[PyTorch FE] Support aten::ravel operation

src/frontends/pytorch/src/op/ravel.cpp

@@ -0,0 +1,28 @@
+// Copyright (C) 2018-2025 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "openvino/frontend/pytorch/node_context.hpp"
+#include "openvino/op/constant.hpp"
+#include "openvino/op/reshape.hpp"
+#include "utils.hpp"
+
+namespace ov {
+namespace frontend {
+namespace pytorch {
+namespace op {
+
+using namespace ov::op;
+
+OutputVector translate_ravel(const NodeContext& context) {
+    // aten::ravel(Tensor self) -> Tensor
+    num_inputs_check(context, 1, 1);
+    auto input = context.get_input(0);
+    auto neg_1 = context.mark_node(v0::Constant::create(element::i64, Shape{1}, {-1}));
+    return {context.mark_node(std::make_shared<v1::Reshape>(input, neg_1, false))};
+};
+
+}  // namespace op
+}  // namespace pytorch
+}  // namespace frontend
+}  // namespace ov

src/frontends/pytorch/src/op_table.cpp

@@ -222,6 +222,7 @@ OP_CONVERTER(translate_randn);
 OP_CONVERTER(translate_randint);
 OP_CONVERTER(translate_rand_like);
 OP_CONVERTER(translate_randn_like);
+OP_CONVERTER(translate_ravel);
 OP_CONVERTER(translate_reciprocal);
 OP_CONVERTER(translate_reflection_pad_nd);
 OP_CONVERTER(translate_relu6);
@@ -676,6 +677,7 @@ const std::unordered_map<std::string, CreatorFunction> get_supported_ops_ts() {
         {"aten::randint", op::translate_randint},
         {"aten::randn", op::translate_randn},
         {"aten::randn_like", op::translate_randn_like},
+        {"aten::ravel", op::translate_ravel},
         {"aten::real", common_translators::translate_real},
         {"aten::reciprocal", op::optional_out<op::translate_reciprocal, 1>},
         {"aten::reciprocal_", op::inplace_op<op::translate_reciprocal>},

tests/layer_tests/pytorch_tests/test_ravel.py

@@ -0,0 +1,41 @@
+# Copyright (C) 2018-2025 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+import numpy as np
+import pytest
+
+from pytorch_layer_test_class import PytorchLayerTest
+
+
+class TestRavel(PytorchLayerTest):
+    def _prepare_input(self, shape, dtype="float32"):
+        return (np.random.randn(*shape).astype(dtype),)
+
+    def create_model(self):
+        import torch
+
+        class aten_ravel(torch.nn.Module):
+            def forward(self, x):
+                return torch.ravel(x)
+
+        return aten_ravel(), "aten::ravel"
+
+    @pytest.mark.parametrize("shape", [
+        [2, 3],
+        [2, 3, 4],
+        [2, 3, 4, 5],
+        [1],
+        [5],
+        [1, 1, 1],
+    ])
+    @pytest.mark.parametrize("dtype", ["float32", "float64", "int32", "int64", "int8"])
+    @pytest.mark.nightly
+    @pytest.mark.precommit
+    def test_ravel(self, shape, dtype, ie_device, precision, ir_version):
+        self._test(
+            *self.create_model(),
+            ie_device,
+            precision,
+            ir_version,
+            kwargs_to_prepare_input={"shape": shape, "dtype": dtype},
+        )