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Rename function and add tests for SoftmaxCrossEntropyLoss
Renamed `impl_softmax_cross_entropy` to `onnx_softmax_crossentropy_loss` in `softmax_crossentropy_loss.cpp` and updated all function calls accordingly. Updated `ONNX_OP` macro for `SoftmaxCrossEntropyLoss` in `opset_13` to use `OPSET_SINCE(13)`. Added new test cases in `onnx_import.in.cpp` for various scenarios of the `SoftmaxCrossEntropyLoss` operation: - `onnx_model_softmax_crossentropy_loss_mean_weight_ii` - `onnx_model_softmax_crossentropy_loss_sum` - `onnx_model_softmax_crossentropy_loss_none` - `onnx_model_softmax_crossentropy_loss_higher_dim` Included new ONNX model files in `prototxt` format for the new test cases: - `softmax_crossentropy_loss_higher_dim.prototxt` - `softmax_crossentropy_loss_mean_weight_ii.prototxt` - `softmax_crossentropy_loss_none.prototxt` - `softmax_crossentropy_loss_sum.prototxt` These files define the graph structure, input/output tensor shapes, and attributes for the `SoftmaxCrossEntropyLoss` operation with different reduction methods and configurations.
1 parent 5c92fde commit 1fc5bbb

6 files changed

+280
-4
lines changed

‎src/frontends/onnx/frontend/src/op/softmax_crossentropy_loss.cpp

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@@ -19,7 +19,7 @@ namespace ov {
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namespace frontend {
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namespace onnx {
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namespace {
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OutputVector impl_softmax_cross_entropy(const Node& node, int64_t axis_default) {
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OutputVector onnx_softmax_crossentropy_loss(const Node& node, int64_t axis_default) {
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const auto inputs = node.get_ov_inputs();
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const auto scores = inputs[0];
@@ -96,15 +96,16 @@ OutputVector impl_softmax_cross_entropy(const Node& node, int64_t axis_default)
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namespace ai_onnx {
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namespace opset_12 {
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OutputVector softmax_cross_entropy_loss(const Node& node) {
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return impl_softmax_cross_entropy(node, 1);
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return onnx_softmax_crossentropy_loss(node, 1);
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}
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ONNX_OP("SoftmaxCrossEntropyLoss", OPSET_IN(12), ai_onnx::opset_12::softmax_cross_entropy_loss);
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} // namespace opset_12
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namespace opset_13 {
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OutputVector softmax_cross_entropy_loss(const Node& node) {
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return impl_softmax_cross_entropy(node, 1);
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// only difference is that opset_13 supports bfloat16 datatype
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return onnx_softmax_crossentropy_loss(node, 1);
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}
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ONNX_OP("SoftmaxCrossEntropyLoss", OPSET_IN(13), ai_onnx::opset_13::softmax_cross_entropy_loss);
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ONNX_OP("SoftmaxCrossEntropyLoss", OPSET_SINCE(13), ai_onnx::opset_13::softmax_cross_entropy_loss);
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} // namespace opset_13
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} // namespace ai_onnx
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} // namespace onnx

‎src/frontends/onnx/tests/models/softmax_crossentropy_loss_higher_dim.prototxt

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@@ -0,0 +1,55 @@
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ir_version: 7
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producer_name: "OpenVINO ONNX Frontend"
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graph {
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node {
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input: "x"
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input: "y"
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output: "z"
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op_type: "SoftmaxCrossEntropyLoss"
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attribute {
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name: "reduction"
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s: "mean"
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type: STRING
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}
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}
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name: "test_sce_higher_dim"
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input {
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name: "x"
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type {
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tensor_type {
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elem_type: 1
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shape {
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dim { dim_value: 2 }
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dim { dim_value: 3 }
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dim { dim_value: 2 }
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dim { dim_value: 2 }
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}
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}
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}
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}
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input {
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name: "y"
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type {
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tensor_type {
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elem_type: 7
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shape {
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dim { dim_value: 2 }
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dim { dim_value: 2 }
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dim { dim_value: 2 }
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}
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}
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}
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}
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output {
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name: "z"
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type {
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tensor_type {
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elem_type: 1
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shape {}
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}
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}
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}
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}
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opset_import {
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version: 13
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}

‎src/frontends/onnx/tests/models/softmax_crossentropy_loss_mean_weight_ii.prototxt

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@@ -0,0 +1,70 @@
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ir_version: 7
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producer_name: "OpenVINO ONNX Frontend"
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graph {
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node {
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input: "x"
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input: "y"
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input: "w"
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output: "z"
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op_type: "SoftmaxCrossEntropyLoss"
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attribute {
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name: "reduction"
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s: "mean"
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type: STRING
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}
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attribute {
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name: "ignore_index"
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i: -1
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type: INT
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}
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}
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name: "test_sce_mean_weight_ii"
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input {
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name: "x"
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type {
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tensor_type {
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elem_type: 1
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shape {
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dim { dim_value: 2 }
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dim { dim_value: 3 }
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dim { dim_value: 2 }
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}
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}
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}
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}
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input {
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name: "y"
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type {
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tensor_type {
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elem_type: 7
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shape {
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dim { dim_value: 2 }
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dim { dim_value: 2 }
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}
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}
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}
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}
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input {
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name: "w"
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type {
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tensor_type {
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elem_type: 1
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shape {
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dim { dim_value: 3 }
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}
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}
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}
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}
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output {
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name: "z"
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type {
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tensor_type {
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elem_type: 1
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shape {}
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}
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}
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}
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}
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opset_import {
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version: 13
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}

‎src/frontends/onnx/tests/models/softmax_crossentropy_loss_none.prototxt

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ir_version: 7
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producer_name: "OpenVINO ONNX Frontend"
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graph {
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node {
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input: "x"
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input: "y"
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output: "z"
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op_type: "SoftmaxCrossEntropyLoss"
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attribute {
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name: "reduction"
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s: "none"
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type: STRING
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}
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}
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name: "test_sce_none"
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input {
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name: "x"
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type {
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tensor_type {
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elem_type: 1
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shape {
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dim { dim_value: 2 }
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dim { dim_value: 3 }
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}
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}
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}
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}
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input {
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name: "y"
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type {
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tensor_type {
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elem_type: 7
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shape {
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dim { dim_value: 2 }
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}
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}
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}
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}
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output {
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name: "z"
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type {
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tensor_type {
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elem_type: 1
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shape {
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dim { dim_value: 2 }
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}
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}
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}
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}
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}
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opset_import {
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version: 13
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}

‎src/frontends/onnx/tests/models/softmax_crossentropy_loss_sum.prototxt

Lines changed: 51 additions & 0 deletions
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@@ -0,0 +1,51 @@
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ir_version: 7
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producer_name: "OpenVINO ONNX Frontend"
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graph {
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node {
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input: "x"
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input: "y"
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output: "z"
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op_type: "SoftmaxCrossEntropyLoss"
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attribute {
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name: "reduction"
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s: "sum"
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type: STRING
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}
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}
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name: "test_sce_sum"
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input {
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name: "x"
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type {
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tensor_type {
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elem_type: 1
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shape {
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dim { dim_value: 2 }
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dim { dim_value: 3 }
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}
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}
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}
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}
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input {
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name: "y"
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type {
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tensor_type {
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elem_type: 7
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shape {
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dim { dim_value: 2 }
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}
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}
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}
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}
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output {
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name: "z"
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type {
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tensor_type {
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elem_type: 1
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shape {}
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}
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}
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}
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}
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opset_import {
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version: 13
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}

‎src/frontends/onnx/tests/onnx_import.in.cpp

Lines changed: 46 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -6945,3 +6945,49 @@ OPENVINO_TEST(${BACKEND_NAME}, onnx_float8e4m3fn_constant) {
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69466946
test_case.run();
69476947
}
6948+
6949+
OPENVINO_TEST(${BACKEND_NAME}, onnx_model_softmax_crossentropy_loss_mean_weight_ii) {
6950+
auto model = convert_model("softmax_crossentropy_loss_mean_weight_ii.onnx");
6951+
6952+
auto test_case = ov::test::TestCase(model, s_device);
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// Input x: shape (2,3,2)
6954+
test_case.add_input<float>({1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f, 8.f, 9.f, 10.f, 11.f, 12.f});
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// Labels with ignore_index -1
6956+
test_case.add_input<int64_t>({0, -1, 2, 1});
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// Weights
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test_case.add_input<float>({0.5f, 1.0f, 2.0f});
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// Expected output
6960+
test_case.add_expected_output<float>(Shape{}, {1.28642857f});
6961+
test_case.run();
6962+
}
6963+
6964+
OPENVINO_TEST(${BACKEND_NAME}, onnx_model_softmax_crossentropy_loss_sum) {
6965+
auto model = convert_model("softmax_crossentropy_loss_sum.onnx");
6966+
6967+
auto test_case = ov::test::TestCase(model, s_device);
6968+
test_case.add_input<float>({0.5f, 1.5f, 2.5f, 3.5f, 4.5f, 5.5f});
6969+
test_case.add_input<int64_t>({1, 2});
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test_case.add_expected_output<float>(Shape{}, {1.8137f});
6971+
test_case.run();
6972+
}
6973+
6974+
OPENVINO_TEST(${BACKEND_NAME}, onnx_model_softmax_crossentropy_loss_none) {
6975+
auto model = convert_model("softmax_crossentropy_loss_none.onnx");
6976+
6977+
auto test_case = ov::test::TestCase(model, s_device);
6978+
test_case.add_input<float>({1.f, 2.f, 3.f, 4.f, 5.f, 6.f});
6979+
test_case.add_input<int64_t>({2, 1});
6980+
test_case.add_expected_output<float>(Shape{2}, {0.407f, 1.4067f});
6981+
test_case.run();
6982+
}
6983+
6984+
OPENVINO_TEST(${BACKEND_NAME}, onnx_model_softmax_crossentropy_loss_higher_dim) {
6985+
auto model = convert_model("softmax_crossentropy_loss_higher_dim.onnx");
6986+
6987+
auto test_case = ov::test::TestCase(model, s_device);
6988+
// Flattened input for shape (2,3,2,2)
6989+
test_case.add_input<float>(std::vector<float>(24, 1.0f)); // Example input
6990+
test_case.add_input<int64_t>({1, 0, 2, 1, 0, 2, 1, 1}); // Labels shape (2,2,2)
6991+
test_case.add_expected_output<float>(Shape{}, {1.2f}); // Example expected value
6992+
test_case.run();
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}

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