[TF FE] Add layer test for Pack (#15518)

Signed-off-by: Kazantsev, Roman <roman.kazantsev@intel.com>
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Roman Kazantsev 2023-02-06 12:49:29 +04:00 committed by GitHub
parent b04513c92e
commit 7845ca499e
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2 changed files with 62 additions and 6 deletions

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@ -14,18 +14,21 @@ namespace tensorflow {
namespace op {
OutputVector translate_pack_op(const NodeContext& node) {
auto axis = node.get_attribute<int64_t>("axis");
default_op_checks(node, 1, {"Pack", "PACK"});
auto num_size = static_cast<int>(node.get_input_size());
auto axis = node.get_attribute<int64_t>("axis", 0);
auto axis_const = make_shared<Constant>(element::i64, Shape{}, axis);
OutputVector concat_inputs;
for (size_t i = 0; i < node.get_input_size(); ++i) {
auto in = node.get_input(static_cast<int>(i));
for (int ind = 0; ind < num_size; ++ind) {
auto in = node.get_input(ind);
concat_inputs.push_back(make_shared<Unsqueeze>(in, axis_const));
}
auto res = make_shared<Concat>(concat_inputs, axis);
set_node_name(node.get_name(), res);
return res->outputs();
auto pack = make_shared<Concat>(concat_inputs, axis);
set_node_name(node.get_name(), pack);
return {pack};
}
} // namespace op
} // namespace tensorflow

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@ -0,0 +1,53 @@
# Copyright (C) 2018-2023 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 TestPack(CommonTFLayerTest):
def _prepare_input(self, inputs_info):
inputs_data = {}
for input_name, input_shape in inputs_info.items():
inputs_data[input_name] = np.random.randint(-5, 5, input_shape).astype(self.input_type)
return inputs_data
def create_pack_net(self, input_shape, input_num, axis, 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:
inputs = []
type_map = {
np.float32: tf.float32,
np.int32: tf.int32,
}
assert input_type in type_map, "Test error: need to update type_map"
tf_type = type_map[input_type]
for ind in range(input_num):
inputs.append(tf.compat.v1.placeholder(tf_type, input_shape, 'input' + str(ind)))
if axis is not None:
tf.raw_ops.Pack(values=inputs, axis=axis)
else:
tf.raw_ops.Pack(values=inputs)
tf.compat.v1.global_variables_initializer()
tf_net = sess.graph_def
return tf_net, None
test_data_basic = [
dict(input_shape=[2, 4], input_num=2, axis=None, input_type=np.float32),
dict(input_shape=[3, 1, 2], input_num=3, axis=1, input_type=np.int32),
]
@pytest.mark.parametrize("params", test_data_basic)
@pytest.mark.precommit_tf_fe
@pytest.mark.nightly
def test_pack_basic(self, params, ie_device, precision, ir_version, temp_dir,
use_new_frontend, use_old_api):
self._test(*self.create_pack_net(**params),
ie_device, precision, ir_version, temp_dir=temp_dir,
use_new_frontend=use_new_frontend, use_old_api=use_old_api)