# Copyright (C) 2018-2026 Intel Corporation
# SPDX-License-Identifier: Apache-2.0

import numpy as np
import pytest

from common.tf_layer_test_class import CommonTFLayerTest


class TestAdd(CommonTFLayerTest):
    def create_add_placeholder_const_net(self, x_shape, y_shape):
        import tensorflow as tf
        tf.compat.v1.reset_default_graph()

        # Create the graph and model
        with tf.compat.v1.Session() as sess:
            x = tf.compat.v1.placeholder(tf.float32, x_shape, 'Input')
            constant_value = np.random.randint(-256, 256, y_shape).astype(np.float32)
            if (constant_value == 0).all():
                # Avoid elimination of the layer from IR
                constant_value = constant_value + 1
            y = tf.constant(constant_value)
            tf.add(x, y, name="Operation")

            tf.compat.v1.global_variables_initializer()
            tf_net = sess.graph_def

        return tf_net, None

    # TODO: implement tests for 2 Consts + Add

    test_data_1D = [
        dict(x_shape=[1], y_shape=[1]),
        pytest.param(dict(x_shape=[3], y_shape=[3]), marks=pytest.mark.xfail(reason="*-19180"))
    ]

    @pytest.mark.parametrize("params", test_data_1D)
    @pytest.mark.nightly
    def test_add_placeholder_const_1D(self, params, ie_device, precision, ir_version, temp_dir):
        self._test(*self.create_add_placeholder_const_net(**params),
                   ie_device, precision, ir_version, temp_dir=temp_dir)

    test_data_2D = [
        dict(x_shape=[1, 1], y_shape=[1, 1]),
        dict(x_shape=[1, 3], y_shape=[1, 3]),
        pytest.param(dict(x_shape=[3, 1], y_shape=[3, 1]),
                     marks=pytest.mark.xfail(reason="*-19180")),
        dict(x_shape=[2, 3], y_shape=[2, 3])
    ]

    @pytest.mark.parametrize("params", test_data_2D)
    @pytest.mark.nightly
    def test_add_placeholder_const_2D(self, params, ie_device, precision, ir_version, temp_dir):
        self._test(*self.create_add_placeholder_const_net(**params),
                   ie_device, precision, ir_version, temp_dir=temp_dir)

    test_data_3D = [
        dict(x_shape=[1, 1, 1], y_shape=[1, 1, 1]),
        pytest.param(dict(x_shape=[1, 3, 1], y_shape=[1, 3, 1]),
                     marks=pytest.mark.xfail(reason="*-19053")),
        pytest.param(dict(x_shape=[1, 1, 3], y_shape=[1, 1, 3]),
                     marks=[pytest.mark.xfail(reason="*-19053"),
                            pytest.mark.xfail(reason="*-18830")]),
        pytest.param(dict(x_shape=[1, 3, 224], y_shape=[1, 3, 224]),
                     marks=pytest.mark.xfail(reason="*-19053"))
    ]

    @pytest.mark.parametrize("params", test_data_3D)
    @pytest.mark.nightly
    def test_add_placeholder_const_3D(self, params, ie_device, precision, ir_version, temp_dir):
        self._test(*self.create_add_placeholder_const_net(**params),
                   ie_device, precision, ir_version, temp_dir=temp_dir)

    test_data_4D = [
        dict(x_shape=[1, 1, 1, 1], y_shape=[1, 1, 1, 1]),
        dict(x_shape=[1, 3, 1, 1], y_shape=[1, 3, 1, 1]),
        pytest.param(dict(x_shape=[1, 1, 1, 3], y_shape=[1, 1, 1, 3]),
                     marks=pytest.mark.xfail(reason="*-19180")),
        dict(x_shape=[1, 3, 222, 224], y_shape=[1, 3, 222, 224])
    ]

    # TODO mark as precommit (after successfully passing in nightly)
    @pytest.mark.parametrize("params", test_data_4D)
    @pytest.mark.nightly
    def test_add_placeholder_const_4D(self, params, ie_device, precision, ir_version, temp_dir):
        self._test(*self.create_add_placeholder_const_net(**params),
                   ie_device, precision, ir_version, temp_dir=temp_dir)

    test_data_5D = [
        dict(x_shape=[1, 1, 1, 1, 1], y_shape=[1, 1, 1, 1, 1]),
        dict(x_shape=[1, 3, 1, 1, 1], y_shape=[1, 3, 1, 1, 1]),
        pytest.param(dict(x_shape=[1, 1, 1, 1, 3], y_shape=[1, 1, 1, 1, 3]),
                     marks=pytest.mark.xfail(reason="*-19180")),
        dict(x_shape=[1, 3, 50, 100, 224], y_shape=[1, 3, 50, 100, 224])
    ]

    # TODO mark as precommit (after successfully passing in nightly)
    @pytest.mark.parametrize("params", test_data_5D)
    @pytest.mark.nightly
    def test_add_placeholder_const_5D(self, params, ie_device, precision, ir_version, temp_dir):
        self._test(*self.create_add_placeholder_const_net(**params),
                   ie_device, precision, ir_version=ir_version, temp_dir=temp_dir)

    ###############################################################################################
    #                                                                                             #
    #                                       Broadcast cases                                       #
    #                                                                                             #
    ###############################################################################################

    test_data_broadcast_1D = [
        dict(x_shape=[3], y_shape=[1])
    ]

    @pytest.mark.parametrize("params", test_data_broadcast_1D)
    @pytest.mark.nightly
    def test_add_placeholder_const_broadcast_1D(self, params, ie_device, precision, ir_version,
                                                temp_dir):
        self._test(*self.create_add_placeholder_const_net(**params),
                   ie_device, precision, ir_version=ir_version, temp_dir=temp_dir)

    test_data_broadcast_2D = [
        dict(x_shape=[1, 1], y_shape=[1]),
        dict(x_shape=[1, 3], y_shape=[1]),
        dict(x_shape=[1, 3], y_shape=[3]),
        dict(x_shape=[3, 1], y_shape=[3]),
        pytest.param(dict(x_shape=[3, 1], y_shape=[1, 3, 1, 1]),
                     marks=pytest.mark.xfail(reason="*-19051"))
    ]

    @pytest.mark.parametrize("params", test_data_broadcast_2D)
    @pytest.mark.nightly
    def test_add_placeholder_const_broadcast_2D(self, params, ie_device, precision, ir_version,
                                                temp_dir):
        self._test(*self.create_add_placeholder_const_net(**params),
                   ie_device, precision, ir_version=ir_version, temp_dir=temp_dir)

    test_data_broadcast_3D = [
        dict(x_shape=[1, 1, 1], y_shape=[1]),
        pytest.param(dict(x_shape=[1, 3, 1], y_shape=[1]),
                     marks=pytest.mark.xfail(reason="*-19053")),
        pytest.param(dict(x_shape=[1, 3, 1], y_shape=[3]),
                     marks=pytest.mark.xfail(reason="*-19053")),
        pytest.param(dict(x_shape=[1, 3, 1], y_shape=[3, 1]),
                     marks=pytest.mark.xfail(reason="*-19053")),
        pytest.param(dict(x_shape=[1, 1, 1], y_shape=[3, 1]),
                     marks=pytest.mark.xfail(reason="*-19053")),
        pytest.param(dict(x_shape=[3, 1, 224], y_shape=[1, 3, 224]),
                     marks=pytest.mark.xfail(reason="*-19053")),
        pytest.param(dict(x_shape=[2, 3, 1], y_shape=[1, 3, 2]),
                     marks=pytest.mark.xfail(reason="*-19053")),
    ]

    @pytest.mark.parametrize("params", test_data_broadcast_3D)
    @pytest.mark.nightly
    def test_add_placeholder_const_broadcast_3D(self, params, ie_device, precision, ir_version,
                                                temp_dir):
        self._test(*self.create_add_placeholder_const_net(**params),
                   ie_device, precision, ir_version=ir_version, temp_dir=temp_dir)

    test_data_broadcast_4D = [
        dict(x_shape=[1, 1, 1, 1], y_shape=[1]),
        dict(x_shape=[1, 3, 1, 1], y_shape=[1]),
        dict(x_shape=[1, 1, 1, 3], y_shape=[3]),
        dict(x_shape=[1, 100, 224, 3], y_shape=[3]),
        dict(x_shape=[1, 1, 1, 3], y_shape=[3]),
        pytest.param(dict(x_shape=[1, 1, 3, 1], y_shape=[3, 1]), marks=pytest.mark.precommit),
        dict(x_shape=[1, 3, 2, 1], y_shape=[3, 1, 2]),
        dict(x_shape=[1, 1, 3, 2], y_shape=[1, 3, 2]),
        dict(x_shape=[1, 3, 100, 224], y_shape=[1, 1, 1, 224]),
        dict(x_shape=[2, 3, 2, 1], y_shape=[1, 3, 2, 1])
    ]

    @pytest.mark.parametrize("params", test_data_broadcast_4D)
    @pytest.mark.nightly
    @pytest.mark.precommit
    def test_add_placeholder_const_broadcast_4D(self, params, ie_device, precision, ir_version,
                                                temp_dir):
        self._test(*self.create_add_placeholder_const_net(**params),
                   ie_device, precision, ir_version=ir_version, temp_dir=temp_dir)

    test_data_broadcast_5D = [
        dict(x_shape=[1, 1, 1, 1, 1], y_shape=[1]),
        dict(x_shape=[1, 3, 1, 1, 1], y_shape=[1, 1]),
        dict(x_shape=[1, 1, 1, 1, 3], y_shape=[3]),
        dict(x_shape=[1, 1, 1, 1, 3], y_shape=[3]),
        dict(x_shape=[1, 1, 1, 3, 1], y_shape=[3, 1]),
        dict(x_shape=[1, 2, 1, 3, 2], y_shape=[1, 3, 2]),
        dict(x_shape=[1, 5, 3, 2, 1], y_shape=[5, 3, 2, 1]),
        dict(x_shape=[1, 3, 50, 100, 224], y_shape=[1, 1, 1, 1, 224]),
        dict(x_shape=[2, 3, 1, 2, 1], y_shape=[1, 3, 2, 1, 1])
    ]

    @pytest.mark.parametrize("params", test_data_broadcast_5D)
    @pytest.mark.nightly
    @pytest.mark.precommit
    def test_add_placeholder_const_broadcast_5D(self, params, ie_device, precision, ir_version,
                                                temp_dir):
        # we do not perform transpose in the test in case of new frontend
        self._test(*self.create_add_placeholder_const_net(**params),
                   ie_device, precision,
                   ir_version=ir_version, temp_dir=temp_dir)


class TestComplexAdd(CommonTFLayerTest):
        def _prepare_input(self, inputs_info):
            rng = np.random.default_rng()
            assert 'param_real_1:0' in inputs_info
            assert 'param_imag_1:0' in inputs_info
            assert 'param_real_2:0' in inputs_info
            assert 'param_imag_2:0' in inputs_info
            param_real_shape_1 = inputs_info['param_real_1:0']
            param_imag_shape_1 = inputs_info['param_imag_1:0']
            param_real_shape_2 = inputs_info['param_real_2:0']
            param_imag_shape_2 = inputs_info['param_imag_2:0']
            inputs_data = {}
            inputs_data['param_real_1:0'] = 4 * rng.random(param_real_shape_1).astype(np.float32) - 2
            inputs_data['param_imag_1:0'] = 4 * rng.random(param_imag_shape_1).astype(np.float32) - 2
            inputs_data['param_real_2:0'] = 4 * rng.random(param_real_shape_2).astype(np.float32) - 2
            inputs_data['param_imag_2:0'] = 4 * rng.random(param_imag_shape_2).astype(np.float32) - 2
            return inputs_data

        def create_complex_addv2_net(self, input_shape):
            import tensorflow as tf
            tf.compat.v1.reset_default_graph()
            # Create the graph and model
            with tf.compat.v1.Session() as sess:
                param_real1 = tf.compat.v1.placeholder(np.float32, input_shape, 'param_real_1')
                param_imag1 = tf.compat.v1.placeholder(np.float32, input_shape, 'param_imag_1')
                param_real2 = tf.compat.v1.placeholder(np.float32, input_shape, 'param_real_2')
                param_imag2 = tf.compat.v1.placeholder(np.float32, input_shape, 'param_imag_2')
                complex1 = tf.raw_ops.Complex(real=param_real1, imag=param_imag1)
                complex2 = tf.raw_ops.Complex(real=param_real2, imag=param_imag2)
                add = tf.raw_ops.AddV2(x=complex1, y=complex2, name="complex_add")
                real = tf.raw_ops.Real(input=add)
                img = tf.raw_ops.Imag(input=add)
                tf.compat.v1.global_variables_initializer()
                tf_net = sess.graph_def

            return tf_net, None


        test_data_basic = [
            dict(input_shape=[]),
            dict(input_shape=[2]),
            dict(input_shape=[1, 3]),
            dict(input_shape=[2, 3, 4]),
            dict(input_shape=[3, 4, 5, 6]),
        ]

        @pytest.mark.parametrize("params", test_data_basic)
        @pytest.mark.precommit
        @pytest.mark.nightly
        def test_complex_add(self, params, ie_device, precision, ir_version, temp_dir):
            self._test(
                *self.create_complex_addv2_net(**params),
                ie_device, precision, ir_version, temp_dir=temp_dir)
