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test_tf_Concat.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 TestConcat(CommonTFLayerTest):
def create_concat_net(self, input_shapes, axis, is_v2, ir_version, use_legacy_frontend):
# tf.concat is equivalent to tf.raw_ops.ConcatV2
# only tf.concat accepts one input
import tensorflow as tf
tf.compat.v1.reset_default_graph()
with tf.compat.v1.Session() as sess:
placeholders = []
for ind, input_shape in enumerate(input_shapes):
placeholders.append(tf.compat.v1.placeholder(tf.float32, input_shape, 'input_{}'.format(ind)))
if len(input_shapes) == 1:
tf.concat(values=placeholders, axis=axis, name='concat')
elif is_v2:
tf.raw_ops.ConcatV2(values=placeholders, axis=axis, name='concat')
else:
tf.raw_ops.Concat(values=placeholders, concat_dim=axis, name='concat')
tf.compat.v1.global_variables_initializer()
tf_net = sess.graph_def
ref_net = None
return tf_net, ref_net
test_data_basic = [
dict(input_shapes=[[1], [3]], axis=-1, is_v2=True),
dict(input_shapes=[[3, 4]], axis=0, is_v2=True),
dict(input_shapes=[[1, 3, 5], [2, 3, 5]], axis=0, is_v2=False),
dict(input_shapes=[[1, 3, 5, 7, 8], [1, 3, 2, 7, 8]], axis=2, is_v2=False),
dict(input_shapes=[[1, 3, 5, 7, 2], [1, 3, 5, 7, 3], [1, 3, 5, 7, 2], [1, 3, 5, 7, 4]],
axis=-1, is_v2=True),
]
@pytest.mark.parametrize("params", test_data_basic)
@pytest.mark.precommit
@pytest.mark.nightly
def test_concat_basic(self, params, ie_device, precision, ir_version, temp_dir, use_legacy_frontend):
self._test(*self.create_concat_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_1D = [
dict(input_shapes=[[1], [2]], axis=0, is_v2=False),
]
@pytest.mark.parametrize("params", test_data_1D)
@pytest.mark.nightly
def test_concat_1D(self, params, ie_device, precision, ir_version, temp_dir, use_legacy_frontend):
self._test(*self.create_concat_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_2D = [
dict(input_shapes=[[1, 4], [1, 2]], axis=-1, is_v2=True)
]
@pytest.mark.parametrize("params", test_data_2D)
@pytest.mark.nightly
def test_concat_2D(self, params, ie_device, precision, ir_version, temp_dir, use_legacy_frontend):
self._test(*self.create_concat_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_3D = [
dict(input_shapes=[[1, 3, 2], [1, 3, 5]], axis=-1, is_v2=True),
dict(input_shapes=[[1, 3, 1], [1, 3, 4], [1, 3, 3]], axis=2, is_v2=True)
]
@pytest.mark.parametrize("params", test_data_3D)
@pytest.mark.nightly
def test_concat_3D(self, params, ie_device, precision, ir_version, temp_dir, use_legacy_frontend):
self._test(*self.create_concat_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_4D = [
dict(input_shapes=[[1, 3, 5, 7], [3, 3, 5, 7], [2, 3, 5, 7]], axis=0, is_v2=False),
dict(input_shapes=[[1, 3, 5, 5], [1, 3, 5, 7]], axis=-1, is_v2=True),
dict(input_shapes=[[1, 3, 5, 7], [1, 3, 3, 7]], axis=2, is_v2=False)
]
@pytest.mark.parametrize("params", test_data_4D)
@pytest.mark.nightly
def test_concat_4D(self, params, ie_device, precision, ir_version, temp_dir, use_legacy_frontend):
self._test(*self.create_concat_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 = [
dict(input_shapes=[[1, 3, 5, 7, 8], [2, 3, 5, 7, 8]], axis=0, is_v2=True),
]
@pytest.mark.parametrize("params", test_data_5D)
@pytest.mark.nightly
def test_concat_5D(self, params, ie_device, precision, ir_version, temp_dir, use_legacy_frontend):
self._test(*self.create_concat_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)