Revise equal

docs/ops/comparison/Equal_1.md

@@ -4,48 +4,51 @@
 
 **Category**: Comparison binary operation
 
-**Short description**: *Equal* performs element-wise comparison operation with two given tensors applying multi-directional broadcast rules.
+**Short description**: *Equal* performs element-wise comparison operation with two given input tensors applying multi-directional broadcast rules specified in the *auto_broadcast* attribute.
+
+**Detailed description**
+Before performing arithmetic operation, input tensors *a* and *b* are broadcasted if their shapes are different and *auto_broadcast* attributes is not *none*. Broadcasting is performed according to *auto_broadcast* value.
+
+After broadcasting *Equal* does the following with the input tensors *a* and *b*:
+
+\f[
+o_{i} = a_{i} == b_{i}
+\f]
 
 **Attributes**:
 
 * *auto_broadcast*
 
   * **Description**: specifies rules used for auto-broadcasting of input tensors.
   * **Range of values**:
-    * *none* - no auto-broadcasting is allowed, all input shapes should match
-    * *numpy* - numpy broadcasting rules, aligned with ONNX Broadcasting. Description is available in <a href="https://github.com/onnx/onnx/blob/master/docs/Broadcasting.md">ONNX docs</a>.
+    * *none* - no auto-broadcasting is allowed, all input shapes should match,
+    * *numpy* - numpy broadcasting rules, description is available in [Broadcast Rules For Elementwise Operations](../broadcast_rules.md),
+    * *pdpd* - PaddlePaddle-style implicit broadcasting, description is available in [Broadcast Rules For Elementwise Operations](../broadcast_rules.md).
   * **Type**: string
   * **Default value**: "numpy"
   * **Required**: *no*
 
 **Inputs**
 
-* **1**: A tensor of type *T*. **Required.**
-* **2**: A tensor of type *T*. **Required.**
+* **1**: A tensor of type *T* and arbitrary shape. **Required.**
+* **2**: A tensor of type *T* and arbitrary shape. **Required.**
 
 **Outputs**
 
-* **1**: The result of element-wise comparison operation. A tensor of type boolean.
+* **1**: The result of element-wise **comparison** operation applied to the input tensors. A tensor of type *T_BOOL* and the same shape equal to broadcasted shape of two inputs.
 
 **Types**
 
 * *T*: arbitrary supported type.
-
-**Detailed description**
-Before performing arithmetic operation, input tensors *a* and *b* are broadcasted if their shapes are different and `auto_broadcast` attributes is not `none`. Broadcasting is performed according to `auto_broadcast` value.
-
-After broadcasting *Equal* does the following with the input tensors *a* and *b*:
-
-\f[
-o_{i} = a_{i} == b_{i}
-\f]
+* *T_BOOL*: `boolean`.
 
 **Examples**
 
-*Example 1*
+*Example 1: no broadcast*
 
 ```xml
 <layer ... type="Equal">
+    <data auto_broadcast="none"/>
     <input>
         <port id="0">
             <dim>256</dim>
@@ -65,9 +68,10 @@ o_{i} = a_{i} == b_{i}
 </layer>
 ```
 
-*Example 2: broadcast*
+*Example 2: numpy broadcast*
 ```xml
 <layer ... type="Equal">
+    <data auto_broadcast="numpy"/>
     <input>
         <port id="0">
             <dim>8</dim>

docs/template_plugin/tests/functional/op_reference/equal.cpp

@@ -75,6 +75,48 @@ std::vector<RefComparisonParams> generateComparisonCombinedParams() {
 
 INSTANTIATE_TEST_SUITE_P(smoke_Comparison_With_Hardcoded_Refs, ReferenceComparisonLayerTest, ::testing::ValuesIn(generateComparisonCombinedParams()),
                          ReferenceComparisonLayerTest::getTestCaseName);
+
+template <element::Type_t IN_ET>
+std::vector<RefComparisonParams> generateNumericParams(const element::Type& type) {
+    using T = typename element_type_traits<IN_ET>::value_type;
+    std::vector<RefComparisonParams> compParams {
+        Builder {}
+            .compType(ComparisonTypes::EQUAL)
+            .input1({{4}, type, std::vector<T> {-2.5f, 25.5f, 2.25f, NAN}})
+            .input2({{4}, type, std::vector<T> {10.0f, 5.0f, 2.25f, 10.0f}})
+            .expected({{4}, element::boolean, std::vector<char> {0, 0, 1, 0, }}),
+        Builder {}
+            .compType(ComparisonTypes::EQUAL)
+            .input1({{2, 3}, type, std::vector<T> {0.0f, NAN, NAN, 1.0f, 21.0f, -INFINITY}})
+            .input2({{2, 3}, type, std::vector<T> {1.0f, NAN, 23.0f, 1.0f, 19.0f, 21.0f}})
+            .expected({{2, 3}, element::boolean, std::vector<char> {0, 0, 0, 1, 0, 0}}),
+        Builder {}
+            .compType(ComparisonTypes::EQUAL)
+            .input1({{1}, type, std::vector<T> {INFINITY}})
+            .input2({{1}, type, std::vector<T> {INFINITY}})
+            .expected({{1}, element::boolean, std::vector<char> {1}}),
+        Builder {}
+            .compType(ComparisonTypes::EQUAL)
+            .input1({{5}, type, std::vector<T> {-2.5f, 25.5f, 2.25f, INFINITY, 6.0f}})
+            .input2({{5}, type, std::vector<T> {10.0f, 5.0f, 2.25f, 10.0f, -INFINITY}})
+            .expected({{5}, element::boolean, std::vector<char> {0, 0, 1, 0, 0}})};
+    return compParams;
+}
+
+std::vector<RefComparisonParams> generateNumericCombinedParams() {
+    const std::vector<std::vector<RefComparisonParams>> compTypeParams {
+        generateNumericParams<element::Type_t::f16>(element::f16),
+        generateNumericParams<element::Type_t::f32>(element::f32)};
+    std::vector<RefComparisonParams> combinedParams;
+
+    for (const auto& params : compTypeParams) {
+        combinedParams.insert(combinedParams.end(), params.begin(), params.end());
+    }
+    return combinedParams;
+}
+
+INSTANTIATE_TEST_SUITE_P(smoke_Numeric_With_Hardcoded_Refs, ReferenceComparisonLayerTest, ::testing::ValuesIn(generateNumericCombinedParams()),
+                         ReferenceComparisonLayerTest::getTestCaseName);
 } // namespace
 } // namespace ComparisonOpsRefTestDefinitions
 } // namespace reference_tests

inference-engine/tests/functional/inference_engine/serialization/single_layer/comparison_ops.hpp

@@ -0,0 +1,16 @@
+// Copyright (C) 2018-2021 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "shared_test_classes/single_layer/comparison.hpp"
+
+struct ComparisionOpsData {
+    const std::map<std::vector<size_t>, std::vector<std::vector<size_t>>> inputShapes;
+    const std::vector<InferenceEngine::Precision> inputsPrecisions;
+    const std::vector<ngraph::helpers::InputLayerType> secondInputTypes;
+    const std::map<std::string, std::string> additional_config;
+    const ngraph::helpers::ComparisonTypes opType;
+    const InferenceEngine::Precision ieInputPrecision;
+    const InferenceEngine::Precision ieOutputPrecision;
+    const std::string deviceName;
+};

inference-engine/tests/functional/inference_engine/serialization/single_layer/equal.cpp

@@ -0,0 +1,63 @@
+// Copyright (C) 2018-2021 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "comparison_ops.hpp"
+
+using namespace LayerTestsDefinitions;
+using namespace LayerTestsDefinitions::ComparisonParams;
+
+namespace {
+TEST_P(ComparisonLayerTest, Serialize) {
+        Serialize();
+    }
+
+ComparisionOpsData data = {
+    // inputsShape
+    {
+        {{1}, {{1}, {17}, {1, 1}, {2, 18}, {1, 1, 2}, {2, 2, 3}, {1, 1, 2, 3}}},
+        {{5}, {{1}, {1, 1}, {2, 5}, {1, 1, 1}, {2, 2, 5}}},
+        {{2, 200}, {{1}, {200}, {1, 200}, {2, 200}, {2, 2, 200}}},
+        {{1, 3, 20}, {{20}, {2, 1, 1}}},
+        {{2, 17, 3, 4}, {{4}, {1, 3, 4}, {2, 1, 3, 4}}},
+        {{2, 17, 3, 4}, {{4}, {1, 3, 4}, {141, 1, 3, 4}}},
+        {{2, 1, 1, 3, 1}, {{1}, {1, 3, 4}, {2, 1, 3, 4}, {1, 1, 1, 1, 1}}},
+    },
+    // inputsPrecisions
+    {
+        InferenceEngine::Precision::FP64,
+        InferenceEngine::Precision::FP32,
+        InferenceEngine::Precision::FP16,
+        InferenceEngine::Precision::I32,
+        InferenceEngine::Precision::U32,
+        InferenceEngine::Precision::BOOL,
+    },
+    // secondIinputsType
+    {
+        ngraph::helpers::InputLayerType::CONSTANT,
+        ngraph::helpers::InputLayerType::PARAMETER,
+    },
+    // additionalConfig
+    {},
+    // opType
+    ngraph::helpers::ComparisonTypes::EQUAL,
+    // ieInputPrecision
+    InferenceEngine::Precision::UNSPECIFIED,
+    // ieOutputPrecision
+    InferenceEngine::Precision::UNSPECIFIED,
+    // deviceName
+    CommonTestUtils::DEVICE_CPU,
+};
+
+const auto SerializeEqualTestParams = ::testing::Combine(
+    ::testing::ValuesIn(CommonTestUtils::combineParams(data.inputShapes)),
+    ::testing::ValuesIn(data.inputsPrecisions),
+    ::testing::Values(data.opType),
+    ::testing::ValuesIn(data.secondInputTypes),
+    ::testing::Values(data.ieInputPrecision),
+    ::testing::Values(data.ieOutputPrecision),
+    ::testing::Values(data.deviceName),
+    ::testing::Values(data.additional_config));
+
+INSTANTIATE_TEST_SUITE_P(smoke_CompareWithRefs, ComparisonLayerTest, SerializeEqualTestParams, ComparisonLayerTest::getTestCaseName);
+} // namespace

inference-engine/tests/functional/inference_engine/serialization/single_layer/greater.cpp

@@ -0,0 +1,63 @@
+// Copyright (C) 2018-2021 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "comparison_ops.hpp"
+
+using namespace LayerTestsDefinitions;
+using namespace LayerTestsDefinitions::ComparisonParams;
+
+namespace {
+TEST_P(ComparisonLayerTest, Serialize) {
+        Serialize();
+    }
+
+ComparisionOpsData data = {
+    // inputsShape
+    {
+        {{1}, {{1}, {17}, {1, 1}, {2, 18}, {1, 1, 2}, {2, 2, 3}, {1, 1, 2, 3}}},
+        {{5}, {{1}, {1, 1}, {2, 5}, {1, 1, 1}, {2, 2, 5}}},
+        {{2, 200}, {{1}, {200}, {1, 200}, {2, 200}, {2, 2, 200}}},
+        {{1, 3, 20}, {{20}, {2, 1, 1}}},
+        {{2, 17, 3, 4}, {{4}, {1, 3, 4}, {2, 1, 3, 4}}},
+        {{2, 17, 3, 4}, {{4}, {1, 3, 4}, {141, 1, 3, 4}}},
+        {{2, 1, 1, 3, 1}, {{1}, {1, 3, 4}, {2, 1, 3, 4}, {1, 1, 1, 1, 1}}},
+    },
+    // inputsPrecisions
+    {
+        InferenceEngine::Precision::FP64,
+        InferenceEngine::Precision::FP32,
+        InferenceEngine::Precision::FP16,
+        InferenceEngine::Precision::I32,
+        InferenceEngine::Precision::U32,
+        InferenceEngine::Precision::BOOL,
+    },
+    // secondIinputsType
+    {
+        ngraph::helpers::InputLayerType::CONSTANT,
+        ngraph::helpers::InputLayerType::PARAMETER,
+    },
+    // additionalConfig
+    {},
+    // opType
+    ngraph::helpers::ComparisonTypes::GREATER,
+    // ieInputPrecision
+    InferenceEngine::Precision::UNSPECIFIED,
+    // ieOutputPrecision
+    InferenceEngine::Precision::UNSPECIFIED,
+    // deviceName
+    CommonTestUtils::DEVICE_CPU,
+};
+
+const auto SerializeGreaterTestParams = ::testing::Combine(
+    ::testing::ValuesIn(CommonTestUtils::combineParams(data.inputShapes)),
+    ::testing::ValuesIn(data.inputsPrecisions),
+    ::testing::Values(data.opType),
+    ::testing::ValuesIn(data.secondInputTypes),
+    ::testing::Values(data.ieInputPrecision),
+    ::testing::Values(data.ieOutputPrecision),
+    ::testing::Values(data.deviceName),
+    ::testing::Values(data.additional_config));
+
+INSTANTIATE_TEST_SUITE_P(smoke_CompareWithRefs, ComparisonLayerTest, SerializeGreaterTestParams, ComparisonLayerTest::getTestCaseName);
+} // namespace

inference-engine/tests/functional/inference_engine/serialization/single_layer/greater_eq.cpp

@@ -0,0 +1,63 @@
+// Copyright (C) 2018-2021 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "comparison_ops.hpp"
+
+using namespace LayerTestsDefinitions;
+using namespace LayerTestsDefinitions::ComparisonParams;
+
+namespace {
+TEST_P(ComparisonLayerTest, Serialize) {
+        Serialize();
+    }
+
+ComparisionOpsData data = {
+    // inputsShape
+    {
+        {{1}, {{1}, {17}, {1, 1}, {2, 18}, {1, 1, 2}, {2, 2, 3}, {1, 1, 2, 3}}},
+        {{5}, {{1}, {1, 1}, {2, 5}, {1, 1, 1}, {2, 2, 5}}},
+        {{2, 200}, {{1}, {200}, {1, 200}, {2, 200}, {2, 2, 200}}},
+        {{1, 3, 20}, {{20}, {2, 1, 1}}},
+        {{2, 17, 3, 4}, {{4}, {1, 3, 4}, {2, 1, 3, 4}}},
+        {{2, 17, 3, 4}, {{4}, {1, 3, 4}, {141, 1, 3, 4}}},
+        {{2, 1, 1, 3, 1}, {{1}, {1, 3, 4}, {2, 1, 3, 4}, {1, 1, 1, 1, 1}}},
+    },
+    // inputsPrecisions
+    {
+        InferenceEngine::Precision::FP64,
+        InferenceEngine::Precision::FP32,
+        InferenceEngine::Precision::FP16,
+        InferenceEngine::Precision::I32,
+        InferenceEngine::Precision::U32,
+        InferenceEngine::Precision::BOOL,
+    },
+    // secondIinputsType
+    {
+        ngraph::helpers::InputLayerType::CONSTANT,
+        ngraph::helpers::InputLayerType::PARAMETER,
+    },
+    // additionalConfig
+    {},
+    // opType
+    ngraph::helpers::ComparisonTypes::GREATER_EQUAL,
+    // ieInputPrecision
+    InferenceEngine::Precision::UNSPECIFIED,
+    // ieOutputPrecision
+    InferenceEngine::Precision::UNSPECIFIED,
+    // deviceName
+    CommonTestUtils::DEVICE_CPU,
+};
+
+const auto SerializeGreaterEqualTestParams = ::testing::Combine(
+    ::testing::ValuesIn(CommonTestUtils::combineParams(data.inputShapes)),
+    ::testing::ValuesIn(data.inputsPrecisions),
+    ::testing::Values(data.opType),
+    ::testing::ValuesIn(data.secondInputTypes),
+    ::testing::Values(data.ieInputPrecision),
+    ::testing::Values(data.ieOutputPrecision),
+    ::testing::Values(data.deviceName),
+    ::testing::Values(data.additional_config));
+
+INSTANTIATE_TEST_SUITE_P(smoke_CompareWithRefs, ComparisonLayerTest, SerializeGreaterEqualTestParams, ComparisonLayerTest::getTestCaseName);
+} // namespace