tensorflow
diff --git a/‎src/backends/backend.ts
+13 b/‎src/backends/backend.ts
+13
diff --git a/‎src/backends/cpu/backend_cpu.ts
+350 b/‎src/backends/cpu/backend_cpu.ts
+350
@@ -468,6 +468,19 @@ export class KernelBackend implements TensorStorage, Backend, BackendTimer {
   avgPoolBackprop(dy: Tensor4D, x: Tensor4D, convInfo: Conv2DInfo): Tensor4D {
     throw new Error('Not yet implemented');
   }
+  avgPool3d(x: Tensor5D, convInfo: Conv3DInfo): Tensor5D {
+    throw new Error('Not yet implemented');
+  }
+  avgPool3dBackprop(dy: Tensor5D, x: Tensor5D, convInfo: Conv3DInfo): Tensor5D {
+    throw new Error('Not yet implemented');
+  }
+  maxPool3d(x: Tensor5D, convInfo: Conv3DInfo): Tensor5D {
+    throw new Error('Not yet implemented');
+  }
+  maxPool3dBackprop(
+      dy: Tensor5D, x: Tensor5D, y: Tensor5D, convInfo: Conv3DInfo): Tensor5D {
+    throw new Error('Not yet implemented');
+  }
 
   reshape<T extends Tensor, R extends Rank>(x: T, shape: ShapeMap[R]):
       Tensor<R> {
 
@@ -2521,6 +2521,356 @@ export class MathBackendCPU implements KernelBackend {
     return dx.toTensor();
   }
 
+  private pool3d(x: Tensor5D, convInfo: Conv3DInfo, poolType: 'max'|'avg'):
+      Tensor5D {
+    this.assertNotComplex(x, 'pool3d');
+
+    const strideDepth = convInfo.strideDepth;
+    const strideHeight = convInfo.strideHeight;
+    const strideWidth = convInfo.strideWidth;
+    const dilationDepth = convInfo.dilationDepth;
+    const dilationHeight = convInfo.dilationHeight;
+    const dilationWidth = convInfo.dilationWidth;
+    const effectiveFilterDepth = convInfo.effectiveFilterDepth;
+    const effectiveFilterHeight = convInfo.effectiveFilterHeight;
+    const effectiveFilterWidth = convInfo.effectiveFilterWidth;
+    const padFront = convInfo.padInfo.front;
+    const padTop = convInfo.padInfo.top;
+    const padLeft = convInfo.padInfo.left;
+
+    const initialValue =
+        (poolType === 'max' ? Number.NEGATIVE_INFINITY :
+                              Number.POSITIVE_INFINITY);
+
+    const xValues = this.readSync(x.dataId) as TypedArray;
+    const output = ops.buffer(convInfo.outShape, x.dtype);
+    const outputVals = output.values;
+
+    const outputBatchStrides = convInfo.outShape[1] * convInfo.outShape[2] *
+        convInfo.outShape[3] * convInfo.outShape[4];
+    const outputDepthStrides =
+        convInfo.outShape[2] * convInfo.outShape[3] * convInfo.outShape[4];
+    const outputRowStrides = convInfo.outShape[3] * convInfo.outShape[4];
+    const outputColStrides = convInfo.outShape[4];
+
+    for (let batch = 0; batch < convInfo.batchSize; ++batch) {
+      const outputBatchOffset = batch * outputBatchStrides;
+      const inputBatchOffset = batch * x.strides[0];
+      for (let channel = 0; channel < convInfo.inChannels; ++channel) {
+        for (let yDepth = 0; yDepth < convInfo.outDepth; ++yDepth) {
+          const xDepthCorner = yDepth * strideDepth - padFront;
+          let xDepthMin = xDepthCorner;
+          while (xDepthMin < 0) {
+            xDepthMin += dilationDepth;
+          }
+          const xDepthMax =
+              Math.min(convInfo.inDepth, effectiveFilterDepth + xDepthCorner);
+          const outputDepthOffset =
+              outputBatchOffset + yDepth * outputDepthStrides;
+          for (let yRow = 0; yRow < convInfo.outHeight; ++yRow) {
+            const xRowCorner = yRow * strideHeight - padTop;
+            let xRowMin = xRowCorner;
+            while (xRowMin < 0) {
+              xRowMin += dilationHeight;
+            }
+            const xRowMax =
+                Math.min(convInfo.inHeight, effectiveFilterHeight + xRowCorner);
+            const outputRowOffset = outputDepthOffset + yRow * outputRowStrides;
+            for (let yCol = 0; yCol < convInfo.outWidth; ++yCol) {
+              const xColCorner = yCol * strideWidth - padLeft;
+              let xColMin = xColCorner;
+              while (xColMin < 0) {
+                xColMin += dilationWidth;
+              }
+              const xColMax =
+                  Math.min(convInfo.inWidth, effectiveFilterWidth + xColCorner);
+              // Shader code begins
+              const outputColOffset = outputRowOffset + yCol * outputColStrides;
+              let minMaxValue = initialValue;
+              let avgValue = 0;
+              let count = 0;
+              for (let xDepth = xDepthMin; xDepth < xDepthMax;
+                   xDepth += dilationDepth) {
+                const xDepthOffset = inputBatchOffset + xDepth * x.strides[1];
+                for (let xRow = xRowMin; xRow < xRowMax;
+                     xRow += dilationHeight) {
+                  const xRowOffset = xDepthOffset + xRow * x.strides[2];
+                  for (let xCol = xColMin; xCol < xColMax;
+                       xCol += dilationWidth) {
+                    const xColOffset = xRowOffset + xCol * x.strides[3];
+                    const pixel = xValues[xColOffset + channel];
+                    if ((poolType === 'max' && pixel > minMaxValue)) {
+                      minMaxValue = pixel;
+                    } else if (poolType === 'avg') {
+                      avgValue += pixel;
+                      count++;
+                    }
+                    if (isNaN(minMaxValue)) {
+                      break;
+                    }
+                  }
+                  if (isNaN(minMaxValue)) {
+                    break;
+                  }
+                }
+                if (isNaN(minMaxValue)) {
+                  break;
+                }
+              }
+              const outputOffset = outputColOffset + channel;
+              outputVals[outputOffset] =
+                  poolType === 'avg' ? avgValue / count : minMaxValue;
+            }
+          }
+        }
+      }
+    }
+    return output.toTensor() as Tensor5D;
+  }
+
+  avgPool3d(x: Tensor5D, convInfo: Conv3DInfo): Tensor5D {
+    this.assertNotComplex(x, 'avgPool3d');
+
+    return this.pool3d(x, convInfo, 'avg').toFloat();
+  }
+
+  avgPool3dBackprop(dy: Tensor5D, x: Tensor5D, convInfo: Conv3DInfo): Tensor5D {
+    this.assertNotComplex([dy, x], 'avgPool3dBackprop');
+
+    const strideDepth = convInfo.strideDepth;
+    const strideHeight = convInfo.strideHeight;
+    const strideWidth = convInfo.strideWidth;
+    const filterDepth = convInfo.filterDepth;
+    const filterHeight = convInfo.filterHeight;
+    const filterWidth = convInfo.filterWidth;
+    const dilationDepth = convInfo.dilationDepth;
+    const dilationHeight = convInfo.dilationHeight;
+    const dilationWidth = convInfo.dilationWidth;
+    const effectiveFilterDepth = convInfo.effectiveFilterDepth;
+    const effectiveFilterHeight = convInfo.effectiveFilterHeight;
+    const effectiveFilterWidth = convInfo.effectiveFilterWidth;
+    const padFront = effectiveFilterDepth - 1 - convInfo.padInfo.front;
+    const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;
+    const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;
+    const dx = ops.buffer<Rank.R5>(x.shape, 'float32');
+
+    const avgMultiplier = 1 / (filterDepth * filterHeight * filterWidth);
+
+    const dyBuf = this.bufferSync(dy);
+
+    for (let batch = 0; batch < convInfo.batchSize; ++batch) {
+      for (let channel = 0; channel < convInfo.inChannels; ++channel) {
+        for (let dxDepth = 0; dxDepth < convInfo.inDepth; ++dxDepth) {
+          for (let dxRow = 0; dxRow < convInfo.inHeight; ++dxRow) {
+            for (let dxCol = 0; dxCol < convInfo.inWidth; ++dxCol) {
+              // Shader code begins.
+              const dyDepthCorner = dxDepth - padFront;
+              const dyRowCorner = dxRow - padTop;
+              const dyColCorner = dxCol - padLeft;
+              let dotProd = 0;
+              for (let wDepth = 0; wDepth < effectiveFilterDepth;
+                   wDepth += dilationDepth) {
+                const dyDepth = (dyDepthCorner + wDepth) / strideDepth;
+                if (dyDepth < 0 || dyDepth >= convInfo.outDepth ||
+                    Math.floor(dyDepth) !== dyDepth) {
+                  continue;
+                }
+                for (let wRow = 0; wRow < effectiveFilterHeight;
+                     wRow += dilationHeight) {
+                  const dyRow = (dyRowCorner + wRow) / strideHeight;
+                  if (dyRow < 0 || dyRow >= convInfo.outHeight ||
+                      Math.floor(dyRow) !== dyRow) {
+                    continue;
+                  }
+                  for (let wCol = 0; wCol < effectiveFilterWidth;
+                       wCol += dilationWidth) {
+                    const dyCol = (dyColCorner + wCol) / strideWidth;
+                    if (dyCol < 0 || dyCol >= convInfo.outWidth ||
+                        Math.floor(dyCol) !== dyCol) {
+                      continue;
+                    }
+
+                    const pixel =
+                        dyBuf.get(batch, dyDepth, dyRow, dyCol, channel);
+                    dotProd += pixel;
+                  }
+                }
+              }
+              dx.set(
+                  dotProd * avgMultiplier, batch, dxDepth, dxRow, dxCol,
+                  channel);
+            }
+          }
+        }
+      }
+    }
+    return dx.toTensor() as Tensor5D;
+  }
+
+  maxPool3d(x: Tensor5D, convInfo: Conv3DInfo): Tensor5D {
+    this.assertNotComplex(x, 'maxPool3d');
+
+    return this.pool3d(x, convInfo, 'max').toFloat();
+  }
+
+  private maxPool3dPositions(x: Tensor5D, convInfo: Conv3DInfo): Tensor5D {
+    const maxPositions = ops.buffer(convInfo.outShape, 'int32');
+    const strideDepth = convInfo.strideDepth;
+    const strideHeight = convInfo.strideHeight;
+    const strideWidth = convInfo.strideWidth;
+    const dilationDepth = convInfo.dilationDepth;
+    const dilationHeight = convInfo.dilationHeight;
+    const dilationWidth = convInfo.dilationWidth;
+    const effectiveFilterDepth = convInfo.effectiveFilterDepth;
+    const effectiveFilterHeight = convInfo.effectiveFilterHeight;
+    const effectiveFilterWidth = convInfo.effectiveFilterWidth;
+    const padFront = convInfo.padInfo.front;
+    const padTop = convInfo.padInfo.top;
+    const padLeft = convInfo.padInfo.left;
+
+    const xBuf = this.bufferSync(x);
+    for (let batch = 0; batch < convInfo.batchSize; ++batch) {
+      for (let channel = 0; channel < convInfo.inChannels; ++channel) {
+        for (let yDepth = 0; yDepth < convInfo.outDepth; ++yDepth) {
+          const xDepthCorner = yDepth * strideDepth - padFront;
+          let xDepthMin = xDepthCorner;
+          while (xDepthMin < 0) {
+            xDepthMin += dilationDepth;
+          }
+          const xDepthMax =
+              Math.min(convInfo.inDepth, effectiveFilterDepth + xDepthCorner);
+          for (let yRow = 0; yRow < convInfo.outHeight; ++yRow) {
+            const xRowCorner = yRow * strideHeight - padTop;
+            let xRowMin = xRowCorner;
+            while (xRowMin < 0) {
+              xRowMin += dilationHeight;
+            }
+            const xRowMax =
+                Math.min(convInfo.inHeight, effectiveFilterHeight + xRowCorner);
+            for (let yCol = 0; yCol < convInfo.outWidth; ++yCol) {
+              const xColCorner = yCol * strideWidth - padLeft;
+              let xColMin = xColCorner;
+              while (xColMin < 0) {
+                xColMin += dilationWidth;
+              }
+              const xColMax =
+                  Math.min(convInfo.inWidth, effectiveFilterWidth + xColCorner);
+
+              // Shader code begins
+              let maxValue = Number.NEGATIVE_INFINITY;
+              let maxPosition = -1;
+
+              for (let xDepth = xDepthMin; xDepth < xDepthMax;
+                   xDepth += dilationDepth) {
+                const wDepth = xDepth - xDepthCorner;
+                for (let xRow = xRowMin; xRow < xRowMax;
+                     xRow += dilationHeight) {
+                  const wRow = xRow - xRowCorner;
+                  for (let xCol = xColMin; xCol < xColMax;
+                       xCol += dilationWidth) {
+                    const wCol = xCol - xColCorner;
+                    const pixel = xBuf.get(batch, xDepth, xRow, xCol, channel);
+                    if (pixel >= maxValue) {
+                      maxValue = pixel;
+                      maxPosition = wDepth * effectiveFilterHeight *
+                              effectiveFilterWidth +
+                          wRow * effectiveFilterHeight + wCol;
+                    }
+                  }
+                }
+              }
+
+              maxPositions.set(maxPosition, batch, yDepth, yRow, yCol, channel);
+            }
+          }
+        }
+      }
+    }
+    return maxPositions.toTensor() as Tensor5D;
+  }
+
+  maxPool3dBackprop(
+      dy: Tensor5D, x: Tensor5D, y: Tensor5D, convInfo: Conv3DInfo): Tensor5D {
+    this.assertNotComplex([x, y], 'maxPool3dBackprop');
+
+    const maxPositions = this.maxPool3dPositions(x, convInfo);
+    const strideDepth = convInfo.strideDepth;
+    const strideHeight = convInfo.strideHeight;
+    const strideWidth = convInfo.strideWidth;
+    const dilationDepth = convInfo.dilationDepth;
+    const dilationHeight = convInfo.dilationHeight;
+    const dilationWidth = convInfo.dilationWidth;
+    const effectiveFilterDepth = convInfo.effectiveFilterDepth;
+    const effectiveFilterHeight = convInfo.effectiveFilterHeight;
+    const effectiveFilterWidth = convInfo.effectiveFilterWidth;
+    const padFront = effectiveFilterDepth - 1 - convInfo.padInfo.front;
+    const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;
+    const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;
+    const dx = ops.buffer<Rank.R5>(x.shape, 'float32');
+
+    const maxPosBuf = this.bufferSync(maxPositions);
+    const dyBuf = this.bufferSync(dy);
+
+    for (let batch = 0; batch < convInfo.batchSize; ++batch) {
+      for (let channel = 0; channel < convInfo.inChannels; ++channel) {
+        for (let dxDepth = 0; dxDepth < convInfo.inDepth; ++dxDepth) {
+          for (let dxRow = 0; dxRow < convInfo.inHeight; ++dxRow) {
+            for (let dxCol = 0; dxCol < convInfo.inWidth; ++dxCol) {
+              // Shader code begins
+              const dyDepthCorner = dxDepth - padFront;
+              const dyRowCorner = dxRow - padTop;
+              const dyColCorner = dxCol - padLeft;
+              let dotProd = 0;
+              for (let wDepth = 0; wDepth < effectiveFilterDepth;
+                   wDepth += dilationDepth) {
+                const dyDepth = (dyDepthCorner + wDepth) / strideDepth;
+                if (dyDepth < 0 || dyDepth >= convInfo.outDepth ||
+                    Math.floor(dyDepth) !== dyDepth) {
+                  continue;
+                }
+                for (let wRow = 0; wRow < effectiveFilterHeight;
+                     wRow += dilationHeight) {
+                  const dyRow = (dyRowCorner + wRow) / strideHeight;
+                  if (dyRow < 0 || dyRow >= convInfo.outHeight ||
+                      Math.floor(dyRow) !== dyRow) {
+                    continue;
+                  }
+                  for (let wCol = 0; wCol < effectiveFilterWidth;
+                       wCol += dilationWidth) {
+                    const dyCol = (dyColCorner + wCol) / strideWidth;
+                    if (dyCol < 0 || dyCol >= convInfo.outWidth ||
+                        Math.floor(dyCol) !== dyCol) {
+                      continue;
+                    }
+
+                    const maxPos = effectiveFilterDepth *
+                            effectiveFilterHeight * effectiveFilterWidth -
+                        1 -
+                        maxPosBuf.get(batch, dyDepth, dyRow, dyCol, channel);
+                    const curPos =
+                        wDepth * effectiveFilterHeight * effectiveFilterWidth +
+                        wRow * effectiveFilterWidth + wCol;
+
+                    const mask = maxPos === curPos ? 1 : 0;
+                    if (mask === 0) {
+                      continue;
+                    }
+
+                    const pixel =
+                        dyBuf.get(batch, dyDepth, dyRow, dyCol, channel);
+                    dotProd += pixel * mask;
+                  }
+                }
+              }
+              dx.set(dotProd, batch, dxDepth, dxRow, dxCol, channel);
+            }
+          }
+        }
+      }
+    }
+    return dx.toTensor() as Tensor5D;
+  }
+
   cast<T extends Tensor>(x: T, dtype: DataType): T {
     return backend_util.castTensor(x, dtype, this);
   }