[TF FE] Add layer test for Pack (#15518)
Signed-off-by: Kazantsev, Roman <roman.kazantsev@intel.com>
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@ -14,18 +14,21 @@ namespace tensorflow {
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namespace op {
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OutputVector translate_pack_op(const NodeContext& node) {
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auto axis = node.get_attribute<int64_t>("axis");
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default_op_checks(node, 1, {"Pack", "PACK"});
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auto num_size = static_cast<int>(node.get_input_size());
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auto axis = node.get_attribute<int64_t>("axis", 0);
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auto axis_const = make_shared<Constant>(element::i64, Shape{}, axis);
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OutputVector concat_inputs;
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for (size_t i = 0; i < node.get_input_size(); ++i) {
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auto in = node.get_input(static_cast<int>(i));
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for (int ind = 0; ind < num_size; ++ind) {
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auto in = node.get_input(ind);
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concat_inputs.push_back(make_shared<Unsqueeze>(in, axis_const));
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}
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auto res = make_shared<Concat>(concat_inputs, axis);
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set_node_name(node.get_name(), res);
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return res->outputs();
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auto pack = make_shared<Concat>(concat_inputs, axis);
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set_node_name(node.get_name(), pack);
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return {pack};
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}
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} // namespace op
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} // namespace tensorflow
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53
tests/layer_tests/tensorflow_tests/test_tf_Pack.py
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53
tests/layer_tests/tensorflow_tests/test_tf_Pack.py
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@ -0,0 +1,53 @@
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# Copyright (C) 2018-2023 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import numpy as np
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import pytest
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import tensorflow as tf
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from common.tf_layer_test_class import CommonTFLayerTest
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class TestPack(CommonTFLayerTest):
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def _prepare_input(self, inputs_info):
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inputs_data = {}
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for input_name, input_shape in inputs_info.items():
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inputs_data[input_name] = np.random.randint(-5, 5, input_shape).astype(self.input_type)
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return inputs_data
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def create_pack_net(self, input_shape, input_num, axis, input_type):
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self.input_type = input_type
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tf.compat.v1.reset_default_graph()
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# Create the graph and model
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with tf.compat.v1.Session() as sess:
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inputs = []
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type_map = {
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np.float32: tf.float32,
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np.int32: tf.int32,
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}
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assert input_type in type_map, "Test error: need to update type_map"
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tf_type = type_map[input_type]
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for ind in range(input_num):
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inputs.append(tf.compat.v1.placeholder(tf_type, input_shape, 'input' + str(ind)))
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if axis is not None:
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tf.raw_ops.Pack(values=inputs, axis=axis)
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else:
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tf.raw_ops.Pack(values=inputs)
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tf.compat.v1.global_variables_initializer()
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tf_net = sess.graph_def
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return tf_net, None
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test_data_basic = [
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dict(input_shape=[2, 4], input_num=2, axis=None, input_type=np.float32),
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dict(input_shape=[3, 1, 2], input_num=3, axis=1, input_type=np.int32),
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]
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@pytest.mark.parametrize("params", test_data_basic)
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@pytest.mark.precommit_tf_fe
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@pytest.mark.nightly
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def test_pack_basic(self, params, ie_device, precision, ir_version, temp_dir,
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use_new_frontend, use_old_api):
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self._test(*self.create_pack_net(**params),
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ie_device, precision, ir_version, temp_dir=temp_dir,
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use_new_frontend=use_new_frontend, use_old_api=use_old_api)
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