Back out "[pt1][tensor] Remove caffe2::ShareData" (#15983)

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/15983

Original commit changeset: 6e4275d02f4c

Reviewed By: supertopher, Yangqing

Differential Revision: D13644123

fbshipit-source-id: 4b15a4c62995c0e68aad58465600409e302e6504

1 files changed, 41 insertions, 0 deletions

diff --git a/c10/core/TensorImpl.h b/c10/core/TensorImpl.h
index 7e7ea618de..5d8a3a0fd3 100644
--- a/c10/core/TensorImpl.h
+++ b/c10/core/TensorImpl.h
@@ -1068,6 +1068,47 @@ struct C10_API TensorImpl : public c10::intrusive_ptr_target {
     storage_offset_ = 0;
   }
 
+  /**
+   * @brief Shares the data with another tensor.
+   *
+   * To share data between two tensors, the sizes of the two tensors must be
+   * equal already. The reason we do not implicitly do a Resize to make the two
+   * tensors have the same shape is that we want to allow tensors of different
+   * shapes but the same number of items to still be able to share data. This
+   * allows one to e.g. have a n-dimensional Tensor and a flattened version
+   * sharing the same underlying storage.
+   *
+   * The source tensor should already have its data allocated.
+   */
+  void ShareData(const TensorImpl& src) {
+    // Right now, we are assuming the device_type are the same, since it is
+    // inherently the same in the non-templatized code. We should probably add
+    // an assert here which might affect perf a little bit.
+    AT_ASSERTM(
+        src.numel_ == numel_,
+        "Size mismatch - did you call reshape before sharing the data?");
+    // It is possible that the source tensor hasn't called mutable_data() yet,
+    // in which case ShareData() doesn't make much sense since we don't really
+    // know what to share yet.
+    // TODO: Add the assert after all uninitialized states are eliminated
+    // AT_ASSERTM(src.dtype_initialized(),
+    //            "Source tensor don't have a data type (did you call mutable_data<T> on the tensor?)");
+    if (!src.dtype_initialized()) {
+      C10_LOG_EVERY_MS(WARNING, 1000) <<
+                   "Source tensor don't have a data type (did you call mutable_data<T> on the tensor?)";
+    }
+    AT_ASSERTM(
+        src.storage_initialized(),
+        "Source tensor has no content and has size > 0");
+    // Finally, do sharing.
+    /* Since we create new Storage whenever we need to change data_type/capacity
+     * this still keeps the original semantics
+     */
+    storage_ = src.storage();
+    data_type_ = src.dtype();
+    storage_offset_ = src.storage_offset();
+  }
+
   void ShareExternalPointer(
       DataPtr&& data_ptr,
       const caffe2::TypeMeta& data_type,