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[TF FE] Support Angle operation for TensorFlow models (#23028)
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### Details:
 - *Support Angle operation for TensorFlow models*
 
### Tickets:
 - Closes #22083

---------

Co-authored-by: Roman Kazantsev <[email protected]>
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rghvsh and rkazants authored Mar 24, 2024
1 parent aebf814 commit dbef32e
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Showing 5 changed files with 140 additions and 1 deletion.
2 changes: 1 addition & 1 deletion src/frontends/tensorflow/docs/supported_ops.md
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Expand Up @@ -26,7 +26,7 @@ A "supported operation" is one that TensorFlow Frontend can convert to the OpenV
| All | YES | |
| AllCandidateSampler | NO | |
| AllToAll | NO | |
| Angle | NO | |
| Angle | YES | |
| AnonymousHashTable | NO | |
| AnonymousIterator | NO | |
| AnonymousIteratorV2 | NO | |
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1 change: 1 addition & 0 deletions src/frontends/tensorflow/src/op_table.cpp
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Expand Up @@ -205,6 +205,7 @@ const std::map<std::string, CreatorFunction> get_supported_ops() {
// Separate translators:
{"AddN", CreatorFunction(translate_add_n_op)},
{"AdjustContrastv2", CreatorFunction(translate_adjust_contrast_op)},
{"Angle", CreatorFunction(translate_angle_op)},
{"ArgMax", CreatorFunction(translate_arg_max_op)},
{"ArgMin", CreatorFunction(translate_arg_min_op)},
{"Assert", CreatorFunction(translate_no_op)},
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Expand Up @@ -35,6 +35,7 @@ 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_angle_op);
OP_CONVERTER(translate_arg_max_op);
OP_CONVERTER(translate_arg_min_op);
OP_CONVERTER(translate_atan2_op);
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90 changes: 90 additions & 0 deletions src/frontends/tensorflow_common/src/op/angle.cpp
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@@ -0,0 +1,90 @@
// Copyright (C) 2018-2024 Intel Corporation
// SPDX-License-Identifier: Apache-2.0

#include "common_op_table.hpp"
#include "helper_ops/complex_type_mark.hpp"
#include "openvino/op/add.hpp"
#include "openvino/op/atan.hpp"
#include "openvino/op/constant.hpp"
#include "openvino/op/convert.hpp"
#include "openvino/op/divide.hpp"
#include "openvino/op/equal.hpp"
#include "openvino/op/gather.hpp"
#include "openvino/op/greater.hpp"
#include "openvino/op/greater_eq.hpp"
#include "openvino/op/less.hpp"
#include "openvino/op/logical_and.hpp"
#include "openvino/op/multiply.hpp"
#include "openvino/op/select.hpp"
#include "openvino/op/subtract.hpp"

using namespace std;
using namespace ov::op;

namespace ov {
namespace frontend {
namespace tensorflow {
namespace op {

OutputVector translate_angle_op(const NodeContext& node) {
default_op_checks(node, 1, {"Angle"}, true);
auto complex = node.get_input(0);
auto result_type = node.get_attribute<ov::element::Type>("Tout");

auto complex_type_mark = as_type_ptr<ComplexTypeMark>(complex.get_node_shared_ptr());

TENSORFLOW_OP_VALIDATION(
node,
complex_type_mark,
"[TensorFlow Frontend] inconsistent model: Angle operation expects complex type tensor on input");

complex = complex_type_mark->input_value(0);
auto real_index = make_shared<v0::Constant>(element::i32, Shape{}, 0);
auto imag_index = make_shared<v0::Constant>(element::i32, Shape{}, 1);
auto gather_axis = make_shared<v0::Constant>(element::i32, Shape{1}, -1);

auto x = make_shared<v8::Gather>(complex, real_index, gather_axis)->output(0);
auto y = make_shared<v8::Gather>(complex, imag_index, gather_axis)->output(0);

// handle the first condition : x>0
auto div_y_x = make_shared<v1::Divide>(y, x);
auto atan = make_shared<v0::Atan>(div_y_x);
auto const_zero = create_same_type_const_scalar<int32_t>(x, 0);
auto result = atan->output(0);

// handle the second condition : x<0 && y>=0
auto const_pi = create_same_type_const_scalar<double>(x, std::atan(1.0) * 4);
auto is_x_negative = make_shared<v1::Less>(x, const_zero);
auto y_non_negative = make_shared<v1::GreaterEqual>(y, const_zero);
auto cond1 = make_shared<v1::LogicalAnd>(is_x_negative, y_non_negative);
auto atan_y_x_plus_pi = make_shared<v1::Add>(atan, const_pi);
result = make_shared<v1::Select>(cond1, atan_y_x_plus_pi, result);

// handle the third condition : x<0 && y<0
auto is_y_negative = make_shared<v1::Less>(y, const_zero);
auto cond2 = make_shared<v1::LogicalAnd>(is_x_negative, is_y_negative);
auto atan_y_x_minus_pi = make_shared<v1::Subtract>(atan, const_pi);
result = make_shared<v1::Select>(cond2, atan_y_x_minus_pi, result);

// handle the fourth condition : x=0 && y>0
auto is_x_zero = make_shared<v1::Equal>(x, const_zero);
auto is_y_positive = make_shared<v1::Greater>(y, const_zero);
auto cond3 = make_shared<v1::LogicalAnd>(is_x_zero, is_y_positive);
auto const_two = create_same_type_const_scalar<int32_t>(x, 2);
auto pi_div_two = make_shared<v1::Divide>(const_pi, const_two);
result = make_shared<v1::Select>(cond3, pi_div_two, result);

// handle the fifth condition : x=0 && y<0
auto cond4 = make_shared<v1::LogicalAnd>(is_x_zero, is_y_negative);
auto const_minus_two = create_same_type_const_scalar<int32_t>(x, -2);
auto pi_div_minus_two = make_shared<v1::Divide>(const_pi, const_minus_two);
result = make_shared<v1::Select>(cond4, pi_div_two, result);
auto result_changed_type = make_shared<v0::Convert>(result, result_type)->output(0);

set_node_name(node.get_name(), result_changed_type.get_node_shared_ptr());
return {result_changed_type};
}
} // namespace op
} // namespace tensorflow
} // namespace frontend
} // namespace ov
47 changes: 47 additions & 0 deletions tests/layer_tests/tensorflow_tests/test_tf_angle.py
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# 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


class TestAngle(CommonTFLayerTest):
def _prepare_input(self, inputs_info):
assert 'y:0' in inputs_info
assert 'x:0' in inputs_info
y_shape = inputs_info['y:0']
x_shape = inputs_info['x:0']
inputs_data = {}
inputs_data['y:0'] = np.random.rand(*y_shape).astype(self.input_type) - np.random.rand(*y_shape).astype(self.input_type)
inputs_data['x:0'] = np.random.rand(*x_shape).astype(self.input_type) - np.random.rand(*x_shape).astype(self.input_type)
return inputs_data

def create_angle_net(self, input_shape, input_type):
self.input_type = input_type
tf.compat.v1.reset_default_graph()
# Create the graph and model
with tf.compat.v1.Session() as sess:
y = tf.compat.v1.placeholder(input_type, input_shape, 'y')
x = tf.compat.v1.placeholder(input_type, input_shape, 'x')
complex = tf.raw_ops.Complex(real=x, imag=y)
tf.raw_ops.Angle(input=complex)
tf.compat.v1.global_variables_initializer()
tf_net = sess.graph_def

return tf_net, None

test_data_basic = [
dict(input_shape=[1, 2], input_type=np.float32),
dict(input_shape=[2, 3, 4], input_type=np.float32),
]

@pytest.mark.parametrize("params", test_data_basic)
@pytest.mark.precommit_tf_fe
@pytest.mark.nightly
def test_angle(self, params, ie_device, precision, ir_version, temp_dir,
use_legacy_frontend):
self._test(*self.create_angle_net(**params),
ie_device, precision, ir_version, temp_dir=temp_dir,
use_legacy_frontend=use_legacy_frontend)

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