old_contents: from __future__ import print_function, division
  
  from sympy import Basic, Q
  from sympy.functions import adjoint, conjugate
  
  from sympy.matrices.expressions.matexpr import MatrixExpr
  from sympy.matrices import MatrixBase
  
  class Transpose(MatrixExpr):
      """
      The transpose of a matrix expression.
  
      This is a symbolic object that simply stores its argument without
      evaluating it. To actually compute the transpose, use the ``transpose()``
      function, or the ``.T`` attribute of matrices.
  
      Examples
      ========
  
      >>> from sympy.matrices import MatrixSymbol, Transpose
      >>> from sympy.functions import transpose
      >>> A = MatrixSymbol('A', 3, 5)
      >>> B = MatrixSymbol('B', 5, 3)
      >>> Transpose(A)
      A'
      >>> A.T == transpose(A) == Transpose(A)
      True
      >>> Transpose(A*B)
      (A*B)'
      >>> transpose(A*B)
      B'*A'
  
      """
      is_Transpose = True
  
      def doit(self, **hints):
          arg = self.arg
          if hints.get('deep', True) and isinstance(arg, Basic):
              arg = arg.doit(**hints)
          try:
              result = arg._eval_transpose()
              return result if result is not None else Transpose(arg)
          except AttributeError:
              return Transpose(arg)
  
      @property
      def arg(self):
          return self.args[0]
  
      @property
      def shape(self):
          return self.arg.shape[::-1]
  
      def _entry(self, i, j):
          return self.arg._entry(j, i)
  
      def _eval_adjoint(self):
          return conjugate(self.arg)
  
      def _eval_conjugate(self):
          return adjoint(self.arg)
  
      def _eval_transpose(self):
          return self.arg
  
      def _eval_trace(self):
          from .trace import Trace
          return Trace(self.arg)  # Trace(X.T) => Trace(X)
  
      def _eval_determinant(self):
          from sympy.matrices.expressions.determinant import det
          return det(self.arg)
  
  def transpose(expr):
      """ Matrix transpose """
      return Transpose(expr).doit()
  
new_contents: from __future__ import print_function, division
  
  from sympy import Basic, Q
  from sympy.functions import adjoint, conjugate
  
  from sympy.matrices.expressions.matexpr import MatrixExpr
  from sympy.matrices import MatrixBase
  
  class Transpose(MatrixExpr):
      """
      The transpose of a matrix expression.
  
      This is a symbolic object that simply stores its argument without
      evaluating it. To actually compute the transpose, use the ``transpose()``
      function, or the ``.T`` attribute of matrices.
  
      Examples
      ========
  
      >>> from sympy.matrices import MatrixSymbol, Transpose
      >>> from sympy.functions import transpose
      >>> A = MatrixSymbol('A', 3, 5)
      >>> B = MatrixSymbol('B', 5, 3)
      >>> Transpose(A)
      A'
      >>> A.T == transpose(A) == Transpose(A)
      True
      >>> Transpose(A*B)
      (A*B)'
      >>> transpose(A*B)
      B'*A'
  
      """
      is_Transpose = True
  
      def doit(self, **hints):
          arg = self.arg
          if hints.get('deep', True) and isinstance(arg, Basic):
              arg = arg.doit(**hints)
          try:
              result = arg._eval_transpose()
              return result if result is not None else Transpose(arg)
          except AttributeError:
              return Transpose(arg)
  
      @property
      def arg(self):
          return self.args[0]
  
      @property
      def shape(self):
          return self.arg.shape[::-1]
  
      def _entry(self, i, j):
          return self.arg._entry(j, i)
  
      def _eval_adjoint(self):
          return conjugate(self.arg)
  
      def _eval_conjugate(self):
          return adjoint(self.arg)
  
      def _eval_transpose(self):
          return self.arg
  
      def _eval_trace(self):
          from .trace import Trace
          return Trace(self.arg)  # Trace(X.T) => Trace(X)
  
      def _eval_determinant(self):
          from sympy.matrices.expressions.determinant import det
          return det(self.arg)
  
  def transpose(expr):
      """ Matrix transpose """
      return Transpose(expr).doit()
  
  
  from sympy.assumptions.ask import ask, Q
  from sympy.assumptions.refine import handlers_dict
  
  
  def refine_Transpose(expr, assumptions):
      """
      >>> from sympy import MatrixSymbol, Q, assuming, refine
      >>> X = MatrixSymbol('X', 2, 2)
      >>> X.T
      X'
      >>> with assuming(Q.symmetric(X)):
      ...     print(refine(X.T))
      X
      """
      if ask(Q.symmetric(expr), assumptions):
          return expr.arg
  
      return expr
  
  handlers_dict['Transpose'] = refine_Transpose
  
subject: add refine_Transpose