revised lstm_cell.js and lstm_cell_test.js

src/lstm_cell.js

@@ -10,25 +10,27 @@ import {transpose} from './transpose.js';
 import {validateLstmCellParams} from './lib/validate-input.js';
 
 /**
- *
+ *A single time step of the Long Short-Term Memory [LSTM] recurrent network
+ *using a cell state, an input, output, and forget gate to compute the cell
+ *state and the hidden state of the next time step that rolls into the output
+ *across the temporal sequence of the network.
  * @param {Tensor} input
  * @param {Tensor} weight
  * @param {Tensor} recurrentWeight
  * @param {Tensor} hiddenState
  * @param {Tensor} cellState
  * @param {Number} hiddenSize
  * @param {MLLstmCellOptions} options
- * return {Tensor}
+ * @return {Tensor}
  */
-
 export function lstmCell(input, weight, recurrentWeight, hiddenState, cellState, hiddenSize,
     {bias, recurrentBias, peepholeWeight,
       layout = 'iofg', activations = [sigmoid, tanh, tanh]}={}) {
   validateLstmCellParams(...arguments);
   const zero = new Scalar(0);
   const inputSize = input.shape[1];
-  const starts = layout === 'iofg' ? {i: 0, o: hiddenSize, f: 2* hiddenSize, g: 3*hiddenSize} :
-  {i: 0, f: hiddenSize, g: 2* hiddenSize, o: 3*hiddenSize};
+  const starts = layout === 'iofg' ? {i: 0, o: hiddenSize, f: 2 * hiddenSize, g: 3 *hiddenSize} :
+  {i: 0, f: hiddenSize, g: 2 * hiddenSize, o: 3 * hiddenSize};
   const activation0 = activations[0];
   const activation1 = activations[1];
   const activation2 = activations[2];

test/lstm_cell_test.js

@@ -6,7 +6,7 @@ import {Tensor} from '../src/lib/tensor.js';
 import * as utils from './utils.js';
 
 describe('test lstmCell', function() {
-  it.only('lstmCell lstmCell activations=[relu, relu, relu]', function() {
+  it('lstmCell lstmCell activations=[relu, relu, relu]', function() {
     const batchSize = 2;
     const inputSize = 2;
     const hiddenSize = 2;