Searched defs:model (Results 426 - 450 of 784) sorted by relevance

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/frameworks/ml/nn/runtime/test/generated/models/
H A Dspace_to_batch_float_3_relaxed.model.cpp2 void CreateModel(Model *model) { argument
8 auto input = model->addOperand(&type0);
9 auto block_size = model->addOperand(&type1);
10 auto paddings = model->addOperand(&type2);
11 auto output = model->addOperand(&type3);
14 model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2);
16 model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4);
17 model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output});
19 model->identifyInputsAndOutputs(
23 model
[all...]
H A Dspace_to_batch_quant8_1.model.cpp2 void CreateModel(Model *model) { argument
8 auto input = model->addOperand(&type0);
9 auto block_size = model->addOperand(&type1);
10 auto paddings = model->addOperand(&type2);
11 auto output = model->addOperand(&type3);
14 model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2);
16 model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4);
17 model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output});
19 model->identifyInputsAndOutputs(
22 assert(model
[all...]
H A Dspace_to_batch_quant8_2.model.cpp2 void CreateModel(Model *model) { argument
8 auto input = model->addOperand(&type0);
9 auto block_size = model->addOperand(&type1);
10 auto paddings = model->addOperand(&type2);
11 auto output = model->addOperand(&type3);
14 model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2);
16 model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4);
17 model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output});
19 model->identifyInputsAndOutputs(
22 assert(model
[all...]
H A Dspace_to_batch_quant8_3.model.cpp2 void CreateModel(Model *model) { argument
8 auto input = model->addOperand(&type0);
9 auto block_size = model->addOperand(&type1);
10 auto paddings = model->addOperand(&type2);
11 auto output = model->addOperand(&type3);
14 model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2);
16 model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4);
17 model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output});
19 model->identifyInputsAndOutputs(
22 assert(model
[all...]
H A Dspace_to_batch_relaxed.model.cpp2 void CreateModel(Model *model) { argument
8 auto input = model->addOperand(&type0);
9 auto block_size = model->addOperand(&type1);
10 auto paddings = model->addOperand(&type2);
11 auto output = model->addOperand(&type3);
14 model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2);
16 model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4);
17 model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output});
19 model->identifyInputsAndOutputs(
23 model
[all...]
H A Dsvdf.model.cpp2 void CreateModel(Model *model) { argument
11 auto input = model->addOperand(&type0);
12 auto weights_feature = model->addOperand(&type1);
13 auto weights_time = model->addOperand(&type2);
14 auto bias = model->addOperand(&type3);
15 auto state_in = model->addOperand(&type4);
16 auto rank_param = model->addOperand(&type5);
17 auto activation_param = model->addOperand(&type5);
18 auto state_out = model->addOperand(&type4);
19 auto output = model
[all...]
H A Dsvdf2.model.cpp2 void CreateModel(Model *model) { argument
11 auto input = model->addOperand(&type0);
12 auto weights_feature = model->addOperand(&type1);
13 auto weights_time = model->addOperand(&type2);
14 auto bias = model->addOperand(&type3);
15 auto state_in = model->addOperand(&type4);
16 auto rank_param = model->addOperand(&type5);
17 auto activation_param = model->addOperand(&type5);
18 auto state_out = model->addOperand(&type4);
19 auto output = model
[all...]
H A Dsvdf2_relaxed.model.cpp2 void CreateModel(Model *model) { argument
11 auto input = model->addOperand(&type0);
12 auto weights_feature = model->addOperand(&type1);
13 auto weights_time = model->addOperand(&type2);
14 auto bias = model->addOperand(&type3);
15 auto state_in = model->addOperand(&type4);
16 auto rank_param = model->addOperand(&type5);
17 auto activation_param = model->addOperand(&type5);
18 auto state_out = model->addOperand(&type4);
19 auto output = model
[all...]
H A Dsvdf_relaxed.model.cpp2 void CreateModel(Model *model) { argument
11 auto input = model->addOperand(&type0);
12 auto weights_feature = model->addOperand(&type1);
13 auto weights_time = model->addOperand(&type2);
14 auto bias = model->addOperand(&type3);
15 auto state_in = model->addOperand(&type4);
16 auto rank_param = model->addOperand(&type5);
17 auto activation_param = model->addOperand(&type5);
18 auto state_out = model->addOperand(&type4);
19 auto output = model
[all...]
H A Dsvdf_state.model.cpp2 void CreateModel(Model *model) { argument
11 auto input = model->addOperand(&type0);
12 auto weights_feature = model->addOperand(&type1);
13 auto weights_time = model->addOperand(&type2);
14 auto bias = model->addOperand(&type3);
15 auto state_in = model->addOperand(&type4);
16 auto rank_param = model->addOperand(&type5);
17 auto activation_param = model->addOperand(&type5);
18 auto state_out = model->addOperand(&type4);
19 auto output = model
[all...]
H A Dsvdf_state_relaxed.model.cpp2 void CreateModel(Model *model) { argument
11 auto input = model->addOperand(&type0);
12 auto weights_feature = model->addOperand(&type1);
13 auto weights_time = model->addOperand(&type2);
14 auto bias = model->addOperand(&type3);
15 auto state_in = model->addOperand(&type4);
16 auto rank_param = model->addOperand(&type5);
17 auto activation_param = model->addOperand(&type5);
18 auto state_out = model->addOperand(&type4);
19 auto output = model
[all...]
/frameworks/ml/nn/runtime/test/specs/V1_0/
H A Dconcat_float_2.mod.py17 # model
18 model = Model() variable
29 model = model.Operation("CONCATENATION", input1, input2, axis0).To(output) variable
H A Dconcat_float_3.mod.py17 # model
18 model = Model() variable
29 model = model.Operation("CONCATENATION", input1, input2, axis1).To(output) variable
H A Dconcat_quant8_2.mod.py17 # model
18 model = Model() variable
29 model = model.Operation("CONCATENATION", input1, input2, axis0).To(output) variable
H A Dconcat_quant8_3.mod.py17 # model
18 model = Model() variable
29 model = model.Operation("CONCATENATION", input1, input2, axis1).To(output) variable
H A Dconv_1_h3_w2_SAME.mod.py0 model = Model()
10 model = model.Conv(i2, i0, i1, i4, i5, i6, i7).To(i3) variable
1 model = Model() variable
H A Dconv_1_h3_w2_VALID.mod.py0 model = Model()
10 model = model.Conv(i2, i0, i1, i4, i5, i6, i7).To(i3) variable
1 model = Model() variable
H A Dconv_3_h3_w2_SAME.mod.py0 model = Model()
10 model = model.Conv(i2, i0, i1, i4, i5, i6, i7).To(i3) variable
1 model = Model() variable
H A Dconv_3_h3_w2_VALID.mod.py0 model = Model()
10 model = model.Conv(i2, i0, i1, i4, i5, i6, i7).To(i3) variable
1 model = Model() variable
H A Dconv_quant8_2.mod.py16 model = Model() variable
28 model = model.Operation("CONV_2D", i1, f1, b1, pad_valid, stride3, variable
H A Ddepthwise_conv.mod.py0 model = Model()
11 model = model.DepthWiseConv(i2, i0, i1, i4, i5, i6, i7, i8).To(i3) variable
1 model = Model() variable
H A Ddepthwise_conv2d_float.mod.py17 model = Model() variable
27 model = model.Operation("DEPTHWISE_CONV_2D", variable
H A Ddepthwise_conv2d_float_2.mod.py17 model = Model() variable
27 model = model.Operation("DEPTHWISE_CONV_2D", variable
H A Ddepthwise_conv2d_float_large.mod.py17 model = Model() variable
27 model = model.Operation("DEPTHWISE_CONV_2D", variable
H A Ddepthwise_conv2d_float_large_2.mod.py17 model = Model() variable
27 model = model.Operation("DEPTHWISE_CONV_2D", variable

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