Added torch frontend function diagflat (#22384)

Co-authored-by: paulaehab<[email protected]>

ivy/functional/frontends/torch/miscellaneous_ops.py

@@ -166,6 +166,15 @@ def diag(input, diagonal=0, *, out=None):
     return ivy.diag(input, k=diagonal)
 
 
+@with_supported_dtypes(
+    {"2.0.1 and below": ("float32", "float64", "int32", "int64")}, "torch"
+)
+@to_ivy_arrays_and_back
+def diagflat(x, offset=0, name=None):
+    arr = ivy.diagflat(x, offset=offset)
+    return arr
+
+
 @with_unsupported_dtypes({"2.0.1 and below": ("float16", "bfloat16")}, "torch")
 @to_ivy_arrays_and_back
 def diagonal(input, offset=0, dim1=0, dim2=1):

ivy_tests/test_ivy/test_frontends/test_torch/test_miscellaneous_ops.py

@@ -812,6 +812,42 @@ def test_torch_diag(
     )
 
 
+# diagflat
+@handle_frontend_test(
+    fn_tree="torch.diagflat",
+    dtype_and_values=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("valid"),
+        min_num_dims=1,
+        max_num_dims=5,
+        min_dim_size=1,
+        max_dim_size=5,
+    ),
+    offset=st.integers(min_value=-4, max_value=4),
+    test_with_out=st.just(False),
+)
+def test_torch_diagflat(
+    dtype_and_values,
+    offset,
+    test_flags,
+    backend_fw,
+    frontend,
+    fn_tree,
+    on_device,
+):
+    input_dtype, x = dtype_and_values
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        frontend=frontend,
+        backend_to_test=backend_fw,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        test_values=False,
+        x=x[0],
+        offset=offset,
+    )
+
+
 @handle_frontend_test(
     fn_tree="torch.diagonal",
     dtype_and_values=helpers.dtype_and_values(