diff --git a/src/frontends/tensorflow/docs/supported_ops.md b/src/frontends/tensorflow/docs/supported_ops.md index e4315fc5c4edff..f4b06fafa06283 100644 --- a/src/frontends/tensorflow/docs/supported_ops.md +++ b/src/frontends/tensorflow/docs/supported_ops.md @@ -57,7 +57,7 @@ A "supported operation" is one that TensorFlow Frontend can convert to the OpenV | ApplyProximalGradientDescent | NO | | | ApplyRMSProp | NO | | | ApproxTopK | NO | | -| ApproximateEqual | NO | | +| ApproximateEqual | YES | | | ArgMax | YES | | | ArgMin | YES | | | AsString | NO | | diff --git a/src/frontends/tensorflow/src/op_table.cpp b/src/frontends/tensorflow/src/op_table.cpp index e3d8db8f0512ab..fb1597c926e6c8 100644 --- a/src/frontends/tensorflow/src/op_table.cpp +++ b/src/frontends/tensorflow/src/op_table.cpp @@ -422,6 +422,7 @@ const std::map get_supported_ops() { {"AssignVariableOp", CreatorFunction(translate_assignvariable_op)}, {"AssignAddVariableOp", CreatorFunction(translate_add_variable_op)}, {"AssignSubVariableOp", CreatorFunction(translate_sub_variable_op)}, + {"ApproximateEqual", CreatorFunction(translate_approximate_equal_op)}, {"IsVariableInitialized", CreatorFunction(translate_varisinitialized_op)}, {"MergeV2Checkpoints", CreatorFunction(translate_identity_op)}, {"ReadVariableOp", CreatorFunction(translate_readvariable_op)}, diff --git a/src/frontends/tensorflow_common/include/common_op_table.hpp b/src/frontends/tensorflow_common/include/common_op_table.hpp index 905d437ec07f6e..6d4e4a971c2f98 100644 --- a/src/frontends/tensorflow_common/include/common_op_table.hpp +++ b/src/frontends/tensorflow_common/include/common_op_table.hpp @@ -33,6 +33,7 @@ OP_T_CONVERTER(translate_binary_op); OP_T_CONVERTER(translate_direct_reduce_op); OP_CONVERTER(translate_addv2_op); OP_CONVERTER(translate_add_n_op); +OP_CONVERTER(translate_approximate_equal_op); OP_CONVERTER(translate_adjust_contrast_op); OP_CONVERTER(translate_arg_max_op); OP_CONVERTER(translate_arg_min_op); diff --git a/src/frontends/tensorflow_common/src/op/approximate_equal_op.cpp b/src/frontends/tensorflow_common/src/op/approximate_equal_op.cpp new file mode 100644 index 00000000000000..7a2cb0f803b392 --- /dev/null +++ b/src/frontends/tensorflow_common/src/op/approximate_equal_op.cpp @@ -0,0 +1,37 @@ +// Copyright (C) 2018-2024 Intel Corporation +// SPDX-License-Identifier: Apache-2.0 +// + +#include "common_op_table.hpp" +#include "openvino/op/abs.hpp" +#include "openvino/op/constant.hpp" +#include "openvino/op/less.hpp" +#include "openvino/op/subtract.hpp" + +using namespace std; +using namespace ov::op; + +namespace ov { +namespace frontend { +namespace tensorflow { +namespace op { + +OutputVector translate_approximate_equal_op(const NodeContext& node) { + default_op_checks(node, 2, {"ApproximateEqual"}); + auto x = node.get_input(0); + auto y = node.get_input(1); + auto tolerance_value = node.get_attribute("tolerance", 1e-5f); + auto tolerance = create_same_type_const_scalar(x, tolerance_value); + // Implement the logic for ApproximateEqual + auto difference = make_shared(x, y); + auto absolute = make_shared(difference); + auto is_less = make_shared(absolute, tolerance); + + // Create and return the corresponding OpenVINO operation + set_node_name(node.get_name(), is_less); + return {is_less}; +} +} // namespace op +} // namespace tensorflow +} // namespace frontend +} // namespace ov \ No newline at end of file diff --git a/tests/layer_tests/tensorflow_tests/test_tf_ApproximateEqual.py b/tests/layer_tests/tensorflow_tests/test_tf_ApproximateEqual.py new file mode 100644 index 00000000000000..c01c85591c73a4 --- /dev/null +++ b/tests/layer_tests/tensorflow_tests/test_tf_ApproximateEqual.py @@ -0,0 +1,45 @@ +# Copyright (C) 2018-2024 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 +import numpy as np +import tensorflow as tf +import pytest +from common.tf_layer_test_class import CommonTFLayerTest + +class TestApproximateEqual(CommonTFLayerTest): + def _prepare_input(self, inputs_info): + rng = np.random.default_rng() + assert 'tensor1:0' in inputs_info + assert 'tensor2:0' in inputs_info + tensor1_shape = inputs_info['tensor1:0'] + tensor2_shape = inputs_info['tensor2:0'] + inputs_data = {} + inputs_data['tensor1:0'] = 4 * rng.random(tensor1_shape).astype(np.float32) - 2 + inputs_data['tensor2:0'] = 4 * rng.random(tensor2_shape).astype(np.float32) - 2 + return inputs_data + + def create_approximate_equal_net(self, input1_shape, input2_shape): + tf.compat.v1.reset_default_graph() + # Create the graph and model + with tf.compat.v1.Session() as sess: + tensor1 = tf.compat.v1.placeholder(tf.float32, input1_shape, 'tensor1') + tensor2 = tf.compat.v1.placeholder(tf.float32, input2_shape, 'tensor2') + approx_equal_op = tf.raw_ops.ApproximateEqual(x=tensor1, y=tensor2, tolerance=0.01) + tf.compat.v1.global_variables_initializer() + tf_net = sess.graph_def + + return tf_net, None + + test_data_basic = [ + dict(input1_shape=[2, 3], input2_shape=[2, 3]), + dict(input1_shape=[3, 4, 5], input2_shape=[3, 4, 5]), + dict(input1_shape=[1, 2, 3, 4], input2_shape=[1, 2, 3, 4]), + ] + + @pytest.mark.parametrize("params", test_data_basic) + @pytest.mark.precommit_tf_fe + @pytest.mark.nightly + def test_approximate_equal_basic(self, params, ie_device, precision, ir_version, temp_dir, + use_legacy_frontend): + self._test(*self.create_approximate_equal_net(**params), + ie_device, precision, ir_version, temp_dir=temp_dir, + use_legacy_frontend=use_legacy_frontend) \ No newline at end of file