/frameworks/ml/nn/runtime/test/generated/models/ |
H A D | avg_pool_float_3_relaxed.model.cpp | 8 auto stride = model->addOperand(&type1); local 15 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 22 model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {i0, padding, padding, padding, padding, stride, stride, filter, filter, activation}, {output});
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H A D | avg_pool_float_4.model.cpp | 8 auto stride = model->addOperand(&type1); local 15 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 22 model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {i0, padding, padding, padding, padding, stride, stride, filter, filter, relu6_activation}, {output});
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H A D | avg_pool_float_4_relaxed.model.cpp | 8 auto stride = model->addOperand(&type1); local 15 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 22 model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {i0, padding, padding, padding, padding, stride, stride, filter, filter, relu6_activation}, {output});
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H A D | avg_pool_quant8_2.model.cpp | 8 auto stride = model->addOperand(&type1); local 15 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 22 model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {i0, padding, padding, padding, padding, stride, stride, filter, filter, activation}, {output});
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H A D | avg_pool_quant8_3.model.cpp | 8 auto stride = model->addOperand(&type1); local 15 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 22 model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {i0, padding, padding, padding, padding, stride, stride, filter, filter, activation}, {output});
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H A D | conv_float.model.cpp | 13 auto stride = model->addOperand(&type3); local 25 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 26 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
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H A D | conv_float_2.model.cpp | 13 auto stride = model->addOperand(&type3); local 25 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 26 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad_same, stride, stride, act_relu}, {op4});
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H A D | conv_float_2_relaxed.model.cpp | 13 auto stride = model->addOperand(&type3); local 25 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 26 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad_same, stride, stride, act_relu}, {op4});
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H A D | conv_float_channels.model.cpp | 13 auto stride = model->addOperand(&type3); local 25 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 26 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
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H A D | conv_float_channels_relaxed.model.cpp | 13 auto stride = model->addOperand(&type3); local 25 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 26 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
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H A D | conv_float_channels_weights_as_inputs.model.cpp | 13 auto stride = model->addOperand(&type3); local 21 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 22 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
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H A D | conv_float_channels_weights_as_inputs_relaxed.model.cpp | 13 auto stride = model->addOperand(&type3); local 21 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 22 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
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H A D | conv_float_large.model.cpp | 13 auto stride = model->addOperand(&type3); local 25 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 26 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
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H A D | conv_float_large_relaxed.model.cpp | 13 auto stride = model->addOperand(&type3); local 25 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 26 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
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H A D | conv_float_large_weights_as_inputs.model.cpp | 13 auto stride = model->addOperand(&type3); local 21 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 22 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
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H A D | conv_float_large_weights_as_inputs_relaxed.model.cpp | 13 auto stride = model->addOperand(&type3); local 21 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 22 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
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H A D | conv_float_relaxed.model.cpp | 13 auto stride = model->addOperand(&type3); local 25 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 26 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
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H A D | conv_float_weights_as_inputs.model.cpp | 13 auto stride = model->addOperand(&type3); local 21 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 22 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
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H A D | conv_float_weights_as_inputs_relaxed.model.cpp | 13 auto stride = model->addOperand(&type3); local 21 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 22 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
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H A D | conv_quant8.model.cpp | 14 auto stride = model->addOperand(&type3); local 26 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 27 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
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H A D | conv_quant8_channels.model.cpp | 14 auto stride = model->addOperand(&type3); local 26 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 27 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
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H A D | conv_quant8_channels_weights_as_inputs.model.cpp | 14 auto stride = model->addOperand(&type3); local 22 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 23 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
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H A D | conv_quant8_large.model.cpp | 14 auto stride = model->addOperand(&type3); local 26 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 27 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
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H A D | conv_quant8_large_weights_as_inputs.model.cpp | 14 auto stride = model->addOperand(&type3); local 22 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 23 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
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H A D | conv_quant8_overflow.model.cpp | 14 auto stride = model->addOperand(&type3); local 26 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 27 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
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