Searched refs:op2 (Results 101 - 125 of 138) sorted by relevance

123456

/frameworks/ml/nn/runtime/test/generated/models/
H A Dfully_connected_float_4d_simple_relaxed.model.cpp10 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});
H A Dfully_connected_float_large.model.cpp9 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});
H A Dfully_connected_float_large_relaxed.model.cpp9 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});
H A Dfully_connected_float_relaxed.model.cpp9 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});
H A Dfully_connected_quant8.model.cpp10 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});
H A Dfully_connected_quant8_2.model.cpp10 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});
H A Dfully_connected_quant8_large.model.cpp9 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});
H A Dconv_1_h3_w2_SAME.model.cpp13 auto op2 = model->addOperand(&type1); local
30 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3});
33 {op2},
H A Dconv_1_h3_w2_SAME_relaxed.model.cpp13 auto op2 = model->addOperand(&type1); local
30 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3});
33 {op2},
H A Dconv_1_h3_w2_VALID.model.cpp13 auto op2 = model->addOperand(&type1); local
30 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3});
33 {op2},
H A Dconv_1_h3_w2_VALID_relaxed.model.cpp13 auto op2 = model->addOperand(&type1); local
30 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3});
33 {op2},
H A Dconv_quant8_2.model.cpp10 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});
H A Ddepthwise_conv.model.cpp13 auto op2 = model->addOperand(&type1); local
32 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op2, op0, op1, b4, b5, b6, b7, b8}, {op3});
35 {op2},
H A Ddepthwise_conv2d_float.model.cpp9 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});
H A Ddepthwise_conv2d_float_2.model.cpp10 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});
H A Ddepthwise_conv2d_float_2_relaxed.model.cpp10 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});
H A Ddepthwise_conv2d_float_large.model.cpp9 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});
H A Ddepthwise_conv2d_float_large_2.model.cpp9 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});
H A Ddepthwise_conv2d_float_large_2_relaxed.model.cpp9 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});
H A Ddepthwise_conv2d_float_large_relaxed.model.cpp9 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});
H A Ddepthwise_conv2d_float_relaxed.model.cpp9 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});
H A Ddepthwise_conv2d_quant8_2.model.cpp10 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});
H A Ddepthwise_conv_relaxed.model.cpp13 auto op2 = model->addOperand(&type1); local
32 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op2, op0, op1, b4, b5, b6, b7, b8}, {op3});
35 {op2},
H A Dconv_3_h3_w2_SAME.model.cpp12 auto op2 = model->addOperand(&type1); local
29 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3});
32 {op2},
/frameworks/base/services/tests/servicestests/src/com/android/server/content/
H A DSyncOperationTest.java67 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")));

Completed in 120 milliseconds

123456