/frameworks/ml/nn/runtime/test/specs/V1_0/ |
H A 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(i3)
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H A 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(i3)
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H A 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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H A 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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H A 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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H A D | conv_quant8_2.mod.py | 22 act_none = Int32Scalar("act_none", 0) variable 29 stride1, act_none).To(output)
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H A 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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H A 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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/frameworks/ml/nn/runtime/test/specs/V1_1/ |
H A 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(i3)
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H A 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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H A 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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H A 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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/frameworks/ml/nn/runtime/test/generated/models/ |
H A D | avg_pool_float_5.model.cpp | 10 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});
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H A D | avg_pool_float_5_relaxed.model.cpp | 10 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});
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H A D | avg_pool_quant8_5.model.cpp | 10 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});
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H A D | l2_pool_float_2.model.cpp | 10 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});
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H A D | l2_pool_float_2_relaxed.model.cpp | 10 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});
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H A D | max_pool_float_4.model.cpp | 10 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});
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H A D | max_pool_float_4_relaxed.model.cpp | 10 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});
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H A D | max_pool_quant8_4.model.cpp | 10 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});
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H A D | conv_quant8_2.model.cpp | 13 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});
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H A D | depthwise_conv2d_float_2.model.cpp | 13 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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H A D | depthwise_conv2d_float_2_relaxed.model.cpp | 13 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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H A D | depthwise_conv2d_quant8_2.model.cpp | 13 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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