s":" ","--tw-backdrop-contrast":" ","--tw-backdrop-grayscale":" ","--tw-backdrop-hue-rotate":" ","--tw-backdrop-invert":" ","--tw-backdrop-opacity":" ","--tw-backdrop-saturate":" ","--tw-backdrop-sepia":" "}),e({".backdrop-filter":{"@defaults backdrop-filter":{},"backdrop-filter":Fe},".backdrop-filter-none":{"backdrop-filter":"none"}})},transitionProperty:({matchUtilities:i,theme:e})=>{let t=e("transitionTimingFunction.DEFAULT"),r=e("transitionDuration.DEFAULT");i({transition:n=>({"transition-pr...

  // CHECK-NEXT: %[[offset_backprop:.*]] = mhlo.convert %[[red2]] : tensor<8xf32>

  // CHECK-NEXT: %[[x_backprop:.*]] = mhlo.convert %[[mul3]] : tensor<8x8x8x8xf32>
  // CHECK-NEXT: return %[[x_backprop]] : tensor<8x8x8x8xf32>

      Value scratch2 =
          ApplyReduction(loc, weighted_grad, reduce_dims, &rewriter);

      // x_backprop = y_backprop * (scale * scratch1)
      auto scaled_grad =
          rewriter.create<mhlo::MulOp>(loc, op.getScale(), scratch1);
      x_backprop = rewriter.create<mhlo::MulOp>(
          loc, grad,
          Broadcast1DToFeatureDim(loc, act, scaled_grad, feature_dim,