[webgpu] Enable test for fusedConv2D

FIX #2660

Author: axinging

tfjs-backend-webgpu/src/backend_webgpu.ts

@@ -805,7 +805,14 @@ export class WebGPUBackend extends KernelBackend {
       convInfo.strideHeight, convInfo.strideWidth
     ];
 
-    return this.compileAndRun(program, [input, filter], output, dimensions);
+    const inputs: Tensor[] = [input, filter];
+    if (hasBias) {
+      inputs.push(bias);
+    }
+    if (hasPreluActivationWeights) {
+      inputs.push(preluActivationWeights);
+    }
+    return this.compileAndRun(program, inputs, output, dimensions);
   }
 
   private argMinMaxReduce(x: Tensor, axis: number, reduceType: 'min'|'max'):

tfjs-backend-webgpu/src/kernels/conv2d_mm_webgpu.ts

@@ -58,9 +58,12 @@ export class Conv2DMMProgram implements WebGPUProgram {
     const tileAOuter = this.workGroupSize[1] * elementsPerThread[1];
     const tileBOuter = this.workGroupSize[0] * elementsPerThread[0];
     const tileInner = tileAOuter > tileBOuter ? tileAOuter : tileBOuter;
-    util.assert(tileInner % this.workGroupSize[0] === 0 &&
-                tileInner % this.workGroupSize[1] === 0,
-                () => 'tileInner must be multiple of workgroupsize.x and workgroupsize.y');
+    util.assert(
+        tileInner % this.workGroupSize[0] === 0 &&
+            tileInner % this.workGroupSize[1] === 0,
+        () =>
+            // tslint:disable-next-line: max-line-length
+        'tileInner must be multiple of workgroupsize.x and workgroupsize.y');
     const tileSizeA = [tileAOuter, tileInner];
     const tileSizeB = [tileInner, tileBOuter];
     const dimAOuter = this.outputShape[1] * this.outputShape[2];
@@ -72,8 +75,8 @@ export class Conv2DMMProgram implements WebGPUProgram {
         `x[getFlatIndex(coord, xShape)]` :
         `coordsInBounds(coord, xShape) ? x[getFlatIndex(coord, xShape)] : 0`;
     const fitB = tilesFitEvenlyIntoShape(tileSizeB, [dimInner, dimBOuter]);
-    const sampleB =
-        fitB ? `W[row * dimBOuter + col]` :
+    const sampleB = fitB ?
+        `W[row * dimBOuter + col]` :
         `coordsInBounds(ivec2(row, col), ivec2(dimInner, dimBOuter)) ?
         W[row * dimBOuter + col] : 0`;
 
@@ -90,7 +93,7 @@ export class Conv2DMMProgram implements WebGPUProgram {
             }`;
       } else {
         activationSnippet = `
-              float activation(float x) {
+              float activation(float a) {
                 ${activation}
               }
             `;
@@ -155,6 +158,7 @@ export class Conv2DMMProgram implements WebGPUProgram {
           mm_matMul(dimAOuter, dimInner, dimBOuter);
         }
       `;
-    this.shaderKey = `conv2dmm'${elementsPerThread.join('')}${fitA}${fitB}`;
+    this.shaderKey = `conv2dmm'${elementsPerThread.join('')}${fitA}${fitB}${
+        addBiasSnippet}${activationSnippet}`;
   }
 }

tfjs-backend-webgpu/src/kernels/unary_op_webgpu.ts

@@ -23,8 +23,8 @@ import {WebGPUProgram} from './webgpu_program';
 
 export const RELU = 'return max(a, 0.0);';
 export const RELU6 = 'return (a < 0.0) ? 0.0 : min(6.0, a);';
-export const LINEAR = `return x;`;
-export const ELU = `return (x >= 0.0) ? x : (exp(x) - 1.0);`;
+export const LINEAR = `return a;`;
+export const ELU = `return (a >= 0.0) ? a : (exp(a) - 1.0);`;
 
 export const SIGMOID = `return 1.0 / (1.0 + exp(-1.0 * a));`;
 export const ABS = `return abs(a);`;

tfjs-backend-webgpu/src/setup_test.ts

@@ -126,6 +126,16 @@ const TEST_FILTERS: TestFilter[] = [
       'fused',     // Not yet implemented.
     ]
   },
+  {
+    include: 'fused conv2d',
+    excludes: [
+      'im2row with prelu',                         // Actual != expected.
+      'pointwise with prelu',                      // Actual != expected.
+      'gradient x=[2,3,3,1] f=[2,2,1,1] s=1 p=0',  // conv2dDerInput not yet
+                                                   // implemented
+      'fused matmul with relu6',                   // step not yet implemented
+    ]
+  },
   {
     include: 'fromPixels',
     excludes: [