Use LogSoftmax-5 in the onnx_importer (#2602)

ngraph/test/models/onnx/logsoftmax13_1D.prototxt

@@ -0,0 +1,39 @@
+ir_version: 7
+producer_name: "nGraph ONNX Importer"
+graph {
+  node {
+    input: "data"
+    output: "y"
+    op_type: "LogSoftmax"
+  }
+  name: "LogSoftmax test"
+  input {
+    name: "data"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+            dim_value: 3
+          }
+        }
+      }
+    }
+  }
+  output {
+    name: "y"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+            dim_value: 3
+          }
+        }
+      }
+    }
+  }
+}
+opset_import {
+  version: 13
+}

ngraph/test/models/onnx/logsoftmax13_2D.prototxt

@@ -0,0 +1,45 @@
+ir_version: 3
+producer_name: "nGraph ONNX Importer"
+graph {
+  node {
+    input: "x"
+    output: "y"
+    op_type: "LogSoftmax"
+  }
+  name: "LogSoftmax test"
+  input {
+    name: "x"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+            dim_value: 2
+          }
+          dim {
+            dim_value: 4
+          }
+        }
+      }
+    }
+  }
+  output {
+    name: "y"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+            dim_value: 2
+          }
+          dim {
+            dim_value: 4
+          }
+        }
+      }
+    }
+  }
+}
+opset_import {
+  version: 13
+}

ngraph/test/models/onnx/logsoftmax_0D.prototxt

@@ -0,0 +1,37 @@
+ir_version: 7
+producer_name: "nGraph ONNX Importer"
+graph {
+  node {
+    input: "data"
+    output: "y"
+    op_type: "LogSoftmax"
+  }
+  name: "LogSoftmax test"
+  input {
+    name: "data"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+          }
+        }
+      }
+    }
+  }
+  output {
+    name: "y"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+          }
+        }
+      }
+    }
+  }
+}
+opset_import {
+  version: 1
+}

ngraph/test/models/onnx/logsoftmax_1D.prototxt

@@ -0,0 +1,44 @@
+ir_version: 7
+producer_name: "nGraph ONNX Importer"
+graph {
+  node {
+    input: "data"
+    output: "y"
+    op_type: "LogSoftmax"
+    attribute {
+      name: "axis"
+      i: 0
+      type: INT
+    }
+  }
+  name: "LogSoftmax test"
+  input {
+    name: "data"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+            dim_value: 3
+          }
+        }
+      }
+    }
+  }
+  output {
+    name: "y"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+            dim_value: 3
+          }
+        }
+      }
+    }
+  }
+}
+opset_import {
+  version: 1
+}

ngraph/test/onnx/onnx_import.in.cpp

@@ -2719,3 +2719,55 @@ NGRAPH_TEST(${BACKEND_NAME}, onnx_group_norm)
     test_case.add_expected_output<float>(shape, output);
     test_case.run();
 }
+
+NGRAPH_TEST(${BACKEND_NAME}, onnx_model_logsoftmax_0D)
+{
+    auto function = onnx_import::import_onnx_model(
+        file_util::path_join(SERIALIZED_ZOO, "onnx/softmax_0D.prototxt"));
+
+    auto test_case = test::TestCase<TestEngine>(function);
+    test_case.add_input<float>({3.141592});
+    test_case.add_expected_output<float>({0.0});
+    test_case.run();
+}
+
+NGRAPH_TEST(${BACKEND_NAME}, onnx_model_logsoftmax_1D)
+{
+    const auto function = onnx_import::import_onnx_model(
+        file_util::path_join(SERIALIZED_ZOO, "onnx/logsoftmax_1D.prototxt"));
+    auto test_case = test::TestCase<TestEngine>(function);
+
+    test_case.add_input<float>({-1.0f, 0.0f, 1.0f});
+    test_case.add_expected_output<float>(Shape{3}, {-2.4076061, -1.407606, -0.407606});
+    test_case.run();
+}
+
+NGRAPH_TEST(${BACKEND_NAME}, onnx_model_logsoftmax13_1D)
+{
+    const auto function = onnx_import::import_onnx_model(
+        file_util::path_join(SERIALIZED_ZOO, "onnx/logsoftmax13_1D.prototxt"));
+    auto test_case = test::TestCase<TestEngine>(function);
+
+    test_case.add_input<float>({-1.0f, 0.0f, 1.0f});
+    test_case.add_expected_output<float>(Shape{3}, {-2.4076061, -1.407606, -0.407606});
+    test_case.run();
+}
+
+NGRAPH_TEST(${BACKEND_NAME}, onnx_model_logsoftmax13_2D)
+{
+    const auto function = onnx_import::import_onnx_model(
+        file_util::path_join(SERIALIZED_ZOO, "onnx/logsoftmax13_2D.prototxt"));
+    auto test_case = test::TestCase<TestEngine>(function);
+
+    test_case.add_input<float>({0.0f, 1.0f, 2.0f, 3.0f, 10000, 10001, 10002, 10003});
+    test_case.add_expected_output<float>(Shape{2, 4},
+                                         {-3.4401896,
+                                          -2.4401896,
+                                          -1.4401896,
+                                          -0.44018966,
+                                          -3.4401896,
+                                          -2.4401896,
+                                          -1.4401896,
+                                          -0.44018966});
+    test_case.run_with_tolerance_as_fp();
+}

ngraph/test/runtime/ie/unit_test.manifest

@@ -69,6 +69,7 @@ bool_const_op
 onnx_model_tile
 onnx_model_tile_static
 onnx_model_softmax_0D
+onnx_model_logsoftmax_0D
 builder_opset1_collapse_none
 
 # nGraph function's output number 0 was not found in the CNNNetwork built from it.

ngraph/test/runtime/interpreter/unit_test.manifest

@@ -141,3 +141,7 @@ lstm_cell_bias_peepholes_clip_input_forget
 
 # unsupported element type f16 
 INTERPRETER.ctc_greedy_decoder_f16
+
+# LogSoftmax's reference implementation doesn't handle scalar input properly
+onnx_model_logsoftmax_0D
+