int64_t bytes_transferred;
    if (offset < buf.size()) {
      size_t bytes_to_copy = std::min<size_t>(buf.size() - offset, n);
      memcpy(buffer, buf.data() + offset, bytes_to_copy);
      bytes_transferred = bytes_to_copy;
    } else {
      bytes_transferred = 0;
    }
    TF_SetStatus(status, TF_OK, "");
    return bytes_transferred;
  };

    tensorflow::AttrValue attr;
    for (const string& v : list) {
      attr.mutable_list()->add_s(v);
    }
    string bytes;
    attr.SerializeToString(&bytes);
    TF_SetAttrValueProto(desc, tensorflow::kColocationAttrName, bytes.data(),
                         bytes.size(), s_);
    ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
  }

  void VerifyCollocation(TF_Operation* op,

}

TF_Tensor* Int32Tensor(int32_t v) {
  const int num_bytes = sizeof(int32_t);
  int32_t* values = new int32_t[1];
  values[0] = v;
  return TF_NewTensor(TF_INT32, nullptr, 0, values, num_bytes,
                      &Int32Deallocator, nullptr);
}

TF_Tensor* DoubleTensor(double v) {
  const int num_bytes = sizeof(double);
  double* values = new double[1];
  values[0] = v;

  // make sure there is no information loss.
  if (proto_len > std::numeric_limits<int>::max()) {
    status->status = InvalidArgument(
        "proto_len (", proto_len,
        " bytes) is too large to be parsed by the protocol buffer library");
    return;
  }
  TensorShapeProto shape;
  if (shape.ParseFromArray(proto, static_cast<int>(proto_len))) {
    desc->node_builder.Attr(attr_name, shape);

        "Unsupported byte_offset (", dl_tensor->byte_offset,
        ") from DLPack, must be zero");
    return nullptr;
  }

  size_t total_bytes = dl_tensor->dtype.bits / 8;
  for (int i = 0; i < num_dims; i++) {
    total_bytes *= dims[i];
  }

  if (dl_tensor->strides != nullptr &&
      !IsValidStrideCompactRowMajorData(dl_tensor->shape, dl_tensor->strides,

// must point to an array of length at least `num_values`.
//
// The elements of values will point to addresses in `storage` which must be at
// least `storage_size` bytes in length.  `num_values` and `storage` can be
// obtained from TF_GetNodesToPreserveSize
//
// Fails if storage_size is too small to hold the requested number of strings.
TF_CAPI_EXPORT extern void TF_GetNodesToPreserveList(

```

## Contribution & Maintenance

The TensorFlow team does not yet have guidelines in place for contributing to
this directory. We are working on it. Please join a TF SIG Build meeting (see:
bit.ly/tf-sig-build-notes) if you'd like to discuss the future of contributions.

### Brief System Overview

The top-level scripts and utility scripts should be fairly well-documented. Here
is a brief explanation of how they tie together:

                                                          TF_Status*);

// This function will block till the operation that produces `h` has
// completed. This is only valid on local TFE_TensorHandles. Returns the size in
// bytes of the memory pointed to by the device pointer returned above.
TF_CAPI_EXPORT extern size_t TFE_TensorHandleDeviceMemorySize(TFE_TensorHandle*,
                                                              TF_Status*);

    *   boosted trees: adding pruning mode.
    *   tf.train.Checkpoint does not delete old checkpoints by default.
    *   tfdbg: Limit the total disk space occupied by dumped tensor data to 100
        GBytes. Add environment variable `TFDBG_DISK_BYTES_LIMIT` to allow
        adjustment of this upper limit.

## Thanks to our Contributors

This release contains contributions from many people at Google, as well as:

      dst += r;
      offset += static_cast<uint64_t>(r);
      n -= r;  // safe as 0 < r <= n so n will never underflow
      read += r;
    } else if (r == 0) {
      TF_SetStatus(status, TF_OUT_OF_RANGE, "Read fewer bytes than requested");
      break;
    } else if (errno == EINTR || errno == EAGAIN) {
      // Retry
    } else {
      TF_SetStatusFromIOError(status, errno, posix_file->filename);
      break;
    }
  }