Searched refs:channelMultiplier (Results 1 - 21 of 21) sorted by relevance

/frameworks/ml/nn/runtime/test/generated/models/
H A Ddepthwise_conv2d_float_large_2_weights_as_inputs.model.cpp15 auto channelMultiplier = model->addOperand(&type3); local
25 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
26 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_weights_as_inputs_relaxed.model.cpp15 auto channelMultiplier = model->addOperand(&type3); local
25 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
26 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
H A Ddepthwise_conv2d_float_large_weights_as_inputs.model.cpp14 auto channelMultiplier = model->addOperand(&type2); local
24 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
H A Ddepthwise_conv2d_float_large_weights_as_inputs_relaxed.model.cpp14 auto channelMultiplier = model->addOperand(&type2); local
24 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
H A Ddepthwise_conv2d_float_weights_as_inputs.model.cpp14 auto channelMultiplier = model->addOperand(&type3); local
24 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
H A Ddepthwise_conv2d_float_weights_as_inputs_relaxed.model.cpp14 auto channelMultiplier = model->addOperand(&type3); local
24 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
H A Ddepthwise_conv2d_quant8.model.cpp14 auto channelMultiplier = model->addOperand(&type2); local
28 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
29 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
H A Ddepthwise_conv2d_quant8_large.model.cpp14 auto channelMultiplier = model->addOperand(&type2); local
28 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
29 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
H A Ddepthwise_conv2d_quant8_large_weights_as_inputs.model.cpp14 auto channelMultiplier = model->addOperand(&type2); local
24 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
H A Ddepthwise_conv2d_quant8_weights_as_inputs.model.cpp14 auto channelMultiplier = model->addOperand(&type2); local
24 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
H A Ddepthwise_conv_2d.model.cpp13 auto channelMultiplier = model->addOperand(&type2); local
23 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
24 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
H A Ddepthwise_conv_2d_quant8.model.cpp14 auto channelMultiplier = model->addOperand(&type2); local
24 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
H A Ddepthwise_conv2d_float.model.cpp14 auto channelMultiplier = model->addOperand(&type3); local
28 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
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.cpp15 auto channelMultiplier = model->addOperand(&type3); local
29 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
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.cpp15 auto channelMultiplier = model->addOperand(&type3); local
29 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
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.cpp14 auto channelMultiplier = model->addOperand(&type2); local
28 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
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.cpp14 auto channelMultiplier = model->addOperand(&type2); local
28 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
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.cpp14 auto channelMultiplier = model->addOperand(&type2); local
28 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
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.cpp14 auto channelMultiplier = model->addOperand(&type2); local
28 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
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.cpp14 auto channelMultiplier = model->addOperand(&type3); local
28 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
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.cpp15 auto channelMultiplier = model->addOperand(&type3); local
29 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
30 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad_valid, stride, stride, channelMultiplier, act_none}, {op4});

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