[TF FE] Support Expm1 operation

src/frontends/tensorflow/docs/supported_ops.md

@@ -419,7 +419,7 @@ A "supported operation" is one that TensorFlow Frontend can convert to the OpenV
 | ExperimentalUnbatchDataset                              | NO                            |                               |
 | ExperimentalUniqueDataset                               | NO                            |                               |
 | Expint                                                  | NO                            |                               |
-| Expm1                                                   | NO                            |                               |
+| Expm1                                                   | YES                           |                               |
 | ExtractGlimpse                                          | NO                            |                               |
 | ExtractGlimpseV2                                        | NO                            |                               |
 | ExtractImagePatches                                     | YES                           |                               |

src/frontends/tensorflow/src/op_table.cpp

@@ -252,6 +252,7 @@ const std::map<std::string, CreatorFunction> get_supported_ops() {
         {"EmptyTensorList", CreatorFunction(translate_empty_tensor_list_op)},
         {"EnsureShape", CreatorFunction(translate_identity_op)},
         {"ExpandDims", CreatorFunction(translate_expand_dims_op)},
+        {"Expm1", CreatorFunction(translate_expm1_op)},
         {"ExtractImagePatches", CreatorFunction(translate_extract_image_patches_op)},
         {"FakeQuantWithMinMaxVars", CreatorFunction(translate_fake_quant_op)},
         {"FakeQuantWithMinMaxVarsPerChannel", CreatorFunction(translate_fake_quant_op)},

src/frontends/tensorflow_common/include/common_op_table.hpp

@@ -74,6 +74,7 @@ OP_CONVERTER(translate_mul_op);
 OP_CONVERTER(translate_dynamic_partition_op);
 OP_CONVERTER(translate_einsum_op);
 OP_CONVERTER(translate_elu_op);
+OP_CONVERTER(translate_expm1_op);
 OP_CONVERTER(translate_expand_dims_op);
 OP_CONVERTER(translate_extract_image_patches_op);
 OP_CONVERTER(translate_fake_quant_op);

src/frontends/tensorflow_common/src/op/expm1.cpp

@@ -0,0 +1,30 @@
+// Copyright (C) 2018-2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "common_op_table.hpp"
+#include "openvino/op/exp.hpp"
+#include "openvino/op/subtract.hpp"
+#include "utils.hpp"
+
+using namespace std;
+using namespace ov::op;
+
+namespace ov {
+namespace frontend {
+namespace tensorflow {
+namespace op {
+
+OutputVector translate_expm1_op(const NodeContext& node) {
+    default_op_checks(node, 1, {"Expm1"});
+    auto input = node.get_input(0);
+    auto const_one = create_same_type_const_scalar<int>(input, 1);
+    auto exp = make_shared<v0::Exp>(input);
+    auto res = make_shared<v1::Subtract>(exp, const_one);
+    set_node_name(node.get_name(), res);
+    return {res};
+}
+}  // namespace op
+}  // namespace tensorflow
+}  // namespace frontend
+}  // namespace ov

tests/layer_tests/tensorflow_tests/test_tf_Expm1.py

@@ -0,0 +1,40 @@
+# Copyright (C) 2018-2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+import numpy as np
+import pytest
+import tensorflow as tf
+from common.tf_layer_test_class import CommonTFLayerTest
+
+rng = np.random.default_rng(345345)
+
+
+class TestExpm1(CommonTFLayerTest):
+    def _prepare_input(self, inputs_info):
+        assert 'x:0' in inputs_info, "Test error: inputs_info must contain `x`"
+        x_shape = inputs_info['x:0']
+        inputs_data = {}
+        inputs_data['x:0'] = rng.uniform(-2.0, 2.0, x_shape).astype(self.x_type)
+        return inputs_data
+
+    def create_expm1_net(self, x_shape, x_type):
+        self.x_type = x_type
+        tf.compat.v1.reset_default_graph()
+        # Create the graph and model
+        with tf.compat.v1.Session() as sess:
+            x = tf.compat.v1.placeholder(x_type, x_shape, 'x')
+            tf.raw_ops.Expm1(x=x)
+            tf.compat.v1.global_variables_initializer()
+            tf_net = sess.graph_def
+
+        return tf_net, None
+
+    @pytest.mark.parametrize('x_shape', [[], [2], [3, 4], [3, 2, 1, 4]])
+    @pytest.mark.parametrize('x_type', [np.float16, np.float32, np.float64])
+    @pytest.mark.precommit
+    @pytest.mark.nightly
+    def test_expm1(self, x_shape, x_type, ie_device, precision, ir_version, temp_dir,
+                   use_legacy_frontend):
+        self._test(*self.create_expm1_net(x_shape, x_type),
+                   ie_device, precision, ir_version, temp_dir=temp_dir,
+                   use_legacy_frontend=use_legacy_frontend)