[TF FE] Support ShapeN operation (#18913)

Signed-off-by: Kazantsev, Roman <roman.kazantsev@intel.com>
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Roman Kazantsev 2023-08-02 17:28:39 +04:00 committed by GitHub
parent 7b4a7e5eb4
commit b44f915a9d
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3 changed files with 64 additions and 8 deletions

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@ -233,6 +233,7 @@ const std::map<std::string, CreatorFunction> get_supported_ops() {
{"Select", CreatorFunction(translate_select_op)},
{"SelectV2", CreatorFunction(translate_select_v2_op)},
{"Shape", CreatorFunction(translate_shape_op)},
{"ShapeN", CreatorFunction(translate_shape_op)},
{"Size", CreatorFunction(translate_size_op)},
{"Slice", CreatorFunction(translate_slice_op)},
{"Snapshot", CreatorFunction(translate_identity_op)},

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@ -3,26 +3,43 @@
//
#include "common_op_table.hpp"
#include "openvino/opsets/opset8.hpp"
#include "openvino/op/shape_of.hpp"
using namespace std;
using namespace ov;
using namespace ov::opset8;
using namespace ov::op;
namespace ov {
namespace frontend {
namespace tensorflow {
namespace op {
ov::OutputVector translate_shape_op(const NodeContext& node) {
default_op_checks(node, 1, {"Shape", "SHAPE"});
auto input = node.get_input(0);
OutputVector translate_shape_op(const NodeContext& node) {
default_op_checks(node, 1, {"Shape", "ShapeN", "SHAPE"});
auto input_size = static_cast<int>(node.get_input_size());
auto out_type = node.get_attribute<element::Type>("out_type", element::i32);
auto shapeof = make_shared<ShapeOf>(input, out_type);
set_node_name(node.get_name(), shapeof);
auto node_name = node.get_name();
if (input_size == 1) {
auto input = node.get_input(0);
auto shapeof = make_shared<v3::ShapeOf>(input, out_type);
set_node_name(node_name, shapeof);
return {shapeof};
}
OutputVector outputs;
for (int input_ind = 0; input_ind < input_size; ++input_ind) {
auto input = node.get_input(input_ind);
auto shapeof = make_shared<v3::ShapeOf>(input, out_type);
shapeof->set_friendly_name(node_name + "_" + to_string(input_ind));
auto shapeof_output = shapeof->output(0);
set_out_name({node_name + ":" + to_string(input_ind)}, shapeof_output);
outputs.push_back(shapeof_output);
}
return outputs;
}
} // namespace op
} // namespace tensorflow
} // namespace frontend

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@ -0,0 +1,38 @@
# Copyright (C) 2018-2023 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import pytest
import tensorflow as tf
from common.tf_layer_test_class import CommonTFLayerTest
class TestShapeN(CommonTFLayerTest):
def create_shape_n_net(self, input_shapes, out_type):
tf.compat.v1.reset_default_graph()
# Create the graph and model
with tf.compat.v1.Session() as sess:
inputs = []
for ind, input_shape in enumerate(input_shapes):
inputs.append(tf.compat.v1.placeholder(tf.float32, input_shape, 'input_{}'.format(ind)))
shapen = tf.raw_ops.ShapeN(input=inputs, out_type=out_type)
tf.raw_ops.ConcatV2(values=shapen, axis=0)
tf.compat.v1.global_variables_initializer()
tf_net = sess.graph_def
return tf_net, None
test_data_basic = [
dict(input_shapes=[[2, 3], [1]], out_type=tf.int32),
dict(input_shapes=[[3], [3, 2, 1], [], [4, 3, 1, 1]], out_type=tf.int64),
]
@pytest.mark.parametrize("params", test_data_basic)
@pytest.mark.precommit_tf_fe
@pytest.mark.nightly
def test_shape_n_basic(self, params, ie_device, precision, ir_version, temp_dir,
use_new_frontend, use_old_api):
self._test(*self.create_shape_n_net(**params),
ie_device, precision, ir_version, temp_dir=temp_dir,
use_new_frontend=use_new_frontend, use_old_api=use_old_api)