DenseTensorView -> DenseValueView

14 files changed, 52 insertions, 45 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]));
 
diff --git a/eval/src/vespa/eval/instruction/dense_lambda_peek_function.cpp b/eval/src/vespa/eval/instruction/dense_lambda_peek_function.cpp
index c590feb3d4c..bf9d5b10a5f 100644
--- a/eval/src/vespa/eval/instruction/dense_lambda_peek_function.cpp
+++ b/eval/src/vespa/eval/instruction/dense_lambda_peek_function.cpp
@@ -32,7 +32,7 @@ void my_lambda_peek_op(InterpretedFunction::State &state, uint64_t param) {
     for (uint32_t idx: lookup_table) {
         *dst++ = src_cells[idx];
     }
-    state.pop_push(state.stash.create<tensor::DenseTensorView>(self.result_type, TypedCells(dst_cells)));
+    state.pop_push(state.stash.create<DenseValueView>(self.result_type, TypedCells(dst_cells)));
 }
 
 struct MyLambdaPeekOp {
diff --git a/eval/src/vespa/eval/instruction/dense_matmul_function.cpp b/eval/src/vespa/eval/instruction/dense_matmul_function.cpp
index 66b4fe05cde..1394a201e6d 100644
--- a/eval/src/vespa/eval/instruction/dense_matmul_function.cpp
+++ b/eval/src/vespa/eval/instruction/dense_matmul_function.cpp
@@ -43,7 +43,7 @@ void my_matmul_op(InterpretedFunction::State &state, uint64_t param) {
         }
         lhs += (lhs_common_inner ? self.common_size : 1);
     }
-    state.pop_pop_push(state.stash.create<tensor::DenseTensorView>(self.result_type, TypedCells(dst_cells)));
+    state.pop_pop_push(state.stash.create<DenseValueView>(self.result_type, TypedCells(dst_cells)));
 }
 
 template <bool lhs_common_inner, bool rhs_common_inner>
@@ -57,7 +57,7 @@ void my_cblas_double_matmul_op(InterpretedFunction::State &state, uint64_t param
                 lhs_cells.cbegin(), lhs_common_inner ? self.common_size : self.lhs_size,
                 rhs_cells.cbegin(), rhs_common_inner ? self.common_size : self.rhs_size,
                 0.0, dst_cells.begin(), self.rhs_size);
-    state.pop_pop_push(state.stash.create<tensor::DenseTensorView>(self.result_type, TypedCells(dst_cells)));
+    state.pop_pop_push(state.stash.create<DenseValueView>(self.result_type, TypedCells(dst_cells)));
 }
 
 template <bool lhs_common_inner, bool rhs_common_inner>
@@ -71,7 +71,7 @@ void my_cblas_float_matmul_op(InterpretedFunction::State &state, uint64_t param)
                 lhs_cells.cbegin(), lhs_common_inner ? self.common_size : self.lhs_size,
                 rhs_cells.cbegin(), rhs_common_inner ? self.common_size : self.rhs_size,
                 0.0, dst_cells.begin(), self.rhs_size);
-    state.pop_pop_push(state.stash.create<tensor::DenseTensorView>(self.result_type, TypedCells(dst_cells)));
+    state.pop_pop_push(state.stash.create<DenseValueView>(self.result_type, TypedCells(dst_cells)));
 }
 
 bool is_matrix(const ValueType &type) {
diff --git a/eval/src/vespa/eval/instruction/dense_multi_matmul_function.cpp b/eval/src/vespa/eval/instruction/dense_multi_matmul_function.cpp
index a5ece2e84cd..6d05c8a8d1e 100644
--- a/eval/src/vespa/eval/instruction/dense_multi_matmul_function.cpp
+++ b/eval/src/vespa/eval/instruction/dense_multi_matmul_function.cpp
@@ -1,7 +1,6 @@
 // Copyright Verizon Media. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
 
 #include "dense_multi_matmul_function.h"
-#include <vespa/eval/tensor/dense/dense_tensor_view.h>
 #include <vespa/vespalib/objects/objectvisitor.h>
 #include <vespa/eval/eval/value.h>
 #include <vespa/eval/eval/operation.h>
@@ -36,7 +35,7 @@ void my_cblas_double_multi_matmul_op(InterpretedFunction::State &state, uint64_t
                     rhs, self.rhs_common_inner() ? self.common_size() : self.rhs_size(),
                     0.0, dst, self.rhs_size());
     }
-    state.pop_pop_push(state.stash.create<tensor::DenseTensorView>(self.result_type(), TypedCells(dst_cells)));
+    state.pop_pop_push(state.stash.create<DenseValueView>(self.result_type(), TypedCells(dst_cells)));
 }
 
 void my_cblas_float_multi_matmul_op(InterpretedFunction::State &state, uint64_t param) {
@@ -57,7 +56,7 @@ void my_cblas_float_multi_matmul_op(InterpretedFunction::State &state, uint64_t
                     rhs, self.rhs_common_inner() ? self.common_size() : self.rhs_size(),
                     0.0, dst, self.rhs_size());
     }
-    state.pop_pop_push(state.stash.create<tensor::DenseTensorView>(self.result_type(), TypedCells(dst_cells)));
+    state.pop_pop_push(state.stash.create<DenseValueView>(self.result_type(), TypedCells(dst_cells)));
 }
 
 InterpretedFunction::op_function my_select(CellType cell_type) {
diff --git a/eval/src/vespa/eval/instruction/dense_simple_expand_function.cpp b/eval/src/vespa/eval/instruction/dense_simple_expand_function.cpp
index 4f2551211db..a656a0249f9 100644
--- a/eval/src/vespa/eval/instruction/dense_simple_expand_function.cpp
+++ b/eval/src/vespa/eval/instruction/dense_simple_expand_function.cpp
@@ -49,7 +49,7 @@ void my_simple_expand_op(State &state, uint64_t param) {
         apply_op2_vec_num(dst, inner_cells.begin(), outer_cell, inner_cells.size(), my_op);
         dst += inner_cells.size();
     }
-    state.pop_pop_push(state.stash.create<tensor::DenseTensorView>(params.result_type, TypedCells(dst_cells)));
+    state.pop_pop_push(state.stash.create<DenseValueView>(params.result_type, TypedCells(dst_cells)));
 }
 
 //-----------------------------------------------------------------------------
diff --git a/eval/src/vespa/eval/instruction/dense_xw_product_function.cpp b/eval/src/vespa/eval/instruction/dense_xw_product_function.cpp
index 3727e782718..7d124555f55 100644
--- a/eval/src/vespa/eval/instruction/dense_xw_product_function.cpp
+++ b/eval/src/vespa/eval/instruction/dense_xw_product_function.cpp
@@ -1,7 +1,6 @@
 // Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
 
 #include "dense_xw_product_function.h"
-#include <vespa/eval/tensor/dense/dense_tensor_view.h>
 #include <vespa/vespalib/objects/objectvisitor.h>
 #include <vespa/eval/eval/value.h>
 #include <vespa/eval/eval/operation.h>
@@ -40,7 +39,7 @@ void my_xw_product_op(InterpretedFunction::State &state, uint64_t param) {
         *dst++ = my_dot_product<LCT,RCT,common_inner>(vector_cells.cbegin(), matrix, self.vector_size, self.result_size);
         matrix += (common_inner ? self.vector_size : 1);
     }
-    state.pop_pop_push(state.stash.create<tensor::DenseTensorView>(self.result_type, TypedCells(dst_cells)));
+    state.pop_pop_push(state.stash.create<DenseValueView>(self.result_type, TypedCells(dst_cells)));
 }
 
 template <bool common_inner>
@@ -54,7 +53,7 @@ void my_cblas_double_xw_product_op(InterpretedFunction::State &state, uint64_t p
                 common_inner ? self.vector_size : self.result_size,
                 1.0, matrix_cells.cbegin(), common_inner ? self.vector_size : self.result_size, vector_cells.cbegin(), 1,
                 0.0, dst_cells.begin(), 1);
-    state.pop_pop_push(state.stash.create<tensor::DenseTensorView>(self.result_type, TypedCells(dst_cells)));
+    state.pop_pop_push(state.stash.create<DenseValueView>(self.result_type, TypedCells(dst_cells)));
 }
 
 template <bool common_inner>
@@ -68,7 +67,7 @@ void my_cblas_float_xw_product_op(InterpretedFunction::State &state, uint64_t pa
                 common_inner ? self.vector_size : self.result_size,
                 1.0, matrix_cells.cbegin(), common_inner ? self.vector_size : self.result_size, vector_cells.cbegin(), 1,
                 0.0, dst_cells.begin(), 1);
-    state.pop_pop_push(state.stash.create<tensor::DenseTensorView>(self.result_type, TypedCells(dst_cells)));
+    state.pop_pop_push(state.stash.create<DenseValueView>(self.result_type, TypedCells(dst_cells)));
 }
 
 bool isDenseTensor(const ValueType &type, size_t d) {
diff --git a/eval/src/vespa/eval/instruction/generic_concat.cpp b/eval/src/vespa/eval/instruction/generic_concat.cpp
index 2d8c206b588..4d949d5e725 100644
--- a/eval/src/vespa/eval/instruction/generic_concat.cpp
+++ b/eval/src/vespa/eval/instruction/generic_concat.cpp
@@ -103,7 +103,7 @@ void my_dense_simple_concat_op(State &state, uint64_t param_in) {
     for (size_t i = 0; i < b.size(); ++i) {
         *pos++ = b[i];
     }
-    Value &ref = state.stash.create<tensor::DenseTensorView>(param.res_type, TypedCells(result));
+    Value &ref = state.stash.create<DenseValueView>(param.res_type, TypedCells(result));
     state.pop_pop_push(ref);
 }
 
diff --git a/eval/src/vespa/eval/tensor/dense/dense_replace_type_function.cpp b/eval/src/vespa/eval/tensor/dense/dense_replace_type_function.cpp
index d7bc7dc860d..ed75d6fff98 100644
--- a/eval/src/vespa/eval/tensor/dense/dense_replace_type_function.cpp
+++ b/eval/src/vespa/eval/tensor/dense/dense_replace_type_function.cpp
@@ -1,11 +1,12 @@
 // Copyright 2018 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
 
 #include "dense_replace_type_function.h"
-#include "dense_tensor_view.h"
 #include <vespa/eval/eval/value.h>
 
 namespace vespalib::tensor {
 
+using eval::DenseValueView;
+using eval::TypedCells;
 using eval::Value;
 using eval::ValueType;
 using eval::TensorFunction;
@@ -17,7 +18,7 @@ namespace {
 void my_replace_type_op(eval::InterpretedFunction::State &state, uint64_t param) {
     const ValueType &type = unwrap_param<ValueType>(param);
     TypedCells cells = state.peek(0).cells();
-    state.pop_push(state.stash.create<DenseTensorView>(type, cells));
+    state.pop_push(state.stash.create<DenseValueView>(type, cells));
 }
 
 } // namespace vespalib::tensor::<unnamed>
diff --git a/eval/src/vespa/eval/tensor/dense/dense_simple_join_function.cpp b/eval/src/vespa/eval/tensor/dense/dense_simple_join_function.cpp
index 8e7bd72a0f6..21b47b67291 100644
--- a/eval/src/vespa/eval/tensor/dense/dense_simple_join_function.cpp
+++ b/eval/src/vespa/eval/tensor/dense/dense_simple_join_function.cpp
@@ -1,7 +1,6 @@
 // Copyright Verizon Media. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
 
 #include "dense_simple_join_function.h"
-#include "dense_tensor_view.h"
 #include <vespa/vespalib/objects/objectvisitor.h>
 #include <vespa/eval/eval/value.h>
 #include <vespa/eval/eval/operation.h>
@@ -15,10 +14,12 @@ namespace vespalib::tensor {
 using vespalib::ArrayRef;
 
 using eval::CellType;
-using eval::Value;
-using eval::ValueType;
+using eval::DenseValueView;
 using eval::TensorFunction;
+using eval::TypedCells;
 using eval::TypifyCellType;
+using eval::Value;
+using eval::ValueType;
 using eval::as;
 
 using namespace eval::operation;
@@ -91,7 +92,7 @@ void my_simple_join_op(State &state, uint64_t param) {
             offset += sec_cells.size();
         }
     }
-    state.pop_pop_push(state.stash.create<DenseTensorView>(params.result_type, TypedCells(dst_cells)));
+    state.pop_pop_push(state.stash.create<DenseValueView>(params.result_type, TypedCells(dst_cells)));
 }
 
 //-----------------------------------------------------------------------------
diff --git a/eval/src/vespa/eval/tensor/dense/dense_simple_map_function.cpp b/eval/src/vespa/eval/tensor/dense/dense_simple_map_function.cpp
index b6376326468..5227b67dd92 100644
--- a/eval/src/vespa/eval/tensor/dense/dense_simple_map_function.cpp
+++ b/eval/src/vespa/eval/tensor/dense/dense_simple_map_function.cpp
@@ -1,7 +1,6 @@
 // Copyright Verizon Media. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
 
 #include "dense_simple_map_function.h"
-#include "dense_tensor_view.h"
 #include <vespa/vespalib/util/typify.h>
 #include <vespa/eval/eval/value.h>
 #include <vespa/eval/eval/operation.h>
@@ -11,10 +10,12 @@ namespace vespalib::tensor {
 
 using vespalib::ArrayRef;
 
-using eval::Value;
-using eval::ValueType;
+using eval::DenseValueView;
 using eval::TensorFunction;
+using eval::TypedCells;
 using eval::TypifyCellType;
+using eval::Value;
+using eval::ValueType;
 using eval::as;
 
 using namespace eval::operation;
@@ -43,7 +44,7 @@ void my_simple_map_op(State &state, uint64_t param) {
     auto dst_cells = make_dst_cells<CT, inplace>(src_cells, state.stash);
     apply_op1_vec(dst_cells.begin(), src_cells.begin(), dst_cells.size(), my_fun);
     if (!inplace) {
-        state.pop_push(state.stash.create<DenseTensorView>(child.type(), TypedCells(dst_cells)));
+        state.pop_push(state.stash.create<DenseValueView>(child.type(), TypedCells(dst_cells)));
     }
 }
 
diff --git a/eval/src/vespa/eval/tensor/dense/dense_single_reduce_function.cpp b/eval/src/vespa/eval/tensor/dense/dense_single_reduce_function.cpp
index 82d4505dc80..f107e85eaa2 100644
--- a/eval/src/vespa/eval/tensor/dense/dense_single_reduce_function.cpp
+++ b/eval/src/vespa/eval/tensor/dense/dense_single_reduce_function.cpp
@@ -9,10 +9,12 @@
 namespace vespalib::tensor {
 
 using eval::Aggr;
+using eval::DenseValueView;
 using eval::InterpretedFunction;
 using eval::TensorFunction;
 using eval::Value;
 using eval::ValueType;
+using eval::TypedCells;
 using eval::TypifyCellType;
 using eval::TypifyAggr;
 using eval::as;
@@ -124,7 +126,7 @@ void my_single_reduce_op(InterpretedFunction::State &state, uint64_t param) {
     } else {
         trace_reduce_impl<CT,AGGR,atleast_8,is_inner>(params, src, dst);
     }
-    state.pop_push(state.stash.create<DenseTensorView>(params.result_type, TypedCells(dst_cells)));
+    state.pop_push(state.stash.create<DenseValueView>(params.result_type, TypedCells(dst_cells)));
 }
 
 struct MyGetFun {
diff --git a/eval/src/vespa/eval/tensor/dense/dense_tensor_create_function.cpp b/eval/src/vespa/eval/tensor/dense/dense_tensor_create_function.cpp
index 4cdaa01eea8..e38cf638e9c 100644
--- a/eval/src/vespa/eval/tensor/dense/dense_tensor_create_function.cpp
+++ b/eval/src/vespa/eval/tensor/dense/dense_tensor_create_function.cpp
@@ -7,6 +7,7 @@
 
 namespace vespalib::tensor {
 
+using eval::DenseValueView;
 using eval::Value;
 using eval::DoubleValue;
 using eval::ValueType;
@@ -27,7 +28,7 @@ void my_tensor_create_op(eval::InterpretedFunction::State &state, uint64_t param
         cells[pending_cells] = (CT) state.peek(0).as_double();
         state.stack.pop_back();
     }
-    const Value &result = state.stash.create<DenseTensorView>(self.result_type, TypedCells(cells)); 
+    const Value &result = state.stash.create<DenseValueView>(self.result_type, TypedCells(cells)); 
     state.stack.emplace_back(result);
 }
 
diff --git a/eval/src/vespa/eval/tensor/dense/onnx_wrapper.cpp b/eval/src/vespa/eval/tensor/dense/onnx_wrapper.cpp
index c49809f265f..0dc8b343627 100644
--- a/eval/src/vespa/eval/tensor/dense/onnx_wrapper.cpp
+++ b/eval/src/vespa/eval/tensor/dense/onnx_wrapper.cpp
@@ -2,7 +2,6 @@
 
 #include "onnx_wrapper.h"
 #include <vespa/eval/eval/value_type.h>
-#include "dense_tensor_view.h"
 #include "dense_tensor.h"
 #include <vespa/vespalib/util/arrayref.h>
 #include <vespa/vespalib/util/stringfmt.h>
@@ -20,8 +19,10 @@ LOG_SETUP(".eval.onnx_wrapper");
 using vespalib::ArrayRef;
 using vespalib::ConstArrayRef;
 using vespalib::eval::CellType;
-using vespalib::eval::ValueType;
+using vespalib::eval::DenseValueView;
+using vespalib::eval::TypedCells;
 using vespalib::eval::TypifyCellType;
+using vespalib::eval::ValueType;
 
 using vespalib::make_string_short::fmt;
 
@@ -73,7 +74,7 @@ struct CreateVespaTensorRef {
     template <typename T> static eval::Value::UP invoke(const eval::ValueType &type_ref, Ort::Value &value) {
         size_t num_cells = type_ref.dense_subspace_size();
         ConstArrayRef<T> cells(value.GetTensorMutableData<T>(), num_cells);
-        return std::make_unique<DenseTensorView>(type_ref, TypedCells(cells));
+        return std::make_unique<DenseValueView>(type_ref, TypedCells(cells));
     }
     eval::Value::UP operator()(const eval::ValueType &type_ref, Ort::Value &value) {
         return typify_invoke<1,MyTypify,CreateVespaTensorRef>(type_ref.cell_type(), type_ref, value);
diff --git a/eval/src/vespa/eval/tensor/dense/vector_from_doubles_function.cpp b/eval/src/vespa/eval/tensor/dense/vector_from_doubles_function.cpp
index 0d653acee4d..19c95c9418d 100644
--- a/eval/src/vespa/eval/tensor/dense/vector_from_doubles_function.cpp
+++ b/eval/src/vespa/eval/tensor/dense/vector_from_doubles_function.cpp
@@ -1,14 +1,16 @@
 // Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
 
 #include "vector_from_doubles_function.h"
-#include "dense_tensor_view.h"
 #include <vespa/eval/eval/value.h>
 
 namespace vespalib::tensor {
 
+using eval::CellType;
+using eval::DenseValueView;
+using eval::TensorFunction;
+using eval::TypedCells;
 using eval::Value;
 using eval::ValueType;
-using eval::TensorFunction;
 using Child = eval::TensorFunction::Child;
 using eval::as;
 using namespace eval::tensor_function;
@@ -34,7 +36,7 @@ void my_vector_from_doubles_op(eval::InterpretedFunction::State &state, uint64_t
     size_t numCells = self.resultSize;
     using MyTypify = eval::TypifyCellType;
     TypedCells cells = typify_invoke<1,MyTypify,CallVectorFromDoubles>(ct, state, numCells);
-    const Value &result = state.stash.create<DenseTensorView>(self.resultType, cells);
+    const Value &result = state.stash.create<DenseValueView>(self.resultType, cells);
     state.stack.emplace_back(result);
 }