create weight row matrices on layer initialization, not call()

src/layers/convolutional/Convolution2D.js

@@ -67,6 +67,8 @@ export default class Convolution2D extends Layer {
       weightsArr[0].tensor = weightsArr[0].tensor.transpose(2, 3, 1, 0)
     }
     super.setWeights(weightsArr)
+
+    this._wRowsMat = this._w2row()
   }
 
   /**
@@ -161,11 +163,10 @@ export default class Convolution2D extends Layer {
 
   /**
    * Convert filter weights to row matrix
-   * @param {Tensor} x
-   * @returns {Tensor} x
+   * @returns {Tensor} wRowsMat
    */
-  _w2row (x) {
-    const inputChannels = x.tensor.shape[2]
+  _w2row () {
+    const inputChannels = this.weights.W.tensor.shape[2]
     const [nbFilter, nbRow, nbCol] = this.kernelShape
     const patchLen = nbRow * nbCol * inputChannels
 
@@ -192,13 +193,24 @@ export default class Convolution2D extends Layer {
     if (this.dimOrdering === 'th') {
       x.tensor = x.tensor.transpose(1, 2, 0)
     }
-
+    let startTime = performance.now()
     this._calcOutputShape(x)
+    let endTime = performance.now()
+    if (this.name === 'conv1') console.log('_calcOutputShape', endTime - startTime)
+    startTime = performance.now()
     this._padInput(x)
-
+    endTime = performance.now()
+    if (this.name === 'conv1') console.log('_padInput', endTime - startTime)
+    startTime = performance.now()
     const imColsMat = this._im2col(x)
-    const wRowsMat = this._w2row(x)
+    endTime = performance.now()
+    if (this.name === 'conv1') console.log('imColsMat', endTime - startTime)
+    startTime = performance.now()
+    const wRowsMat = this._wRowsMat
+    endTime = performance.now()
+    if (this.name === 'conv1') console.log('wRowsMat', endTime - startTime)
 
+    startTime = performance.now()
     const nbFilter = this.kernelShape[0]
     const outputRows = this.outputShape[0]
     const outputCols = this.outputShape[1]
@@ -222,7 +234,10 @@ export default class Convolution2D extends Layer {
     } else {
       gemm(matMul.tensor, imColsMat.tensor, wRowsMat.tensor, 1, 1)
     }
+    endTime = performance.now()
+    if (this.name === 'conv1') console.log('gemm', endTime - startTime)
 
+    startTime = performance.now()
     let output = new Tensor([], this.outputShape)
     let outputChannelRaveled = new Tensor([], [outputRows * outputCols])
     let outputChannel = new Tensor([], [outputRows, outputCols])
@@ -232,8 +247,13 @@ export default class Convolution2D extends Layer {
       ops.assign(output.tensor.pick(null, null, n), outputChannel.tensor)
     }
     x.tensor = output.tensor
+    endTime = performance.now()
+    if (this.name === 'conv1') console.log('createOutput', endTime - startTime)
 
+    startTime = performance.now()
     this.activation(x)
+    endTime = performance.now()
+    if (this.name === 'conv1') console.log('activation', endTime - startTime)
 
     // convert back to th ordering if necessary
     if (this.dimOrdering === 'th') {

src/layers/convolutional/Convolution3D.js

@@ -180,11 +180,10 @@ export default class Convolution3D extends Layer {
 
   /**
    * Convert filter weights to row matrix
-   * @param {Tensor} x
-   * @returns {Tensor} x
+   * @returns {Tensor} wRowsMat
    */
-  _w2row (x) {
-    const inputChannels = x.tensor.shape[3]
+  _w2row () {
+    const inputChannels = this.weights.W.tensor.shape[3]
     const [nbFilter, kernelDim1, kernelDim2, kernelDim3] = this.kernelShape
     const patchLen = kernelDim1 * kernelDim2 * kernelDim3 * inputChannels
 
@@ -216,7 +215,7 @@ export default class Convolution3D extends Layer {
     this._padInput(x)
 
     const volColsMat = this._vol2col(x)
-    const wRowsMat = this._w2row(x)
+    const wRowsMat = this._w2row()
 
     const nbFilter = this.kernelShape[0]
     const outputDim1 = this.outputShape[0]

src/layers/convolutional/Deconvolution2D.js

@@ -140,10 +140,9 @@ export default class Deconvolution2D extends Layer {
   /**
    * Convert filter weights to row matrix, along channels axis
    * shape: [nbRow, nbCol, inputChannels, nbFilter] -> [inputChannels, nbRow * nbCol * nbFilter]
-   * @param {Tensor} x
-   * @returns {Tensor} x
+   * @returns {Tensor} wRowsMat
    */
-  _w2row (x) {
+  _w2row () {
     const [nbRow, nbCol, inputChannels, nbFilter] = this.weights.W.tensor.shape
 
     const wRowsMat = new Tensor([], [inputChannels, nbRow * nbCol * nbFilter])
@@ -169,7 +168,7 @@ export default class Deconvolution2D extends Layer {
     }
 
     const imColsMat = this._im2col(x)
-    const wRowsMat = this._w2row(x)
+    const wRowsMat = this._w2row()
 
     const inputRows = x.tensor.shape[0]
     const inputCols = x.tensor.shape[1]