DenseTensorView -> DenseValueView

1 files changed, 14 insertions, 14 deletions

diff --git a/eval/src/tests/tensor/onnx_wrapper/onnx_wrapper_test.cpp b/eval/src/tests/tensor/onnx_wrapper/onnx_wrapper_test.cpp
index efab0571e62..3cd7f697067 100644
--- a/eval/src/tests/tensor/onnx_wrapper/onnx_wrapper_test.cpp
+++ b/eval/src/tests/tensor/onnx_wrapper/onnx_wrapper_test.cpp
@@ -136,17 +136,17 @@ TEST(OnnxTest, simple_onnx_model_can_be_evaluated)
 
     ValueType query_type = ValueType::from_spec("tensor<float>(a[1],b[4])");
     std::vector<float> query_values({1.0, 2.0, 3.0, 4.0});
-    DenseTensorView query(query_type, TypedCells(query_values));
+    DenseValueView query(query_type, TypedCells(query_values));
     EXPECT_TRUE(planner.bind_input_type(query_type, model.inputs()[0]));
 
     ValueType attribute_type = ValueType::from_spec("tensor<float>(a[4],b[1])");
     std::vector<float> attribute_values({5.0, 6.0, 7.0, 8.0});
-    DenseTensorView attribute(attribute_type, TypedCells(attribute_values));
+    DenseValueView attribute(attribute_type, TypedCells(attribute_values));
     EXPECT_TRUE(planner.bind_input_type(attribute_type, model.inputs()[1]));
 
     ValueType bias_type = ValueType::from_spec("tensor<float>(a[1],b[1])");
     std::vector<float> bias_values({9.0});
-    DenseTensorView bias(bias_type, TypedCells(bias_values));
+    DenseValueView bias(bias_type, TypedCells(bias_values));
     EXPECT_TRUE(planner.bind_input_type(bias_type, model.inputs()[2]));
 
     EXPECT_EQ(planner.make_output_type(model.outputs()[0]).to_spec(),
@@ -168,7 +168,7 @@ TEST(OnnxTest, simple_onnx_model_can_be_evaluated)
     EXPECT_EQ(GetCell::from(cells, 0), 79.0);
     //-------------------------------------------------------------------------
     std::vector<float> new_bias_values({10.0});
-    DenseTensorView new_bias(bias_type, TypedCells(new_bias_values));
+    DenseValueView new_bias(bias_type, TypedCells(new_bias_values));
     ctx.bind_param(2, new_bias);
     ctx.eval();
     EXPECT_EQ(GetCell::from(output.cells(), 0), 80.0);
@@ -182,17 +182,17 @@ TEST(OnnxTest, dynamic_onnx_model_can_be_evaluated)
 
     ValueType query_type = ValueType::from_spec("tensor<float>(a[1],b[4])");
     std::vector<float> query_values({1.0, 2.0, 3.0, 4.0});
-    DenseTensorView query(query_type, TypedCells(query_values));
+    DenseValueView query(query_type, TypedCells(query_values));
     EXPECT_TRUE(planner.bind_input_type(query_type, model.inputs()[0]));
 
     ValueType attribute_type = ValueType::from_spec("tensor<float>(a[4],b[1])");
     std::vector<float> attribute_values({5.0, 6.0, 7.0, 8.0});
-    DenseTensorView attribute(attribute_type, TypedCells(attribute_values));
+    DenseValueView attribute(attribute_type, TypedCells(attribute_values));
     EXPECT_TRUE(planner.bind_input_type(attribute_type, model.inputs()[1]));
 
     ValueType bias_type = ValueType::from_spec("tensor<float>(a[1],b[2])");
     std::vector<float> bias_values({4.0, 5.0});
-    DenseTensorView bias(bias_type, TypedCells(bias_values));
+    DenseValueView bias(bias_type, TypedCells(bias_values));
     EXPECT_TRUE(planner.bind_input_type(bias_type, model.inputs()[2]));
 
     EXPECT_EQ(planner.make_output_type(model.outputs()[0]).to_spec(),
@@ -214,7 +214,7 @@ TEST(OnnxTest, dynamic_onnx_model_can_be_evaluated)
     EXPECT_EQ(GetCell::from(cells, 0), 79.0);
     //-------------------------------------------------------------------------
     std::vector<float> new_bias_values({5.0,6.0});
-    DenseTensorView new_bias(bias_type, TypedCells(new_bias_values));
+    DenseValueView new_bias(bias_type, TypedCells(new_bias_values));
     ctx.bind_param(2, new_bias);
     ctx.eval();
     EXPECT_EQ(GetCell::from(output.cells(), 0), 81.0);
@@ -228,17 +228,17 @@ TEST(OnnxTest, int_types_onnx_model_can_be_evaluated)
 
     ValueType query_type = ValueType::from_spec("tensor<float>(a[1],b[4])");
     std::vector<float> query_values({1.0, 2.0, 3.0, 4.0});
-    DenseTensorView query(query_type, TypedCells(query_values));
+    DenseValueView query(query_type, TypedCells(query_values));
     EXPECT_TRUE(planner.bind_input_type(query_type, model.inputs()[0]));
 
     ValueType attribute_type = ValueType::from_spec("tensor<double>(a[4],b[1])");
     std::vector<double> attribute_values({5.0, 6.0, 7.0, 8.0});
-    DenseTensorView attribute(attribute_type, TypedCells(attribute_values));
+    DenseValueView attribute(attribute_type, TypedCells(attribute_values));
     EXPECT_TRUE(planner.bind_input_type(attribute_type, model.inputs()[1]));
 
     ValueType bias_type = ValueType::from_spec("tensor<double>(a[1],b[1])");
     std::vector<double> bias_values({9.0});
-    DenseTensorView bias(bias_type, TypedCells(bias_values));
+    DenseValueView bias(bias_type, TypedCells(bias_values));
     EXPECT_TRUE(planner.bind_input_type(bias_type, model.inputs()[2]));
 
     EXPECT_EQ(planner.make_output_type(model.outputs()[0]),
@@ -260,7 +260,7 @@ TEST(OnnxTest, int_types_onnx_model_can_be_evaluated)
     EXPECT_EQ(GetCell::from(cells, 0), 79.0);
     //-------------------------------------------------------------------------
     std::vector<double> new_bias_values({10.0});
-    DenseTensorView new_bias(bias_type, TypedCells(new_bias_values));
+    DenseValueView new_bias(bias_type, TypedCells(new_bias_values));
     ctx.bind_param(2, new_bias);
     ctx.eval();
     EXPECT_EQ(GetCell::from(output.cells(), 0), 80.0);
@@ -274,13 +274,13 @@ TEST(OnnxTest, we_guess_batch_dimension_size_when_inference_fails) {
 
     ValueType in_3_type = ValueType::from_spec("tensor<float>(a[3])");
     std::vector<float> in_3_values({1.0, 2.0, 3.0});
-    DenseTensorView in_3(in_3_type, TypedCells(in_3_values));
+    DenseValueView in_3(in_3_type, TypedCells(in_3_values));
     EXPECT_TRUE(planner_3.bind_input_type(in_3_type, model.inputs()[0]));
     EXPECT_TRUE(planner_3.bind_input_type(in_3_type, model.inputs()[1]));
 
     ValueType in_4_type = ValueType::from_spec("tensor<float>(a[4])");
     std::vector<float> in_4_values({1.0, 2.0, 3.0, 4.0});
-    DenseTensorView in_4(in_4_type, TypedCells(in_4_values));
+    DenseValueView in_4(in_4_type, TypedCells(in_4_values));
     EXPECT_TRUE(planner_4.bind_input_type(in_4_type, model.inputs()[0]));
     EXPECT_TRUE(planner_4.bind_input_type(in_4_type, model.inputs()[1]));