/frameworks/ml/nn/runtime/test/generated/models/ |
D | conv_3_h3_w2_VALID.model.cpp | 14 auto b5 = model->addOperand(&type0); in CreateModel() local 26 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel() 31 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); in CreateModel() 55 auto b5 = model->addOperand(&type0); in CreateModel_dynamic_output_shape() local 67 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 72 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); in CreateModel_dynamic_output_shape() 96 auto b5 = model->addOperand(&type0); in CreateModel_2() local 108 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel_2() 113 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); in CreateModel_2() 137 auto b5 = model->addOperand(&type0); in CreateModel_dynamic_output_shape_2() local [all …]
|
D | conv_1_h3_w2_SAME.model.cpp | 14 auto b5 = model->addOperand(&type0); in CreateModel() local 26 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel() 31 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); in CreateModel() 55 auto b5 = model->addOperand(&type0); in CreateModel_dynamic_output_shape() local 67 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 72 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); in CreateModel_dynamic_output_shape() 96 auto b5 = model->addOperand(&type0); in CreateModel_2() local 108 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel_2() 113 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); in CreateModel_2() 137 auto b5 = model->addOperand(&type0); in CreateModel_dynamic_output_shape_2() local [all …]
|
D | conv_1_h3_w2_VALID_relaxed.model.cpp | 14 auto b5 = model->addOperand(&type0); in CreateModel() local 26 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel() 31 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); in CreateModel() 57 auto b5 = model->addOperand(&type0); in CreateModel_dynamic_output_shape() local 69 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 74 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); in CreateModel_dynamic_output_shape() 100 auto b5 = model->addOperand(&type0); in CreateModel_2() local 112 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel_2() 117 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); in CreateModel_2() 143 auto b5 = model->addOperand(&type0); in CreateModel_dynamic_output_shape_2() local [all …]
|
D | conv_1_h3_w2_SAME_relaxed.model.cpp | 14 auto b5 = model->addOperand(&type0); in CreateModel() local 26 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel() 31 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); in CreateModel() 57 auto b5 = model->addOperand(&type0); in CreateModel_dynamic_output_shape() local 69 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 74 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); in CreateModel_dynamic_output_shape() 100 auto b5 = model->addOperand(&type0); in CreateModel_2() local 112 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel_2() 117 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); in CreateModel_2() 143 auto b5 = model->addOperand(&type0); in CreateModel_dynamic_output_shape_2() local [all …]
|
D | conv_3_h3_w2_SAME_relaxed.model.cpp | 13 auto b5 = model->addOperand(&type0); in CreateModel() local 25 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel() 30 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); in CreateModel() 56 auto b5 = model->addOperand(&type0); in CreateModel_dynamic_output_shape() local 68 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 73 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); in CreateModel_dynamic_output_shape() 98 auto b5 = model->addOperand(&type0); in CreateModel_2() local 110 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel_2() 115 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); in CreateModel_2() 141 auto b5 = model->addOperand(&type0); in CreateModel_dynamic_output_shape_2() local [all …]
|
D | conv_1_h3_w2_VALID.model.cpp | 14 auto b5 = model->addOperand(&type0); in CreateModel() local 26 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel() 31 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); in CreateModel() 55 auto b5 = model->addOperand(&type0); in CreateModel_dynamic_output_shape() local 67 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 72 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); in CreateModel_dynamic_output_shape() 96 auto b5 = model->addOperand(&type0); in CreateModel_2() local 108 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel_2() 113 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); in CreateModel_2() 137 auto b5 = model->addOperand(&type0); in CreateModel_dynamic_output_shape_2() local [all …]
|
D | conv_3_h3_w2_SAME.model.cpp | 13 auto b5 = model->addOperand(&type0); in CreateModel() local 25 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel() 30 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); in CreateModel() 54 auto b5 = model->addOperand(&type0); in CreateModel_dynamic_output_shape() local 66 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 71 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); in CreateModel_dynamic_output_shape() 94 auto b5 = model->addOperand(&type0); in CreateModel_2() local 106 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel_2() 111 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); in CreateModel_2() 135 auto b5 = model->addOperand(&type0); in CreateModel_dynamic_output_shape_2() local [all …]
|
D | conv_3_h3_w2_VALID_relaxed.model.cpp | 14 auto b5 = model->addOperand(&type0); in CreateModel() local 26 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel() 31 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); in CreateModel() 57 auto b5 = model->addOperand(&type0); in CreateModel_dynamic_output_shape() local 69 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 74 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); in CreateModel_dynamic_output_shape() 100 auto b5 = model->addOperand(&type0); in CreateModel_2() local 112 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel_2() 117 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); in CreateModel_2() 143 auto b5 = model->addOperand(&type0); in CreateModel_dynamic_output_shape_2() local [all …]
|
D | depthwise_conv_relaxed.model.cpp | 13 auto b5 = model->addOperand(&type0); in CreateModel() local 26 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel() 33 …model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op2, op0, op1, b4, b5, b6, b7, b8}, {op3}); in CreateModel() 59 auto b5 = model->addOperand(&type0); in CreateModel_dynamic_output_shape() local 72 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 79 …model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op2, op0, op1, b4, b5, b6, b7, b8}, {op3}); in CreateModel_dynamic_output_shape() 104 auto b5 = model->addOperand(&type0); in CreateModel_2() local 117 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel_2() 124 …model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op2, op0, op1, b4, b5, b6, b7, b8}, {op3}); in CreateModel_2() 150 auto b5 = model->addOperand(&type0); in CreateModel_dynamic_output_shape_2() local [all …]
|
D | depthwise_conv.model.cpp | 13 auto b5 = model->addOperand(&type0); in CreateModel() local 26 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel() 33 …model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op2, op0, op1, b4, b5, b6, b7, b8}, {op3}); in CreateModel() 57 auto b5 = model->addOperand(&type0); in CreateModel_dynamic_output_shape() local 70 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 77 …model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op2, op0, op1, b4, b5, b6, b7, b8}, {op3}); in CreateModel_dynamic_output_shape() 100 auto b5 = model->addOperand(&type0); in CreateModel_2() local 113 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); in CreateModel_2() 120 …model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op2, op0, op1, b4, b5, b6, b7, b8}, {op3}); in CreateModel_2() 144 auto b5 = model->addOperand(&type0); in CreateModel_dynamic_output_shape_2() local [all …]
|
/frameworks/ml/nn/runtime/test/specs/V1_2/ |
D | transpose_conv2d.mod.py | 157 b5 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0]) # bias variable 159 Model().Operation("TRANSPOSE_CONV_2D", i5, w5, b5, 1, 2, 2, 1, 1, 1, 0, layout).To(o5) 165 b5: ("TENSOR_INT32", 0.125, 0), 175 }).AddNchw(i5, o5, layout).AddVariations("relaxed", quant8, "float16").AddInput(w5, b5)
|
D | conv2d_v1_2.mod.py | 146 b5 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0.]) variable 149 model_1_same = Model("1_H3_W2_SAME").Operation("CONV_2D", i5, f5, b5, 1, 1, 1, 0, layout).To(o5) 150 model_1_valid = Model("1_H3_W2_VALID").Operation("CONV_2D", i5, f5, b5, 2, 1, 1, 0, layout).To(o6)
|
/frameworks/opt/gamesdk/third_party/protobuf-3.0.0/csharp/src/Google.Protobuf/ |
D | CodedOutputStream.cs | 461 public void WriteRawTag(byte b1, byte b2, byte b3, byte b4, byte b5) in WriteRawTag() argument 467 WriteRawByte(b5); in WriteRawTag()
|
D | CodedInputStream.cs | 883 ulong b5 = ReadRawByte(); in ReadRawLittleEndian64() 888 | (b5 << 32) | (b6 << 40) | (b7 << 48) | (b8 << 56); in ReadRawLittleEndian64()
|
/frameworks/base/services/tests/servicestests/assets/KeyStoreRecoveryControllerTest/pem/ |
D | valid-cert.pem | 129 5b:bf:9f:26:b5:87:e9:5b:8b:67:40:75:7e:3d:be: 134 e3:b5:60:d5:f4:0f:7a:17:a3:6c:e3:44:d6:70:48: 172 4a:65:0e:f0:2f:b4:7a:8c:aa:e3:fc:6b:42:0d:ec:b5:5a:bd: 178 8f:e3:98:90:a6:8e:53:e8:b5:55:32:b9:2d:2d:fe:5e:23:3c: 180 ac:00:82:2c:f5:ef:17:1d:b5:49:24:0d:09:75:ee:eb:b4:08:
|
/frameworks/opt/gamesdk/third_party/protobuf-3.0.0/javanano/src/main/java/com/google/protobuf/nano/ |
D | CodedInputByteBufferNano.java | 353 final byte b5 = readRawByte(); in readRawLittleEndian64() 361 (((long)b5 & 0xff) << 32) | in readRawLittleEndian64()
|
/frameworks/base/cmds/statsd/src/ |
D | atoms.proto | 4874 // Build.VERSION.RELEASE. The user-visible version string. E.g., "1.0" or "3.4b5" or "bananas".
|