Add log2_ to torch frontend api with test

ivy/functional/frontends/torch/tensor.py

@@ -361,6 +361,11 @@ def arctanh_(self):
     def log(self):
         return torch_frontend.log(self)
 
+    @with_supported_dtypes({"2.0.1 and below": ("float32", "float64")}, "torch")
+    def log2_(self):
+        self.ivy_array = self.log2().ivy_array
+        return self
+
     @with_unsupported_dtypes({"2.0.1 and below": ("float16",)}, "torch")
     def arccosh(self):
         return torch_frontend.arccosh(self)

ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py

@@ -2081,6 +2081,42 @@ def test_torch_tensor_log(
     )
 
 
+# log2_
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="log2_",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("valid"),
+        allow_inf=False,
+    ),
+)
+def test_torch_tensor_log2_(
+    dtype_and_x,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    frontend,
+    on_device,
+    backend_fw,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_method(
+        init_input_dtypes=input_dtype,
+        backend_to_test=backend_fw,
+        init_all_as_kwargs_np={
+            "data": x[0],
+        },
+        method_input_dtypes=input_dtype,
+        method_all_as_kwargs_np={},
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        on_device=on_device,
+    )
+
+
 # log_
 @handle_frontend_method(
     class_tree=CLASS_TREE,