From ce5d8913e957151c7cd2c0e184ae8e310e31e06e Mon Sep 17 00:00:00 2001
From: Henning Baldersheim <balder@yahoo-inc.com>
Date: Sun, 12 Mar 2023 23:10:54 +0100
Subject: Revert "Arnej/unify cell type conversion"

---
 .../evaluator/TensorConverter.java                 | 23 +++-----------
 .../importer/onnx/TypeConverter.java               | 36 +++++++++-------------
 model-integration/src/main/protobuf/onnx.proto     |  6 +---
 3 files changed, 21 insertions(+), 44 deletions(-)

diff --git a/model-integration/src/main/java/ai/vespa/modelintegration/evaluator/TensorConverter.java b/model-integration/src/main/java/ai/vespa/modelintegration/evaluator/TensorConverter.java
index eef75a32c0a..9c79961eddf 100644
--- a/model-integration/src/main/java/ai/vespa/modelintegration/evaluator/TensorConverter.java
+++ b/model-integration/src/main/java/ai/vespa/modelintegration/evaluator/TensorConverter.java
@@ -180,25 +180,12 @@ class TensorConverter {
     }
 
     static private TensorType.Value toVespaValueType(TensorInfo.OnnxTensorType onnxType) {
-        // NOTE:
-        // should match best_cell_type in onnx_wrapper.cpp
         switch (onnxType) {
-            case ONNX_TENSOR_ELEMENT_DATA_TYPE_BOOL:
-            case ONNX_TENSOR_ELEMENT_DATA_TYPE_INT8:
-                return TensorType.Value.INT8;
-
-            case ONNX_TENSOR_ELEMENT_DATA_TYPE_BFLOAT16:
-                return TensorType.Value.BFLOAT16;
-
-            case ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT8:
-            case ONNX_TENSOR_ELEMENT_DATA_TYPE_INT16:
-            case ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT16:
-            case ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT:
-                return TensorType.Value.FLOAT;
-
-            case ONNX_TENSOR_ELEMENT_DATA_TYPE_DOUBLE:
-                return TensorType.Value.DOUBLE;
-            }
+            case ONNX_TENSOR_ELEMENT_DATA_TYPE_INT8: return TensorType.Value.INT8;
+            case ONNX_TENSOR_ELEMENT_DATA_TYPE_BFLOAT16: return TensorType.Value.BFLOAT16;
+            case ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT: return TensorType.Value.FLOAT;
+            case ONNX_TENSOR_ELEMENT_DATA_TYPE_DOUBLE: return TensorType.Value.DOUBLE;
+        }
         return TensorType.Value.DOUBLE;
     }
 
diff --git a/model-integration/src/main/java/ai/vespa/rankingexpression/importer/onnx/TypeConverter.java b/model-integration/src/main/java/ai/vespa/rankingexpression/importer/onnx/TypeConverter.java
index 2c008dbb922..35ec1d8c54a 100644
--- a/model-integration/src/main/java/ai/vespa/rankingexpression/importer/onnx/TypeConverter.java
+++ b/model-integration/src/main/java/ai/vespa/rankingexpression/importer/onnx/TypeConverter.java
@@ -56,27 +56,21 @@ class TypeConverter {
                                                    tensor.getDimsList());
     }
 
-    private static TensorType.Value toValueType(Onnx.TensorProto.DataType onnxType) {
-        // NOTE:
-        // should match best_cell_type in onnx_wrapper.cpp
-        switch (onnxType) {
-            case BOOL: // Imperfect conversion fallthrough
-            case INT8:
-                return TensorType.Value.INT8;
-            case BFLOAT16:
-                return TensorType.Value.BFLOAT16;
-            case UINT8: // Imperfect conversion fallthrough
-            case INT16: // Imperfect conversion fallthrough
-            case UINT16: // Imperfect conversion fallthrough
-            case FLOAT:
-                return TensorType.Value.FLOAT;
-            case INT32: // Imperfect conversion fallthrough
-            case INT64: // Imperfect conversion fallthrough
-            case UINT32: // Imperfect conversion fallthrough
-            case UINT64: // Imperfect conversion fallthrough
-            case DOUBLE:
-                return TensorType.Value.DOUBLE;
-            default: throw new IllegalArgumentException("A ONNX tensor with data type " + onnxType +
+    private static TensorType.Value toValueType(Onnx.TensorProto.DataType dataType) {
+        switch (dataType) {
+            case FLOAT: return TensorType.Value.FLOAT;
+            case DOUBLE: return TensorType.Value.DOUBLE;
+            // Imperfect conversion, for now:
+            case BOOL: return TensorType.Value.FLOAT;
+            case INT8: return TensorType.Value.FLOAT;
+            case INT16: return TensorType.Value.FLOAT;
+            case INT32: return TensorType.Value.FLOAT;
+            case INT64: return TensorType.Value.FLOAT;
+            case UINT8: return TensorType.Value.FLOAT;
+            case UINT16: return TensorType.Value.FLOAT;
+            case UINT32: return TensorType.Value.FLOAT;
+            case UINT64: return TensorType.Value.FLOAT;
+            default: throw new IllegalArgumentException("A ONNX tensor with data type " + dataType +
                                                         " cannot be converted to a Vespa tensor type");
         }
     }
diff --git a/model-integration/src/main/protobuf/onnx.proto b/model-integration/src/main/protobuf/onnx.proto
index 27f1fdef4b3..dc6542867e0 100644
--- a/model-integration/src/main/protobuf/onnx.proto
+++ b/model-integration/src/main/protobuf/onnx.proto
@@ -298,10 +298,6 @@ message TensorProto {
     UINT64 = 13;
     COMPLEX64 = 14;     // complex with float32 real and imaginary components
     COMPLEX128 = 15;    // complex with float64 real and imaginary components
-    // Non-IEEE floating-point format based on IEEE754 single-precision
-    // floating-point number truncated to 16 bits.
-    // This format has 1 sign bit, 8 exponent bits, and 7 mantissa bits.
-    BFLOAT16 = 16;
     // Future extensions go here.
   }
 
@@ -465,4 +461,4 @@ message OperatorSetIdProto {
   // The version of the operator set being identified.
   // This field MUST be present in this version of the IR.
   optional int64 version = 2;
-}
+}
\ No newline at end of file
-- 
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