feat: adds stack function to paddle tensor class

ivy/functional/frontends/paddle/manipulation.py

@@ -153,6 +153,9 @@ def squeeze(x, axis=None, name=None):
     return ivy.squeeze(x, axis=axis)
 
 
+@with_supported_dtypes(
+    {"2.5.1 and below": ("float32", "float64", "int32", "int64")}, "paddle"
+)
 @to_ivy_arrays_and_back
 def stack(x, axis=0, name=None):
     return ivy.stack(x, axis=axis)

ivy/functional/frontends/paddle/tensor/tensor.py

@@ -798,3 +798,6 @@ def real(self, name=None):
     )
     def cast(self, dtype):
         return paddle_frontend.cast(self, dtype)
+
+    def stack(self, axis=0, name=None):
+        return paddle_frontend.stack(self._ivy_array, axis=axis)

ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_tensor.py

@@ -7,7 +7,7 @@
 
 # local
 import ivy_tests.test_ivy.helpers as helpers
-from ivy.functional.frontends.paddle import Tensor
+from ivy.functional.frontends.paddle import Tensor, to_tensor
 from ivy_tests.test_ivy.helpers import assert_all_close
 from ivy_tests.test_ivy.helpers import handle_frontend_method, BackendHandler
 from ivy_tests.test_ivy.test_functional.test_experimental.test_core.test_manipulation import (  # noqa E501
@@ -152,6 +152,27 @@ def _get_dtype_and_values_for_lerp(draw):
         return input_dtype, x[0], x[1], weight
 
 
+# stack
+@st.composite
+def _get_stack_inputs(draw):
+    num_dims = draw(st.shared(helpers.ints(min_value=2, max_value=5), key="num_dims"))
+    common_shape = draw(
+        helpers.list_of_size(
+            x=helpers.ints(min_value=0, max_value=2),
+            size=num_dims - 1,
+        )
+    )
+    axis = draw(st.sampled_from(list(range(num_dims))))
+    dtypes, x = draw(
+        helpers.dtype_and_values(
+            available_dtypes=draw(helpers.get_dtypes("numeric")),
+            shape=common_shape,
+        )
+    )
+    x = to_tensor(x)
+    return x, dtypes, axis
+
+
 @st.composite
 def _reshape_helper(draw):
     # generate a shape s.t len(shape) > 0
@@ -3809,6 +3830,41 @@ def test_paddle_tensor_squeeze_(
     )
 
 
+# stack
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="stack",
+    input_values=_get_stack_inputs(),
+)
+def test_paddle_tensor_stack(
+    input_values,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    frontend,
+    on_device,
+    backend_fw,
+):
+    data, input_dtype, axis = input_values
+    helpers.test_frontend_method(
+        init_input_dtypes=input_dtype,
+        backend_to_test=backend_fw,
+        init_all_as_kwargs_np={
+            "data": data,
+        },
+        method_input_dtypes=input_dtype,
+        method_all_as_kwargs_np={
+            "axis": axis,
+        },
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        on_device=on_device,
+    )
+
+
 # stanh
 @handle_frontend_method(
     class_tree=CLASS_TREE,