numpy frontend instance sort, copy

ivy/functional/frontends/numpy/creation_routines/from_existing_data.py

@@ -17,4 +17,4 @@ def asarray(
 
 @to_ivy_arrays_and_back
 def copy(a, order="K", subok=False):
-    return ivy.copy_array(a, dtype=a.dtype())
+    return ivy.copy_array(a)

ivy/functional/frontends/numpy/ndarray/ndarray.py

@@ -113,3 +113,9 @@ def cumsum(self, *, axis=None, dtype=dtype, out=None):
             dtype=dtype,
             out=out,
         )
+
+    def sort(self, *, axis=-1, kind=None, order=None):
+        return np_frontend.sort(self.data, axis=axis, kind=kind, order=order)
+
+    def copy(self, order='C'):
+        return np_frontend.copy(self.data, order=order)

ivy_tests/test_ivy/test_frontends/test_numpy/test_ndarray/test_ndarray.py

@@ -4,7 +4,7 @@
 
 # local
 import ivy_tests.test_ivy.helpers as helpers
-from ivy_tests.test_ivy.helpers import handle_cmd_line_args
+from ivy_tests.test_ivy.helpers import handle_cmd_line_args, assert_all_close
 import ivy_tests.test_ivy.test_frontends.test_numpy.helpers as np_frontend_helpers
 
 
@@ -591,3 +591,92 @@ def test_numpy_instance_cumsum(
         class_name="ndarray",
         method_name="cumsum",
     )
+
+
+@handle_cmd_line_args
+@given(
+    dtype_x_axis=helpers.dtype_values_axis(
+        available_dtypes=helpers.get_dtypes("float"),
+        min_axis=-1,
+        max_axis=0,
+        min_num_dims=1,
+        force_int_axis=True,
+    ),
+    num_positional_args_method=helpers.num_positional_args(
+        fn_name="ivy.functional.frontends.numpy.ndarray.sort"
+    ),
+)
+def test_numpy_instance_sort(
+    dtype_x_axis,
+    as_variable,
+    num_positional_args_method,
+    native_array,
+):
+    input_dtype, x, axis = dtype_x_axis
+
+    ret, frontend_ret = helpers.test_frontend_method(
+        input_dtypes_init=input_dtype,
+        input_dtypes_method=input_dtype,
+        as_variable_flags_init=as_variable,
+        num_positional_args_init=1,
+        num_positional_args_method=num_positional_args_method,
+        native_array_flags_init=native_array,
+        as_variable_flags_method=as_variable,
+        native_array_flags_method=native_array,
+        all_as_kwargs_np_init={
+            "data": x[0],
+        },
+        all_as_kwargs_np_method={
+            "axis": axis,
+        },
+        frontend="numpy",
+        class_name="ndarray",
+        method_name="sort",
+        test_values=False,
+    )
+    frontend_ret = np.sort(x[0], axis=axis)
+    assert_all_close(
+        ret_np=ret,
+        ret_from_gt_np=frontend_ret,
+        rtol=1e-2,
+        atol=1e-2,
+        ground_truth_backend="numpy",
+    )
+
+
+@handle_cmd_line_args
+@given(
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("numeric"),
+        min_num_dims=1,
+    ),
+    num_positional_args_method=helpers.num_positional_args(
+        fn_name="ivy.functional.frontends.numpy.ndarray.copy"
+    ),
+)
+def test_numpy_instance_copy(
+    dtype_and_x,
+    as_variable,
+    num_positional_args_method,
+    native_array,
+):
+    input_dtype, x = dtype_and_x
+
+    helpers.test_frontend_method(
+        input_dtypes_init=input_dtype,
+        input_dtypes_method=input_dtype,
+        as_variable_flags_init=as_variable,
+        num_positional_args_init=1,
+        num_positional_args_method=num_positional_args_method,
+        native_array_flags_init=native_array,
+        as_variable_flags_method=as_variable,
+        native_array_flags_method=native_array,
+        all_as_kwargs_np_init={
+            "data": x[0],
+        },
+        all_as_kwargs_np_method={
+        },
+        frontend="numpy",
+        class_name="ndarray",
+        method_name="copy",
+    )