15 explicit BatchNormalizationFixture(
const std::string &inputShape,
16 const std::string &outputShape,
17 const std::string &meanShape,
18 const std::string &varianceShape,
19 const std::string &offsetShape,
20 const std::string &scaleShape,
21 const std::string &dataType,
22 const std::string &dataLayout)
30 layer_type: "InputLayer", 36 layerName: "InputLayer", 40 connection: {sourceLayerIndex:0, outputSlotIndex:0 }, 45 dimensions: )" + inputShape + R"(, 46 dataType: ")" + dataType + R"(", 47 quantizationScale: 0.5, 56 layer_type: "BatchNormalizationLayer", 60 layerName: "BatchNormalizationLayer", 61 layerType: "BatchNormalization", 64 connection: {sourceLayerIndex:0, outputSlotIndex:0 }, 69 dimensions: )" + outputShape + R"(, 70 dataType: ")" + dataType + R"(" 76 dataLayout: ")" + dataLayout + R"(" 80 dimensions: )" + meanShape + R"(, 81 dataType: ")" + dataType + R"(" 90 dimensions: )" + varianceShape + R"(, 91 dataType: ")" + dataType + R"(" 100 dimensions: )" + offsetShape + R"(, 101 dataType: ")" + dataType + R"(" 110 dimensions: )" + scaleShape + R"(, 111 dataType: ")" + dataType + R"(" 121 layer_type: "OutputLayer", 127 layerName: "OutputLayer", 131 connection: {sourceLayerIndex:1, outputSlotIndex:0 }, 136 dimensions: )" + outputShape + R"(, 137 dataType: ")" + dataType + R"(" 149 struct BatchNormFixture : BatchNormalizationFixture
151 BatchNormFixture():BatchNormalizationFixture(
"[ 1, 3, 3, 1 ]",
163 RunTest<4, armnn::DataType::Float32>(0,
164 {{
"InputLayer", { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f }}},
165 {{
"OutputLayer",{ -2.8277204f, -2.12079024f, -1.4138602f,
166 -0.7069301f, 0.0f, 0.7069301f,
167 1.4138602f, 2.12079024f, 2.8277204f }}});
TEST_CASE_FIXTURE(ClContextControlFixture, "CopyBetweenNeonAndGpu")
TEST_SUITE("Deserializer_BatchNormalization")