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[TF FE] Implement a loader for ListDiff operation (#12868)

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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
2022-09-02 16:35:54 +03:00
committed by GitHub
parent 1d3e63c40e
commit e2e01bff32
2 changed files with 57 additions and 0 deletions
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55
src/frontends/tensorflow/src/op/list_diff.cpp Normal file
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@@ -0,0 +1,55 @@
// Copyright (C) 2018-2022 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//
#include "op_table.hpp"
#include "openvino/opsets/opset8.hpp"
using namespace std;
using namespace ov::opset8;
namespace ov {
namespace frontend {
namespace tensorflow {
namespace op {
OutputVector translate_list_diff_op(const NodeContext& node) {
// ListDiff computes the difference between two lists of numbers
default_op_checks(node, 2, {"ListDiff"});
auto x = node.get_input(0);
auto y = node.get_input(1);
// retrieve attribute
auto out_idx = node.get_attribute<ov::element::Type>("out_idx", ov::element::i32);
// unsqueeze both operand to make comparison elements between each other
auto unsqueeze_x =
make_shared<Unsqueeze>(x, make_shared<Constant>(ov::element::i64, ov::Shape{}, std::vector<int64_t>{1}));
auto unsqueeze_y =
make_shared<Unsqueeze>(y, make_shared<Constant>(ov::element::i64, ov::Shape{}, std::vector<int64_t>{0}));
// generate a mask where elements x and y are different
auto x_is_non_equal_y =
make_shared<ReduceLogicalOr>(make_shared<NotEqual>(unsqueeze_x, unsqueeze_y),
make_shared<Constant>(ov::element::i64, ov::Shape{}, std::vector<int64_t>{1}),
false);
auto mask01_x_is_non_equal_y =
make_shared<Select>(x_is_non_equal_y,
make_shared<Constant>(ov::element::i64, ov::Shape{}, std::vector<int64_t>{1}),
make_shared<Constant>(ov::element::i64, ov::Shape{}, std::vector<int64_t>{0}));
// compute indices of x elements different from elements of y
auto diff_output_indices =
make_shared<Reshape>(make_shared<NonZero>(mask01_x_is_non_equal_y, out_idx),
make_shared<Constant>(ov::element::i64, ov::Shape{1}, std::vector<int64_t>{-1}),
false);
// gather elements from x that occur in y
auto diff_x = make_shared<Gather>(x,
diff_output_indices,
make_shared<Constant>(ov::element::i64, ov::Shape{}, std::vector<int64_t>{0}));
return {diff_x, diff_output_indices};
}
} // namespace op
} // namespace tensorflow
} // namespace frontend
} // namespace ov

2
src/frontends/tensorflow/src/op_table.cpp
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@@ -54,6 +54,7 @@ OP_CONVERTER(translate_interpolate_op);
OP_CONVERTER(translate_is_finite_op);
OP_CONVERTER(translate_l2_loss_op);
OP_CONVERTER(translate_linspace_op);
OP_CONVERTER(translate_list_diff_op);
OP_CONVERTER(translate_leaky_relu_op);
OP_CONVERTER(translate_log_softmax_op);
OP_CONVERTER(translate_log_1p_op);
@@ -201,6 +202,7 @@ const std::map<std::string, CreatorFunction> get_supported_ops() {
{"L2Loss", translate_l2_loss_op},
{"LeakyRelu", translate_leaky_relu_op},
{"LinSpace", translate_linspace_op},
{"ListDiff", translate_list_diff_op},
{"LogSoftmax", translate_log_softmax_op},
{"Log1p", translate_log_1p_op},
{"LRN", translate_lrn_op},