Searched defs:model (Results 201 - 225 of 784) sorted by relevance

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/frameworks/ml/nn/runtime/test/generated/models/
H A Dmul_relu.model.cpp2 void CreateModel(Model *model) { argument
6 auto op1 = model->addOperand(&type0);
7 auto op2 = model->addOperand(&type0);
8 auto act = model->addOperand(&type1);
9 auto op3 = model->addOperand(&type0);
12 model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
13 model->addOperation(ANEURALNETWORKS_MUL, {op1, op2, act}, {op3});
15 model->identifyInputsAndOutputs(
18 assert(model->isValid());
H A Dmul_relu_relaxed.model.cpp2 void CreateModel(Model *model) { argument
6 auto op1 = model->addOperand(&type0);
7 auto op2 = model->addOperand(&type0);
8 auto act = model->addOperand(&type1);
9 auto op3 = model->addOperand(&type0);
12 model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
13 model->addOperation(ANEURALNETWORKS_MUL, {op1, op2, act}, {op3});
15 model->identifyInputsAndOutputs(
19 model->relaxComputationFloat32toFloat16(true);
20 assert(model
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H A Dpad.model.cpp2 void CreateModel(Model *model) { argument
7 auto op1 = model->addOperand(&type0);
8 auto op2 = model->addOperand(&type1);
9 auto op3 = model->addOperand(&type2);
12 model->setOperandValue(op2, op2_init, sizeof(int32_t) * 8);
13 model->addOperation(ANEURALNETWORKS_PAD, {op1, op2}, {op3});
15 model->identifyInputsAndOutputs(
18 assert(model->isValid());
H A Dpad_float_1.model.cpp2 void CreateModel(Model *model) { argument
7 auto op1 = model->addOperand(&type0);
8 auto op2 = model->addOperand(&type1);
9 auto op3 = model->addOperand(&type2);
12 model->setOperandValue(op2, op2_init, sizeof(int32_t) * 8);
13 model->addOperation(ANEURALNETWORKS_PAD, {op1, op2}, {op3});
15 model->identifyInputsAndOutputs(
18 assert(model->isValid());
H A Dpad_float_1_relaxed.model.cpp2 void CreateModel(Model *model) { argument
7 auto op1 = model->addOperand(&type0);
8 auto op2 = model->addOperand(&type1);
9 auto op3 = model->addOperand(&type2);
12 model->setOperandValue(op2, op2_init, sizeof(int32_t) * 8);
13 model->addOperation(ANEURALNETWORKS_PAD, {op1, op2}, {op3});
15 model->identifyInputsAndOutputs(
19 model->relaxComputationFloat32toFloat16(true);
20 assert(model->isValid());
H A Dpad_relaxed.model.cpp2 void CreateModel(Model *model) { argument
7 auto op1 = model->addOperand(&type0);
8 auto op2 = model->addOperand(&type1);
9 auto op3 = model->addOperand(&type2);
12 model->setOperandValue(op2, op2_init, sizeof(int32_t) * 8);
13 model->addOperation(ANEURALNETWORKS_PAD, {op1, op2}, {op3});
15 model->identifyInputsAndOutputs(
19 model->relaxComputationFloat32toFloat16(true);
20 assert(model->isValid());
H A Dreshape.model.cpp2 void CreateModel(Model *model) { argument
7 auto op1 = model->addOperand(&type0);
8 auto op2 = model->addOperand(&type1);
9 auto op3 = model->addOperand(&type2);
12 model->setOperandValue(op2, op2_init, sizeof(int32_t) * 1);
13 model->addOperation(ANEURALNETWORKS_RESHAPE, {op1, op2}, {op3});
15 model->identifyInputsAndOutputs(
18 assert(model->isValid());
H A Dreshape_quant8.model.cpp2 void CreateModel(Model *model) { argument
7 auto op1 = model->addOperand(&type0);
8 auto op2 = model->addOperand(&type1);
9 auto op3 = model->addOperand(&type2);
12 model->setOperandValue(op2, op2_init, sizeof(int32_t) * 1);
13 model->addOperation(ANEURALNETWORKS_RESHAPE, {op1, op2}, {op3});
15 model->identifyInputsAndOutputs(
18 assert(model->isValid());
H A Dreshape_quant8_weights_as_inputs.model.cpp2 void CreateModel(Model *model) { argument
7 auto op1 = model->addOperand(&type0);
8 auto op2 = model->addOperand(&type1);
9 auto op3 = model->addOperand(&type2);
11 model->addOperation(ANEURALNETWORKS_RESHAPE, {op1, op2}, {op3});
13 model->identifyInputsAndOutputs(
16 assert(model->isValid());
H A Dreshape_relaxed.model.cpp2 void CreateModel(Model *model) { argument
7 auto op1 = model->addOperand(&type0);
8 auto op2 = model->addOperand(&type1);
9 auto op3 = model->addOperand(&type2);
12 model->setOperandValue(op2, op2_init, sizeof(int32_t) * 1);
13 model->addOperation(ANEURALNETWORKS_RESHAPE, {op1, op2}, {op3});
15 model->identifyInputsAndOutputs(
19 model->relaxComputationFloat32toFloat16(true);
20 assert(model->isValid());
H A Dreshape_weights_as_inputs.model.cpp2 void CreateModel(Model *model) { argument
7 auto op1 = model->addOperand(&type0);
8 auto op2 = model->addOperand(&type1);
9 auto op3 = model->addOperand(&type2);
11 model->addOperation(ANEURALNETWORKS_RESHAPE, {op1, op2}, {op3});
13 model->identifyInputsAndOutputs(
16 assert(model->isValid());
H A Dreshape_weights_as_inputs_relaxed.model.cpp2 void CreateModel(Model *model) { argument
7 auto op1 = model->addOperand(&type0);
8 auto op2 = model->addOperand(&type1);
9 auto op3 = model->addOperand(&type2);
11 model->addOperation(ANEURALNETWORKS_RESHAPE, {op1, op2}, {op3});
13 model->identifyInputsAndOutputs(
17 model->relaxComputationFloat32toFloat16(true);
18 assert(model->isValid());
H A Dsoftmax_float_1.model.cpp2 void CreateModel(Model *model) { argument
6 auto input = model->addOperand(&type0);
7 auto beta = model->addOperand(&type1);
8 auto output = model->addOperand(&type0);
11 model->setOperandValue(beta, beta_init, sizeof(float) * 1);
12 model->addOperation(ANEURALNETWORKS_SOFTMAX, {input, beta}, {output});
14 model->identifyInputsAndOutputs(
17 assert(model->isValid());
H A Dsoftmax_float_1_relaxed.model.cpp2 void CreateModel(Model *model) { argument
6 auto input = model->addOperand(&type0);
7 auto beta = model->addOperand(&type1);
8 auto output = model->addOperand(&type0);
11 model->setOperandValue(beta, beta_init, sizeof(float) * 1);
12 model->addOperation(ANEURALNETWORKS_SOFTMAX, {input, beta}, {output});
14 model->identifyInputsAndOutputs(
18 model->relaxComputationFloat32toFloat16(true);
19 assert(model->isValid());
H A Dsoftmax_float_2.model.cpp2 void CreateModel(Model *model) { argument
6 auto input = model->addOperand(&type0);
7 auto beta = model->addOperand(&type1);
8 auto output = model->addOperand(&type0);
11 model->setOperandValue(beta, beta_init, sizeof(float) * 1);
12 model->addOperation(ANEURALNETWORKS_SOFTMAX, {input, beta}, {output});
14 model->identifyInputsAndOutputs(
17 assert(model->isValid());
H A Dsoftmax_float_2_relaxed.model.cpp2 void CreateModel(Model *model) { argument
6 auto input = model->addOperand(&type0);
7 auto beta = model->addOperand(&type1);
8 auto output = model->addOperand(&type0);
11 model->setOperandValue(beta, beta_init, sizeof(float) * 1);
12 model->addOperation(ANEURALNETWORKS_SOFTMAX, {input, beta}, {output});
14 model->identifyInputsAndOutputs(
18 model->relaxComputationFloat32toFloat16(true);
19 assert(model->isValid());
H A Dsoftmax_quant8_1.model.cpp2 void CreateModel(Model *model) { argument
7 auto input = model->addOperand(&type0);
8 auto beta = model->addOperand(&type1);
9 auto output = model->addOperand(&type2);
12 model->setOperandValue(beta, beta_init, sizeof(float) * 1);
13 model->addOperation(ANEURALNETWORKS_SOFTMAX, {input, beta}, {output});
15 model->identifyInputsAndOutputs(
18 assert(model->isValid());
H A Dsoftmax_quant8_2.model.cpp2 void CreateModel(Model *model) { argument
7 auto input = model->addOperand(&type0);
8 auto beta = model->addOperand(&type1);
9 auto output = model->addOperand(&type2);
12 model->setOperandValue(beta, beta_init, sizeof(float) * 1);
13 model->addOperation(ANEURALNETWORKS_SOFTMAX, {input, beta}, {output});
15 model->identifyInputsAndOutputs(
18 assert(model->isValid());
H A Dspace_to_depth_float_1.model.cpp2 void CreateModel(Model *model) { argument
7 auto input = model->addOperand(&type0);
8 auto block_size = model->addOperand(&type1);
9 auto output = model->addOperand(&type2);
12 model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 1);
13 model->addOperation(ANEURALNETWORKS_SPACE_TO_DEPTH, {input, block_size}, {output});
15 model->identifyInputsAndOutputs(
18 assert(model->isValid());
H A Dspace_to_depth_float_1_relaxed.model.cpp2 void CreateModel(Model *model) { argument
7 auto input = model->addOperand(&type0);
8 auto block_size = model->addOperand(&type1);
9 auto output = model->addOperand(&type2);
12 model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 1);
13 model->addOperation(ANEURALNETWORKS_SPACE_TO_DEPTH, {input, block_size}, {output});
15 model->identifyInputsAndOutputs(
19 model->relaxComputationFloat32toFloat16(true);
20 assert(model->isValid());
H A Dspace_to_depth_float_2.model.cpp2 void CreateModel(Model *model) { argument
7 auto input = model->addOperand(&type0);
8 auto block_size = model->addOperand(&type1);
9 auto output = model->addOperand(&type2);
12 model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 1);
13 model->addOperation(ANEURALNETWORKS_SPACE_TO_DEPTH, {input, block_size}, {output});
15 model->identifyInputsAndOutputs(
18 assert(model->isValid());
H A Dspace_to_depth_float_2_relaxed.model.cpp2 void CreateModel(Model *model) { argument
7 auto input = model->addOperand(&type0);
8 auto block_size = model->addOperand(&type1);
9 auto output = model->addOperand(&type2);
12 model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 1);
13 model->addOperation(ANEURALNETWORKS_SPACE_TO_DEPTH, {input, block_size}, {output});
15 model->identifyInputsAndOutputs(
19 model->relaxComputationFloat32toFloat16(true);
20 assert(model->isValid());
H A Dspace_to_depth_float_3.model.cpp2 void CreateModel(Model *model) { argument
7 auto input = model->addOperand(&type0);
8 auto block_size = model->addOperand(&type1);
9 auto output = model->addOperand(&type2);
12 model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 1);
13 model->addOperation(ANEURALNETWORKS_SPACE_TO_DEPTH, {input, block_size}, {output});
15 model->identifyInputsAndOutputs(
18 assert(model->isValid());
H A Dspace_to_depth_float_3_relaxed.model.cpp2 void CreateModel(Model *model) { argument
7 auto input = model->addOperand(&type0);
8 auto block_size = model->addOperand(&type1);
9 auto output = model->addOperand(&type2);
12 model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 1);
13 model->addOperation(ANEURALNETWORKS_SPACE_TO_DEPTH, {input, block_size}, {output});
15 model->identifyInputsAndOutputs(
19 model->relaxComputationFloat32toFloat16(true);
20 assert(model->isValid());
H A Dspace_to_depth_quant8_1.model.cpp2 void CreateModel(Model *model) { argument
7 auto input = model->addOperand(&type0);
8 auto radius = model->addOperand(&type1);
9 auto output = model->addOperand(&type2);
12 model->setOperandValue(radius, radius_init, sizeof(int32_t) * 1);
13 model->addOperation(ANEURALNETWORKS_SPACE_TO_DEPTH, {input, radius}, {output});
15 model->identifyInputsAndOutputs(
18 assert(model->isValid());

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