Searched defs:model (Results 226 - 250 of 784) sorted by relevance

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/frameworks/ml/nn/runtime/test/generated/models/
H A Dspace_to_depth_quant8_2.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());
H A Dsqueeze.model.cpp2 void CreateModel(Model *model) { argument
7 auto input = model->addOperand(&type0);
8 auto squeezeDims = model->addOperand(&type1);
9 auto output = model->addOperand(&type2);
12 model->setOperandValue(squeezeDims, squeezeDims_init, sizeof(int32_t) * 2);
13 model->addOperation(ANEURALNETWORKS_SQUEEZE, {input, squeezeDims}, {output});
15 model->identifyInputsAndOutputs(
18 assert(model->isValid());
H A Dsqueeze_float_1.model.cpp2 void CreateModel(Model *model) { argument
7 auto input = model->addOperand(&type0);
8 auto squeezeDims = model->addOperand(&type1);
9 auto output = model->addOperand(&type2);
12 model->setOperandValue(squeezeDims, squeezeDims_init, sizeof(int32_t) * 1);
13 model->addOperation(ANEURALNETWORKS_SQUEEZE, {input, squeezeDims}, {output});
15 model->identifyInputsAndOutputs(
18 assert(model->isValid());
H A Dsqueeze_float_1_relaxed.model.cpp2 void CreateModel(Model *model) { argument
7 auto input = model->addOperand(&type0);
8 auto squeezeDims = model->addOperand(&type1);
9 auto output = model->addOperand(&type2);
12 model->setOperandValue(squeezeDims, squeezeDims_init, sizeof(int32_t) * 1);
13 model->addOperation(ANEURALNETWORKS_SQUEEZE, {input, squeezeDims}, {output});
15 model->identifyInputsAndOutputs(
19 model->relaxComputationFloat32toFloat16(true);
20 assert(model->isValid());
H A Dsqueeze_quant8_1.model.cpp2 void CreateModel(Model *model) { argument
7 auto input = model->addOperand(&type0);
8 auto squeezeDims = model->addOperand(&type1);
9 auto output = model->addOperand(&type2);
12 model->setOperandValue(squeezeDims, squeezeDims_init, sizeof(int32_t) * 1);
13 model->addOperation(ANEURALNETWORKS_SQUEEZE, {input, squeezeDims}, {output});
15 model->identifyInputsAndOutputs(
18 assert(model->isValid());
H A Dsqueeze_relaxed.model.cpp2 void CreateModel(Model *model) { argument
7 auto input = model->addOperand(&type0);
8 auto squeezeDims = model->addOperand(&type1);
9 auto output = model->addOperand(&type2);
12 model->setOperandValue(squeezeDims, squeezeDims_init, sizeof(int32_t) * 2);
13 model->addOperation(ANEURALNETWORKS_SQUEEZE, {input, squeezeDims}, {output});
15 model->identifyInputsAndOutputs(
19 model->relaxComputationFloat32toFloat16(true);
20 assert(model->isValid());
H A Dsub.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_SUB, {op1, op2, act}, {op3});
15 model->identifyInputsAndOutputs(
18 assert(model->isValid());
H A Dsub_broadcast_float.model.cpp2 void CreateModel(Model *model) { argument
7 auto op1 = model->addOperand(&type0);
8 auto op2 = model->addOperand(&type1);
9 auto act = model->addOperand(&type2);
10 auto op3 = model->addOperand(&type1);
13 model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
14 model->addOperation(ANEURALNETWORKS_SUB, {op1, op2, act}, {op3});
16 model->identifyInputsAndOutputs(
19 assert(model->isValid());
H A Dsub_broadcast_float_relaxed.model.cpp2 void CreateModel(Model *model) { argument
7 auto op1 = model->addOperand(&type0);
8 auto op2 = model->addOperand(&type1);
9 auto act = model->addOperand(&type2);
10 auto op3 = model->addOperand(&type1);
13 model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
14 model->addOperation(ANEURALNETWORKS_SUB, {op1, op2, act}, {op3});
16 model->identifyInputsAndOutputs(
20 model->relaxComputationFloat32toFloat16(true);
21 assert(model
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H A Dsub_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_SUB, {op1, op2, act}, {op3});
15 model->identifyInputsAndOutputs(
19 model->relaxComputationFloat32toFloat16(true);
20 assert(model
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H A Dtranspose.model.cpp2 void CreateModel(Model *model) { argument
6 auto input = model->addOperand(&type0);
7 auto perms = model->addOperand(&type1);
8 auto output = model->addOperand(&type0);
11 model->setOperandValue(perms, perms_init, sizeof(int32_t) * 4);
12 model->addOperation(ANEURALNETWORKS_TRANSPOSE, {input, perms}, {output});
14 model->identifyInputsAndOutputs(
17 assert(model->isValid());
H A Dtranspose_float_1.model.cpp2 void CreateModel(Model *model) { argument
7 auto input = model->addOperand(&type0);
8 auto perms = model->addOperand(&type1);
9 auto output = model->addOperand(&type2);
12 model->setOperandValue(perms, perms_init, sizeof(int32_t) * 4);
13 model->addOperation(ANEURALNETWORKS_TRANSPOSE, {input, perms}, {output});
15 model->identifyInputsAndOutputs(
18 assert(model->isValid());
H A Dtranspose_float_1_relaxed.model.cpp2 void CreateModel(Model *model) { argument
7 auto input = model->addOperand(&type0);
8 auto perms = model->addOperand(&type1);
9 auto output = model->addOperand(&type2);
12 model->setOperandValue(perms, perms_init, sizeof(int32_t) * 4);
13 model->addOperation(ANEURALNETWORKS_TRANSPOSE, {input, perms}, {output});
15 model->identifyInputsAndOutputs(
19 model->relaxComputationFloat32toFloat16(true);
20 assert(model->isValid());
H A Dtranspose_quant8_1.model.cpp2 void CreateModel(Model *model) { argument
7 auto input = model->addOperand(&type0);
8 auto perms = model->addOperand(&type1);
9 auto output = model->addOperand(&type2);
12 model->setOperandValue(perms, perms_init, sizeof(int32_t) * 4);
13 model->addOperation(ANEURALNETWORKS_TRANSPOSE, {input, perms}, {output});
15 model->identifyInputsAndOutputs(
18 assert(model->isValid());
H A Dtranspose_relaxed.model.cpp2 void CreateModel(Model *model) { argument
6 auto input = model->addOperand(&type0);
7 auto perms = model->addOperand(&type1);
8 auto output = model->addOperand(&type0);
11 model->setOperandValue(perms, perms_init, sizeof(int32_t) * 4);
12 model->addOperation(ANEURALNETWORKS_TRANSPOSE, {input, perms}, {output});
14 model->identifyInputsAndOutputs(
18 model->relaxComputationFloat32toFloat16(true);
19 assert(model->isValid());
/frameworks/ml/nn/runtime/test/specs/V1_0/
H A Davg_pool_float_1.mod.py17 # model
18 model = Model() variable
24 model = model.Operation("AVERAGE_POOL_2D", i1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act).To(i3) variable
H A Davg_pool_float_5.mod.py17 # model
18 model = Model() variable
24 model = model.Operation("AVERAGE_POOL_2D", i1, pad_same, cons2, cons2, cons2, cons2, act_none).To(i3) variable
H A Davg_pool_quant8_1.mod.py17 # model
18 model = Model() variable
24 model = model.Operation("AVERAGE_POOL_2D", i1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act).To(o) variable
H A Davg_pool_quant8_4.mod.py17 # model
18 model = Model() variable
24 model = model.Operation("AVERAGE_POOL_2D", i1, pad0, pad0, pad0, pad0, cons1, cons1, cons1, cons1, act2).To(o) variable
H A Davg_pool_quant8_5.mod.py17 # model
18 model = Model() variable
24 model = model.Operation("AVERAGE_POOL_2D", i1, pad_same, cons2, cons2, cons2, cons2, act_none).To(i3) variable
H A Dconv_float.mod.py17 model = Model() variable
28 model = model.Operation("CONV_2D", i1, f1, b1, pad0, pad0, pad0, pad0, stride, stride, act).To(output) variable
H A Dconv_float_2.mod.py17 model = Model() variable
26 model = model.Operation("CONV_2D", i1, f1, b1, pad_same, stride, stride, act_relu).To(output) variable
H A Dconv_float_channels.mod.py17 model = Model() variable
28 model = model.Operation("CONV_2D", i1, f1, b1, pad0, pad0, pad0, pad0, stride, stride, act).To(output) variable
H A Dconv_float_channels_weights_as_inputs.mod.py17 model = Model() variable
28 model = model.Operation("CONV_2D", i1, f1, b1, pad0, pad0, pad0, pad0, stride, stride, act).To(output) variable
H A Dconv_float_large.mod.py17 model = Model() variable
28 model = model.Operation("CONV_2D", i1, f1, b1, pad0, pad0, pad0, pad0, stride, stride, act).To(output) variable

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