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Fixed static analysis issues (transformations) (#3281)

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This commit is contained in:
Maxim Andronov 2020-11-23 14:16:23 +03:00 committed by GitHub
parent 7e2305543a
commit a555efe287
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GPG Key ID: 4AEE18F83AFDEB23
6 changed files with 26 additions and 5 deletions
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15
inference-engine/src/legacy_api/src/transformations/convert_opset1_to_legacy/convert_sequences_to_sequences_ie.cpp
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@ -112,7 +112,10 @@ ngraph::pass::ConvertLSTMSequenceMatcher::ConvertLSTMSequenceMatcher() {
if (seq_axis == 1) {
ngraph::replace_node(lstm_sequence, {unsqueeze_1->output(0), unsqueeze_2->output(0), unsqueeze_3->output(0)});
} else {
auto transpose_after = lstm_sequence->output(0).get_target_inputs().begin()->get_node()->shared_from_this();
const auto &lstm_target_inputs = lstm_sequence->output(0).get_target_inputs();
if (lstm_target_inputs.empty())
return false;
auto transpose_after = lstm_target_inputs.begin()->get_node()->shared_from_this();
ngraph::replace_node(transpose_after, unsqueeze_1);
ngraph::replace_node(lstm_sequence, {lstm_sequence_ie->output(0), unsqueeze_2->output(0), unsqueeze_3->output(0)});
}
@ -179,7 +182,10 @@ ngraph::pass::ConvertGRUSequenceMatcher::ConvertGRUSequenceMatcher() {
if (seq_axis == 1) {
ngraph::replace_node(gru_sequence, {unsqueeze_1->output(0), unsqueeze_2->output(0)});
} else {
auto transpose_after = gru_sequence->output(0).get_target_inputs().begin()->get_node()->shared_from_this();
const auto &gru_target_inputs = gru_sequence->output(0).get_target_inputs();
if (gru_target_inputs.empty())
return false;
auto transpose_after = gru_target_inputs.begin()->get_node()->shared_from_this();
ngraph::replace_node(transpose_after, unsqueeze_1);
ngraph::replace_node(gru_sequence, {gru_sequence_ie->output(0), unsqueeze_2->output(0)});
}
@ -247,7 +253,10 @@ ngraph::pass::ConvertRNNSequenceMatcher::ConvertRNNSequenceMatcher() {
if (seq_axis == 1) {
ngraph::replace_node(rnn_sequence, {unsqueeze_1->output(0), unsqueeze_2->output(0)});
} else {
auto transpose_after = rnn_sequence->output(0).get_target_inputs().begin()->get_node()->shared_from_this();
const auto &rnn_target_inputs = rnn_sequence->output(0).get_target_inputs();
if (rnn_target_inputs.empty())
return false;
auto transpose_after = rnn_target_inputs.begin()->get_node()->shared_from_this();
ngraph::replace_node(transpose_after, unsqueeze_1);
ngraph::replace_node(rnn_sequence, {rnn_sequence_ie->output(0), unsqueeze_2->output(0)});
}

2
inference-engine/src/low_precision_transformations/src/concat.cpp
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@ -214,7 +214,7 @@ bool ConcatTransformation::isPrecisionPreserved(std::shared_ptr<Node>) const noe
bool ConcatTransformation::canBeTransformed(const TransformationContext& context, std::shared_ptr<Node> layer) const {
std::shared_ptr<opset1::Concat> concat = as_type_ptr<opset1::Concat>(layer);
return concat->get_axis() == 1ul;
return concat && concat->get_axis() == 1ul;
}

4
inference-engine/src/transformations/src/transformations/common_optimizations/nop_elimination.cpp
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@ -194,6 +194,8 @@ static bool eliminate_unsqueeze(const std::shared_ptr<Node>& node) {
}
auto unsqueeze = as_type_ptr<opset3::Unsqueeze>(node);
if (unsqueeze == nullptr)
return false;
auto input = unsqueeze->input_value(0).get_node_shared_ptr();
auto squeeze = as_type_ptr<opset3::Squeeze>(input);
auto replace_unsqueeze_only = [&](const vector<int64_t>& axes) {
@ -260,6 +262,8 @@ static bool eliminate_squeeze(const std::shared_ptr<Node>& node) {
}
auto squeeze = as_type_ptr<opset3::Squeeze>(node);
if (squeeze == nullptr)
return false;
auto input = squeeze->input_value(0).get_node_shared_ptr();
auto replace_squeeze_only = [&](const vector<int64_t>& axes) {
auto axes_const = opset3::Constant::create<int64_t>(element::i64, Shape{axes.size()}, axes);

2
inference-engine/src/transformations/src/transformations/convert_precision.cpp
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@ -349,6 +349,8 @@ static std::shared_ptr<Node> change_constant_precision(std::shared_ptr<opset4::C
auto new_constant = std::make_shared<ngraph::opset4::Constant>(PREC_TO, constant->get_shape());
auto * dst_data = const_cast<dst_type *>(reinterpret_cast<const dst_type *>(new_constant->get_data_ptr()));
if (dst_data == nullptr)
throw ngraph_error("Can't get destination data pointer");
std::vector<dst_type> final_data;
for (size_t i = 0; i < size; ++i) {

6
inference-engine/src/transformations/src/transformations/op_conversions/convert_ti_to_sequences.cpp
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@ -132,6 +132,8 @@ ngraph::pass::ConvertTensorIteratorToLSTMSequence::ConvertTensorIteratorToLSTMSe
auto seq_lengths = ngraph::opset5::Constant::create(element::i32, Shape{batch_size}, {ti->get_num_iterations()});
const auto& lstm_cell = std::dynamic_pointer_cast<ngraph::op::util::RNNCellBase>(found_cell);
if (lstm_cell == nullptr)
return false;
auto in_0 = ti->input_values()[ordered_in_descs[0]->m_input_index];
if (slice_axis == 0) {
auto order = ngraph::opset5::Constant::create(ngraph::element::i64, ngraph::Shape{3}, {1, 0, 2});
@ -283,6 +285,8 @@ ngraph::pass::ConvertTensorIteratorToRNNSequence::ConvertTensorIteratorToRNNSequ
}
const auto& rnn_cell = std::dynamic_pointer_cast<ngraph::opset5::RNNCell>(pattern_map[cell]);
if (rnn_cell == nullptr)
return false;
auto in_0 = ti->input_values()[ordered_in_descs[0]->m_input_index];
if (slice_axis == 0) {
@ -434,6 +438,8 @@ ngraph::pass::ConvertTensorIteratorToGRUSequence::ConvertTensorIteratorToGRUSequ
}
const auto& rnn_cell = std::dynamic_pointer_cast<ngraph::opset5::GRUCell>(pattern_map[cell]);
if (rnn_cell == nullptr)
return false;
auto in_0 = ti->input_values()[ordered_in_descs[0]->m_input_index];
if (slice_axis == 0) {

2
inference-engine/src/transformations/src/transformations/op_conversions/log_softmax_decomposition.cpp
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@ -20,7 +20,7 @@ ngraph::pass::LogSoftmaxDecomposition::LogSoftmaxDecomposition() {
auto& pattern_to_output = m.get_pattern_value_map();
auto log_softmax_node = std::dynamic_pointer_cast<ngraph::opset5::LogSoftmax>(pattern_to_output.at(log_softmax).get_node_shared_ptr());
if (m_transformation_callback(log_softmax_node)) {
if (log_softmax_node == nullptr || m_transformation_callback(log_softmax_node)) {
return false;
}