| /frameworks/ml/nn/runtime/test/specs/V1_0/ |
| H A D | svdf_state.mod.py | 28 state_in = Input("state_in", "TENSOR_FLOAT32", "{%d, %d}" % (batches, memory_size*units)) variable
34 model = model.Operation("SVDF", input, weights_feature, weights_time, bias, state_in,
63 input0[state_in] = [
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| H A D | svdf.mod.py | 30 state_in = Input("state_in", "TENSOR_FLOAT32", "{%d, %d}" % (batches, memory_size*features)) variable
36 model = model.Operation("SVDF", input, weights_feature, weights_time, bias, state_in,
60 state_in: [0 for _ in range(batches * memory_size * features)],
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| H A D | svdf2.mod.py | 30 state_in = Input("state_in", "TENSOR_FLOAT32", "{%d, %d}" % (batches, memory_size*features)) variable
36 model = model.Operation("SVDF", input, weights_feature, weights_time, bias, state_in,
75 state_in: [0 for _ in range(batches * memory_size * features)],
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| /frameworks/ml/nn/runtime/test/specs/V1_1/ |
| H A D | svdf_state_relaxed.mod.py | 28 state_in = Input("state_in", "TENSOR_FLOAT32", "{%d, %d}" % (batches, memory_size*units)) variable
34 model = model.Operation("SVDF", input, weights_feature, weights_time, bias, state_in,
64 input0[state_in] = [
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| H A D | svdf2_relaxed.mod.py | 30 state_in = Input("state_in", "TENSOR_FLOAT32", "{%d, %d}" % (batches, memory_size*features)) variable
36 model = model.Operation("SVDF", input, weights_feature, weights_time, bias, state_in,
76 state_in: [0 for _ in range(batches * memory_size * features)],
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| H A D | svdf_relaxed.mod.py | 30 state_in = Input("state_in", "TENSOR_FLOAT32", "{%d, %d}" % (batches, memory_size*features)) variable
36 model = model.Operation("SVDF", input, weights_feature, weights_time, bias, state_in,
61 state_in: [0 for _ in range(batches * memory_size * features)],
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| /frameworks/ml/nn/runtime/test/generated/models/ |
| H A D | svdf.model.cpp | 15 auto state_in = model->addOperand(&type4); local
25 model->addOperation(ANEURALNETWORKS_SVDF, {input, weights_feature, weights_time, bias, state_in, rank_param, activation_param}, {state_out, output});
28 {input, weights_feature, weights_time, bias, state_in},
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| H A D | svdf2.model.cpp | 15 auto state_in = model->addOperand(&type4); local
25 model->addOperation(ANEURALNETWORKS_SVDF, {input, weights_feature, weights_time, bias, state_in, rank_param, activation_param}, {state_out, output});
28 {input, weights_feature, weights_time, bias, state_in},
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| H A D | svdf2_relaxed.model.cpp | 15 auto state_in = model->addOperand(&type4); local
25 model->addOperation(ANEURALNETWORKS_SVDF, {input, weights_feature, weights_time, bias, state_in, rank_param, activation_param}, {state_out, output});
28 {input, weights_feature, weights_time, bias, state_in},
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| H A D | svdf_relaxed.model.cpp | 15 auto state_in = model->addOperand(&type4); local
25 model->addOperation(ANEURALNETWORKS_SVDF, {input, weights_feature, weights_time, bias, state_in, rank_param, activation_param}, {state_out, output});
28 {input, weights_feature, weights_time, bias, state_in},
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| H A D | svdf_state.model.cpp | 15 auto state_in = model->addOperand(&type4); local
25 model->addOperation(ANEURALNETWORKS_SVDF, {input, weights_feature, weights_time, bias, state_in, rank_param, activation_param}, {state_out, output});
28 {input, weights_feature, weights_time, bias, state_in},
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| H A D | svdf_state_relaxed.model.cpp | 15 auto state_in = model->addOperand(&type4); local
25 model->addOperation(ANEURALNETWORKS_SVDF, {input, weights_feature, weights_time, bias, state_in, rank_param, activation_param}, {state_out, output});
28 {input, weights_feature, weights_time, bias, state_in},
|