Revise less equal

docs/ops/comparison/LessEqual_1.md

@@ -4,48 +4,50 @@
 
 **Category**: Comparison binary operation
 
-**Short description**: *LessEqual* performs element-wise comparison operation with two given tensors applying multi-directional broadcast rules.
+**Short description**: *LessEqual* performs element-wise comparison operation with two given 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 *LessEqual* 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 **boolean** and  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 *LessEqual* does the following with the input tensors *a* and *b*:
-
-\f[
-o_{i} = a_{i} <= b_{i}
-\f]
-
 **Examples**
 
-*Example 1*
+*Example 1: no broadcast*
 
 ```xml
 <layer ... type="LessEqual">
+    <data auto_broadcast="none"/>
     <input>
         <port id="0">
             <dim>256</dim>
@@ -65,9 +67,10 @@ o_{i} = a_{i} <= b_{i}
 </layer>
 ```
 
-*Example 2: broadcast*
+*Example 2: numpy broadcast*
 ```xml
 <layer ... type="LessEqual">
+    <data auto_broadcast="numpy"/>
     <input>
         <port id="0">
             <dim>8</dim>

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

@@ -0,0 +1,115 @@
+// Copyright (C) 2018-2021 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include <gtest/gtest.h>
+
+#include <ie_core.hpp>
+#include <ie_ngraph_utils.hpp>
+#include <ngraph/ngraph.hpp>
+#include <shared_test_classes/base/layer_test_utils.hpp>
+#include <tuple>
+
+#include "base_reference_test.hpp"
+
+using namespace ngraph;
+using namespace InferenceEngine;
+using namespace reference_tests;
+
+namespace {
+struct LessEqualParams {
+    template <class IT, class OT>
+    LessEqualParams(const ngraph::PartialShape& input_shape1, const ngraph::PartialShape& input_shape2 , const ngraph::element::Type& iType,
+                const ngraph::element::Type& oType, const std::vector<IT>& iValues1, const std::vector<IT>& iValues2, const std::vector<OT>& oValues)
+        : pshape1(input_shape1), pshape2(input_shape2), inType(iType), outType(oType), inputData1(CreateBlob(iType, iValues1)),
+        inputData2(CreateBlob(iType, iValues2)), refData(CreateBlob(oType, oValues)) {}
+    ngraph::PartialShape pshape1;
+    ngraph::PartialShape pshape2;
+    ngraph::element::Type inType;
+    ngraph::element::Type outType;
+    InferenceEngine::Blob::Ptr inputData1;
+    InferenceEngine::Blob::Ptr inputData2;
+    InferenceEngine::Blob::Ptr refData;
+};
+
+class ReferenceLessEqualLayerTest : public testing::TestWithParam<LessEqualParams>, public CommonReferenceTest {
+public:
+    void SetUp() override {
+        auto params = GetParam();
+        function = CreateFunction(params.pshape1, params.pshape2, params.inType, params.outType);
+        inputData = {params.inputData1, params.inputData2};
+        refOutData = {params.refData};
+    }
+    static std::string getTestCaseName(const testing::TestParamInfo<LessEqualParams>& obj) {
+        auto param = obj.param;
+        std::ostringstream result;
+        result << "inpt_shape1=" << param.pshape1 << "_";
+        result << "inpt_shape2=" << param.pshape2 << "_";
+        result << "iType=" << param.inType << "_";
+        result << "oType=" << param.outType;
+        return result.str();
+    }
+
+private:
+    static std::shared_ptr<Function> CreateFunction(const PartialShape& input_shape1, const PartialShape& input_shape2, const element::Type& input_type,
+                                                    const element::Type& expected_output_type) {
+        const auto in = std::make_shared<op::Parameter>(input_type, input_shape1);
+        const auto in2 = std::make_shared<op::Parameter>(input_type, input_shape2);
+        const auto LessEqual = std::make_shared<op::v1::LessEqual>(in, in2);
+        return std::make_shared<Function>(NodeVector {LessEqual}, ParameterVector {in, in2});
+    }
+};
+
+TEST_P(ReferenceLessEqualLayerTest, CompareWithHardcodedRefs) {
+    Exec();
+}
+
+template <element::Type_t IN_ET>
+std::vector<LessEqualParams> generateLessEqualParams(const ngraph::element::Type& type) {
+    using T = typename element_type_traits<IN_ET>::value_type;
+    std::vector<LessEqualParams> lessEqParams {
+        // 1D // 2D // 3D // 4D
+        LessEqualParams(ngraph::PartialShape {2, 2}, ngraph::PartialShape {2, 2}, type, ngraph::element::boolean,
+                std::vector<T> {0, 12, 23, 0},
+                std::vector<T> {0, 12, 23, 0},
+                std::vector<char> {1, 1, 1, 1}),
+        LessEqualParams(ngraph::PartialShape {2, 3}, ngraph::PartialShape {2, 3}, type, ngraph::element::boolean,
+                std::vector<T> {0, 6, 45, 1, 21, 21},
+                std::vector<T> {1, 18, 23, 1, 19, 21},
+                std::vector<char> {1, 1, 0, 1, 0, 1}),
+        LessEqualParams(ngraph::PartialShape {1}, ngraph::PartialShape {1},  type, ngraph::element::boolean,
+                std::vector<T> {53},
+                std::vector<T> {53},
+                std::vector<char> {1}),
+        LessEqualParams(ngraph::PartialShape {2, 4}, ngraph::PartialShape {2, 4}, type, ngraph::element::boolean,
+                std::vector<T> {0, 6, 25, 0, 11, 5, 11, 8},
+                std::vector<T> {1, 12, 23, 0, 10, 5, 13, 8},
+                std::vector<char> {1, 1, 0, 1, 0, 1, 1, 1}),
+        LessEqualParams(ngraph::PartialShape {3, 1, 2}, ngraph::PartialShape {1, 2, 1}, type, ngraph::element::boolean,
+                std::vector<T> {2, 1, 4, 1, 3, 1},
+                std::vector<T> {1, 1},
+                std::vector<char> {0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1}),
+        LessEqualParams(ngraph::PartialShape {2, 1, 2, 1}, ngraph::PartialShape {1, 2, 1}, type, ngraph::element::boolean,
+                std::vector<T> {2, 1, 4, 1},
+                std::vector<T> {1, 1},
+                std::vector<char> {0, 1, 0, 1})};
+    return lessEqParams;
+}
+
+std::vector<LessEqualParams> generateLessEqualCombinedParams() {
+    const std::vector<std::vector<LessEqualParams>> LessEqualTypeParams {generateLessEqualParams<element::Type_t::f32>(ngraph::element::f32),
+                                                                         generateLessEqualParams<element::Type_t::f16>(ngraph::element::f16),
+                                                                         generateLessEqualParams<element::Type_t::i32>(ngraph::element::i32),
+                                                                         generateLessEqualParams<element::Type_t::u32>(ngraph::element::u32),
+                                                                         generateLessEqualParams<element::Type_t::u8>(ngraph::element::boolean)};
+    std::vector<LessEqualParams> combinedParams;
+
+    for (const auto& params : LessEqualTypeParams) {
+        combinedParams.insert(combinedParams.end(), params.begin(), params.end());
+    }
+    return combinedParams;
+}
+
+INSTANTIATE_TEST_SUITE_P(smoke_LessEqual_With_Hardcoded_Refs, ReferenceLessEqualLayerTest, ::testing::ValuesIn(generateLessEqualCombinedParams()),
+                                 ReferenceLessEqualLayerTest::getTestCaseName);
+}  // namespace

inference-engine/tests/ie_test_utils/functional_test_utils/layer_tests_summary/utils/constants.py

@@ -53,6 +53,7 @@
     'HSwish-4',
     'HardSigmoid-1',
     'Interpolate-4',
+    'LessEqual-1'
     'LRN-1',
     'LSTMCell-4',
     'LSTMSequence-5',

ngraph/test/backend/comparison.in.cpp

@@ -151,70 +151,3 @@ NGRAPH_TEST(${BACKEND_NAME}, less)
     handle->call_with_validate({result}, {a, b});
     EXPECT_EQ((vector<char>{0, 0, 1, 0, 1, 0, 0, 1}), read_vector<char>(result));
 }
-
-NGRAPH_TEST(${BACKEND_NAME}, lesseq)
-{
-    Shape shape{2, 2, 2};
-    auto A = make_shared<op::Parameter>(element::f32, shape);
-    auto B = make_shared<op::Parameter>(element::f32, shape);
-    auto f = make_shared<Function>(make_shared<op::v1::LessEqual>(A, B), ParameterVector{A, B});
-
-    auto backend = runtime::Backend::create("${BACKEND_NAME}");
-
-    // Create some tensors for input/output
-    auto a = backend->create_tensor(element::f32, shape);
-    copy_data(a, vector<float>{1, 8, -8, 17, -0.5, 0, 2, 1});
-    auto b = backend->create_tensor(element::f32, shape);
-    copy_data(b, vector<float>{1, 2, -8, 8, 0, 0, 0.5, 1.5});
-    auto result = backend->create_tensor(element::boolean, shape);
-
-    auto handle = backend->compile(f);
-    handle->call_with_validate({result}, {a, b});
-    EXPECT_EQ((vector<char>{1, 0, 1, 0, 1, 1, 0, 1}), read_vector<char>(result));
-}
-
-NGRAPH_TEST(${BACKEND_NAME}, lesseq_int32)
-{
-    Shape shape{2, 2};
-    auto A = make_shared<op::Parameter>(element::i32, shape);
-    auto B = make_shared<op::Parameter>(element::i32, shape);
-    auto f = make_shared<Function>(make_shared<op::v1::LessEqual>(A, B), ParameterVector{A, B});
-
-    auto backend = runtime::Backend::create("${BACKEND_NAME}");
-
-    // Create some tensors for input/output
-    auto a = backend->create_tensor(element::i32, shape);
-    copy_data(a, vector<int32_t>{0x40000170, 0x40000005, 0x40000005, -5});
-    auto b = backend->create_tensor(element::i32, shape);
-    copy_data(b, vector<int32_t>{0x40000140, 0x40000001, 0x40000005, 0});
-    auto result = backend->create_tensor(element::boolean, shape);
-
-    auto handle = backend->compile(f);
-    handle->call_with_validate({result}, {a, b});
-    EXPECT_EQ((vector<char>{0, 0, 1, 1}), read_vector<char>(result)); // NNP result {1, 1, 0, 1}
-}
-
-NGRAPH_TEST(${BACKEND_NAME}, lesseq_bool)
-{
-    Shape shape{2, 2, 2};
-    auto A = make_shared<op::Parameter>(element::boolean, shape);
-    auto B = make_shared<op::Parameter>(element::boolean, shape);
-    auto f = make_shared<Function>(make_shared<op::v1::LessEqual>(A, B), ParameterVector{A, B});
-
-    auto backend = runtime::Backend::create("${BACKEND_NAME}");
-
-    // Create some tensors for input/output
-    auto a = backend->create_tensor(element::boolean, shape);
-    copy_data(a, vector<char>{1, 1, 1, 1, 1, 1, 1, 1});
-    auto b = backend->create_tensor(element::boolean, shape);
-    copy_data(b, vector<char>{0, 0, 0, 0, 0, 0, 0, 0});
-    auto result = backend->create_tensor(element::boolean, shape);
-
-    // Overwrite the initial result vector to make sure we're not just coincidentally getting the
-    // right value.
-    copy_data(result, vector<char>{1, 1, 1, 1, 1, 1, 1, 1});
-
-    auto handle = backend->compile(f);
-    handle->call_with_validate({result}, {a, b});
-    EXPECT_EQ((vector<char>{0, 0, 0, 0, 0, 0, 0, 0}), read_vector<char>(result));
-}

ngraph/test/runtime/ie/unit_test.manifest

@@ -426,7 +426,6 @@ notequal
 greater
 greatereq
 less
-lesseq
 sum_3d_to_scalar_int32
 sum_2d_to_scalar_int8
 max_pool_uint8
@@ -486,7 +485,6 @@ logical_xor
 logical_or
 logical_and
 gather_axis_0_bool
-lesseq_bool
 auto_bcast_binary_elementwise
 auto_bcast_binary_elementwise_pdpd
 any_2x2_to_scalar_true
@@ -755,7 +753,6 @@ strided_slice_stride_optional
 divide_int32
 divide_cpp_rounding_int32
 divide_python_rounding_int32
-lesseq_int32
 
 # Constant and Low Precision
 constant_equality_u4_2x2x3