class_docstr: Tensorflow printer which handles vectorized piecewise functions,
  logical operators, max/min, and relational operators.
class_docstr_tok: ["Tensorflow","printer","which","handles","vectorized","piecewise","functions",",","logical","operators",",","max\/min",",","and","relational","operators","."]
code: def _print_Piecewise(self, expr):
      version = self.tensorflow_version
      if version and version_tuple(version) < version_tuple("1.0"):
          tensorflow_piecewise = "tensorflow.select"
      else:
          tensorflow_piecewise = "tensorflow.where"
  
      from sympy.functions.elementary.piecewise import Piecewise
  
      e, cond = expr.args[0].args
      if len(expr.args) == 1:
          return "{}({}, {}, {})".format(
              self._module_format(tensorflow_piecewise),
              self._print(cond),
              self._print(e),
              0,
          )
  
      return "{}({}, {}, {})".format(
          self._module_format(tensorflow_piecewise),
          self._print(cond),
          self._print(e),
          self._print(Piecewise(*expr.args[1:])),
      )
  
imports: from sympy.external.importtools import version_tuple
  from collections.abc import Iterable
  from sympy.core.mul import Mul
  from sympy.core.singleton import S
  from sympy.codegen.cfunctions import Sqrt
  from sympy.external import import_module
  from sympy.printing.precedence import PRECEDENCE
  from sympy.printing.pycode import AbstractPythonCodePrinter, ArrayPrinter
  import sympy
label_desc: Use image node_id 6 for calling the TensorflowPrinter obj's underlying member method code with example usage: obj._print_Piecewise(expr) and returns: str, str