Eliminate reader tests (openvinotoolkit#13409)

* remove reader tests #1

* remove reader tests #2

* remove reader tests #3

* remove reader tests #4

* Add clone_with_new_inputs to visitor tests

* fixes

Author: olpipi

src/core/tests/CMakeLists.txt

@@ -270,6 +270,7 @@ set(SRC
     visitors/dimension.cpp
     visitors/user_op.cpp
     visitors/value_map.cpp
+    visitors/op/abs.cpp
     visitors/op/acos.cpp
     visitors/op/acosh.cpp
     visitors/op/adaptive_avg_pool.cpp
@@ -288,6 +289,7 @@ set(SRC
     visitors/op/bucketize.cpp
     visitors/op/ceiling.cpp
     visitors/op/clamp.cpp
+    visitors/op/concat.cpp
     visitors/op/constant.cpp
     visitors/op/convert.cpp
     visitors/op/convert_color_i420.cpp
@@ -380,6 +382,7 @@ set(SRC
     visitors/op/proposal.cpp
     visitors/op/psroi_pooling.cpp
     visitors/op/random_uniform.cpp
+    visitors/op/range.cpp
     visitors/op/rdft.cpp
     visitors/op/read_value.cpp
     visitors/op/reduce_l1.cpp
@@ -430,6 +433,7 @@ set(SRC
     visitors/op/tan.cpp
     visitors/op/tanh.cpp
     visitors/op/tensor_iterator.cpp
+    visitors/op/tile.cpp
     visitors/op/topk.cpp
     visitors/op/transpose.cpp
     visitors/op/unsqueeze.cpp

src/core/tests/visitors/op/abs.cpp

@@ -0,0 +1,9 @@
+// Copyright (C) 2018-2022 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "unary_ops.hpp"
+
+using Type = ::testing::Types<UnaryOperatorType<ngraph::op::Abs, ngraph::element::f32>>;
+
+INSTANTIATE_TYPED_TEST_SUITE_P(visitor_without_attribute, UnaryOperatorVisitor, Type, UnaryOperatorTypeName);

src/core/tests/visitors/op/adaptive_avg_pool.cpp

@@ -18,7 +18,7 @@ TEST(attributes, adaptive_avg_pool_op) {
     const auto out_shape = op::Constant::create<int64_t>(element::i64, Shape{2}, {4, 3});
 
     const auto adaptive_pool = make_shared<opset8::AdaptiveAvgPool>(A, out_shape);
-    NodeBuilder builder(adaptive_pool);
+    NodeBuilder builder(adaptive_pool, {A, out_shape});
 
     const auto expected_attr_count = 0;
     EXPECT_EQ(builder.get_value_map_size(), expected_attr_count);

src/core/tests/visitors/op/adaptive_max_pool.cpp

@@ -18,7 +18,7 @@ TEST(attributes, adaptive_max_pool_op) {
     const auto out_shape = op::Constant::create<int64_t>(element::i64, Shape{2}, {4, 3});
 
     const auto adaptive_pool = make_shared<opset8::AdaptiveMaxPool>(A, out_shape);
-    NodeBuilder builder(adaptive_pool);
+    NodeBuilder builder(adaptive_pool, {A, out_shape});
     auto g_adaptive_pool = ov::as_type_ptr<opset8::AdaptiveMaxPool>(builder.create());
 
     const auto expected_attr_count = 1;

src/core/tests/visitors/op/assign.cpp

@@ -20,7 +20,7 @@ TEST(attributes, assign_v3_op) {
     const string variable_id = "v0";
     const auto read_value = make_shared<opset3::ReadValue>(in, variable_id);
     const auto assign = make_shared<opset3::Assign>(read_value, variable_id);
-    NodeBuilder builder(assign);
+    NodeBuilder builder(assign, {read_value});
 
     // attribute count
     const auto expected_attr_count = 1;
@@ -33,7 +33,7 @@ TEST(attributes, assign_v6_op) {
     const auto variable = std::make_shared<Variable>(VariableInfo{PartialShape::dynamic(), element::dynamic, "v0"});
     const auto read_value = make_shared<opset6::ReadValue>(in, variable);
     const auto assign = make_shared<opset6::Assign>(read_value, variable);
-    NodeBuilder builder(assign);
+    NodeBuilder builder(assign, {read_value});
 
     // attribute count
     const auto expected_attr_count = 1;

src/core/tests/visitors/op/avg_pool.cpp

@@ -29,7 +29,7 @@ TEST(attributes, avg_pool_op) {
     auto avg_pool =
         make_shared<opset1::AvgPool>(data, strides, pads_begin, pads_end, kernel, exclude_pad, rounding_mode, auto_pad);
 
-    NodeBuilder builder(avg_pool);
+    NodeBuilder builder(avg_pool, {data});
     auto g_avg_pool = ov::as_type_ptr<opset1::AvgPool>(builder.create());
 
     EXPECT_EQ(g_avg_pool->get_strides(), avg_pool->get_strides());
@@ -54,7 +54,7 @@ TEST(attributes, avg_pool_v8_op) {
 
     const auto avg_pool =
         make_shared<opset8::AvgPool>(data, strides, pads_begin, pads_end, kernel, exclude_pad, rounding_mode, auto_pad);
-    NodeBuilder builder(avg_pool);
+    NodeBuilder builder(avg_pool, {data});
     auto g_avg_pool = ov::as_type_ptr<opset8::AvgPool>(builder.create());
 
     EXPECT_EQ(g_avg_pool->get_strides(), avg_pool->get_strides());

src/core/tests/visitors/op/batch_norm.cpp

@@ -16,34 +16,44 @@ using namespace ngraph;
 using ngraph::test::NodeBuilder;
 using ngraph::test::ValueMap;
 
-template <class T>
-class BatchNormAttrTest : public ::testing::Test {};
-
-TYPED_TEST_SUITE_P(BatchNormAttrTest);
-
-TYPED_TEST_P(BatchNormAttrTest, batch_norm_inference_op) {
+TEST(attributes, batch_norm_inference_op_v5) {
     PartialShape in_shape{1, 10};
     PartialShape ch_shape{in_shape[1]};
     element::Type et = element::f32;
     double epsilon = 0.001;
 
-    NodeBuilder::get_ops().register_factory<TypeParam>();
+    NodeBuilder::get_ops().register_factory<op::v5::BatchNormInference>();
     auto data_batch = make_shared<op::Parameter>(et, in_shape);
     auto gamma = make_shared<op::Parameter>(et, ch_shape);
     auto beta = make_shared<op::Parameter>(et, ch_shape);
     auto mean = make_shared<op::Parameter>(et, ch_shape);
     auto var = make_shared<op::Parameter>(et, ch_shape);
-    auto batch_norm = make_shared<TypeParam>(data_batch, gamma, beta, mean, var, epsilon);
+    auto batch_norm = make_shared<op::v5::BatchNormInference>(data_batch, gamma, beta, mean, var, epsilon);
 
     const auto expected_attr_count = 1;
-    NodeBuilder builder(batch_norm);
+    NodeBuilder builder(batch_norm, {data_batch, gamma, beta, mean, var});
     EXPECT_EQ(builder.get_value_map_size(), expected_attr_count);
-    auto g_batch_norm = ov::as_type_ptr<TypeParam>(builder.create());
+    auto g_batch_norm = ov::as_type_ptr<op::v5::BatchNormInference>(builder.create());
     EXPECT_EQ(g_batch_norm->get_eps_value(), batch_norm->get_eps_value());
 }
 
-REGISTER_TYPED_TEST_SUITE_P(BatchNormAttrTest, batch_norm_inference_op);
+TEST(attributes, batch_norm_inference_op_v0) {
+    PartialShape in_shape{1, 10};
+    PartialShape ch_shape{in_shape[1]};
+    element::Type et = element::f32;
+    double epsilon = 0.001;
 
-using Types = ::testing::Types<op::v0::BatchNormInference, op::v5::BatchNormInference>;
+    NodeBuilder::get_ops().register_factory<op::v0::BatchNormInference>();
+    auto data_batch = make_shared<op::Parameter>(et, in_shape);
+    auto gamma = make_shared<op::Parameter>(et, ch_shape);
+    auto beta = make_shared<op::Parameter>(et, ch_shape);
+    auto mean = make_shared<op::Parameter>(et, ch_shape);
+    auto var = make_shared<op::Parameter>(et, ch_shape);
+    auto batch_norm = make_shared<op::v0::BatchNormInference>(data_batch, gamma, beta, mean, var, epsilon);
 
-INSTANTIATE_TYPED_TEST_SUITE_P(attributes, BatchNormAttrTest, Types);
+    const auto expected_attr_count = 1;
+    NodeBuilder builder(batch_norm, {gamma, beta, data_batch, mean, var});
+    EXPECT_EQ(builder.get_value_map_size(), expected_attr_count);
+    auto g_batch_norm = ov::as_type_ptr<op::v0::BatchNormInference>(builder.create());
+    EXPECT_EQ(g_batch_norm->get_eps_value(), batch_norm->get_eps_value());
+}

src/core/tests/visitors/op/batch_to_space.cpp

@@ -19,7 +19,7 @@ TEST(attributes, batch_to_space_op) {
     auto crops_end = make_shared<op::Constant>(element::i64, Shape{2}, vector<int64_t>{0, 0});
     auto batch2space = make_shared<op::v1::BatchToSpace>(data, block_shape, crops_begin, crops_end);
 
-    NodeBuilder builder(batch2space);
+    NodeBuilder builder(batch2space, {data});
     const auto expected_attr_count = 0;
 
     EXPECT_EQ(builder.get_value_map_size(), expected_attr_count);

src/core/tests/visitors/op/binary_convolution.cpp

@@ -40,7 +40,7 @@ TEST(attributes, bin_convolution) {
                                                        mode,
                                                        pad_value,
                                                        auto_pad);
-    NodeBuilder builder(conv);
+    NodeBuilder builder(conv, {data_batch, filters});
     auto g_convolution = ov::as_type_ptr<op::v1::BinaryConvolution>(builder.create());
 
     // attribute count

src/core/tests/visitors/op/binary_ops.hpp

@@ -49,12 +49,32 @@ TYPED_TEST_P(BinaryOperatorVisitor, Auto_Broadcast)
     auto auto_broadcast = ngraph::op::AutoBroadcastType::NUMPY;
 
     const auto op_func = std::make_shared<OP_Type>(A, B, auto_broadcast);
-    ngraph::test::NodeBuilder builder(op_func);
+    ngraph::test::NodeBuilder builder(op_func, {A, B});
     const auto g_op_func = ngraph::as_type_ptr<OP_Type>(builder.create());
 
     const auto expected_attr_count = 1;
     EXPECT_EQ(builder.get_value_map_size(), expected_attr_count);
     EXPECT_EQ(op_func->get_autob(), g_op_func->get_autob());
 }
 
-REGISTER_TYPED_TEST_SUITE_P(BinaryOperatorVisitor, Auto_Broadcast);
+TYPED_TEST_P(BinaryOperatorVisitor, No_Broadcast)
+{
+    using OP_Type = typename TypeParam::op_type;
+    const ngraph::element::Type_t element_type = TypeParam::element_type;
+
+    ngraph::test::NodeBuilder::get_ops().register_factory<OP_Type>();
+    const auto A =
+        std::make_shared<ngraph::op::Parameter>(element_type, ngraph::PartialShape{1, 2, 3});
+    const auto B =
+        std::make_shared<ngraph::op::Parameter>(element_type, ngraph::PartialShape{1, 2, 3});
+
+    const auto op_func = std::make_shared<OP_Type>(A, B);
+    ngraph::test::NodeBuilder builder(op_func, {A, B});
+    const auto g_op_func = ngraph::as_type_ptr<OP_Type>(builder.create());
+
+    const auto expected_attr_count = 1;
+    EXPECT_EQ(builder.get_value_map_size(), expected_attr_count);
+    EXPECT_EQ(op_func->get_autob(), g_op_func->get_autob());
+}
+
+REGISTER_TYPED_TEST_SUITE_P(BinaryOperatorVisitor, Auto_Broadcast, No_Broadcast);