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/frameworks/ml/nn/runtime/test/generated/models/
Dconv_3_h3_w2_VALID.model.cpp14 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
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Dconv_1_h3_w2_SAME.model.cpp14 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
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Dconv_1_h3_w2_VALID_relaxed.model.cpp14 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
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Dconv_1_h3_w2_SAME_relaxed.model.cpp14 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
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Dconv_3_h3_w2_SAME_relaxed.model.cpp13 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
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Dconv_1_h3_w2_VALID.model.cpp14 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
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Dconv_3_h3_w2_SAME.model.cpp13 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
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Dconv_3_h3_w2_VALID_relaxed.model.cpp14 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
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Ddepthwise_conv_relaxed.model.cpp13 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
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Ddepthwise_conv.model.cpp13 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
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/frameworks/ml/nn/runtime/test/specs/V1_2/
Dtranspose_conv2d.mod.py157 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)
Dconv2d_v1_2.mod.py146 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/
DCodedOutputStream.cs461 public void WriteRawTag(byte b1, byte b2, byte b3, byte b4, byte b5) in WriteRawTag() argument
467 WriteRawByte(b5); in WriteRawTag()
DCodedInputStream.cs883 ulong b5 = ReadRawByte(); in ReadRawLittleEndian64()
888 | (b5 << 32) | (b6 << 40) | (b7 << 48) | (b8 << 56); in ReadRawLittleEndian64()
/frameworks/base/services/tests/servicestests/assets/KeyStoreRecoveryControllerTest/pem/
Dvalid-cert.pem129 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/
DCodedInputByteBufferNano.java353 final byte b5 = readRawByte(); in readRawLittleEndian64()
361 (((long)b5 & 0xff) << 32) | in readRawLittleEndian64()
/frameworks/base/cmds/statsd/src/
Datoms.proto4874 // Build.VERSION.RELEASE. The user-visible version string. E.g., "1.0" or "3.4b5" or "bananas".