Method Resize

tensorflow/core/framework/hash_table/tensible_variable.cc:45–94

}

void TensibleVariable::Resize(
    int64 size, const std::function<void(Status)>& done) {
  if (size <= size_) {
    done(Status::OK());
    return;
  }
  int64_t segment_count = (size - size_ - 1) / segment_size_ + 1;
  StatusCollector* stc = new StatusCollector(segment_count, [this, done](Status st) {
    if (st.ok()) {
      ptrs_ = all_ptr_vec_.back().ptr.get();
      size_ = tensors_.size() * segment_size_;
    }
    done(st);
  });
  for (int i = 0; i < segment_count; i++) {
    generator_->GetNextTensor([this, stc] (Status st, const Tensor& tensor) {
      auto fn = [&]() -> Status {
        mutex_lock lock(structure_update_mu_);
        if (!st.ok()) {
          return st;
        }
        if (tensor.shape() != shape_) {
          return errors::InvalidArgument(
              "Tensor Generator generate shape error ",
              tensor.shape().DebugString(), " vs ", shape_.DebugString());
        }
        if (tensor.dtype() != dtype_) {
          return errors::InvalidArgument(
              "Tensor Generator generate dtype error ",
              tensor.dtype(), " vs ", dtype_);
        }
        tensors_.push_back(tensor);
        if (all_ptr_vec_.back().size < tensors_.size()) {
          all_ptr_vec_.emplace_back();
          auto&& old_spec = all_ptr_vec_[all_ptr_vec_.size() - 2];
          auto&& new_spec = all_ptr_vec_[all_ptr_vec_.size() - 1];
          new_spec.size = old_spec.size * 2;
          new_spec.ptr.reset(new char*[new_spec.size]);
          memcpy(new_spec.ptr.get(), old_spec.ptr.get(),
              old_spec.size * sizeof(char*));
        }
        all_ptr_vec_.back().ptr[tensors_.size() - 1] =
          const_cast<char*>(tensor.tensor_data().data());
        return Status::OK();
      };
      stc->AddStatus(fn());
    });
  }
  stc->Start();
}

void TensibleVariable::ZeroCostResize(int64 size) {
  mutex_lock lock(structure_update_mu_);