message: Langjian/batch norm unittest
  Fix the FusedBatchNorm with the Bessel correction in variance
diff: @@ -1724,12 +1724,23 @@ static Status TranslateFusedBatchNormOp(
  ng_y = make_shared<ng::op::GetOutputElement>(ng_batch_norm, 0);
  ng_mean = make_shared<ng::op::GetOutputElement>(ng_batch_norm, 1);
  ng_variance = make_shared<ng::op::GetOutputElement>(ng_batch_norm, 2);
  + // This is for Bessel's correction in ng_variance:
  + int ng_input_size = ng::shape_size(ng_input->get_shape());
  + int num_channels = ng::shape_size(ng_variance->get_shape());
  + int sample_size = ng_input_size / num_channels;
  + int sample_size_minus_one = sample_size > 1 ? (sample_size - 1) : 1;
  + float factor = float(sample_size) / float(sample_size_minus_one);
  + std::vector<float> Bessel_factor(num_channels, factor);
  + auto Bessel_scale = std::make_shared<ng::op::Constant>(
  + ng_variance->get_element_type(), ng_variance->get_shape(),
  + Bessel_factor);
  + auto variance = ng_variance * Bessel_scale;
  BatchToTensorflow(is_nhwc, ng_y);
  SaveNgOp(ng_op_map, op->name(), ng_y);
  SaveNgOp(ng_op_map, op->name(), ng_mean);
  - SaveNgOp(ng_op_map, op->name(), ng_variance);
  + SaveNgOp(ng_op_map, op->name(), variance);
  // Output reserve_space_1: A 1D Tensor for the computed batch mean, to be
  // reused in the gradient computation.
  SaveNgOp(ng_op_map, op->name(), ng_mean);
  @@ -1744,7 +1755,6 @@ static Status TranslateFusedBatchNormOp(
  SaveNgOp(ng_op_map, op->name(), ng_batch_norm);
  }
  - SaveNgOp(ng_op_map, op->name(), ng_batch_norm);
  return Status::OK();
  }
  