diff --git a/docs/ops/movement/VariadicSplit_1.md b/docs/ops/movement/VariadicSplit_1.md index 50bbbd6e959..87c9ac67b65 100644 --- a/docs/ops/movement/VariadicSplit_1.md +++ b/docs/ops/movement/VariadicSplit_1.md @@ -26,7 +26,7 @@ Where D is the rank of input tensor `data`. The sum of elements in `split_length * **2**: `axis`. Axis along `data` to split. A scalar of type `T2` with value from range `-rank(data) .. rank(data)-1`. Negative values address dimensions from the end. **Required.** -* **3**: `split_lengths`. A list containing the dimension values of each output tensor shape along the split `axis`. A 1D tensor of type `T2`. The number of elements in `split_lengths` determines the number of outputs. The sum of elements in `split_lengths` must match `data.shape[axis]`. In addition `split_lenghts` can contain a single `-1` element, which means, all remaining items along specified `axis` that are not consumed by other parts. **Required.** +* **3**: `split_lengths`. A list containing the dimension values of each output tensor shape along the split `axis`. A 1D tensor of type `T2`. The number of elements in `split_lengths` determines the number of outputs. The sum of elements in `split_lengths` must match `data.shape[axis]`. In addition `split_lengths` can contain a single `-1` element, which means, all remaining items along specified `axis` that are not consumed by other parts. **Required.** **Outputs** diff --git a/inference-engine/src/legacy_api/include/legacy/ngraph_ops/lstm_sequence_ie.hpp b/inference-engine/src/legacy_api/include/legacy/ngraph_ops/lstm_sequence_ie.hpp index 68f2688a57f..641f93bd063 100644 --- a/inference-engine/src/legacy_api/include/legacy/ngraph_ops/lstm_sequence_ie.hpp +++ b/inference-engine/src/legacy_api/include/legacy/ngraph_ops/lstm_sequence_ie.hpp @@ -24,7 +24,7 @@ public: LSTMSequenceIE(const Output &X, const Output &H_t, const Output &C_t, - const Output &seq_lenghts, + const Output &seq_lengths, const Output &WR, const Output &B, size_t hidden_size, diff --git a/inference-engine/src/legacy_api/src/ngraph_ops/gru_sequence_ie.cpp b/inference-engine/src/legacy_api/src/ngraph_ops/gru_sequence_ie.cpp index 296e65a786d..1920221c476 100644 --- a/inference-engine/src/legacy_api/src/ngraph_ops/gru_sequence_ie.cpp +++ b/inference-engine/src/legacy_api/src/ngraph_ops/gru_sequence_ie.cpp @@ -16,7 +16,7 @@ NGRAPH_RTTI_DEFINITION(op::GRUSequenceIE, "GRUSequenceIE", 4); op::GRUSequenceIE::GRUSequenceIE(const Output& X, const Output& H_t, - const Output& seq_lenghts, + const Output& seq_lengths, const Output& WR, const Output& B, std::size_t hidden_size, @@ -27,7 +27,7 @@ op::GRUSequenceIE::GRUSequenceIE(const Output& X, float clip, bool linear_before_reset, int64_t seq_axis) - : RNNCellBase({X, H_t, seq_lenghts, WR, B}, hidden_size, clip, activations, activations_alpha, activations_beta), + : RNNCellBase({X, H_t, seq_lengths, WR, B}, hidden_size, clip, activations, activations_alpha, activations_beta), m_direction(direction), m_linear_before_reset(linear_before_reset), m_seq_axis(seq_axis) { @@ -50,7 +50,7 @@ void op::GRUSequenceIE::validate_and_infer_types() { auto b_pshape = get_input_partial_shape(4); std::vector pshapes = {x_pshape, h_state_pshape, seq_lengths_pshape, wr_pshape, b_pshape}; - std::vector in_names = {"X", "H", "seq_lenghts", "WR", "B"}; + std::vector in_names = {"X", "H", "seq_lengths", "WR", "B"}; // num_direction dimension should be squeezed, we don't support bidirectional case std::vector ranks = {3, 2, 1, 2, 1}; for (size_t i = 0; i < pshapes.size(); ++i) { diff --git a/inference-engine/src/legacy_api/src/ngraph_ops/lstm_sequence_ie.cpp b/inference-engine/src/legacy_api/src/ngraph_ops/lstm_sequence_ie.cpp index e0aa3f3ef77..b32ae8205ef 100644 --- a/inference-engine/src/legacy_api/src/ngraph_ops/lstm_sequence_ie.cpp +++ b/inference-engine/src/legacy_api/src/ngraph_ops/lstm_sequence_ie.cpp @@ -17,7 +17,7 @@ NGRAPH_RTTI_DEFINITION(op::LSTMSequenceIE, "LSTMSequenceIE", 5); op::LSTMSequenceIE::LSTMSequenceIE(const Output &X, const Output &H_t, const Output &C_t, - const Output &seq_lenghts, + const Output &seq_lengths, const Output &WR, const Output &B, std::size_t hidden_size, @@ -27,7 +27,7 @@ op::LSTMSequenceIE::LSTMSequenceIE(const Output &X, const std::vector &activations_beta, float clip, int64_t seq_axis) - : RNNCellBase({X, H_t, C_t, seq_lenghts, WR, B}, hidden_size, clip, activations, activations_alpha, activations_beta), + : RNNCellBase({X, H_t, C_t, seq_lengths, WR, B}, hidden_size, clip, activations, activations_alpha, activations_beta), m_direction(direction), m_seq_axis(seq_axis) { constructor_validate_and_infer_types(); @@ -52,7 +52,7 @@ void op::LSTMSequenceIE::validate_and_infer_types() { std::vector pshapes = {x_pshape, h_state_pshape, c_state_pshape, seq_lengths_pshape, wr_pshape, b_pshape}; - std::vector in_names = {"X", "H", "C", "seq_lenghts", "WR", "B"}; + std::vector in_names = {"X", "H", "C", "seq_lengths", "WR", "B"}; // num_direction dimension should be squeezed, we don't support bidirectional case std::vector ranks = {3, 2, 2, 1, 2, 1}; for (size_t i = 0; i < pshapes.size(); ++i) { diff --git a/inference-engine/src/legacy_api/src/ngraph_ops/rnn_sequence_ie.cpp b/inference-engine/src/legacy_api/src/ngraph_ops/rnn_sequence_ie.cpp index 6b0a1c97dd4..168885de406 100644 --- a/inference-engine/src/legacy_api/src/ngraph_ops/rnn_sequence_ie.cpp +++ b/inference-engine/src/legacy_api/src/ngraph_ops/rnn_sequence_ie.cpp @@ -48,7 +48,7 @@ void op::RNNSequenceIE::validate_and_infer_types() { auto b_pshape = get_input_partial_shape(4); std::vector pshapes = {x_pshape, h_state_pshape, seq_lengths_pshape, wr_pshape, b_pshape}; - std::vector in_names = {"X", "H", "seq_lenghts", "WR", "B"}; + std::vector in_names = {"X", "H", "seq_lengths", "WR", "B"}; // num_direction dimension should be squeezed, we don't support bidirectional case std::vector ranks = {3, 2, 1, 2, 1}; for (size_t i = 0; i < pshapes.size(); ++i) { diff --git a/inference-engine/src/vpu/myriad_plugin/myriad_metrics.cpp b/inference-engine/src/vpu/myriad_plugin/myriad_metrics.cpp index 3d314cc873c..fc022ff4184 100644 --- a/inference-engine/src/vpu/myriad_plugin/myriad_metrics.cpp +++ b/inference-engine/src/vpu/myriad_plugin/myriad_metrics.cpp @@ -81,13 +81,13 @@ std::vector MyriadMetrics::AvailableDevicesNames( std::string MyriadMetrics::FullName(std::string deviceName) const { std::string nameDelimiter("-ma"); - unsigned int indexLenght = 4; + unsigned int indexLength = 4; unsigned int placeOfTypeId = 2; auto indexStr = deviceName; indexStr.erase(0, indexStr.find(nameDelimiter) + nameDelimiter.length()); - if (indexLenght != indexStr.length()) { + if (indexLength != indexStr.length()) { return deviceName; } else { auto myriadId = std::string(1, indexStr[placeOfTypeId]); diff --git a/inference-engine/tests/functional/inference_engine/onnx_reader/onnx_reader_external_data.cpp b/inference-engine/tests/functional/inference_engine/onnx_reader/onnx_reader_external_data.cpp index 3a72dbf6e80..2ae931d76b8 100644 --- a/inference-engine/tests/functional/inference_engine/onnx_reader/onnx_reader_external_data.cpp +++ b/inference-engine/tests/functional/inference_engine/onnx_reader/onnx_reader_external_data.cpp @@ -64,7 +64,7 @@ TEST(ONNX_Reader_Tests, ImportModelWithExternalDataFromStringException) { EXPECT_PRED_FORMAT2( testing::IsSubstring, - std::string("data/tensor.data, offset: 0, data_lenght: 0, sha1_digest: 0)"), + std::string("data/tensor.data, offset: 0, data_length: 0, sha1_digest: 0)"), e.what()); } catch(...) { diff --git a/inference-engine/tests/functional/inference_engine/transformations/convert_sequences_to_sequences_ie_test.cpp b/inference-engine/tests/functional/inference_engine/transformations/convert_sequences_to_sequences_ie_test.cpp index 30e69d7f7b7..76b4cce3f4c 100644 --- a/inference-engine/tests/functional/inference_engine/transformations/convert_sequences_to_sequences_ie_test.cpp +++ b/inference-engine/tests/functional/inference_engine/transformations/convert_sequences_to_sequences_ie_test.cpp @@ -229,7 +229,7 @@ TEST(TransformationTests, LSTMSequenceConversionTest) { ngraph::Shape{batch_size, num_directions, hidden_size}); const auto C_t = std::make_shared(ngraph::element::f32, ngraph::Shape{batch_size, num_directions, hidden_size}); - const auto seq_lenghts = std::make_shared(ngraph::element::f32, + const auto seq_lengths = std::make_shared(ngraph::element::f32, ngraph::Shape{batch_size}); const auto B = std::make_shared(ngraph::element::f32, ngraph::Shape{num_directions, @@ -245,7 +245,7 @@ TEST(TransformationTests, LSTMSequenceConversionTest) { auto sequence_ie = std::make_shared(X, in_1, in_2, - seq_lenghts, + seq_lengths, in_3, in_4, sequence->get_hidden_size(), diff --git a/inference-engine/tests/functional/plugin/cpu/shared_tests_instances/single_layer_tests/gru_sequence.cpp b/inference-engine/tests/functional/plugin/cpu/shared_tests_instances/single_layer_tests/gru_sequence.cpp index 7e3dea8b04f..5521023a192 100644 --- a/inference-engine/tests/functional/plugin/cpu/shared_tests_instances/single_layer_tests/gru_sequence.cpp +++ b/inference-engine/tests/functional/plugin/cpu/shared_tests_instances/single_layer_tests/gru_sequence.cpp @@ -16,7 +16,7 @@ namespace { ngraph::helpers::SequenceTestsMode::PURE_SEQ_RAND_SEQ_LEN_PARAM, ngraph::helpers::SequenceTestsMode::PURE_SEQ_RAND_SEQ_LEN_CONST, ngraph::helpers::SequenceTestsMode::PURE_SEQ}; - // output values increase rapidly without clip, so use only seq_lenghts = 2 + // output values increase rapidly without clip, so use only seq_lengths = 2 std::vector seq_lengths_zero_clip{2}; std::vector seq_lengths_clip_non_zero{20}; std::vector batch{10}; diff --git a/inference-engine/tests/functional/plugin/cpu/shared_tests_instances/single_layer_tests/loop.cpp b/inference-engine/tests/functional/plugin/cpu/shared_tests_instances/single_layer_tests/loop.cpp index ad294a4ce1f..1a14f9a97e4 100644 --- a/inference-engine/tests/functional/plugin/cpu/shared_tests_instances/single_layer_tests/loop.cpp +++ b/inference-engine/tests/functional/plugin/cpu/shared_tests_instances/single_layer_tests/loop.cpp @@ -9,7 +9,7 @@ using namespace LayerTestsDefinitions; namespace { - // without clip values increase rapidly, so use only seq_lenghts = 2 + // without clip values increase rapidly, so use only seq_lengths = 2 std::vector execute_first_iteration{true}; std::vector is_body_condition_const{true/*, false*/}; std::vector body_condition{true/*, false*/}; // works only if is_body_condition_const == true diff --git a/inference-engine/tests/functional/plugin/cpu/shared_tests_instances/single_layer_tests/lstm_sequence.cpp b/inference-engine/tests/functional/plugin/cpu/shared_tests_instances/single_layer_tests/lstm_sequence.cpp index 1fbe1190a76..3ccbddc8f31 100644 --- a/inference-engine/tests/functional/plugin/cpu/shared_tests_instances/single_layer_tests/lstm_sequence.cpp +++ b/inference-engine/tests/functional/plugin/cpu/shared_tests_instances/single_layer_tests/lstm_sequence.cpp @@ -16,7 +16,7 @@ namespace { ngraph::helpers::SequenceTestsMode::PURE_SEQ, ngraph::helpers::SequenceTestsMode::PURE_SEQ_RAND_SEQ_LEN_CONST, ngraph::helpers::SequenceTestsMode::PURE_SEQ_RAND_SEQ_LEN_PARAM}; - // output values increase rapidly without clip, so use only seq_lenghts = 2 + // output values increase rapidly without clip, so use only seq_lengths = 2 std::vector seq_lengths_zero_clip{2}; std::vector seq_lengths_clip_non_zero{20}; std::vector batch{10}; diff --git a/inference-engine/tests/functional/plugin/cpu/shared_tests_instances/single_layer_tests/rnn_sequence.cpp b/inference-engine/tests/functional/plugin/cpu/shared_tests_instances/single_layer_tests/rnn_sequence.cpp index 0805ff960d6..3db31d471c5 100644 --- a/inference-engine/tests/functional/plugin/cpu/shared_tests_instances/single_layer_tests/rnn_sequence.cpp +++ b/inference-engine/tests/functional/plugin/cpu/shared_tests_instances/single_layer_tests/rnn_sequence.cpp @@ -16,7 +16,7 @@ namespace { ngraph::helpers::SequenceTestsMode::PURE_SEQ_RAND_SEQ_LEN_PARAM, ngraph::helpers::SequenceTestsMode::PURE_SEQ_RAND_SEQ_LEN_CONST, ngraph::helpers::SequenceTestsMode::PURE_SEQ}; - // output values increase rapidly without clip, so use only seq_lenghts = 2 + // output values increase rapidly without clip, so use only seq_lengths = 2 std::vector seq_lengths_zero_clip{2}; std::vector seq_lengths_clip_non_zero{20}; std::vector batch{1, 10}; diff --git a/inference-engine/tests/functional/plugin/cpu/shared_tests_instances/single_layer_tests/tensor_iterator.cpp b/inference-engine/tests/functional/plugin/cpu/shared_tests_instances/single_layer_tests/tensor_iterator.cpp index 2531a6668c4..2a551b695f9 100644 --- a/inference-engine/tests/functional/plugin/cpu/shared_tests_instances/single_layer_tests/tensor_iterator.cpp +++ b/inference-engine/tests/functional/plugin/cpu/shared_tests_instances/single_layer_tests/tensor_iterator.cpp @@ -11,7 +11,7 @@ using namespace LayerTestsDefinitions; namespace { std::vector should_decompose = {true, false}; - // output values increase rapidly without clip, so use only seq_lenghts = 2 + // output values increase rapidly without clip, so use only seq_lengths = 2 std::vector seq_lengths_zero_clip{2}; std::vector seq_lengths_clip_non_zero{20}; std::vector batch{1, 10}; diff --git a/inference-engine/tests/functional/plugin/cpu/single_layer_tests/gru_sequence.cpp b/inference-engine/tests/functional/plugin/cpu/single_layer_tests/gru_sequence.cpp index b3f7b213136..55ece3f0a66 100644 --- a/inference-engine/tests/functional/plugin/cpu/single_layer_tests/gru_sequence.cpp +++ b/inference-engine/tests/functional/plugin/cpu/single_layer_tests/gru_sequence.cpp @@ -46,7 +46,7 @@ protected: CPUSpecificParams cpuParams; std::map additionalConfig; - size_t seq_lenghts; + size_t seq_lengths; size_t batch; size_t hidden_size; size_t input_size = 10; @@ -60,11 +60,11 @@ protected: std::tie(basicParamsSet, cpuParams, additionalConfig) = this->GetParam(); std::tie(inFmts, outFmts, priority, selectedType) = cpuParams; - std::tie(m_mode, seq_lenghts, batch, hidden_size, activations, clip, linear_before_reset, direction, netPrecision, targetDevice) = basicParamsSet; + std::tie(m_mode, seq_lengths, batch, hidden_size, activations, clip, linear_before_reset, direction, netPrecision, targetDevice) = basicParamsSet; size_t num_directions = direction == ngraph::op::RecurrentSequenceDirection::BIDIRECTIONAL ? 2 : 1; std::vector> inputShapes = { - {{batch, seq_lenghts, input_size}, + {{batch, seq_lengths, input_size}, {batch, num_directions, hidden_size}, {batch}, {num_directions, 3 * hidden_size, input_size}, @@ -89,7 +89,7 @@ protected: selectedType += "_"; selectedType += outPrc.name(); - m_max_seq_len = seq_lenghts; + m_max_seq_len = seq_lengths; auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(Precision::FP32); auto params = ngraph::builder::makeParams(ngPrc, {inputShapes[0], inputShapes[1]}); if (m_mode == ngraph::helpers::SequenceTestsMode::CONVERT_TO_TI_MAX_SEQ_LEN_PARAM @@ -174,7 +174,7 @@ CPUSpecificParams cpuParams{{ntc, ntc}, {tnc, ntc}, {"ref_any"}, "ref_any"}; CPUSpecificParams cpuParamsBatchSizeOne{{ntc, ntc}, {tnc, ntc}, {"ref_any"}, "ref_any"};; std::vector mode{ngraph::helpers::SequenceTestsMode::PURE_SEQ}; -// output values increase rapidly without clip, so use only seq_lenghts = 2 +// output values increase rapidly without clip, so use only seq_lengths = 2 std::vector seq_lengths_zero_clip{2}; std::vector batch{10}; std::vector batch_size_one{1}; diff --git a/inference-engine/tests/functional/plugin/cpu/single_layer_tests/lstm_sequence.cpp b/inference-engine/tests/functional/plugin/cpu/single_layer_tests/lstm_sequence.cpp index 538ca675a7f..234a579085c 100644 --- a/inference-engine/tests/functional/plugin/cpu/single_layer_tests/lstm_sequence.cpp +++ b/inference-engine/tests/functional/plugin/cpu/single_layer_tests/lstm_sequence.cpp @@ -47,7 +47,7 @@ protected: CPUSpecificParams cpuParams; std::map additionalConfig; - size_t seq_lenghts; + size_t seq_lengths; size_t batch; size_t hidden_size; size_t input_size; @@ -60,12 +60,12 @@ protected: std::tie(basicParamsSet, cpuParams, additionalConfig) = this->GetParam(); std::tie(inFmts, outFmts, priority, selectedType) = cpuParams; - std::tie(m_mode, seq_lenghts, batch, hidden_size, input_size, activations, clip, direction, netPrecision, targetDevice) = basicParamsSet; + std::tie(m_mode, seq_lengths, batch, hidden_size, input_size, activations, clip, direction, netPrecision, targetDevice) = basicParamsSet; size_t num_directions = direction == ngraph::op::RecurrentSequenceDirection::BIDIRECTIONAL ? 2 : 1; - m_max_seq_len = seq_lenghts; + m_max_seq_len = seq_lengths; std::vector> inputShapes = { - {{batch, seq_lenghts, input_size}, + {{batch, seq_lengths, input_size}, {batch, num_directions, hidden_size}, {batch, num_directions, hidden_size}, {batch}, diff --git a/inference-engine/tests/functional/plugin/cpu/single_layer_tests/rnn_sequence.cpp b/inference-engine/tests/functional/plugin/cpu/single_layer_tests/rnn_sequence.cpp index 009dcdd01f2..6c7f873cc95 100644 --- a/inference-engine/tests/functional/plugin/cpu/single_layer_tests/rnn_sequence.cpp +++ b/inference-engine/tests/functional/plugin/cpu/single_layer_tests/rnn_sequence.cpp @@ -46,7 +46,7 @@ protected: CPUSpecificParams cpuParams; std::map additionalConfig; - size_t seq_lenghts; + size_t seq_lengths; size_t batch; size_t hidden_size; size_t input_size; @@ -59,11 +59,11 @@ protected: std::tie(basicParamsSet, cpuParams, additionalConfig) = this->GetParam(); std::tie(inFmts, outFmts, priority, selectedType) = cpuParams; - std::tie(m_mode, seq_lenghts, batch, hidden_size, input_size, activations, clip, direction, netPrecision, targetDevice) = basicParamsSet; + std::tie(m_mode, seq_lengths, batch, hidden_size, input_size, activations, clip, direction, netPrecision, targetDevice) = basicParamsSet; size_t num_directions = direction == ngraph::op::RecurrentSequenceDirection::BIDIRECTIONAL ? 2 : 1; std::vector> inputShapes = { - {{batch, seq_lenghts, input_size}, + {{batch, seq_lengths, input_size}, {batch, num_directions, hidden_size}, {batch}, {num_directions, hidden_size, input_size}, @@ -82,7 +82,7 @@ protected: selectedType += "_"; selectedType += outPrc.name(); - m_max_seq_len = seq_lenghts; + m_max_seq_len = seq_lengths; auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(Precision::FP32); auto params = ngraph::builder::makeParams(ngPrc, {inputShapes[0], inputShapes[1]}); if (m_mode == ngraph::helpers::SequenceTestsMode::CONVERT_TO_TI_MAX_SEQ_LEN_PARAM @@ -152,7 +152,7 @@ CPUSpecificParams cpuParams{{ntc, ntc}, {tnc, ntc}, {"ref_any"}, "ref_any"}; CPUSpecificParams cpuParamsBatchSizeOne{{ntc, ntc}, {tnc, ntc}, {"ref_any"}, "ref_any"}; std::vector mode{ngraph::helpers::SequenceTestsMode::PURE_SEQ}; -// output values increase rapidly without clip, so use only seq_lenghts = 2 +// output values increase rapidly without clip, so use only seq_lengths = 2 std::vector seq_lengths_zero_clip{2}; std::vector batch{10}; std::vector batch_size_one{1}; diff --git a/inference-engine/tests/functional/plugin/gpu/shared_tests_instances/single_layer_tests/gru_sequence.cpp b/inference-engine/tests/functional/plugin/gpu/shared_tests_instances/single_layer_tests/gru_sequence.cpp index 9474335c2fe..d0033f4f473 100644 --- a/inference-engine/tests/functional/plugin/gpu/shared_tests_instances/single_layer_tests/gru_sequence.cpp +++ b/inference-engine/tests/functional/plugin/gpu/shared_tests_instances/single_layer_tests/gru_sequence.cpp @@ -16,7 +16,7 @@ namespace { ngraph::helpers::SequenceTestsMode::PURE_SEQ_RAND_SEQ_LEN_CONST, ngraph::helpers::SequenceTestsMode::PURE_SEQ_RAND_SEQ_LEN_PARAM, ngraph::helpers::SequenceTestsMode::PURE_SEQ}; - // output values increase rapidly without clip, so use only seq_lenghts = 2 + // output values increase rapidly without clip, so use only seq_lengths = 2 std::vector seq_lengths_zero_clip{2}; std::vector seq_lengths_clip_non_zero{20}; std::vector batch{10}; diff --git a/inference-engine/tests/functional/plugin/gpu/shared_tests_instances/single_layer_tests/lstm_sequence.cpp b/inference-engine/tests/functional/plugin/gpu/shared_tests_instances/single_layer_tests/lstm_sequence.cpp index 01c28409301..d79cee69eea 100644 --- a/inference-engine/tests/functional/plugin/gpu/shared_tests_instances/single_layer_tests/lstm_sequence.cpp +++ b/inference-engine/tests/functional/plugin/gpu/shared_tests_instances/single_layer_tests/lstm_sequence.cpp @@ -16,7 +16,7 @@ std::vector mode{ngraph::helpers::SequenceTe ngraph::helpers::SequenceTestsMode::PURE_SEQ_RAND_SEQ_LEN_CONST, ngraph::helpers::SequenceTestsMode::PURE_SEQ_RAND_SEQ_LEN_PARAM, ngraph::helpers::SequenceTestsMode::PURE_SEQ}; -// output values increase rapidly without clip, so use only seq_lenghts = 2 +// output values increase rapidly without clip, so use only seq_lengths = 2 std::vector seq_lengths_zero_clip{2}; std::vector seq_lengths_clip_non_zero{20}; std::vector batch{10}; diff --git a/inference-engine/tests/functional/plugin/gpu/shared_tests_instances/single_layer_tests/rnn_sequence.cpp b/inference-engine/tests/functional/plugin/gpu/shared_tests_instances/single_layer_tests/rnn_sequence.cpp index 10f888cec1e..718c1b6e771 100644 --- a/inference-engine/tests/functional/plugin/gpu/shared_tests_instances/single_layer_tests/rnn_sequence.cpp +++ b/inference-engine/tests/functional/plugin/gpu/shared_tests_instances/single_layer_tests/rnn_sequence.cpp @@ -16,7 +16,7 @@ std::vector mode{ngraph::helpers::SequenceTe ngraph::helpers::SequenceTestsMode::PURE_SEQ_RAND_SEQ_LEN_CONST, ngraph::helpers::SequenceTestsMode::PURE_SEQ_RAND_SEQ_LEN_PARAM, ngraph::helpers::SequenceTestsMode::PURE_SEQ}; -// output values increase rapidly without clip, so use only seq_lenghts = 2 +// output values increase rapidly without clip, so use only seq_lengths = 2 std::vector seq_lengths_zero_clip{2}; std::vector seq_lengths_clip_non_zero{20}; std::vector batch{1, 10}; diff --git a/inference-engine/tests/functional/shared_test_classes/include/shared_test_classes/single_layer/ctc_loss.hpp b/inference-engine/tests/functional/shared_test_classes/include/shared_test_classes/single_layer/ctc_loss.hpp index bcf89fef2b7..7b8a67d95c4 100644 --- a/inference-engine/tests/functional/shared_test_classes/include/shared_test_classes/single_layer/ctc_loss.hpp +++ b/inference-engine/tests/functional/shared_test_classes/include/shared_test_classes/single_layer/ctc_loss.hpp @@ -14,7 +14,7 @@ namespace LayerTestsDefinitions { typedef std::tuple< std::vector, // Logits shapes - std::vector, // logits lenght + std::vector, // logits length std::vector>, // labels std::vector, // labels length int, // blank index diff --git a/inference-engine/tests/functional/shared_test_classes/src/single_layer/gru_sequence.cpp b/inference-engine/tests/functional/shared_test_classes/src/single_layer/gru_sequence.cpp index c89a1bc06e2..f43cca3ca6d 100644 --- a/inference-engine/tests/functional/shared_test_classes/src/single_layer/gru_sequence.cpp +++ b/inference-engine/tests/functional/shared_test_classes/src/single_layer/gru_sequence.cpp @@ -10,7 +10,7 @@ namespace LayerTestsDefinitions { std::string GRUSequenceTest::getTestCaseName(const testing::TestParamInfo &obj) { ngraph::helpers::SequenceTestsMode mode; - size_t seq_lenghts; + size_t seq_lengths; size_t batch; size_t hidden_size; size_t input_size = 10; @@ -22,7 +22,7 @@ namespace LayerTestsDefinitions { ngraph::op::RecurrentSequenceDirection direction; InferenceEngine::Precision netPrecision; std::string targetDevice; - std::tie(mode, seq_lenghts, batch, hidden_size, activations, clip, linear_before_reset, direction, netPrecision, + std::tie(mode, seq_lengths, batch, hidden_size, activations, clip, linear_before_reset, direction, netPrecision, targetDevice) = obj.param; std::vector> inputShapes = { {{batch, input_size}, {batch, hidden_size}, {batch, hidden_size}, {3 * hidden_size, input_size}, @@ -30,7 +30,7 @@ namespace LayerTestsDefinitions { }; std::ostringstream result; result << "mode=" << mode << "_"; - result << "seq_lenghts=" << seq_lenghts << "_"; + result << "seq_lengths=" << seq_lengths << "_"; result << "batch=" << batch << "_"; result << "hidden_size=" << hidden_size << "_"; result << "input_size=" << input_size << "_"; @@ -45,7 +45,7 @@ namespace LayerTestsDefinitions { void GRUSequenceTest::SetUp() { using namespace ngraph::helpers; - size_t seq_lenghts; + size_t seq_lengths; size_t batch; size_t hidden_size; size_t input_size = 10; @@ -56,15 +56,15 @@ namespace LayerTestsDefinitions { bool linear_before_reset; ngraph::op::RecurrentSequenceDirection direction; InferenceEngine::Precision netPrecision; - std::tie(m_mode, seq_lenghts, batch, hidden_size, activations, clip, linear_before_reset, direction, netPrecision, + std::tie(m_mode, seq_lengths, batch, hidden_size, activations, clip, linear_before_reset, direction, netPrecision, targetDevice) = this->GetParam(); size_t num_directions = direction == ngraph::op::RecurrentSequenceDirection::BIDIRECTIONAL ? 2 : 1; std::vector> inputShapes = { - {{batch, seq_lenghts, input_size}, {batch, num_directions, hidden_size}, {batch}, + {{batch, seq_lengths, input_size}, {batch, num_directions, hidden_size}, {batch}, {num_directions, 3 * hidden_size, input_size}, {num_directions, 3 * hidden_size, hidden_size}, {num_directions, (linear_before_reset ? 4 : 3) * hidden_size}}, }; - m_max_seq_len = seq_lenghts; + m_max_seq_len = seq_lengths; auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision); auto params = ngraph::builder::makeParams(ngPrc, {inputShapes[0], inputShapes[1]}); if (m_mode == SequenceTestsMode::CONVERT_TO_TI_MAX_SEQ_LEN_PARAM || diff --git a/inference-engine/tests/functional/shared_test_classes/src/single_layer/lstm_sequence.cpp b/inference-engine/tests/functional/shared_test_classes/src/single_layer/lstm_sequence.cpp index f26475d84eb..7bb4289ec73 100644 --- a/inference-engine/tests/functional/shared_test_classes/src/single_layer/lstm_sequence.cpp +++ b/inference-engine/tests/functional/shared_test_classes/src/single_layer/lstm_sequence.cpp @@ -11,7 +11,7 @@ namespace LayerTestsDefinitions { std::string LSTMSequenceTest::getTestCaseName(const testing::TestParamInfo &obj) { ngraph::helpers::SequenceTestsMode mode; - size_t seq_lenghts; + size_t seq_lengths; size_t batch; size_t hidden_size; size_t input_size; @@ -22,7 +22,7 @@ namespace LayerTestsDefinitions { ngraph::op::RecurrentSequenceDirection direction; InferenceEngine::Precision netPrecision; std::string targetDevice; - std::tie(mode, seq_lenghts, batch, hidden_size, input_size, activations, clip, direction, netPrecision, + std::tie(mode, seq_lengths, batch, hidden_size, input_size, activations, clip, direction, netPrecision, targetDevice) = obj.param; std::vector> inputShapes = { {{batch, input_size}, {batch, hidden_size}, {batch, hidden_size}, {4 * hidden_size, input_size}, @@ -30,7 +30,7 @@ namespace LayerTestsDefinitions { }; std::ostringstream result; result << "mode=" << mode << "_"; - result << "seq_lenghts=" << seq_lenghts << "_"; + result << "seq_lengths=" << seq_lengths << "_"; result << "batch=" << batch << "_"; result << "hidden_size=" << hidden_size << "_"; result << "input_size=" << input_size << "_"; @@ -46,7 +46,7 @@ namespace LayerTestsDefinitions { void LSTMSequenceTest::SetUp() { using namespace ngraph::helpers; using namespace ngraph::builder; - size_t seq_lenghts; + size_t seq_lengths; size_t batch; size_t hidden_size; @@ -57,12 +57,12 @@ namespace LayerTestsDefinitions { float clip; ngraph::op::RecurrentSequenceDirection direction; InferenceEngine::Precision netPrecision; - std::tie(m_mode, seq_lenghts, batch, hidden_size, input_size, activations, clip, direction, netPrecision, + std::tie(m_mode, seq_lengths, batch, hidden_size, input_size, activations, clip, direction, netPrecision, targetDevice) = this->GetParam(); size_t num_directions = direction == ngraph::op::RecurrentSequenceDirection::BIDIRECTIONAL ? 2 : 1; - m_max_seq_len = seq_lenghts; + m_max_seq_len = seq_lengths; std::vector> inputShapes = { - {{batch, seq_lenghts, input_size}, {batch, num_directions, hidden_size}, {batch, num_directions, hidden_size}, + {{batch, seq_lengths, input_size}, {batch, num_directions, hidden_size}, {batch, num_directions, hidden_size}, {batch}, {num_directions, 4 * hidden_size, input_size}, {num_directions, 4 * hidden_size, hidden_size}, {num_directions, 4 * hidden_size}}, }; auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision); diff --git a/inference-engine/tests/functional/shared_test_classes/src/single_layer/rnn_sequence.cpp b/inference-engine/tests/functional/shared_test_classes/src/single_layer/rnn_sequence.cpp index c8ffc311196..a87e79ed9dd 100644 --- a/inference-engine/tests/functional/shared_test_classes/src/single_layer/rnn_sequence.cpp +++ b/inference-engine/tests/functional/shared_test_classes/src/single_layer/rnn_sequence.cpp @@ -10,7 +10,7 @@ namespace LayerTestsDefinitions { std::string RNNSequenceTest::getTestCaseName(const testing::TestParamInfo &obj) { ngraph::helpers::SequenceTestsMode mode; - size_t seq_lenghts; + size_t seq_lengths; size_t batch; size_t hidden_size; size_t input_size; @@ -21,7 +21,7 @@ namespace LayerTestsDefinitions { ngraph::op::RecurrentSequenceDirection direction; InferenceEngine::Precision netPrecision; std::string targetDevice; - std::tie(mode, seq_lenghts, batch, hidden_size, input_size, activations, clip, direction, netPrecision, + std::tie(mode, seq_lengths, batch, hidden_size, input_size, activations, clip, direction, netPrecision, targetDevice) = obj.param; std::vector> inputShapes = { {{batch, input_size}, {batch, hidden_size}, {batch, hidden_size}, {hidden_size, input_size}, @@ -29,7 +29,7 @@ namespace LayerTestsDefinitions { }; std::ostringstream result; result << "mode=" << mode << "_"; - result << "seq_lenghts=" << seq_lenghts << "_"; + result << "seq_lengths=" << seq_lengths << "_"; result << "batch=" << batch << "_"; result << "hidden_size=" << hidden_size << "_"; result << "input_size=" << input_size << "_"; @@ -44,7 +44,7 @@ namespace LayerTestsDefinitions { void RNNSequenceTest::SetUp() { using namespace ngraph::helpers; - size_t seq_lenghts; + size_t seq_lengths; size_t batch; size_t hidden_size; size_t input_size; @@ -54,15 +54,15 @@ namespace LayerTestsDefinitions { float clip; ngraph::op::RecurrentSequenceDirection direction; InferenceEngine::Precision netPrecision; - std::tie(m_mode, seq_lenghts, batch, hidden_size, input_size, activations, clip, direction, netPrecision, + std::tie(m_mode, seq_lengths, batch, hidden_size, input_size, activations, clip, direction, netPrecision, targetDevice) = this->GetParam(); size_t num_directions = direction == ngraph::op::RecurrentSequenceDirection::BIDIRECTIONAL ? 2 : 1; std::vector> inputShapes = { - {{batch, seq_lenghts, input_size}, {batch, num_directions, hidden_size}, {batch}, + {{batch, seq_lengths, input_size}, {batch, num_directions, hidden_size}, {batch}, {num_directions, hidden_size, input_size}, {num_directions, hidden_size, hidden_size}, {num_directions, hidden_size}}, }; - m_max_seq_len = seq_lenghts; + m_max_seq_len = seq_lengths; auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision); auto params = ngraph::builder::makeParams(ngPrc, {inputShapes[0], inputShapes[1]}); if (m_mode == SequenceTestsMode::CONVERT_TO_TI_MAX_SEQ_LEN_PARAM || diff --git a/inference-engine/tests/functional/shared_test_classes/src/single_layer/tensor_iterator.cpp b/inference-engine/tests/functional/shared_test_classes/src/single_layer/tensor_iterator.cpp index 6686c917e9d..ebbcd2753a8 100644 --- a/inference-engine/tests/functional/shared_test_classes/src/single_layer/tensor_iterator.cpp +++ b/inference-engine/tests/functional/shared_test_classes/src/single_layer/tensor_iterator.cpp @@ -9,7 +9,7 @@ namespace LayerTestsDefinitions { std::string TensorIteratorTest::getTestCaseName(const testing::TestParamInfo &obj) { bool should_decompose; - size_t seq_lenghts; + size_t seq_lengths; size_t batch; size_t hidden_size; size_t input_size = 10; @@ -19,7 +19,7 @@ namespace LayerTestsDefinitions { ngraph::op::RecurrentSequenceDirection direction; InferenceEngine::Precision netPrecision; std::string targetDevice; - std::tie(should_decompose, seq_lenghts, batch, hidden_size, sequence_axis, clip, ti_body, direction, netPrecision, + std::tie(should_decompose, seq_lengths, batch, hidden_size, sequence_axis, clip, ti_body, direction, netPrecision, targetDevice) = obj.param; std::vector> inputShapes = {}; @@ -44,7 +44,7 @@ namespace LayerTestsDefinitions { std::ostringstream result; result << "unrolling=" << should_decompose << "_"; - result << "seq_len=" << seq_lenghts << "_"; + result << "seq_len=" << seq_lengths << "_"; result << "seq_len_axis=" << sequence_axis << "_"; result << "batch=" << batch << "_"; result << "hidden_size=" << hidden_size << "_"; @@ -59,7 +59,7 @@ namespace LayerTestsDefinitions { } void TensorIteratorTest::SetUp() { - size_t seq_lenghts; + size_t seq_lengths; bool should_decompose; size_t batch; size_t hidden_size; @@ -69,7 +69,7 @@ namespace LayerTestsDefinitions { float clip; ngraph::op::RecurrentSequenceDirection direction; InferenceEngine::Precision netPrecision; - std::tie(should_decompose, seq_lenghts, batch, hidden_size, sequence_axis, clip, ti_body, direction, netPrecision, + std::tie(should_decompose, seq_lengths, batch, hidden_size, sequence_axis, clip, ti_body, direction, netPrecision, targetDevice) = this->GetParam(); std::vector> inputShapes; auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision); @@ -84,7 +84,7 @@ namespace LayerTestsDefinitions { switch (ti_body) { case ngraph::helpers::TensorIteratorBody::LSTM: { inputShapes = { - {{batch, seq_lenghts, input_size}, {batch, hidden_size}, {batch, hidden_size}, {4 * hidden_size, input_size}, + {{batch, seq_lengths, input_size}, {batch, hidden_size}, {batch, hidden_size}, {4 * hidden_size, input_size}, {4 * hidden_size, hidden_size}, {4 * hidden_size}}, }; if (sequence_axis == 0) { @@ -130,7 +130,7 @@ namespace LayerTestsDefinitions { } case ngraph::helpers::TensorIteratorBody::GRU: { inputShapes = { - {{batch, seq_lenghts, input_size}, {batch, hidden_size}, {3 * hidden_size, input_size}, + {{batch, seq_lengths, input_size}, {batch, hidden_size}, {3 * hidden_size, input_size}, {3 * hidden_size, hidden_size}, {3 * hidden_size}}, }; if (sequence_axis == 0) { @@ -172,7 +172,7 @@ namespace LayerTestsDefinitions { break; } case ngraph::helpers::TensorIteratorBody::RNN: { - inputShapes = {{batch, seq_lenghts, input_size}, + inputShapes = {{batch, seq_lengths, input_size}, {batch, hidden_size}, {hidden_size, input_size}, {hidden_size, hidden_size}, diff --git a/inference-engine/thirdparty/clDNN/src/graph_optimizer/prepare_buffer_fusing.cpp b/inference-engine/thirdparty/clDNN/src/graph_optimizer/prepare_buffer_fusing.cpp index d3618d1034b..befc677b6f7 100644 --- a/inference-engine/thirdparty/clDNN/src/graph_optimizer/prepare_buffer_fusing.cpp +++ b/inference-engine/thirdparty/clDNN/src/graph_optimizer/prepare_buffer_fusing.cpp @@ -209,7 +209,7 @@ void concat_in_place_optimization::optimize_cascade(concatenation_node& node, st // apply concatenation in place optimization for (auto input : node.get_dependencies()) { - auto input_lenght = input->get_output_layout().size.raw[concat_axis]; + auto input_length = input->get_output_layout().size.raw[concat_axis]; if (input->is_type() && input->can_be_optimized()) need_reoptimization.push_back(&input->as()); @@ -218,7 +218,7 @@ void concat_in_place_optimization::optimize_cascade(concatenation_node& node, st // // |--- lower padd ---| |---------- upper padd -----------| // |-- output padd ---| ----- input1 ------|----- input2 -----|-- out padd --| - upper_padd.raw[concat_axis] -= input_lenght; + upper_padd.raw[concat_axis] -= input_length; // set new padding for input input->set_output_padding(padding(lower_padd.sizes(), upper_padd.sizes())); @@ -227,7 +227,7 @@ void concat_in_place_optimization::optimize_cascade(concatenation_node& node, st // // |-------------- lower padd -------------|---------- upper padd -----------| // |-- output padd ---| ----- input1 ------|----- input2 -----|-- out padd --| - lower_padd.raw[concat_axis] += input_lenght; + lower_padd.raw[concat_axis] += input_length; } node.can_be_optimized(true); diff --git a/inference-engine/thirdparty/mkl-dnn b/inference-engine/thirdparty/mkl-dnn index d8514fcf88e..a5fffb52b01 160000 --- a/inference-engine/thirdparty/mkl-dnn +++ b/inference-engine/thirdparty/mkl-dnn @@ -1 +1 @@ -Subproject commit d8514fcf88e9770f671074ffe0ea853d734ebbcd +Subproject commit a5fffb52b012b31c65ace894638ecfb8948de9ec diff --git a/inference-engine/thirdparty/movidius/mvnc/tests/mvnc_no_boot_tests.cpp b/inference-engine/thirdparty/movidius/mvnc/tests/mvnc_no_boot_tests.cpp index 4293da658a8..fe8c522ac3c 100644 --- a/inference-engine/thirdparty/movidius/mvnc/tests/mvnc_no_boot_tests.cpp +++ b/inference-engine/thirdparty/movidius/mvnc/tests/mvnc_no_boot_tests.cpp @@ -31,20 +31,20 @@ TEST_F(MvncNoBootOpenDevice, OpenTwiceSameHandler) { deviceDesc.platform = NC_ANY_PLATFORM; char dev_addr_first_open[MAX_DEV_NAME]; - unsigned int data_lenght_first = MAX_DEV_NAME; + unsigned int data_length_first = MAX_DEV_NAME; char dev_addr_second_open[MAX_DEV_NAME]; - unsigned int data_lenght_second = MAX_DEV_NAME; + unsigned int data_length_second = MAX_DEV_NAME; // First open, get device name ASSERT_NO_ERROR(ncDeviceOpen(&deviceHandle, deviceDesc, watchdogInterval, firmwarePath)); ASSERT_NO_ERROR(ncDeviceGetOption(deviceHandle, NC_RO_DEVICE_NAME, - dev_addr_first_open, &data_lenght_first)); + dev_addr_first_open, &data_length_first)); // Second open, get device name ASSERT_NO_ERROR(ncDeviceOpen(&deviceHandle, deviceDesc, watchdogInterval, firmwarePath)); ASSERT_NO_ERROR(ncDeviceGetOption(deviceHandle, NC_RO_DEVICE_NAME, - dev_addr_second_open, &data_lenght_second)); + dev_addr_second_open, &data_length_second)); ASSERT_NO_ERROR(ncDeviceClose(&deviceHandle)); // Should be the same device diff --git a/inference-engine/thirdparty/movidius/mvnc/tests/mvnc_tests_common.cpp b/inference-engine/thirdparty/movidius/mvnc/tests/mvnc_tests_common.cpp index 02eda4c3dca..0f7b69d1b49 100644 --- a/inference-engine/thirdparty/movidius/mvnc/tests/mvnc_tests_common.cpp +++ b/inference-engine/thirdparty/movidius/mvnc/tests/mvnc_tests_common.cpp @@ -220,20 +220,20 @@ TEST_P(MvncOpenDevice, OpenTwiceSameHandler) { deviceDesc.platform = NC_ANY_PLATFORM; char dev_addr_first_open[MAX_DEV_NAME]; - unsigned int data_lenght_first = MAX_DEV_NAME; + unsigned int data_length_first = MAX_DEV_NAME; char dev_addr_second_open[MAX_DEV_NAME]; - unsigned int data_lenght_second = MAX_DEV_NAME; + unsigned int data_length_second = MAX_DEV_NAME; // First open, get device name ASSERT_NO_ERROR(ncDeviceOpen(&deviceHandle, deviceDesc, m_ncDeviceOpenParams)); ASSERT_NO_ERROR(ncDeviceGetOption(deviceHandle, NC_RO_DEVICE_NAME, - dev_addr_first_open, &data_lenght_first)); + dev_addr_first_open, &data_length_first)); // Second open, get device name ASSERT_NO_ERROR(ncDeviceOpen(&deviceHandle, deviceDesc, m_ncDeviceOpenParams)); ASSERT_NO_ERROR(ncDeviceGetOption(deviceHandle, NC_RO_DEVICE_NAME, - dev_addr_second_open, &data_lenght_second)); + dev_addr_second_open, &data_length_second)); ASSERT_NO_ERROR(ncDeviceClose(&deviceHandle, m_watchdogHndl)); // Should be the same device diff --git a/inference-engine/thirdparty/movidius/mvnc/tests/mvnc_tests_usb.cpp b/inference-engine/thirdparty/movidius/mvnc/tests/mvnc_tests_usb.cpp index 65a2a09fb23..87544a6e0c6 100644 --- a/inference-engine/thirdparty/movidius/mvnc/tests/mvnc_tests_usb.cpp +++ b/inference-engine/thirdparty/movidius/mvnc/tests/mvnc_tests_usb.cpp @@ -113,7 +113,7 @@ TEST_F(MvncOpenUSBDevice, OpenAvailableDeviceByName) { GTEST_SKIP(); char dev_addr_open[NC_MAX_NAME_SIZE]; - unsigned int data_lenght = NC_MAX_NAME_SIZE; + unsigned int data_length = NC_MAX_NAME_SIZE; auto availableDevices = getDevicesList(); @@ -122,7 +122,7 @@ TEST_F(MvncOpenUSBDevice, OpenAvailableDeviceByName) { ASSERT_NO_ERROR(ncDeviceOpen(&deviceHandle_, deviceDesc_, m_ncDeviceOpenParams)); ASSERT_NO_ERROR(ncDeviceGetOption(deviceHandle_, NC_RO_DEVICE_NAME, - dev_addr_open, &data_lenght)); + dev_addr_open, &data_length)); ASSERT_TRUE(strncmp(dev_addr_open, deviceDesc_.name, NC_MAX_NAME_SIZE) == 0); ASSERT_NO_ERROR(ncDeviceClose(&deviceHandle_, m_watchdogHndl)); @@ -147,10 +147,10 @@ TEST_F(MvncOpenUSBDevice, OpenTwiceSameHandlerByName) { GTEST_SKIP(); char dev_addr_first_open[MAX_DEV_NAME]; - unsigned int data_lenght_first = MAX_DEV_NAME; + unsigned int data_length_first = MAX_DEV_NAME; char dev_addr_second_open[MAX_DEV_NAME]; - unsigned int data_lenght_second = MAX_DEV_NAME; + unsigned int data_length_second = MAX_DEV_NAME; auto availableDevices = getDevicesList(); @@ -159,12 +159,12 @@ TEST_F(MvncOpenUSBDevice, OpenTwiceSameHandlerByName) { ASSERT_NO_ERROR(ncDeviceOpen(&deviceHandle_, deviceDesc_, m_ncDeviceOpenParams)); ASSERT_NO_ERROR(ncDeviceGetOption(deviceHandle_, NC_RO_DEVICE_NAME, - dev_addr_first_open, &data_lenght_first)); + dev_addr_first_open, &data_length_first)); // Second open, get device name ASSERT_NO_ERROR(ncDeviceOpen(&deviceHandle_, deviceDesc_, m_ncDeviceOpenParams)); ASSERT_NO_ERROR(ncDeviceGetOption(deviceHandle_, NC_RO_DEVICE_NAME, - dev_addr_second_open, &data_lenght_second)); + dev_addr_second_open, &data_length_second)); ASSERT_NO_ERROR(ncDeviceClose(&deviceHandle_, m_watchdogHndl)); // Should be the same device diff --git a/inference-engine/thirdparty/pugixml/src/pugixml.cpp b/inference-engine/thirdparty/pugixml/src/pugixml.cpp index 69eba5e1277..e6c409bc0f5 100644 --- a/inference-engine/thirdparty/pugixml/src/pugixml.cpp +++ b/inference-engine/thirdparty/pugixml/src/pugixml.cpp @@ -3953,9 +3953,9 @@ PUGI__NS_BEGIN // skip ]] if we stopped at ]]>, > will go to the next CDATA section if (*s) s += 2; - size_t bufLenght = static_cast(s - prev); + size_t bufLength = static_cast(s - prev); - writer.write_buffer(prev, bufLenght); + writer.write_buffer(prev, bufLength); writer.write(']', ']', '>'); } @@ -4013,9 +4013,9 @@ PUGI__NS_BEGIN // look for -\0 or -- sequence - we can't output it since -- is illegal in comment body while (*s && !(s[0] == '-' && (s[1] == '-' || s[1] == 0))) ++s; - size_t bufLenght = static_cast(s - prev); + size_t bufLength = static_cast(s - prev); - writer.write_buffer(prev, bufLenght); + writer.write_buffer(prev, bufLength); if (*s) { diff --git a/ngraph/core/include/ngraph/op/ctc_loss.hpp b/ngraph/core/include/ngraph/op/ctc_loss.hpp index 23f8e4ff570..b5e364877af 100644 --- a/ngraph/core/include/ngraph/op/ctc_loss.hpp +++ b/ngraph/core/include/ngraph/op/ctc_loss.hpp @@ -21,7 +21,7 @@ namespace ngraph /// \brief Constructs a CTCLoss operation /// /// \param logits 3-D tensor of logits - /// \param logit_length 1-D tensor of lenght for each object from + /// \param logit_length 1-D tensor of length for each object from /// a batch /// \param labels 2-D tensor of labels for which likelyhood /// is estimated using logist diff --git a/ngraph/core/include/ngraph/op/lstm_sequence.hpp b/ngraph/core/include/ngraph/op/lstm_sequence.hpp index b5c0ec5dfef..eb0692efcd0 100644 --- a/ngraph/core/include/ngraph/op/lstm_sequence.hpp +++ b/ngraph/core/include/ngraph/op/lstm_sequence.hpp @@ -98,13 +98,13 @@ namespace ngraph private: /// - /// \brief Gets the masked value according to sequence lenght in a batch. + /// \brief Gets the masked value according to sequence length in a batch. /// /// \note Zeros out values or sets them to default value for inputs with - /// sequence lenght shorter than currently procssed time step. + /// sequence length shorter than currently procssed time step. /// /// \param[in] data The input value. - /// \param[in] time_step The current time step denoting sequence lenght. + /// \param[in] time_step The current time step denoting sequence length. /// \param[in] batch_axis The batch axis index of data tensor. /// \param[in] default_value The default value for masked elements. /// diff --git a/ngraph/frontend/onnx_import/src/op/slice.cpp b/ngraph/frontend/onnx_import/src/op/slice.cpp index 2b9f5f0b520..26010a5bda0 100644 --- a/ngraph/frontend/onnx_import/src/op/slice.cpp +++ b/ngraph/frontend/onnx_import/src/op/slice.cpp @@ -54,7 +54,7 @@ namespace ngraph /// value) or ignored (1 value) /// /// \param[in] axes Axes input of ONNX Slice operator - /// \param[in] slice_indices_length Lenght of Slice indices + /// \param[in] slice_indices_length Length of Slice indices /// (starts, ends, steps) /// /// \return Mask attribute in format required by StridedSlice:v1 diff --git a/ngraph/frontend/onnx_import/src/utils/tensor_external_data.cpp b/ngraph/frontend/onnx_import/src/utils/tensor_external_data.cpp index 77b6db14beb..fe593b47619 100644 --- a/ngraph/frontend/onnx_import/src/utils/tensor_external_data.cpp +++ b/ngraph/frontend/onnx_import/src/utils/tensor_external_data.cpp @@ -25,7 +25,7 @@ namespace ngraph if (entry.key() == "offset") m_offset = std::stoi(entry.value()); if (entry.key() == "length") - m_data_lenght = std::stoi(entry.value()); + m_data_length = std::stoi(entry.value()); if (entry.key() == "checksum") m_sha1_digest = std::stoi(entry.value()); } @@ -43,11 +43,11 @@ namespace ngraph if (external_data_stream.fail()) throw error::invalid_external_data{*this}; - std::streamsize read_data_lenght; - if (m_data_lenght == 0) // read entire file - read_data_lenght = external_data_stream.tellg(); + std::streamsize read_data_length; + if (m_data_length == 0) // read entire file + read_data_length = external_data_stream.tellg(); else - read_data_lenght = m_data_lenght; + read_data_length = m_data_length; const auto page_size = 4096; if (m_offset != 0 && m_offset % page_size != 0) @@ -65,8 +65,8 @@ namespace ngraph } std::string read_data; - read_data.resize(read_data_lenght); - external_data_stream.read(&read_data[0], read_data_lenght); + read_data.resize(read_data_length); + external_data_stream.read(&read_data[0], read_data_length); external_data_stream.close(); return read_data; @@ -78,7 +78,7 @@ namespace ngraph s << "ExternalDataInfo("; s << "data_full_path: " << m_data_location; s << ", offset: " << m_offset; - s << ", data_lenght: " << m_data_lenght; + s << ", data_length: " << m_data_length; s << ", sha1_digest: " << m_sha1_digest << ")"; return s.str(); } diff --git a/ngraph/frontend/onnx_import/src/utils/tensor_external_data.hpp b/ngraph/frontend/onnx_import/src/utils/tensor_external_data.hpp index 6db383428ea..8af53e407c1 100644 --- a/ngraph/frontend/onnx_import/src/utils/tensor_external_data.hpp +++ b/ngraph/frontend/onnx_import/src/utils/tensor_external_data.hpp @@ -35,7 +35,7 @@ namespace ngraph private: std::string m_data_location{}; int m_offset = 0; - int m_data_lenght = 0; + int m_data_length = 0; int m_sha1_digest = 0; }; } // namespace detail diff --git a/ngraph/python/tests/test_ngraph/test_data_movement.py b/ngraph/python/tests/test_ngraph/test_data_movement.py index aa1c41dbfd9..f9693147e97 100644 --- a/ngraph/python/tests/test_ngraph/test_data_movement.py +++ b/ngraph/python/tests/test_ngraph/test_data_movement.py @@ -63,17 +63,17 @@ def test_reverse_sequence(): ], dtype=np.int32, ).reshape([2, 3, 4, 2]) - seq_lenghts = np.array([1, 2, 1, 2], dtype=np.int32) + seq_lengths = np.array([1, 2, 1, 2], dtype=np.int32) batch_axis = 2 sequence_axis = 1 input_param = ng.parameter(input_data.shape, name="input", dtype=np.int32) - seq_lengths_param = ng.parameter(seq_lenghts.shape, name="sequence lengths", dtype=np.int32) + seq_lengths_param = ng.parameter(seq_lengths.shape, name="sequence lengths", dtype=np.int32) model = ng.reverse_sequence(input_param, seq_lengths_param, batch_axis, sequence_axis) runtime = get_runtime() computation = runtime.computation(model, input_param, seq_lengths_param) - result = computation(input_data, seq_lenghts) + result = computation(input_data, seq_lengths) expected = np.array( [ diff --git a/ngraph/test/backend/reverse_sequence.in.cpp b/ngraph/test/backend/reverse_sequence.in.cpp index 4dcc954e4c0..bab37dfa5a6 100644 --- a/ngraph/test/backend/reverse_sequence.in.cpp +++ b/ngraph/test/backend/reverse_sequence.in.cpp @@ -44,8 +44,8 @@ NGRAPH_TEST(${BACKEND_NAME}, reverse_sequence_n2c3h4w2) 12, 0, 15, 0, 18, 0, 21, 0, 13, 0, 16, 0, 19, 0, 22, 0, 14, 0, 17, 0, 20, 0, 23, 0, }; - std::vector seq_lenghts{1, 2, 1, 2}; - copy_data(b, seq_lenghts); + std::vector seq_lengths{1, 2, 1, 2}; + copy_data(b, seq_lengths); std::vector expected{ 0, 0, 4, 0, 6, 0, 10, 0, 1, 0, 3, 0, 7, 0, 9, 0, 2, 0, 5, 0, 8, 0, 11, 0, @@ -81,8 +81,8 @@ NGRAPH_TEST(${BACKEND_NAME}, reverse_sequence_n4c3h2w2) shared_ptr result = backend->create_tensor(element::i32, shape); - std::vector seq_lenghts{1, 2, 3, 3}; - copy_data(b, seq_lenghts); + std::vector seq_lengths{1, 2, 3, 3}; + copy_data(b, seq_lengths); std::vector input{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, @@ -137,8 +137,8 @@ NGRAPH_TEST(${BACKEND_NAME}, reverse_sequence_n4d2c3h2w2) copy_data(a, input); - std::vector seq_lenghts{1, 2, 1, 2}; - copy_data(b, seq_lenghts); + std::vector seq_lengths{1, 2, 1, 2}; + copy_data(b, seq_lengths); auto handle = backend->compile(f); handle->call_with_validate({result}, {a, b}); @@ -171,8 +171,8 @@ NGRAPH_TEST(${BACKEND_NAME}, reverse_sequence_negative_axes) 12, 0, 15, 0, 18, 0, 21, 0, 13, 0, 16, 0, 19, 0, 22, 0, 14, 0, 17, 0, 20, 0, 23, 0, }; - std::vector seq_lenghts{1, 2, 1, 2}; - copy_data(b, seq_lenghts); + std::vector seq_lengths{1, 2, 1, 2}; + copy_data(b, seq_lengths); std::vector expected{ 0, 0, 4, 0, 6, 0, 10, 0, 1, 0, 3, 0, 7, 0, 9, 0, 2, 0, 5, 0, 8, 0, 11, 0, diff --git a/ngraph/test/onnx/onnx_import_external_data.in.cpp b/ngraph/test/onnx/onnx_import_external_data.in.cpp index 6d318ca0436..10638eaa200 100644 --- a/ngraph/test/onnx/onnx_import_external_data.in.cpp +++ b/ngraph/test/onnx/onnx_import_external_data.in.cpp @@ -101,7 +101,7 @@ NGRAPH_TEST(${BACKEND_NAME}, onnx_external_invalid_external_data_exception) { EXPECT_PRED_FORMAT2( testing::IsSubstring, - std::string("not_existed_file.data, offset: 4096, data_lenght: 16, sha1_digest: 0)"), + std::string("not_existed_file.data, offset: 4096, data_length: 16, sha1_digest: 0)"), error.what()); } catch (...) @@ -123,7 +123,7 @@ NGRAPH_TEST(${BACKEND_NAME}, onnx_external_invalid_up_dir_path) { EXPECT_PRED_FORMAT2(testing::IsSubstring, std::string("tensor.data, offset: 4096, " - "data_lenght: 16, sha1_digest: 0)"), + "data_length: 16, sha1_digest: 0)"), error.what()); } catch (...) diff --git a/ngraph/test/type_prop/reverse_sequence.cpp b/ngraph/test/type_prop/reverse_sequence.cpp index 38be9f2aec4..fa1b57bea45 100644 --- a/ngraph/test/type_prop/reverse_sequence.cpp +++ b/ngraph/test/type_prop/reverse_sequence.cpp @@ -12,13 +12,13 @@ using namespace ngraph; TEST(type_prop, reverse_sequence_1_dim) { auto data = make_shared(element::f32, Shape{4, 3, 2}); - auto seq_lenghts = make_shared(element::f32, Shape{4, 4}); + auto seq_lengths = make_shared(element::f32, Shape{4, 4}); try { size_t batch_axis = 0; size_t seq_axis = 1; - auto bc = make_shared(data, seq_lenghts, batch_axis, seq_axis); - FAIL() << "ReverseSequence c-tor should throw for seq_lenghts whose rank isn't equal to 1"; + auto bc = make_shared(data, seq_lengths, batch_axis, seq_axis); + FAIL() << "ReverseSequence c-tor should throw for seq_lengths whose rank isn't equal to 1"; } catch (const NodeValidationFailure& error) { @@ -34,12 +34,12 @@ TEST(type_prop, reverse_sequence_1_dim) TEST(type_prop, reverse_sequence_batch_index_oob) { auto data = make_shared(element::f32, Shape{4, 3, 2}); - auto seq_lenghts = make_shared(element::f32, Shape{3}); + auto seq_lengths = make_shared(element::f32, Shape{3}); try { size_t batch_axis = 3; size_t seq_axis = 1; - auto bc = make_shared(data, seq_lenghts, batch_axis, seq_axis); + auto bc = make_shared(data, seq_lengths, batch_axis, seq_axis); FAIL() << "ReverseSequence c-tor should throw for out-of-bounds batch axis index"; } catch (const ngraph_error& error) @@ -76,12 +76,12 @@ TEST(type_prop, reverse_sequence_sequence_index_oob) TEST(type_prop, reverse_sequence_seq_len_size_equal_to_batch_dim) { auto data = make_shared(element::f32, Shape{4, 3, 2}); - auto seq_lenghts = make_shared(element::f32, Shape{3}); + auto seq_lengths = make_shared(element::f32, Shape{3}); try { size_t batch_axis = 0; size_t seq_axis = 1; - auto bc = make_shared(data, seq_lenghts, batch_axis, seq_axis); + auto bc = make_shared(data, seq_lengths, batch_axis, seq_axis); FAIL() << "ReverseSequence c-tor should throw when sequence length size isn't equal to " "batch dimension"; }