| /frameworks/ml/nn/runtime/test/specs/V1_0/ |
| rnn_state.mod.py | 27 hidden_state_in = Input("hidden_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (batches, units)) variable
34 model = model.Operation("RNN", input, weights, recurrent_weights, bias, hidden_state_in,
94 input0[hidden_state_in] = [
|
| rnn.mod.py | 27 hidden_state_in = Input("hidden_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (batches, units)) variable
34 model = model.Operation("RNN", input, weights, recurrent_weights, bias, hidden_state_in,
193 input0[hidden_state_in] = [0 for x in range(batches * units)]
|
| /frameworks/ml/nn/runtime/test/specs/V1_1/ |
| rnn_state_relaxed.mod.py | 27 hidden_state_in = Input("hidden_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (batches, units)) variable
34 model = model.Operation("RNN", input, weights, recurrent_weights, bias, hidden_state_in,
95 input0[hidden_state_in] = [
|
| rnn_relaxed.mod.py | 27 hidden_state_in = Input("hidden_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (batches, units)) variable
34 model = model.Operation("RNN", input, weights, recurrent_weights, bias, hidden_state_in,
194 input0[hidden_state_in] = [0 for x in range(batches * units)]
|
| /frameworks/ml/nn/runtime/test/generated/models/ |
| rnn.model.cpp | 14 auto hidden_state_in = model->addOperand(&type4); local
21 model->addOperation(ANEURALNETWORKS_RNN, {input, weights, recurrent_weights, bias, hidden_state_in, activation_param}, {hidden_state_out, output});
24 {input, weights, recurrent_weights, bias, hidden_state_in},
|
| rnn_relaxed.model.cpp | 14 auto hidden_state_in = model->addOperand(&type4); local
21 model->addOperation(ANEURALNETWORKS_RNN, {input, weights, recurrent_weights, bias, hidden_state_in, activation_param}, {hidden_state_out, output});
24 {input, weights, recurrent_weights, bias, hidden_state_in},
|
| rnn_state.model.cpp | 14 auto hidden_state_in = model->addOperand(&type4); local
21 model->addOperation(ANEURALNETWORKS_RNN, {input, weights, recurrent_weights, bias, hidden_state_in, activation_param}, {hidden_state_out, output});
24 {input, weights, recurrent_weights, bias, hidden_state_in},
|
| rnn_state_relaxed.model.cpp | 14 auto hidden_state_in = model->addOperand(&type4); local
21 model->addOperation(ANEURALNETWORKS_RNN, {input, weights, recurrent_weights, bias, hidden_state_in, activation_param}, {hidden_state_out, output});
24 {input, weights, recurrent_weights, bias, hidden_state_in},
|
