Searched refs:act_none (Results 1 - 24 of 24) sorted by relevance

/frameworks/ml/nn/runtime/test/specs/V1_0/
H A Davg_pool_float_5.mod.py22 act_none = Int32Scalar("act_none", 0) variable
24 model = model.Operation("AVERAGE_POOL_2D", i1, pad_same, cons2, cons2, cons2, cons2, act_none).To(i3)
H A Davg_pool_quant8_5.mod.py22 act_none = Int32Scalar("act_none", 0) variable
24 model = model.Operation("AVERAGE_POOL_2D", i1, pad_same, cons2, cons2, cons2, cons2, act_none).To(i3)
H A Dl2_pool_float_2.mod.py22 act_none = Int32Scalar("act_none", 0) variable
24 model = model.Operation("L2_POOL_2D", i1, pad_same, cons2, cons2, cons2, cons2, act_none).To(i3)
H A Dmax_pool_float_4.mod.py22 act_none = Int32Scalar("act_none", 0) variable
24 model = model.Operation("MAX_POOL_2D", i1, pad_same, cons2, cons2, cons2, cons2, act_none).To(i3)
H A Dmax_pool_quant8_4.mod.py22 act_none = Int32Scalar("act_none", 0) variable
24 model = model.Operation("MAX_POOL_2D", i1, pad_same, cons2, cons2, cons2, cons2, act_none).To(i3)
H A Dconv_quant8_2.mod.py22 act_none = Int32Scalar("act_none", 0) variable
29 stride1, act_none).To(output)
H A Ddepthwise_conv2d_float_2.mod.py22 act_none = Int32Scalar("act_none", 0) variable
31 cm, act_none).To(output)
H A Ddepthwise_conv2d_quant8_2.mod.py22 act_none = Int32Scalar("act_none", 0) variable
31 cm, act_none).To(output)
/frameworks/ml/nn/runtime/test/specs/V1_1/
H A Davg_pool_float_5_relaxed.mod.py22 act_none = Int32Scalar("act_none", 0) variable
24 model = model.Operation("AVERAGE_POOL_2D", i1, pad_same, cons2, cons2, cons2, cons2, act_none).To(i3)
H A Dl2_pool_float_2_relaxed.mod.py22 act_none = Int32Scalar("act_none", 0) variable
24 model = model.Operation("L2_POOL_2D", i1, pad_same, cons2, cons2, cons2, cons2, act_none).To(i3)
H A Dmax_pool_float_4_relaxed.mod.py22 act_none = Int32Scalar("act_none", 0) variable
24 model = model.Operation("MAX_POOL_2D", i1, pad_same, cons2, cons2, cons2, cons2, act_none).To(i3)
H A Ddepthwise_conv2d_float_2_relaxed.mod.py22 act_none = Int32Scalar("act_none", 0) variable
31 cm, act_none).To(output)
/frameworks/ml/nn/runtime/test/generated/models/
H A Davg_pool_float_5.model.cpp10 auto act_none = model->addOperand(&type1); local
18 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1);
19 model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3});
H A Davg_pool_float_5_relaxed.model.cpp10 auto act_none = model->addOperand(&type1); local
18 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1);
19 model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3});
H A Davg_pool_quant8_5.model.cpp10 auto act_none = model->addOperand(&type1); local
18 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1);
19 model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3});
H A Dl2_pool_float_2.model.cpp10 auto act_none = model->addOperand(&type1); local
18 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1);
19 model->addOperation(ANEURALNETWORKS_L2_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3});
H A Dl2_pool_float_2_relaxed.model.cpp10 auto act_none = model->addOperand(&type1); local
18 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1);
19 model->addOperation(ANEURALNETWORKS_L2_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3});
H A Dmax_pool_float_4.model.cpp10 auto act_none = model->addOperand(&type1); local
18 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1);
19 model->addOperation(ANEURALNETWORKS_MAX_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3});
H A Dmax_pool_float_4_relaxed.model.cpp10 auto act_none = model->addOperand(&type1); local
18 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1);
19 model->addOperation(ANEURALNETWORKS_MAX_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3});
H A Dmax_pool_quant8_4.model.cpp10 auto act_none = model->addOperand(&type1); local
18 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1);
19 model->addOperation(ANEURALNETWORKS_MAX_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3});
H A Dconv_quant8_2.model.cpp13 auto act_none = model->addOperand(&type3); local
25 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1);
30 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad_valid, stride3, stride1, act_none}, {op4});
H A Ddepthwise_conv2d_float_2.model.cpp13 auto act_none = model->addOperand(&type3); local
25 model->setOperandValue(act_none, act_none_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.cpp13 auto act_none = model->addOperand(&type3); local
25 model->setOperandValue(act_none, act_none_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_quant8_2.model.cpp13 auto act_none = model->addOperand(&type3); local
25 model->setOperandValue(act_none, act_none_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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