Searched refs:op2 (Results 76 - 100 of 138) sorted by relevance

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/frameworks/ml/nn/runtime/test/generated/models/
H A D	conv_float_weights_as_inputs.model.cpp	9 auto op2 = model->addOperand(&type1); local 22 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4}); 25 {op1, op2, op3},
H A D	conv_float_weights_as_inputs_relaxed.model.cpp	9 auto op2 = model->addOperand(&type1); local 22 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4}); 25 {op1, op2, op3},
H A D	conv_quant8.model.cpp	10 auto op2 = model->addOperand(&type1); local 18 model->setOperandValue(op2, op2_init, sizeof(uint8_t) * 4); 27 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
H A D	conv_quant8_channels.model.cpp	10 auto op2 = model->addOperand(&type1); local 18 model->setOperandValue(op2, op2_init, sizeof(uint8_t) * 9); 27 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
H A D	conv_quant8_channels_weights_as_inputs.model.cpp	10 auto op2 = model->addOperand(&type1); local 23 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4}); 26 {op1, op2, op3},
H A D	conv_quant8_large.model.cpp	10 auto op2 = model->addOperand(&type1); local 18 model->setOperandValue(op2, op2_init, sizeof(uint8_t) * 9); 27 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
H A D	conv_quant8_large_weights_as_inputs.model.cpp	10 auto op2 = model->addOperand(&type1); local 23 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4}); 26 {op1, op2, op3},
H A D	conv_quant8_overflow.model.cpp	10 auto op2 = model->addOperand(&type1); local 18 model->setOperandValue(op2, op2_init, sizeof(uint8_t) * 9); 27 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
H A D	conv_quant8_overflow_weights_as_inputs.model.cpp	10 auto op2 = model->addOperand(&type1); local 23 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4}); 26 {op1, op2, op3},
H A D	conv_quant8_weights_as_inputs.model.cpp	10 auto op2 = model->addOperand(&type1); local 23 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4}); 26 {op1, op2, op3},
H A D	depthwise_conv2d_float_large_2_weights_as_inputs.model.cpp	10 auto op2 = model->addOperand(&type1); local 26 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4}); 29 {op1, op2, op3},
H A D	depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.model.cpp	10 auto op2 = model->addOperand(&type1); local 26 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4}); 29 {op1, op2, op3},
H A D	depthwise_conv2d_float_large_weights_as_inputs.model.cpp	9 auto op2 = model->addOperand(&type0); local 25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4}); 28 {op1, op2, op3},
H A D	depthwise_conv2d_float_large_weights_as_inputs_relaxed.model.cpp	9 auto op2 = model->addOperand(&type0); local 25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4}); 28 {op1, op2, op3},
H A D	depthwise_conv2d_float_weights_as_inputs.model.cpp	9 auto op2 = model->addOperand(&type1); local 25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4}); 28 {op1, op2, op3},
H A D	depthwise_conv2d_float_weights_as_inputs_relaxed.model.cpp	9 auto op2 = model->addOperand(&type1); local 25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4}); 28 {op1, op2, op3},
H A D	depthwise_conv2d_quant8.model.cpp	9 auto op2 = model->addOperand(&type0); local 18 model->setOperandValue(op2, op2_init, sizeof(uint8_t) * 8); 29 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
H A D	depthwise_conv2d_quant8_large.model.cpp	9 auto op2 = model->addOperand(&type0); local 18 model->setOperandValue(op2, op2_init, sizeof(uint8_t) * 8); 29 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
H A D	depthwise_conv2d_quant8_large_weights_as_inputs.model.cpp	9 auto op2 = model->addOperand(&type0); local 25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4}); 28 {op1, op2, op3},
H A D	depthwise_conv2d_quant8_weights_as_inputs.model.cpp	9 auto op2 = model->addOperand(&type0); local 25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4}); 28 {op1, op2, op3},
H A D	depthwise_conv_2d.model.cpp	8 auto op2 = model->addOperand(&type0); local 24 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4}); 27 {op1, op2, op3},
H A D	depthwise_conv_2d_quant8.model.cpp	9 auto op2 = model->addOperand(&type0); local 25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4}); 28 {op1, op2, op3},
H A D	fully_connected_float.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});
H A D	fully_connected_float_3.model.cpp	10 auto op2 = model->addOperand(&type1); local 16 model->setOperandValue(op2, op2_init, sizeof(float) * 2); 21 model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act}, {op3});
H A D	fully_connected_float_4d_simple.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});

Completed in 68 milliseconds

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Indexes created Sun Aug 12 02:23:12 CEST 2018