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[TF FE] Fix TopK translator and add test to the pre-commit (#13971)

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Signed-off-by: Kazantsev, Roman <roman.kazantsev@intel.com>

Signed-off-by: Kazantsev, Roman <roman.kazantsev@intel.com>
This commit is contained in:
Roman Kazantsev 2022-11-14 13:02:12 +03:00 committed by GitHub
parent bbd221e6d3
commit 3b7a5c691d
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2 changed files with 55 additions and 1 deletions
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2
src/frontends/tensorflow/src/op/top_k.cpp
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@ -25,7 +25,7 @@ OutputVector translate_top_k_base_op(const NodeContext& node, const ov::Output<o
sorted ? TopK::SortType::SORT_VALUES : TopK::SortType::SORT_INDICES,
ov::element::i32);
set_node_name(node.get_name(), top_k);
return {top_k};
return top_k->outputs();
}
OutputVector translate_top_k_op(const NodeContext& node) {
// retrieve k attribute

54
tests/layer_tests/tensorflow_tests/test_tf_TopKV2.py Normal file
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@ -0,0 +1,54 @@
# Copyright (C) 2018-2022 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 TestTopKV2(CommonTFLayerTest):
def _prepare_input(self, inputs_info):
# generate elements so that the input tensor may contain repeating elements
assert 'input' in inputs_info, "Test error: inputs_info must contain `input`"
x_shape = inputs_info['input']
inputs_data = {}
inputs_data['input'] = np.random.randint(-10, 10, x_shape)
return inputs_data
def create_topk_v2_net(self, input_shape, input_type, k, sorted, is_first_output, is_second_output):
tf.compat.v1.reset_default_graph()
with tf.compat.v1.Session() as sess:
input = tf.compat.v1.placeholder(input_type, input_shape, 'input')
k = tf.constant(k, dtype=tf.int32, shape=[])
topk = tf.raw_ops.TopKV2(input=input, k=k, sorted=sorted)
if is_first_output:
tf.identity(topk[0], name='topk_values')
if is_second_output:
tf.identity(topk[1], name='unique_indices')
tf.compat.v1.global_variables_initializer()
tf_net = sess.graph_def
ref_net = None
return tf_net, None
test_basic = [
dict(input_shape=[10], input_type=tf.float32, k=5, sorted=True, is_first_output=True, is_second_output=False),
dict(input_shape=[2, 3, 10], input_type=tf.int32, k=10, sorted=True, is_first_output=True,
is_second_output=False),
# Currently, OpenVINO TopK supports only TensorFlow TopK with sorted=True and the first output
# For other cases, we need to introduce new version of TopK in OpenVINO opset due to multiple misalignments
# described in 88024
pytest.param(dict(input_shape=[4, 12], input_type=tf.float32, k=10, sorted=True, is_first_output=True,
is_second_output=True), marks=pytest.mark.xfail(reason="88024")),
pytest.param(dict(input_shape=[5, 10], input_type=tf.int32, k=8, sorted=False, is_first_output=True,
is_second_output=True), marks=pytest.mark.xfail(reason="88024")),
]
@pytest.mark.parametrize("params", test_basic)
@pytest.mark.precommit_tf_fe
def test_topk_v2_basic(self, params, ie_device, precision, ir_version, temp_dir, use_new_frontend,
use_old_api):
self._test(*self.create_topk_v2_net(**params),
ie_device, precision, ir_version, temp_dir=temp_dir,
use_new_frontend=use_new_frontend, use_old_api=use_old_api)