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.
openvinotoolkit · Feb 12, 2025 · bdedc9e · bdedc9e
1 parent 187fed8
commit bdedc9e
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diff --git a/src/frontends/onnx/frontend/src/op/softmax_crossentropy_loss.cpp b/src/frontends/onnx/frontend/src/op/softmax_crossentropy_loss.cpp
@@ -19,7 +19,7 @@ namespace ov {
 namespace frontend {
 namespace onnx {
 namespace {
-OutputVector impl_softmax_cross_entropy(const Node& node, int64_t axis_default) {
+OutputVector onnx_softmax_crossentropy_loss(const Node& node, int64_t axis_default) {
     const auto inputs = node.get_ov_inputs();
 
     const auto scores = inputs[0];
@@ -96,15 +96,16 @@ OutputVector impl_softmax_cross_entropy(const Node& node, int64_t axis_default)
 namespace ai_onnx {
 namespace opset_12 {
 OutputVector softmax_cross_entropy_loss(const Node& node) {
-    return impl_softmax_cross_entropy(node, 1);
+    return onnx_softmax_crossentropy_loss(node, 1);
 }
 ONNX_OP("SoftmaxCrossEntropyLoss", OPSET_IN(12), ai_onnx::opset_12::softmax_cross_entropy_loss);
 }  // namespace opset_12
 namespace opset_13 {
 OutputVector softmax_cross_entropy_loss(const Node& node) {
-    return impl_softmax_cross_entropy(node, 1);
+    // only difference is that opset_13 supports bfloat16 datatype
+    return onnx_softmax_crossentropy_loss(node, 1);
 }
-ONNX_OP("SoftmaxCrossEntropyLoss", OPSET_IN(13), ai_onnx::opset_13::softmax_cross_entropy_loss);
+ONNX_OP("SoftmaxCrossEntropyLoss", OPSET_SINCE(13), ai_onnx::opset_13::softmax_cross_entropy_loss);
 }  // namespace opset_13
 }  // namespace ai_onnx
 }  // namespace onnx

diff --git a/src/frontends/onnx/tests/models/softmax_crossentropy_loss_higher_dim.prototxt b/src/frontends/onnx/tests/models/softmax_crossentropy_loss_higher_dim.prototxt
@@ -0,0 +1,55 @@
+ir_version: 7
+producer_name: "OpenVINO ONNX Frontend"
+graph {
+  node {
+    input: "x"
+    input: "y"
+    output: "z"
+    op_type: "SoftmaxCrossEntropyLoss"
+    attribute {
+      name: "reduction"
+      s: "mean"
+      type: STRING
+    }
+  }
+  name: "test_sce_higher_dim"
+  input {
+    name: "x"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim { dim_value: 2 }
+          dim { dim_value: 3 }
+          dim { dim_value: 2 }
+          dim { dim_value: 2 }
+        }
+      }
+    }
+  }
+  input {
+    name: "y"
+    type {
+      tensor_type {
+        elem_type: 7
+        shape {
+          dim { dim_value: 2 }
+          dim { dim_value: 2 }
+          dim { dim_value: 2 }
+        }
+      }
+    }
+  }
+  output {
+    name: "z"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {}
+      }
+    }
+  }
+}
+opset_import {
+  version: 13
+}
diff --git a/src/frontends/onnx/tests/models/softmax_crossentropy_loss_mean_weight_ii.prototxt b/src/frontends/onnx/tests/models/softmax_crossentropy_loss_mean_weight_ii.prototxt
@@ -0,0 +1,70 @@
+ir_version: 7
+producer_name: "OpenVINO ONNX Frontend"
+graph {
+  node {
+    input: "x"
+    input: "y"
+    input: "w"
+    output: "z"
+    op_type: "SoftmaxCrossEntropyLoss"
+    attribute {
+      name: "reduction"
+      s: "mean"
+      type: STRING
+    }
+    attribute {
+      name: "ignore_index"
+      i: -1
+      type: INT
+    }
+  }
+  name: "test_sce_mean_weight_ii"
+  input {
+    name: "x"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim { dim_value: 2 }
+          dim { dim_value: 3 }
+          dim { dim_value: 2 }
+        }
+      }
+    }
+  }
+  input {
+    name: "y"
+    type {
+      tensor_type {
+        elem_type: 7
+        shape {
+          dim { dim_value: 2 }
+          dim { dim_value: 2 }
+        }
+      }
+    }
+  }
+  input {
+    name: "w"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim { dim_value: 3 }
+        }
+      }
+    }
+  }
+  output {
+    name: "z"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {}
+      }
+    }
+  }
+}
+opset_import {
+  version: 13
+}
diff --git a/src/frontends/onnx/tests/models/softmax_crossentropy_loss_none.prototxt b/src/frontends/onnx/tests/models/softmax_crossentropy_loss_none.prototxt
@@ -0,0 +1,53 @@
+ir_version: 7
+producer_name: "OpenVINO ONNX Frontend"
+graph {
+  node {
+    input: "x"
+    input: "y"
+    output: "z"
+    op_type: "SoftmaxCrossEntropyLoss"
+    attribute {
+      name: "reduction"
+      s: "none"
+      type: STRING
+    }
+  }
+  name: "test_sce_none"
+  input {
+    name: "x"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim { dim_value: 2 }
+          dim { dim_value: 3 }
+        }
+      }
+    }
+  }
+  input {
+    name: "y"
+    type {
+      tensor_type {
+        elem_type: 7
+        shape {
+          dim { dim_value: 2 }
+        }
+      }
+    }
+  }
+  output {
+    name: "z"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim { dim_value: 2 }
+        }
+      }
+    }
+  }
+}
+opset_import {
+  version: 13
+}
diff --git a/src/frontends/onnx/tests/models/softmax_crossentropy_loss_sum.prototxt b/src/frontends/onnx/tests/models/softmax_crossentropy_loss_sum.prototxt
@@ -0,0 +1,51 @@
+ir_version: 7
+producer_name: "OpenVINO ONNX Frontend"
+graph {
+  node {
+    input: "x"
+    input: "y"
+    output: "z"
+    op_type: "SoftmaxCrossEntropyLoss"
+    attribute {
+      name: "reduction"
+      s: "sum"
+      type: STRING
+    }
+  }
+  name: "test_sce_sum"
+  input {
+    name: "x"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim { dim_value: 2 }
+          dim { dim_value: 3 }
+        }
+      }
+    }
+  }
+  input {
+    name: "y"
+    type {
+      tensor_type {
+        elem_type: 7
+        shape {
+          dim { dim_value: 2 }
+        }
+      }
+    }
+  }
+  output {
+    name: "z"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {}
+      }
+    }
+  }
+}
+opset_import {
+  version: 13
+}
diff --git a/src/frontends/onnx/tests/onnx_import.in.cpp b/src/frontends/onnx/tests/onnx_import.in.cpp
@@ -6945,3 +6945,49 @@ OPENVINO_TEST(${BACKEND_NAME}, onnx_float8e4m3fn_constant) {
 
     test_case.run();
 }
+
+OPENVINO_TEST(${BACKEND_NAME}, onnx_model_softmax_crossentropy_loss_mean_weight_ii) {
+    auto model = convert_model("softmax_crossentropy_loss_mean_weight_ii.onnx");
+
+    auto test_case = ov::test::TestCase(model, s_device);
+    // Input x: shape (2,3,2)
+    test_case.add_input<float>({1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f, 8.f, 9.f, 10.f, 11.f, 12.f});
+    // Labels with ignore_index -1
+    test_case.add_input<int64_t>({0, -1, 2, 1});
+    // Weights
+    test_case.add_input<float>({0.5f, 1.0f, 2.0f});
+    // Expected output
+    test_case.add_expected_output<float>(Shape{}, {1.28642857f});
+    test_case.run();
+}
+
+OPENVINO_TEST(${BACKEND_NAME}, onnx_model_softmax_crossentropy_loss_sum) {
+    auto model = convert_model("softmax_crossentropy_loss_sum.onnx");
+
+    auto test_case = ov::test::TestCase(model, s_device);
+    test_case.add_input<float>({0.5f, 1.5f, 2.5f, 3.5f, 4.5f, 5.5f});
+    test_case.add_input<int64_t>({1, 2});
+    test_case.add_expected_output<float>(Shape{}, {1.8137f});
+    test_case.run();
+}
+
+OPENVINO_TEST(${BACKEND_NAME}, onnx_model_softmax_crossentropy_loss_none) {
+    auto model = convert_model("softmax_crossentropy_loss_none.onnx");
+
+    auto test_case = ov::test::TestCase(model, s_device);
+    test_case.add_input<float>({1.f, 2.f, 3.f, 4.f, 5.f, 6.f});
+    test_case.add_input<int64_t>({2, 1});
+    test_case.add_expected_output<float>(Shape{2}, {0.407f, 1.4067f});
+    test_case.run();
+}
+
+OPENVINO_TEST(${BACKEND_NAME}, onnx_model_softmax_crossentropy_loss_higher_dim) {
+    auto model = convert_model("softmax_crossentropy_loss_higher_dim.onnx");
+
+    auto test_case = ov::test::TestCase(model, s_device);
+    // Flattened input for shape (2,3,2,2)
+    test_case.add_input<float>(std::vector<float>(24, 1.0f));  // Example input
+    test_case.add_input<int64_t>({1, 0, 2, 1, 0, 2, 1, 1});    // Labels shape (2,2,2)
+    test_case.add_expected_output<float>(Shape{}, {1.2f});     // Example expected value
+    test_case.run();
+}