lowering div/add operator to version 13

Signed-off-by: Jason Wang <jasowang@microsoft.com>
onnx · May 31, 2022 · 95a2a4d · 95a2a4d
1 parent b6cff38
commit 95a2a4d
Showing 1 changed file with 15 additions and 15 deletions.
diff --git a/onnxmltools/convert/sparkml/operator_converters/k_means.py b/onnxmltools/convert/sparkml/operator_converters/k_means.py
@@ -75,11 +75,11 @@ def convert_sparkml_k_means_model(scope: Scope, operator: Operator, container: M
         # Euclidean Distance Squared = input_row_squared_sum - 2 * input * Transpose(Center) + Transpose(centers_row_squared_sum)
         # [N x K]
         container.add_node(
-            op_type = "Add",
-            inputs = [gemm_output_variable_name, centers_row_squared_sum_variable_name],
-            outputs = [distance_output_variable_name],
-            op_domain = "ai.onnx",
-            op_version = 14,
+            op_type="Add",
+            inputs=[gemm_output_variable_name, centers_row_squared_sum_variable_name],
+            outputs=[distance_output_variable_name],
+            op_domain="ai.onnx",
+            op_version=13,
         )
     elif op.getDistanceMeasure() == "cosine":
         # centers_row_norm2: [1 x K]
@@ -127,19 +127,19 @@ def convert_sparkml_k_means_model(scope: Scope, operator: Operator, container: M
         # Cosine similarity = gemm_output / input_row_norm2 / centers_row_norm2: [N x K]
         div_output_variable_name = scope.get_unique_variable_name("div_output")
         container.add_node(
-            op_type = "Div",
-            inputs = [gemm_output_variable_name, input_row_norm2_variable_name],
-            outputs = [div_output_variable_name],
-            op_domain = "ai.onnx",
-            op_version = 14,
+            op_type="Div",
+            inputs=[gemm_output_variable_name, input_row_norm2_variable_name],
+            outputs=[div_output_variable_name],
+            op_domain="ai.onnx",
+            op_version=13,
         )
         cosine_similarity_output_variable_name = scope.get_unique_variable_name("cosine_similarity_output")
         container.add_node(
-            op_type = "Div",
-            inputs = [div_output_variable_name, centers_row_norm2_variable_name],
-            outputs = [cosine_similarity_output_variable_name],
-            op_domain = "ai.onnx",
-            op_version = 14,
+            op_type="Div",
+            inputs=[div_output_variable_name, centers_row_norm2_variable_name],
+            outputs=[cosine_similarity_output_variable_name],
+            op_domain="ai.onnx",
+            op_version=13,
         )
 
         # Cosine distance - 1 = -Cosine similarity: [N x K]