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test_tf_Add.py
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# Copyright (C) 2018-2025 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, use_legacy_frontend):
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,
use_legacy_frontend):
self._test(*self.create_add_placeholder_const_net(**params, use_legacy_frontend=use_legacy_frontend),
ie_device, precision, ir_version, temp_dir=temp_dir,
use_legacy_frontend=use_legacy_frontend)
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,
use_legacy_frontend):
self._test(*self.create_add_placeholder_const_net(**params,
use_legacy_frontend=use_legacy_frontend),
ie_device, precision, ir_version, temp_dir=temp_dir,
use_legacy_frontend=use_legacy_frontend)
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,
use_legacy_frontend):
self._test(*self.create_add_placeholder_const_net(**params,
use_legacy_frontend=use_legacy_frontend),
ie_device, precision, ir_version, temp_dir=temp_dir,
use_legacy_frontend=use_legacy_frontend)
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,
use_legacy_frontend):
self._test(*self.create_add_placeholder_const_net(**params,
use_legacy_frontend=use_legacy_frontend),
ie_device, precision, ir_version, temp_dir=temp_dir,
use_legacy_frontend=use_legacy_frontend)
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,
use_legacy_frontend):
self._test(*self.create_add_placeholder_const_net(**params,
use_legacy_frontend=use_legacy_frontend),
ie_device, precision, ir_version=ir_version, temp_dir=temp_dir,
use_legacy_frontend=use_legacy_frontend)
###############################################################################################
# #
# 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, use_legacy_frontend):
self._test(*self.create_add_placeholder_const_net(**params,
use_legacy_frontend=use_legacy_frontend),
ie_device, precision, ir_version=ir_version, temp_dir=temp_dir,
use_legacy_frontend=use_legacy_frontend)
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, use_legacy_frontend):
self._test(*self.create_add_placeholder_const_net(**params,
use_legacy_frontend=use_legacy_frontend),
ie_device, precision, ir_version=ir_version, temp_dir=temp_dir,
use_legacy_frontend=use_legacy_frontend)
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, use_legacy_frontend):
self._test(*self.create_add_placeholder_const_net(**params,
use_legacy_frontend=use_legacy_frontend),
ie_device, precision, ir_version=ir_version, temp_dir=temp_dir,
use_legacy_frontend=use_legacy_frontend)
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, use_legacy_frontend):
self._test(*self.create_add_placeholder_const_net(**params,
use_legacy_frontend=use_legacy_frontend),
ie_device, precision, ir_version=ir_version, temp_dir=temp_dir,
use_legacy_frontend=use_legacy_frontend)
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, use_legacy_frontend):
# we do not perform transpose in the test in case of new frontend
self._test(*self.create_add_placeholder_const_net(**params,
use_legacy_frontend=use_legacy_frontend),
ie_device, precision,
ir_version=ir_version, temp_dir=temp_dir, use_legacy_frontend=use_legacy_frontend)
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,
use_legacy_frontend):
self._test(
*self.create_complex_addv2_net(**params),
ie_device, precision, ir_version, temp_dir=temp_dir,
use_legacy_frontend=use_legacy_frontend)