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/frameworks/ml/nn/runtime/test/generated/models/
conv_quant8_large_weights_as_inputs.model.cpp	12 auto pad0 = model->addOperand(&type3); local 18 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); 23 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
conv_quant8_overflow.model.cpp	12 auto pad0 = model->addOperand(&type3); local 22 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); 27 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
conv_quant8_overflow_weights_as_inputs.model.cpp	12 auto pad0 = model->addOperand(&type3); local 18 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); 23 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
conv_quant8_weights_as_inputs.model.cpp	12 auto pad0 = model->addOperand(&type3); local 18 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); 23 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
depthwise_conv2d_float_large_2_weights_as_inputs.model.cpp	12 auto pad0 = model->addOperand(&type3); local 19 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); 26 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.model.cpp	12 auto pad0 = model->addOperand(&type3); local 19 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); 26 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
depthwise_conv2d_float_large_weights_as_inputs.model.cpp	11 auto pad0 = model->addOperand(&type2); local 18 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); 25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
depthwise_conv2d_float_large_weights_as_inputs_relaxed.model.cpp	11 auto pad0 = model->addOperand(&type2); local 18 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); 25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
depthwise_conv2d_float_weights_as_inputs.model.cpp	11 auto pad0 = model->addOperand(&type3); local 18 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); 25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
depthwise_conv2d_float_weights_as_inputs_relaxed.model.cpp	11 auto pad0 = model->addOperand(&type3); local 18 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); 25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
depthwise_conv2d_quant8_large_weights_as_inputs.model.cpp	11 auto pad0 = model->addOperand(&type2); local 18 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); 25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
depthwise_conv2d_quant8_weights_as_inputs.model.cpp	11 auto pad0 = model->addOperand(&type2); local 18 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); 25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
depthwise_conv_2d.model.cpp	10 auto pad0 = model->addOperand(&type2); local 17 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); 24 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
depthwise_conv_2d_quant8.model.cpp	11 auto pad0 = model->addOperand(&type2); local 18 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); 25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
l2_pool_float.model.cpp	8 auto pad0 = model->addOperand(&type1); local 15 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); 18 model->addOperation(ANEURALNETWORKS_L2_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {op3});
l2_pool_float_relaxed.model.cpp	8 auto pad0 = model->addOperand(&type1); local 15 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); 18 model->addOperation(ANEURALNETWORKS_L2_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {op3});
max_pool_float_1.model.cpp	8 auto pad0 = model->addOperand(&type1); local 15 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); 18 model->addOperation(ANEURALNETWORKS_MAX_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {op3});
max_pool_float_1_relaxed.model.cpp	8 auto pad0 = model->addOperand(&type1); local 15 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); 18 model->addOperation(ANEURALNETWORKS_MAX_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {op3});
max_pool_quant8_1.model.cpp	8 auto pad0 = model->addOperand(&type1); local 15 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); 18 model->addOperation(ANEURALNETWORKS_MAX_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {op3});
/frameworks/ml/nn/runtime/test/specs/V1_0/
depthwise_conv2d_float.mod.py	21 pad0 = Int32Scalar("pad0", 0) variable 29 pad0, pad0, pad0, pad0,
depthwise_conv2d_float_large.mod.py	21 pad0 = Int32Scalar("pad0", 0) variable 29 pad0, pad0, pad0, pad0,
depthwise_conv2d_float_large_2.mod.py	21 pad0 = Int32Scalar("pad0", 0) variable 29 pad0, pad0, pad0, pad0,
depthwise_conv2d_float_large_2_weights_as_inputs.mod.py	21 pad0 = Int32Scalar("pad0", 0) variable 29 pad0, pad0, pad0, pad0,
depthwise_conv2d_float_large_weights_as_inputs.mod.py	21 pad0 = Int32Scalar("pad0", 0) variable 29 pad0, pad0, pad0, pad0,
depthwise_conv2d_float_weights_as_inputs.mod.py	21 pad0 = Int32Scalar("pad0", 0) variable 29 pad0, pad0, pad0, pad0,

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