Apply codestyle (openvinotoolkit#107)

* Apply codestyle * Remove commented line
mvafin · Jan 16, 2023 · 1330219 · 1330219
1 parent 7c3c8fe
commit 1330219
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Showing 7 changed files with 8 additions and 6 deletions.
diff --git a/src/frontends/pytorch/src/frontend.cpp b/src/frontends/pytorch/src/frontend.cpp
@@ -137,7 +137,6 @@ ov::frontend::InputModel::Ptr FrontEnd::load_impl(const std::vector<ov::Any>& va
     auto decoder = variants[0].as<std::shared_ptr<IDecoder>>();
     auto tdecoder = std::dynamic_pointer_cast<TorchDecoder>(decoder);
     FRONT_END_GENERAL_CHECK(tdecoder, "Couldn't cast");
-    //auto tdecoder = variants[0].as<std::shared_ptr<TorchDecoder>>();
     return std::make_shared<pytorch::InputModel>(tdecoder);
 }
 

diff --git a/src/frontends/pytorch/src/op/nms.cpp b/src/frontends/pytorch/src/op/nms.cpp
@@ -1,4 +1,4 @@
-// Copyright (C) 2018-2022 Intel Corporation
+// Copyright (C) 2018-2023 Intel Corporation
 // SPDX-License-Identifier: Apache-2.0
 //
 

diff --git a/src/frontends/pytorch/src/utils.cpp b/src/frontends/pytorch/src/utils.cpp
@@ -280,7 +280,7 @@ OutputVector convert_node(NodeContext* context) {
 ///  conversion.
 /// \return fully converted OV Model
 std::shared_ptr<ov::Model> convert_pytorch_model2(std::shared_ptr<TorchDecoder> pytorch_model,
-                                                 const TensorMap& external_tensor_map) {
+                                                  const TensorMap& external_tensor_map) {
     std::shared_ptr<ov::Model> resulting_model;  // define here to make a conversion in a nested scope
     {
         ParameterVector parameters;

diff --git a/src/frontends/pytorch/src/utils.hpp b/src/frontends/pytorch/src/utils.hpp
@@ -55,7 +55,7 @@ ov::element::Type convert_dtype(NodeContext& context, size_t input_id);
 std::shared_ptr<Node> concat_list_construct(std::shared_ptr<Node> input);
 
 std::shared_ptr<ov::Model> convert_pytorch_model2(std::shared_ptr<TorchDecoder> pytorch_model,
-                                                 const TensorMap& external_tensor_map = {});
+                                                  const TensorMap& external_tensor_map = {});
 
 OutputVector convert_node(NodeContext* context);
 

diff --git a/tests/layer_tests/pytorch_tests/test_batch_norm.py b/tests/layer_tests/pytorch_tests/test_batch_norm.py
@@ -1,4 +1,4 @@
-# Copyright (C) 2018-2022 Intel Corporation
+# Copyright (C) 2018-2023 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
 import pytest
@@ -42,6 +42,7 @@ def forward(self, x):
         {"ndim": 5}
     ])
     @pytest.mark.nightly
+    @pytest.mark.precommit
     def test_batch_norm(self, weights, bias, eps, ie_device, precision, ir_version, kwargs_to_prepare_input):
         self._test(*self.create_model(weights, bias, eps),
                    ie_device, precision, ir_version, kwargs_to_prepare_input=kwargs_to_prepare_input, dynamic_shapes=False)
diff --git a/tests/layer_tests/pytorch_tests/test_nms.py b/tests/layer_tests/pytorch_tests/test_nms.py
@@ -1,4 +1,4 @@
-# Copyright (C) 2018-2022 Intel Corporation
+# Copyright (C) 2018-2023 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
 import pytest
@@ -33,6 +33,7 @@ def forward(self, boxes, scores):
         return torchvision_nms(), ref_net, "torchvision::nms"
 
     @pytest.mark.nightly
+    @pytest.mark.precommit
     def test_nms(self, ie_device, precision, ir_version, boxes_num):
         self.boxes_num = boxes_num
         self._test(*self.create_model(), ie_device, precision, ir_version)
diff --git a/tests/layer_tests/requirements.txt b/tests/layer_tests/requirements.txt
@@ -1,4 +1,5 @@
 requests>=2.25.1
 numpy>=1.19.2
 torch
+torchvision
 pytest