/frameworks/ml/nn/runtime/test/generated/models/ |
D | l2_pool_float.model.cpp | 9 auto cons1 = model->addOperand(&type1); in CreateModel() local 16 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1); in CreateModel() 19 …tion(ANEURALNETWORKS_L2_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {… in CreateModel() 39 auto cons1 = model->addOperand(&type1); in CreateModel_dynamic_output_shape() local 46 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 49 …tion(ANEURALNETWORKS_L2_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {… in CreateModel_dynamic_output_shape()
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D | max_pool_float_1_relaxed.model.cpp | 9 auto cons1 = model->addOperand(&type1); in CreateModel() local 16 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1); in CreateModel() 19 …ion(ANEURALNETWORKS_MAX_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {… in CreateModel() 41 auto cons1 = model->addOperand(&type1); in CreateModel_dynamic_output_shape() local 48 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 51 …ion(ANEURALNETWORKS_MAX_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {… in CreateModel_dynamic_output_shape()
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D | avg_pool_quant8_4.model.cpp | 9 auto cons1 = model->addOperand(&type1); in CreateModel() local 16 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1); in CreateModel() 19 …ANEURALNETWORKS_AVERAGE_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, relu1_a… in CreateModel() 39 auto cons1 = model->addOperand(&type1); in CreateModel_dynamic_output_shape() local 46 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 49 …ANEURALNETWORKS_AVERAGE_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, relu1_a… in CreateModel_dynamic_output_shape()
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D | l2_pool_float_relaxed.model.cpp | 9 auto cons1 = model->addOperand(&type1); in CreateModel() local 16 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1); in CreateModel() 19 …tion(ANEURALNETWORKS_L2_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {… in CreateModel() 41 auto cons1 = model->addOperand(&type1); in CreateModel_dynamic_output_shape() local 48 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 51 …tion(ANEURALNETWORKS_L2_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {… in CreateModel_dynamic_output_shape()
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D | avg_pool_float_1_relaxed.model.cpp | 9 auto cons1 = model->addOperand(&type1); in CreateModel() local 16 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1); in CreateModel() 19 …ANEURALNETWORKS_AVERAGE_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {… in CreateModel() 41 auto cons1 = model->addOperand(&type1); in CreateModel_dynamic_output_shape() local 48 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 51 …ANEURALNETWORKS_AVERAGE_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {… in CreateModel_dynamic_output_shape()
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D | max_pool_float_1.model.cpp | 9 auto cons1 = model->addOperand(&type1); in CreateModel() local 16 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1); in CreateModel() 19 …ion(ANEURALNETWORKS_MAX_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {… in CreateModel() 39 auto cons1 = model->addOperand(&type1); in CreateModel_dynamic_output_shape() local 46 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 49 …ion(ANEURALNETWORKS_MAX_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {… in CreateModel_dynamic_output_shape()
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D | avg_pool_quant8_1.model.cpp | 9 auto cons1 = model->addOperand(&type1); in CreateModel() local 16 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1); in CreateModel() 19 …ANEURALNETWORKS_AVERAGE_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {… in CreateModel() 39 auto cons1 = model->addOperand(&type1); in CreateModel_dynamic_output_shape() local 46 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 49 …ANEURALNETWORKS_AVERAGE_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {… in CreateModel_dynamic_output_shape()
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D | max_pool_quant8_1.model.cpp | 9 auto cons1 = model->addOperand(&type1); in CreateModel() local 16 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1); in CreateModel() 19 …ion(ANEURALNETWORKS_MAX_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {… in CreateModel() 39 auto cons1 = model->addOperand(&type1); in CreateModel_dynamic_output_shape() local 46 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 49 …ion(ANEURALNETWORKS_MAX_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {… in CreateModel_dynamic_output_shape()
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D | avg_pool_float_1.model.cpp | 9 auto cons1 = model->addOperand(&type1); in CreateModel() local 16 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1); in CreateModel() 19 …ANEURALNETWORKS_AVERAGE_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {… in CreateModel() 39 auto cons1 = model->addOperand(&type1); in CreateModel_dynamic_output_shape() local 46 model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1); in CreateModel_dynamic_output_shape() 49 …ANEURALNETWORKS_AVERAGE_POOL_2D, {op1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act}, {… in CreateModel_dynamic_output_shape()
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/frameworks/ml/nn/runtime/test/specs/V1_0/ |
D | l2_pool_float.mod.py | 19 cons1 = Int32Scalar("cons1", 1) variable 23 model = model.Operation("L2_POOL_2D", i1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act).…
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D | avg_pool_float_1.mod.py | 20 cons1 = Int32Scalar("cons1", 1) variable 24 model = model.Operation("AVERAGE_POOL_2D", i1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, …
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D | max_pool_quant8_1.mod.py | 20 cons1 = Int32Scalar("cons1", 1) variable 24 model = model.Operation("MAX_POOL_2D", i1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act)…
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D | max_pool_float_1.mod.py | 20 cons1 = Int32Scalar("cons1", 1) variable 24 model = model.Operation("MAX_POOL_2D", i1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act)…
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D | avg_pool_quant8_1.mod.py | 20 cons1 = Int32Scalar("cons1", 1) variable 24 model = model.Operation("AVERAGE_POOL_2D", i1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, …
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D | avg_pool_quant8_4.mod.py | 20 cons1 = Int32Scalar("cons1", 1) variable 24 model = model.Operation("AVERAGE_POOL_2D", i1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, …
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/frameworks/ml/nn/runtime/test/specs/V1_1/ |
D | l2_pool_float_relaxed.mod.py | 19 cons1 = Int32Scalar("cons1", 1) variable 23 model = model.Operation("L2_POOL_2D", i1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act).…
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D | max_pool_float_1_relaxed.mod.py | 20 cons1 = Int32Scalar("cons1", 1) variable 24 model = model.Operation("MAX_POOL_2D", i1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act)…
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D | avg_pool_float_1_relaxed.mod.py | 20 cons1 = Int32Scalar("cons1", 1) variable 24 model = model.Operation("AVERAGE_POOL_2D", i1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, …
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