/frameworks/ml/nn/runtime/test/generated/models/ |
D | l2_pool_float_2_relaxed.model.cpp | 11 auto act_none = model->addOperand(&type1); in CreateModel() local 19 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1); in CreateModel() 20 …peration(ANEURALNETWORKS_L2_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3}); in CreateModel() 43 auto act_none = model->addOperand(&type1); in CreateModel_dynamic_output_shape() local 51 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 52 …peration(ANEURALNETWORKS_L2_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3}); in CreateModel_dynamic_output_shape()
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D | max_pool_float_4.model.cpp | 11 auto act_none = model->addOperand(&type1); in CreateModel() local 19 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1); in CreateModel() 20 …eration(ANEURALNETWORKS_MAX_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3}); in CreateModel() 41 auto act_none = model->addOperand(&type1); in CreateModel_dynamic_output_shape() local 49 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 50 …eration(ANEURALNETWORKS_MAX_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3}); in CreateModel_dynamic_output_shape()
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D | avg_pool_quant8_5.model.cpp | 11 auto act_none = model->addOperand(&type1); in CreateModel() local 19 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1); in CreateModel() 20 …ion(ANEURALNETWORKS_AVERAGE_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3}); in CreateModel() 41 auto act_none = model->addOperand(&type1); in CreateModel_dynamic_output_shape() local 49 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 50 …ion(ANEURALNETWORKS_AVERAGE_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3}); in CreateModel_dynamic_output_shape()
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D | avg_pool_float_5_relaxed.model.cpp | 11 auto act_none = model->addOperand(&type1); in CreateModel() local 19 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1); in CreateModel() 20 …ion(ANEURALNETWORKS_AVERAGE_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3}); in CreateModel() 43 auto act_none = model->addOperand(&type1); in CreateModel_dynamic_output_shape() local 51 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 52 …ion(ANEURALNETWORKS_AVERAGE_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3}); in CreateModel_dynamic_output_shape()
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D | max_pool_float_4_relaxed.model.cpp | 11 auto act_none = model->addOperand(&type1); in CreateModel() local 19 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1); in CreateModel() 20 …eration(ANEURALNETWORKS_MAX_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3}); in CreateModel() 43 auto act_none = model->addOperand(&type1); in CreateModel_dynamic_output_shape() local 51 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 52 …eration(ANEURALNETWORKS_MAX_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3}); in CreateModel_dynamic_output_shape()
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D | max_pool_quant8_4.model.cpp | 11 auto act_none = model->addOperand(&type1); in CreateModel() local 19 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1); in CreateModel() 20 …eration(ANEURALNETWORKS_MAX_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3}); in CreateModel() 41 auto act_none = model->addOperand(&type1); in CreateModel_dynamic_output_shape() local 49 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 50 …eration(ANEURALNETWORKS_MAX_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3}); in CreateModel_dynamic_output_shape()
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D | l2_pool_float_2.model.cpp | 11 auto act_none = model->addOperand(&type1); in CreateModel() local 19 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1); in CreateModel() 20 …peration(ANEURALNETWORKS_L2_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3}); in CreateModel() 41 auto act_none = model->addOperand(&type1); in CreateModel_dynamic_output_shape() local 49 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 50 …peration(ANEURALNETWORKS_L2_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3}); in CreateModel_dynamic_output_shape()
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D | avg_pool_float_5.model.cpp | 11 auto act_none = model->addOperand(&type1); in CreateModel() local 19 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1); in CreateModel() 20 …ion(ANEURALNETWORKS_AVERAGE_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3}); in CreateModel() 41 auto act_none = model->addOperand(&type1); in CreateModel_dynamic_output_shape() local 49 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 50 …ion(ANEURALNETWORKS_AVERAGE_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3}); in CreateModel_dynamic_output_shape()
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D | depthwise_conv2d_float_2.model.cpp | 16 auto act_none = model->addOperand(&type3); in CreateModel() local 30 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1); in CreateModel() 31 …DEPTHWISE_CONV_2D, {op1, op2, op3, pad_valid, stride, stride, channelMultiplier, act_none}, {op4}); in CreateModel() 57 auto act_none = model->addOperand(&type3); in CreateModel_dynamic_output_shape() local 71 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 72 …DEPTHWISE_CONV_2D, {op1, op2, op3, pad_valid, stride, stride, channelMultiplier, act_none}, {op4}); in CreateModel_dynamic_output_shape()
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D | depthwise_conv2d_float_2_relaxed.model.cpp | 16 auto act_none = model->addOperand(&type3); in CreateModel() local 30 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1); in CreateModel() 31 …DEPTHWISE_CONV_2D, {op1, op2, op3, pad_valid, stride, stride, channelMultiplier, act_none}, {op4}); in CreateModel() 59 auto act_none = model->addOperand(&type3); in CreateModel_dynamic_output_shape() local 73 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 74 …DEPTHWISE_CONV_2D, {op1, op2, op3, pad_valid, stride, stride, channelMultiplier, act_none}, {op4}); in CreateModel_dynamic_output_shape()
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D | depthwise_conv2d_quant8_2.model.cpp | 16 auto act_none = model->addOperand(&type3); in CreateModel() local 30 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1); in CreateModel() 31 …DEPTHWISE_CONV_2D, {op1, op2, op3, pad_valid, stride, stride, channelMultiplier, act_none}, {op4}); in CreateModel() 57 auto act_none = model->addOperand(&type3); in CreateModel_dynamic_output_shape() local 71 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 72 …DEPTHWISE_CONV_2D, {op1, op2, op3, pad_valid, stride, stride, channelMultiplier, act_none}, {op4}); in CreateModel_dynamic_output_shape()
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D | conv_quant8_2.model.cpp | 16 auto act_none = model->addOperand(&type3); in CreateModel() local 30 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1); in CreateModel() 31 …dOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad_valid, stride3, stride1, act_none}, {op4}); in CreateModel() 57 auto act_none = model->addOperand(&type3); in CreateModel_dynamic_output_shape() local 71 model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 72 …dOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad_valid, stride3, stride1, act_none}, {op4}); in CreateModel_dynamic_output_shape()
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/frameworks/ml/nn/runtime/test/specs/V1_0/ |
D | avg_pool_quant8_5.mod.py | 22 act_none = Int32Scalar("act_none", 0) variable 24 model = model.Operation("AVERAGE_POOL_2D", i1, pad_same, cons2, cons2, cons2, cons2, act_none).To(i…
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D | max_pool_quant8_4.mod.py | 22 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)
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D | avg_pool_float_5.mod.py | 22 act_none = Int32Scalar("act_none", 0) variable 24 model = model.Operation("AVERAGE_POOL_2D", i1, pad_same, cons2, cons2, cons2, cons2, act_none).To(i…
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D | max_pool_float_4.mod.py | 22 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)
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D | l2_pool_float_2.mod.py | 22 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)
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D | conv_quant8_2.mod.py | 22 act_none = Int32Scalar("act_none", 0) variable 29 stride1, act_none).To(output)
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D | depthwise_conv2d_quant8_2.mod.py | 22 act_none = Int32Scalar("act_none", 0) variable 31 cm, act_none).To(output)
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D | depthwise_conv2d_float_2.mod.py | 22 act_none = Int32Scalar("act_none", 0) variable 31 cm, act_none).To(output)
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/frameworks/ml/nn/runtime/test/specs/V1_1/ |
D | l2_pool_float_2_relaxed.mod.py | 22 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)
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D | avg_pool_float_5_relaxed.mod.py | 22 act_none = Int32Scalar("act_none", 0) variable 24 model = model.Operation("AVERAGE_POOL_2D", i1, pad_same, cons2, cons2, cons2, cons2, act_none).To(i…
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D | max_pool_float_4_relaxed.mod.py | 22 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)
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D | depthwise_conv2d_float_2_relaxed.mod.py | 22 act_none = Int32Scalar("act_none", 0) variable 31 cm, act_none).To(output)
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