Searched refs:stride (Results 51 - 75 of 337) sorted by relevance

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/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});
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});
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});
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});
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});
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});
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});
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});
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});
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});
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});
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});
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});
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});
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});
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});
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});
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});
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});
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});
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});
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});
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});
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});
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});

Completed in 71 milliseconds

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Indexes created Sun Aug 12 02:23:12 CEST 2018