Method Compute

tensorflow/core/kernels/resource_variable_ops.cc:130–163

}  // namespace

void ReadVariableOp::Compute(OpKernelContext* ctx) {
  core::RefCountPtr<Var> variable;
  const ResourceHandle& handle = HandleFromInput(ctx, 0);
  const auto status = LookupResource(ctx, handle, &variable);
  OP_REQUIRES(ctx, status.ok(),
              errors::FailedPrecondition(
                  "Error while reading resource variable ", handle.name(),
                  " from Container: ", handle.container(),
                  ". This could mean that the variable was uninitialized. ",
                  status.ToString()));

  {
    tf_shared_lock ml(*variable->mu());
    // We're acquiring a reference to the underlying buffer while
    // holding a shared lock to guarantee ordering of reads and
    // writes when in copy-on-write mode.
    if (!variable->copy_on_read_mode.load()) {
      const Tensor* t = variable->tensor();
      OP_REQUIRES(
          ctx, dtype_ == t->dtype(),
          errors::InvalidArgument(
              "Trying to read variable with wrong dtype. Expected ",
              DataTypeString(dtype_), " got ", DataTypeString(t->dtype())));
      ctx->set_output(0, *t);
      return;
    }
  }
  // Note: no need to check copy_on_read_mode again here as it only changes from
  // false to true, never the other way around. We here do the copy under an
  // exclusive lock to avoid racing writes.
  mutex_lock ml(*variable->mu());
  const Tensor* t = variable->tensor();
  OP_REQUIRES_OK(ctx, CopyVariable(0, ctx, t));
}

ReadVariablesOp::ReadVariablesOp(OpKernelConstruction* c) : OpKernel(c) {
  int n;