@@ -95,7 +95,7 @@ const applyActivation =
9595 * - `activation` Name of activation kernel (defaults to `linear`).
9696 * - `preluActivationWeights` Tensor of prelu weights.
9797 */
98- function matMul_ < T extends Tensor > ( {
98+ function fusedMatMul_ < T extends Tensor > ( {
9999 a,
100100 b,
101101 transposeA = false ,
@@ -305,7 +305,7 @@ function matMul_<T extends Tensor>({
305305 * @param preluActivationWeights Tensor of prelu weights to be applied as part
306306 * of a `prelu` activation, typically the same shape as `x`.
307307 */
308- function conv2d_ < T extends Tensor3D | Tensor4D > ( {
308+ function fusedConv2d_ < T extends Tensor3D | Tensor4D > ( {
309309 x,
310310 filter,
311311 strides,
@@ -508,7 +508,7 @@ function conv2d_<T extends Tensor3D|Tensor4D>({
508508 * @param preluActivationWeights Tensor of prelu weights to be applied as part
509509 * of a `prelu` activation, typically the same shape as `x`.
510510 */
511- function depthwiseConv2d_ < T extends Tensor3D | Tensor4D > ( {
511+ function fusedDepthwiseConv2d_ < T extends Tensor3D | Tensor4D > ( {
512512 x,
513513 filter,
514514 strides,
@@ -655,8 +655,8 @@ function depthwiseConv2d_<T extends Tensor3D|Tensor4D>({
655655 return res as T ;
656656}
657657
658- export const matMul = op ( { matMul_ } ) ;
659- export const conv2d = op ( { conv2d_ } ) ;
660- export const depthwiseConv2d = op ( { depthwiseConv2d_ } ) ;
658+ export const matMul = op ( { fusedMatMul_ } ) ;
659+ export const conv2d = op ( { fusedConv2d_ } ) ;
660+ export const depthwiseConv2d = op ( { fusedDepthwiseConv2d_ } ) ;
661661
662662export { Activation } ;
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