Searched refs:hidden_state_in (Results 1 - 4 of 4) sorted by relevance
| /frameworks/ml/nn/runtime/test/specs/ |
| H A D | 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,
95 input0[hidden_state_in] = [
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| H A D | 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,
194 input0[hidden_state_in] = [0 for x in range(batches * units)]
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| /frameworks/ml/nn/runtime/test/generated/models/ |
| H A D | rnn.model.cpp | 14 auto hidden_state_in = model->addOperand(&type4); local
19 model->addOperation(ANEURALNETWORKS_RNN, {input, weights, recurrent_weights, bias, hidden_state_in, activation_param}, {hidden_state_out, output});
22 {input, weights, recurrent_weights, bias, hidden_state_in, activation_param},
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| H A D | rnn_state.model.cpp | 14 auto hidden_state_in = model->addOperand(&type4); local
19 model->addOperation(ANEURALNETWORKS_RNN, {input, weights, recurrent_weights, bias, hidden_state_in, activation_param}, {hidden_state_out, output});
22 {input, weights, recurrent_weights, bias, hidden_state_in, activation_param},
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