/frameworks/ml/nn/runtime/test/generated/models/ |
H A D | fully_connected_float_4d_simple_relaxed.model.cpp | 10 auto op2 = model->addOperand(&type1); local 16 model->setOperandValue(op2, op2_init, sizeof(float) * 30); 21 model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act}, {op3});
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H A D | fully_connected_float_large.model.cpp | 9 auto op2 = model->addOperand(&type0); local 15 model->setOperandValue(op2, op2_init, sizeof(float) * 5); 20 model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act}, {op3});
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H A D | fully_connected_float_large_relaxed.model.cpp | 9 auto op2 = model->addOperand(&type0); local 15 model->setOperandValue(op2, op2_init, sizeof(float) * 5); 20 model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act}, {op3});
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H A D | fully_connected_float_relaxed.model.cpp | 9 auto op2 = model->addOperand(&type1); local 15 model->setOperandValue(op2, op2_init, sizeof(float) * 1); 20 model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act}, {op3});
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H A D | fully_connected_quant8.model.cpp | 10 auto op2 = model->addOperand(&type1); local 16 model->setOperandValue(op2, op2_init, sizeof(uint8_t) * 1); 21 model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act}, {op3});
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H A D | fully_connected_quant8_2.model.cpp | 10 auto op2 = model->addOperand(&type1); local 16 model->setOperandValue(op2, op2_init, sizeof(uint8_t) * 30); 21 model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act_relu}, {op3});
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H A D | fully_connected_quant8_large.model.cpp | 9 auto op2 = model->addOperand(&type0); local 15 model->setOperandValue(op2, op2_init, sizeof(uint8_t) * 5); 20 model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act}, {op3});
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H A D | conv_1_h3_w2_SAME.model.cpp | 13 auto op2 = model->addOperand(&type1); local 30 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); 33 {op2},
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H A D | conv_1_h3_w2_SAME_relaxed.model.cpp | 13 auto op2 = model->addOperand(&type1); local 30 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); 33 {op2},
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H A D | conv_1_h3_w2_VALID.model.cpp | 13 auto op2 = model->addOperand(&type1); local 30 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); 33 {op2},
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H A D | conv_1_h3_w2_VALID_relaxed.model.cpp | 13 auto op2 = model->addOperand(&type1); local 30 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); 33 {op2},
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H A D | conv_quant8_2.model.cpp | 10 auto op2 = model->addOperand(&type1); local 19 model->setOperandValue(op2, op2_init, sizeof(uint8_t) * 4); 30 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad_valid, stride3, stride1, act_none}, {op4});
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H A D | depthwise_conv.model.cpp | 13 auto op2 = model->addOperand(&type1); local 32 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op2, op0, op1, b4, b5, b6, b7, b8}, {op3}); 35 {op2},
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H A D | depthwise_conv2d_float.model.cpp | 9 auto op2 = model->addOperand(&type1); local 18 model->setOperandValue(op2, op2_init, sizeof(float) * 16); 29 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
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H A D | depthwise_conv2d_float_2.model.cpp | 10 auto op2 = model->addOperand(&type1); local 19 model->setOperandValue(op2, op2_init, sizeof(float) * 16); 30 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad_valid, stride, stride, channelMultiplier, act_none}, {op4});
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H A D | depthwise_conv2d_float_2_relaxed.model.cpp | 10 auto op2 = model->addOperand(&type1); local 19 model->setOperandValue(op2, op2_init, sizeof(float) * 16); 30 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad_valid, stride, stride, channelMultiplier, act_none}, {op4});
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H A D | depthwise_conv2d_float_large.model.cpp | 9 auto op2 = model->addOperand(&type0); local 18 model->setOperandValue(op2, op2_init, sizeof(float) * 8); 29 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
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H A D | depthwise_conv2d_float_large_2.model.cpp | 9 auto op2 = model->addOperand(&type0); local 18 model->setOperandValue(op2, op2_init, sizeof(float) * 16); 29 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
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H A D | depthwise_conv2d_float_large_2_relaxed.model.cpp | 9 auto op2 = model->addOperand(&type0); local 18 model->setOperandValue(op2, op2_init, sizeof(float) * 16); 29 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
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H A D | depthwise_conv2d_float_large_relaxed.model.cpp | 9 auto op2 = model->addOperand(&type0); local 18 model->setOperandValue(op2, op2_init, sizeof(float) * 8); 29 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
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H A D | depthwise_conv2d_float_relaxed.model.cpp | 9 auto op2 = model->addOperand(&type1); local 18 model->setOperandValue(op2, op2_init, sizeof(float) * 16); 29 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
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H A D | depthwise_conv2d_quant8_2.model.cpp | 10 auto op2 = model->addOperand(&type1); local 19 model->setOperandValue(op2, op2_init, sizeof(uint8_t) * 16); 30 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad_valid, stride, stride, channelMultiplier, act_none}, {op4});
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H A D | depthwise_conv_relaxed.model.cpp | 13 auto op2 = model->addOperand(&type1); local 32 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op2, op0, op1, b4, b5, b6, b7, b8}, {op3}); 35 {op2},
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H A D | conv_3_h3_w2_SAME.model.cpp | 12 auto op2 = model->addOperand(&type1); local 29 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); 32 {op2},
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/frameworks/base/services/tests/servicestests/src/com/android/server/content/ |
H A D | SyncOperationTest.java | 67 SyncOperation op2 = new SyncOperation(account1, 0, 102 assertEquals(op1.key, op2.key); 124 SyncOperation op2 = SyncOperation.maybeCreateFromJobExtras(pb); 127 account1.equals(op2.extras.get("acc"))); 128 assertTrue("Fields in extras not persisted", "String".equals(op2.extras.getString("str")));
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