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test_tf_Eltwise.py
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# Copyright (C) 2018-2025 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import pytest
from common.tf_layer_test_class import CommonTFLayerTest
class TestEltwise(CommonTFLayerTest):
def create_eltwise_net(self, shape, operation, ir_version, 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, shape, 'Input')
y = tf.compat.v1.placeholder(tf.float32, shape, 'Input') # Input_1 in graph_def
if operation == 'sum':
tf.add(x, y, name='Operation')
elif operation == 'max':
tf.maximum(x, y, name='Operation')
elif operation == 'mul':
tf.multiply(x, y, name='Operation')
tf.compat.v1.global_variables_initializer()
tf_net = sess.graph_def
ref_net = None
return tf_net, ref_net
test_data = []
for operation in ['sum', 'max', 'mul']:
test_data.extend([dict(shape=[1, 224], operation=operation),
pytest.param(dict(shape=[1, 224, 224], operation=operation),
marks=pytest.mark.precommit),
dict(shape=[1, 3, 224, 224], operation=operation)])
@pytest.mark.parametrize("params", test_data)
@pytest.mark.nightly
def test_eltwise(self, params, ie_device, precision, ir_version, temp_dir, use_legacy_frontend):
self._test(*self.create_eltwise_net(**params, ir_version=ir_version,
use_legacy_frontend=use_legacy_frontend),
ie_device, precision, ir_version, temp_dir=temp_dir,
use_legacy_frontend=use_legacy_frontend)
test_data_5D = []
for operation in ['sum', 'max', 'mul']:
test_data_5D.extend([dict(shape=[1, 3, 224, 224, 224], operation=operation)])
@pytest.mark.parametrize("params", test_data_5D)
@pytest.mark.precommit
@pytest.mark.nightly
def test_eltwise_5D_precommit(self, params, ie_device, precision, ir_version, temp_dir,
use_legacy_frontend):
if ie_device == 'GPU':
pytest.skip("5D tensors is not supported on GPU")
self._test(*self.create_eltwise_net(**params, ir_version=ir_version,
use_legacy_frontend=use_legacy_frontend),
ie_device, precision, ir_version, temp_dir=temp_dir,
use_legacy_frontend=use_legacy_frontend)