@@ -115,9 +115,9 @@ def tanh(input: "tripy.Tensor") -> "tripy.Tensor":
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16"]},
 )
 def sin(input: "tripy.Tensor") -> "tripy.Tensor":
     """
@@ -142,9 +142,9 @@ def sin(input: "tripy.Tensor") -> "tripy.Tensor":
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16"]},
 )
 def cos(input: "tripy.Tensor") -> "tripy.Tensor":
     """
@@ -169,9 +169,9 @@ def cos(input: "tripy.Tensor") -> "tripy.Tensor":
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "float8"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "float8"]},
 )
 def rsqrt(input: "tripy.Tensor") -> "tripy.Tensor":
     """
@@ -196,9 +196,9 @@ def rsqrt(input: "tripy.Tensor") -> "tripy.Tensor":
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "float8"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "float8"]},
 )
 def sqrt(input: "tripy.Tensor") -> "tripy.Tensor":
     """
@@ -223,9 +223,9 @@ def sqrt(input: "tripy.Tensor") -> "tripy.Tensor":
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16"]},
 )
 def log(input: "tripy.Tensor") -> "tripy.Tensor":
     """
@@ -250,9 +250,9 @@ def log(input: "tripy.Tensor") -> "tripy.Tensor":
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={"T1": ["float32", "float16", "bfloat16", "int8", "int32", "int64"]},
+@wrappers.interface(
+    dtype_constraints={"input": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "int8", "int32", "int64"]},
 )
 def abs(input: "tripy.Tensor") -> "tripy.Tensor":
     r"""
diff --git a/tripy/tripy/frontend/trace/ops/where.py b/tripy/tripy/frontend/trace/ops/where.py
index 5f20f72f9..44415fa3e 100644
--- a/tripy/tripy/frontend/trace/ops/where.py
+++ b/tripy/tripy/frontend/trace/ops/where.py
@@ -19,7 +19,7 @@
 from dataclasses import dataclass
 
 import tripy.frontend.trace.ops.utils as op_utils
-from tripy import constraints, export
+from tripy import export, wrappers
 from tripy.frontend.trace.ops.base import BaseTraceOp
 
 
@@ -91,9 +91,9 @@ def to_flat_ir(self, inputs, outputs):
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"condition": "T2", "input": "T1", "other": "T1", constraints.RETURN_VALUE: "T1"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"condition": "T2", "input": "T1", "other": "T1", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"],
         "T2": ["bool"],
     },
@@ -130,9 +130,9 @@ def where(condition: "tripy.Tensor", input: "tripy.Tensor", other: "tripy.Tensor
 
 
 @export.public_api(document_under="operations/functions")
-@constraints.interface(
-    dtype_constraints={"input": "T1", "mask": "T2", constraints.RETURN_VALUE: "T1"},
-    variables={
+@wrappers.interface(
+    dtype_constraints={"input": "T1", "mask": "T2", wrappers.RETURN_VALUE: "T1"},
+    dtype_variables={
         "T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"],
         "T2": ["bool"],
     },
diff --git a/tripy/tripy/utils/stack_info.py b/tripy/tripy/utils/stack_info.py
index d037a2bda..addd4c114 100644
--- a/tripy/tripy/utils/stack_info.py
+++ b/tripy/tripy/utils/stack_info.py
@@ -140,6 +140,6 @@ def get_module_names_to_exclude_from_stack_info():
     or trying to retrieve column information from code.
     """
     import tripy.function_registry
-    import tripy.constraints
+    import tripy.wrappers
 
-    return {mod.__name__ for mod in [tripy.function_registry, tripy.constraints]}
+    return {mod.__name__ for mod in [tripy.function_registry, tripy.wrappers]}
diff --git a/tripy/tripy/constraints.py b/tripy/tripy/wrappers.py
similarity index 94%
rename from tripy/tripy/constraints.py
rename to tripy/tripy/wrappers.py
index e1db4b409..2fe0d4f05 100644
--- a/tripy/tripy/constraints.py
+++ b/tripy/tripy/wrappers.py
@@ -224,10 +224,10 @@ def add_arg(arg):
 
 def interface(
     dtype_constraints: Dict[str, str] = {},
-    variables: Dict[str, List[str]] = {},
+    dtype_variables: Dict[str, List[str]] = {},
     dtype_exceptions: List[Dict[str, str]] = [],
     aliases: List[str] = [],
-    convert_tensor_and_shape_likes: Union[bool, Set[str]] = False,
+    convert_to_tensors: Union[bool, Set[str]] = False,
     conversion_preprocess_func: Optional[Callable] = None,
 ):
     """
@@ -242,11 +242,11 @@ def interface(
 
     Args:
         dtype_constraints: Maps parameters and return values to data type constraint variables.
-            Use the special value `constraints.RETURN_VALUE` to denote return values.
+            Use the special value `wrappers.RETURN_VALUE` to denote return values.
             For example:
-                {"input": "T1", "other": T2, constraints.RETURN_VALUE: "T1"}
+                {"input": "T1", "other": T2, wrappers.RETURN_VALUE: "T1"}
 
-        variables: Maps data type constraints variables to their supported data types.
+        dtype_variables: Maps data type constraints variables to their supported data types.
             For example:
                 {"T1": ["float32", "float16"], "T2": ["int32", "int64"]}
 
@@ -260,7 +260,7 @@ def interface(
             (e.g. `__add__` and `__radd__`), this will enable type information to be added to the
             documentation for the aliases as well.
 
-        convert_tensor_and_shape_likes: If False or an empty set, no argument types will be converted.
+        convert_to_tensors: If False or an empty set, no argument types will be converted.
             If True, all arguments with the `TensorLike` or `ShapeLike` annotations will be
             converted into `Tensor`s or, whenever possible, `DimensionSize`. If the argument
             is a set of argument names, conversions will be done only for those arguments.
@@ -268,7 +268,7 @@ def interface(
             The conversions will respect any datatype constraints, casting the `TensorLike` values as necessary,
             but will raise an exception for lossy casts like float to int (but *not* for, e.g., `float32` to `float16`).
 
-        conversion_preprocess_func: If `convert_tensor_and_shape_likes` is true, this argument is a callback that is
+        conversion_preprocess_func: If `convert_to_tensors` is true, this argument is a callback that is
             used to preprocess the arguments before potential conversion. In this case, if provided, the callback
             will be called regardless of whether the decorator performs any conversions.
 
@@ -282,18 +282,18 @@ def decorator(func):
 
         return_dtype = dtype_constraints.get(RETURN_VALUE, None)
         VerifInfo = namedtuple("VerifInfo", ["obj", "inputs", "exceptions", "return_dtype", "dtypes", "constraints"])
-        verif_info = VerifInfo(func, {}, dtype_exceptions, return_dtype, variables, dtype_constraints)
+        verif_info = VerifInfo(func, {}, dtype_exceptions, return_dtype, dtype_variables, dtype_constraints)
 
         signature = inspect.signature(func)
         conversion_targets = (
-            convert_tensor_and_shape_likes
-            if isinstance(convert_tensor_and_shape_likes, Set)
+            convert_to_tensors
+            if isinstance(convert_to_tensors, Set)
             else {name for name, param in signature.parameters.items() if param.annotation in {TensorLike, ShapeLike}}
         )
         shape_likes = {name for name, param in signature.parameters.items() if param.annotation is ShapeLike}
 
         # if no dtype constraints have been specified at all, do not add to the table so we don't generate invalid tests
-        if dtype_constraints or variables or dtype_exceptions:
+        if dtype_constraints or dtype_variables or dtype_exceptions:
             for key in [func.__qualname__] + aliases:
                 TYPE_VERIFICATION[key] = verif_info
 
@@ -301,7 +301,7 @@ def decorator(func):
         def wrapper(*args, **kwargs):
             merged_args, var_arg_info = utils.merge_function_arguments(func, *args, **kwargs)
 
-            if convert_tensor_and_shape_likes:
+            if convert_to_tensors:
                 args, kwargs, merged_args = convert_input_types(
                     func,
                     args,
@@ -339,7 +339,7 @@ def wrapper(*args, **kwargs):
                     arg_dtype = arg_dtype.value
 
                     # Check if the type is supported at all
-                    supported_dtypes = variables[type_var]
+                    supported_dtypes = dtype_variables[type_var]
                     if arg_dtype.name not in supported_dtypes:
                         raise_error(
                             f"Unsupported data type for '{func.__qualname__}'.",