Aml 20867 paddle frontend var

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

@@ -47,6 +47,16 @@ def median(x, axis=None, keepdim=False, name=None):
     return ivy.median(x, axis=axis, keepdims=keepdim)
 
 
+@with_supported_dtypes({"2.5.1 and below": ("float32", "float64")}, "paddle")
+@to_ivy_arrays_and_back
+def var(x, axis=None, unbiased=True, keepdim=False, name=None):
+    if unbiased:
+        correction = 1
+    else:
+        correction = 0
+    return ivy.var(x, axis=axis, correction=correction, keepdims=keepdim)
+
+
 @with_supported_dtypes(
     {"2.5.0 and below": ("float16", "float32", "float64", "uint16")},
     "paddle",

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

@@ -133,6 +133,37 @@ def test_paddle_median(
     )
 
 
+# var
+@handle_frontend_test(
+    fn_tree="paddle.var",
+    dtype_and_x=_statistical_dtype_values(function="var"),
+    unbiased=st.booleans(),
+    keepdim=st.booleans(),
+)
+def test_paddle_var(
+    *,
+    unbiased,
+    dtype_and_x,
+    keepdim,
+    fn_tree,
+    frontend,
+    backend_fw,
+    test_flags,
+):
+    input_dtype, x, axis, _ = dtype_and_x
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        backend_to_test=backend_fw,
+        frontend=frontend,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        x=x[0],
+        axis=axis,
+        unbiased=unbiased,
+        keepdim=keepdim,
+    )
+
+
 @handle_frontend_test(
     fn_tree="paddle.nanmedian",
     dtype_x_and_axis=helpers.dtype_values_axis(