*   Second, the rewrite pass will apply transformations to the first
    convolution, the padding before the first convolution, first convolution's
    filters and its Conv2DBackPropFilter;
*   At last, the rewrite pass will insert SpaceToDepthOp after IteratorGetNext
    where the iterator's result has the same shape as the first convolution's
    input.

  return builder->create<TF::SliceOp>(input.getLoc(), slice_result_type, input,
                                      start_position, slice_size_op);
}

// Transforms Conv2DBackPropFilter for space to depth.
void HandleConv2DBackPropFilter(TF::Conv2DBackpropFilterOp backprop,
                                ArrayRef<int32_t> old_filter_shape,

    // CHECK: %[[BACKPROP:.*]] = "tf.Conv2DBackpropFilter"
    // CHECK-SAME: strides = [1, 1, 1, 1]
    // CHECK-SAME: (tensor<2x115x115x12xf32>, tensor<4xi32>, tensor<2x112x112x64xf32>) -> tensor<4x4x12x64xf32>

    ([CVE-2021-29536](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-29536))
*   Fixes a division by zero in `Conv2DBackpropFilter`
    ([CVE-2021-29538](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-29538))
*   Fixes a heap buffer overflow in `Conv2DBackpropFilter`
    ([CVE-2021-29540](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-29540))
*   Fixes a heap buffer overflow in `StringNGrams`

      "BiasAddV1",
      "Bincount",
      "Bucketize",
      "Case",
      "CheckNumerics",
      "Cholesky",
      "ControlTrigger",
      "Conv",
      "Conv2D",
      "Conv2DBackpropFilter",
      "Conv2DBackpropInput",
      "Conv3D",
      "Conv3DBackpropFilterV2",
      "Conv3DBackpropInputV2",
      "Cross",
      "Cumprod",
      "Cumsum",
      "CumulativeLogsumexp",

    std::vector<int64_t> explicit_paddings;
    if (padding == tensorflow::Padding::EXPLICIT) {
      // EXPLICIT padding mode and the associated attribute is limited to
      // Conv2DBackpropFilter. So, fetch attribute by identifier instead of the
      // op.explicit_paddings() attribute getter.
      ArrayRef<Attribute> explicit_paddings_attr =

    // InferTypeOpInterface:
    static bool isCompatibleReturnTypes(TypeRange l, TypeRange r) {
      return ArraysAreCastCompatible(l, r);
    }
  }];
}

def TF_Conv2DBackpropFilterOp : TF_Op<"Conv2DBackpropFilter", [Pure, TF_LayoutSensitiveInterface]> {
  let summary = [{
Computes the gradients of convolution with respect to the filter.
  }];

  let arguments = (ins