Release 18.08
diff --git a/src/armnnOnnxParser/test/Conv2D.cpp b/src/armnnOnnxParser/test/Conv2D.cpp
new file mode 100644
index 0000000..11a5d1e
--- /dev/null
+++ b/src/armnnOnnxParser/test/Conv2D.cpp
@@ -0,0 +1,469 @@
+//
+// 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 SimpleConv2DFixture : public armnnUtils::ParserPrototxtFixture<armnnOnnxParser::IOnnxParser>
+{
+ SimpleConv2DFixture()
+ {
+ 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: 3
+ }
+ dim {
+ dim_value: 3
+ }
+ }
+ }
+ }
+ }
+ input {
+ name: "Weight"
+ type {
+ tensor_type {
+ elem_type: FLOAT
+ shape {
+ dim {
+ dim_value: 1
+ }
+ dim {
+ dim_value: 1
+ }
+ dim {
+ dim_value: 3
+ }
+ dim {
+ dim_value: 3
+ }
+ }
+ }
+ }
+ }
+ initializer {
+ dims: 1
+ dims: 1
+ dims: 3
+ dims: 3
+ data_type: FLOAT
+ float_data: 2
+ float_data: 1
+ float_data: 0
+ float_data: 6
+ float_data: 2
+ float_data: 1
+ float_data: 4
+ float_data: 1
+ float_data: 2
+ name: "Weight"
+ }
+ node {
+ input: "Input"
+ input: "Weight"
+ output: "Output"
+ name: "Convolution"
+ op_type: "Conv"
+ attribute {
+ name: "kernel_shape"
+ ints: 3
+ ints: 3
+ type: INTS
+ }
+ attribute {
+ name: "strides"
+ ints: 1
+ ints: 1
+ type: INTS
+ }
+ attribute {
+ name: "auto_pad"
+ s: "VALID"
+ type: STRING
+ }
+ attribute {
+ name: "group"
+ i: 1
+ type: INT
+ }
+ attribute {
+ name: "dilations"
+ ints: 1
+ ints: 1
+ type: INTS
+ }
+ doc_string: ""
+ domain: ""
+ }
+ 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();
+ }
+};
+
+struct Conv2DWithBiasesFixture : public armnnUtils::ParserPrototxtFixture<armnnOnnxParser::IOnnxParser>
+{
+ Conv2DWithBiasesFixture() {
+ 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
+ }
+ }
+ }
+ }
+ }
+ input {
+ name: "Weight"
+ type {
+ tensor_type {
+ elem_type: FLOAT
+ shape {
+ dim {
+ dim_value: 1
+ }
+ dim {
+ dim_value: 1
+ }
+ dim {
+ dim_value: 2
+ }
+ dim {
+ dim_value: 2
+ }
+ }
+ }
+ }
+ }
+ initializer {
+ dims: 1
+ dims: 1
+ dims: 2
+ dims: 2
+ data_type: FLOAT
+ float_data: 2
+ float_data: 1
+ float_data: 0
+ float_data: 6
+ name: "Weight"
+ }
+ input {
+ name: "Bias"
+ type {
+ tensor_type {
+ elem_type: FLOAT
+ shape {
+ dim {
+ dim_value: 4
+ }
+ }
+ }
+ }
+ }
+ initializer {
+ dims: 4
+ data_type: FLOAT
+ float_data: 10
+ float_data: 0
+ float_data: 0
+ float_data: 0
+ name: "Bias"
+ }
+ node {
+ input: "Input"
+ input: "Weight"
+ input: "Bias"
+ output: "Output"
+ name: "Convolution"
+ op_type: "Conv"
+ attribute {
+ name: "kernel_shape"
+ ints: 2
+ ints: 2
+ type: INTS
+ }
+ attribute {
+ name: "strides"
+ ints: 1
+ ints: 1
+ type: INTS
+ }
+ attribute {
+ name: "auto_pad"
+ s: "SAME_UPPER"
+ type: STRING
+ }
+ attribute {
+ name: "group"
+ i: 1
+ type: INT
+ }
+ attribute {
+ name: "dilations"
+ ints: 1
+ ints: 1
+ type: INTS
+ }
+ doc_string: ""
+ domain: ""
+ }
+ output {
+ name: "Output"
+ type {
+ tensor_type {
+ elem_type: FLOAT
+ shape {
+ dim {
+ dim_value: 1
+ }
+ dim {
+ dim_value: 1
+ }
+ dim {
+ dim_value: 2
+ }
+ dim {
+ dim_value: 2
+ }
+ }
+ }
+ }
+ }
+ }
+ opset_import {
+ version: 7
+ })";
+ Setup();
+ }
+};
+
+
+struct Conv2DDimReducingFixture : public armnnUtils::ParserPrototxtFixture<armnnOnnxParser::IOnnxParser>
+{
+ Conv2DDimReducingFixture() {
+ 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: 3
+ }
+ dim {
+ dim_value: 2
+ }
+ dim {
+ dim_value: 2
+ }
+ }
+ }
+ }
+ }
+ input {
+ name: "Weight"
+ type {
+ tensor_type {
+ elem_type: FLOAT
+ shape {
+ dim {
+ dim_value: 2
+ }
+ dim {
+ dim_value: 3
+ }
+ dim {
+ dim_value: 1
+ }
+ dim {
+ dim_value: 1
+ }
+ }
+ }
+ }
+ }
+ initializer {
+ dims: 2
+ dims: 3
+ dims: 1
+ dims: 1
+ data_type: FLOAT
+ float_data: -1
+ float_data: 2
+ float_data: 0
+ float_data: 1
+ float_data: 0
+ float_data: 0
+ name: "Weight"
+ }
+ node {
+ input: "Input"
+ input: "Weight"
+ output: "Output"
+ name: "Convolution"
+ op_type: "Conv"
+ attribute {
+ name: "kernel_shape"
+ ints: 1
+ ints: 1
+ type: INTS
+ }
+ attribute {
+ name: "strides"
+ ints: 1
+ ints: 1
+ type: INTS
+ }
+ attribute {
+ name: "group"
+ i: 1
+ type: INT
+ }
+ attribute {
+ name: "dilations"
+ ints: 1
+ ints: 1
+ type: INTS
+ }
+ doc_string: ""
+ domain: ""
+ }
+ output {
+ name: "Output"
+ type {
+ tensor_type {
+ elem_type: FLOAT
+ shape {
+ dim {
+ dim_value: 1
+ }
+ dim {
+ dim_value: 2
+ }
+ dim {
+ dim_value: 2
+ }
+ dim {
+ dim_value: 2
+ }
+ }
+ }
+ }
+ }
+ }
+ opset_import {
+ version: 7
+ })";
+ Setup();
+ }
+};
+
+BOOST_FIXTURE_TEST_CASE(ValidConvTest, SimpleConv2DFixture)
+{
+ RunTest<4>({{"Input", {1.0, 2.0, 3.0,
+ 4.0, 5.0, 6.0,
+ 7.0, 8.0, 9.0}}},
+ {{"Output", {1.0 * 2 + 2.0 * 1 + 3.0 * 0 +
+ 4.0 * 6 + 5.0 * 2 + 6.0 * 1 +
+ 7.0 * 4 + 8.0 * 1 + 9.0 * 2}}});
+}
+
+BOOST_FIXTURE_TEST_CASE(ValidConvWithBiasTest, Conv2DWithBiasesFixture)
+{
+ RunTest<4>({{"Input", {1.0, 2.0,
+ 3.0, 4.0}}},
+ {{"Output", {1.0 * 2 + 2.0 * 1 + 3.0 * 0 + 4 * 6 + 10,
+ 2.0 * 2 + 0 * 1 + 4.0 * 0 + 0 * 6 + 10,
+ 3.0 * 2 + 4.0 * 1 + 0 * 0 + 0 * 6 + 10,
+ 4.0 * 2 + 0 * 1 + 0 * 0 + 0 * 6 + 10}}});
+}
+
+BOOST_FIXTURE_TEST_CASE(ValidConvDimReducTest, Conv2DDimReducingFixture)
+{
+ RunTest<4>({{"Input", {1.0, 2.0, 3.0, 4.0, -1, -2, 3, 4, 1 , 1, 1, 1 }}},
+ {{"Output", {-1 * 1 + 2 * -1, -1 * 2 + 2 * -2,
+ -1 * 3 + 2 * 3, -1 * 4 + 2 * 4,
+ 1, 2, 3, 4}}});
+}
+
+BOOST_AUTO_TEST_SUITE_END()