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-rw-r--r--src/armnnOnnxParser/test/Pooling.cpp310
1 files changed, 310 insertions, 0 deletions
diff --git a/src/armnnOnnxParser/test/Pooling.cpp b/src/armnnOnnxParser/test/Pooling.cpp
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+++ b/src/armnnOnnxParser/test/Pooling.cpp
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+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// See LICENSE file in the project root for full license information.
+//
+
+#include <boost/test/unit_test.hpp>
+#include "armnnOnnxParser/IOnnxParser.hpp"
+#include "ParserPrototxtFixture.hpp"
+
+BOOST_AUTO_TEST_SUITE(OnnxParser)
+
+struct PoolingMainFixture : public armnnUtils::ParserPrototxtFixture<armnnOnnxParser::IOnnxParser>
+{
+ PoolingMainFixture(const std::string& dataType, const std::string& op)
+ {
+ m_Prototext = R"(
+ ir_version: 3
+ producer_name: "CNTK"
+ producer_version: "2.5.1"
+ domain: "ai.cntk"
+ model_version: 1
+ graph {
+ name: "CNTKGraph"
+ input {
+ name: "Input"
+ type {
+ tensor_type {
+ elem_type: )" + dataType + R"(
+ shape {
+ dim {
+ dim_value: 1
+ }
+ dim {
+ dim_value: 1
+ }
+ dim {
+ dim_value: 2
+ }
+ dim {
+ dim_value: 2
+ }
+ }
+ }
+ }
+ }
+ node {
+ input: "Input"
+ output: "Output"
+ name: "Pooling"
+ op_type: )" + op + R"(
+ attribute {
+ name: "kernel_shape"
+ ints: 2
+ ints: 2
+ type: INTS
+ }
+ attribute {
+ name: "strides"
+ ints: 1
+ ints: 1
+ type: INTS
+ }
+ attribute {
+ name: "pads"
+ ints: 0
+ ints: 0
+ ints: 0
+ ints: 0
+ type: INTS
+ }
+ }
+ output {
+ name: "Output"
+ type {
+ tensor_type {
+ elem_type: FLOAT
+ shape {
+ dim {
+ dim_value: 1
+ }
+ dim {
+ dim_value: 1
+ }
+ dim {
+ dim_value: 1
+ }
+ dim {
+ dim_value: 1
+ }
+ }
+ }
+ }
+ }
+ }
+ opset_import {
+ version: 7
+ })";
+ }
+};
+
+struct MaxPoolValidFixture : PoolingMainFixture
+{
+ MaxPoolValidFixture() : PoolingMainFixture("FLOAT", "\"MaxPool\"") {
+ Setup();
+ }
+};
+
+struct MaxPoolInvalidFixture : PoolingMainFixture
+{
+ MaxPoolInvalidFixture() : PoolingMainFixture("FLOAT16", "\"MaxPool\"") { }
+};
+
+BOOST_FIXTURE_TEST_CASE(ValidMaxPoolTest, MaxPoolValidFixture)
+{
+ RunTest<4>({{"Input", {1.0f, 2.0f, 3.0f, -4.0f}}}, {{"Output", {3.0f}}});
+}
+
+struct AvgPoolValidFixture : PoolingMainFixture
+{
+ AvgPoolValidFixture() : PoolingMainFixture("FLOAT", "\"AveragePool\"") {
+ Setup();
+ }
+};
+
+struct PoolingWithPadFixture : public armnnUtils::ParserPrototxtFixture<armnnOnnxParser::IOnnxParser>
+{
+ PoolingWithPadFixture()
+ {
+ m_Prototext = R"(
+ ir_version: 3
+ producer_name: "CNTK"
+ producer_version: "2.5.1"
+ domain: "ai.cntk"
+ model_version: 1
+ graph {
+ name: "CNTKGraph"
+ input {
+ name: "Input"
+ type {
+ tensor_type {
+ elem_type: FLOAT
+ shape {
+ dim {
+ dim_value: 1
+ }
+ dim {
+ dim_value: 1
+ }
+ dim {
+ dim_value: 2
+ }
+ dim {
+ dim_value: 2
+ }
+ }
+ }
+ }
+ }
+ node {
+ input: "Input"
+ output: "Output"
+ name: "Pooling"
+ op_type: "AveragePool"
+ attribute {
+ name: "kernel_shape"
+ ints: 4
+ ints: 4
+ type: INTS
+ }
+ attribute {
+ name: "strides"
+ ints: 1
+ ints: 1
+ type: INTS
+ }
+ attribute {
+ name: "pads"
+ ints: 1
+ ints: 1
+ ints: 1
+ ints: 1
+ type: INTS
+ }
+ attribute {
+ name: "count_include_pad"
+ i: 1
+ type: INT
+ }
+ }
+ output {
+ name: "Output"
+ type {
+ tensor_type {
+ elem_type: FLOAT
+ shape {
+ dim {
+ dim_value: 1
+ }
+ dim {
+ dim_value: 1
+ }
+ dim {
+ dim_value: 1
+ }
+ dim {
+ dim_value: 1
+ }
+ }
+ }
+ }
+ }
+ }
+ opset_import {
+ version: 7
+ })";
+ Setup();
+ }
+};
+
+BOOST_FIXTURE_TEST_CASE(AveragePoolValid, AvgPoolValidFixture)
+{
+ RunTest<4>({{"Input", {1.0f, 2.0f, 3.0f, -4.0f}}}, {{"Output", {0.5}}});
+}
+
+BOOST_FIXTURE_TEST_CASE(ValidAvgWithPadTest, PoolingWithPadFixture)
+{
+ RunTest<4>({{"Input", {1.0f, 2.0f, 3.0f, -4.0f}}}, {{"Output", {1.0/8.0}}});
+}
+
+struct GlobalAvgFixture : public armnnUtils::ParserPrototxtFixture<armnnOnnxParser::IOnnxParser>
+{
+ GlobalAvgFixture()
+ {
+ m_Prototext = R"(
+ ir_version: 3
+ producer_name: "CNTK"
+ producer_version: "2.5.1"
+ domain: "ai.cntk"
+ model_version: 1
+ graph {
+ name: "CNTKGraph"
+ input {
+ name: "Input"
+ type {
+ tensor_type {
+ elem_type: FLOAT
+ shape {
+ dim {
+ dim_value: 1
+ }
+ dim {
+ dim_value: 2
+ }
+ dim {
+ dim_value: 2
+ }
+ dim {
+ dim_value: 2
+ }
+ }
+ }
+ }
+ }
+ node {
+ input: "Input"
+ output: "Output"
+ name: "Pooling"
+ op_type: "GlobalAveragePool"
+ }
+ output {
+ name: "Output"
+ type {
+ tensor_type {
+ elem_type: FLOAT
+ shape {
+ dim {
+ dim_value: 1
+ }
+ dim {
+ dim_value: 2
+ }
+ dim {
+ dim_value: 1
+ }
+ dim {
+ dim_value: 1
+ }
+ }
+ }
+ }
+ }
+ }
+ opset_import {
+ version: 7
+ })";
+ Setup();
+ }
+};
+
+BOOST_FIXTURE_TEST_CASE(GlobalAvgTest, GlobalAvgFixture)
+{
+ RunTest<4>({{"Input", {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0}}}, {{"Output", {10/4.0, 26/4.0}}});
+}
+
+BOOST_FIXTURE_TEST_CASE(IncorrectDataTypeMaxPool, MaxPoolInvalidFixture)
+{
+ BOOST_CHECK_THROW(Setup(), armnn::ParseException);
+}
+
+BOOST_AUTO_TEST_SUITE_END()