class_docstr: An auto-batching DSL context.
  
  Auto-batching DSL operations are methods on the `ProgramBuilder` object.  It's
  used like this:
  
  ```python
  ab = dsl.ProgramBuilder()
  
  def fib_type(arg_types):
    return arg_types[0]
  
  with ab.function(type_inference=fib_type) as fibonacci:
    n = ab.param('n')
    ab.var.cond = ab.primop(lambda n: n > 1)
    with ab.if_(ab.var.cond):
      ab.var.nm1 = ab.primop(lambda n: n - 1)
      ab.var.fibm1 = ab.call(fibonacci, [ab.var.nm1])
      ab.var.nm2 = ab.primop(lambda n: n - 2)
      ab.var.fibm2 = ab.call(fibonacci, [ab.var.nm2])
      ab.var.ans = ab.primop(lambda fibm1, fibm2: fibm1 + fibm2)
    with ab.else_():
      ab.var.ans = ab.const(1)
    ab.return_(ab.var.ans)
  
  prog = ab.program(main=fibonacci)
  # Now `prog` is a well-formed `instructions.Program`, and the context
  # `ab` is no longer needed.
  ```
  
  Note the sequence of method calls on `ProgramBuilder` corresponds to the
  source code of the `Program` being defined, not its runtime behavior.  This is
  because (a) functions are defined with a context manager (rather than a Python
  function) which executes its body immediately and exactly once; and (b)
  function call instructions (and primitive operations) are just recorded, not
  entered recursively.
docstr: Auto-batching variables visible in the current scope.
  
  Overrides `setattr` and `getattr` to provide a smooth interface
  to reading and defining variables:
  
  - `ProgramBuilder.var.foo = ProgramBuilder.{call,primop}`
    records an assignment to the auto-batched variable `foo`, possibly
    binding it, and
  
  - `ProgramBuilder.var.foo` reads from the auto-batched variable `foo`
    (if it is bound).
  
  Example:
  
  ```python
  ab = dsl.ProgramBuilder()
  
  ab.var.seven = ab.const(7)
  ```
  
  Returns:
    vars: A `_MagicVars` instance representing the local scope as above.
code: def var(self):
      """Auto-batching variables visible in the current scope.
  
      Overrides `setattr` and `getattr` to provide a smooth interface
      to reading and defining variables:
  
      - `ProgramBuilder.var.foo = ProgramBuilder.{call,primop}`
        records an assignment to the auto-batched variable `foo`, possibly
        binding it, and
  
      - `ProgramBuilder.var.foo` reads from the auto-batched variable `foo`
        (if it is bound).
  
      Example:
  
      ```python
      ab = dsl.ProgramBuilder()
  
      ab.var.seven = ab.const(7)
      ```
  
      Returns:
        vars: A `_MagicVars` instance representing the local scope as above.
      """
      return self._magic_vars
  
imports: import collections
  import contextlib
  import inspect
  from tensorflow_probability.python.experimental.auto_batching import instructions
label_desc: Use image node_id 6 for calling the ProgramBuilder obj's underlying member method code with example usage: obj.var() and returns: self