Python six.get_function_globals方法代碼示例

# 需要導入模塊: import six [as 別名]
# 或者: from six import get_function_globals [as 別名]
def __init__(self, func):
    self.func = func
    self.namespace = six.get_function_globals(func)
    if six.get_function_closure(func):
      self.namespace.update(dict(zip(
          func.__code__.co_freevars,
          (cell.cell_contents for cell in six.get_function_closure(func))))) 

# 需要導入模塊: import six [as 別名]
# 或者: from six import get_function_globals [as 別名]
def fix_js_args(func):
    '''Use this function when unsure whether func takes this and arguments as its last 2 args.
       It will append 2 args if it does not.'''
    fcode = six.get_function_code(func)
    fargs = fcode.co_varnames[fcode.co_argcount - 2:fcode.co_argcount]
    if fargs == ('this', 'arguments') or fargs == ('arguments', 'var'):
        return func
    code = append_arguments(six.get_function_code(func), ('this', 'arguments'))

    return types.FunctionType(
        code,
        six.get_function_globals(func),
        func.__name__,
        closure=six.get_function_closure(func)) 

# 需要導入模塊: import six [as 別名]
# 或者: from six import get_function_globals [as 別名]
def fix_js_args(func):
    '''Use this function when unsure whether func takes this and arguments as its last 2 args.
       It will append 2 args if it does not.'''
    fcode = six.get_function_code(func)
    fargs = fcode.co_varnames[fcode.co_argcount-2:fcode.co_argcount]
    if fargs==('this', 'arguments') or fargs==('arguments', 'var'):
        return func
    code = append_arguments(six.get_function_code(func), ('this','arguments'))

    return types.FunctionType(code, six.get_function_globals(func), func.__name__, closure=six.get_function_closure(func)) 

# 需要導入模塊: import six [as 別名]
# 或者: from six import get_function_globals [as 別名]
def construct_new_test_function(original_func, name, build_params):
    """Builds a new test function based on parameterized data.

    :param original_func: The original test function that is used as a template
    :param name: The fullname of the new test function
    :param build_params: A dictionary or list containing args or kwargs
        for the new test
    :return: A new function object
    """
    new_func = types.FunctionType(
        six.get_function_code(original_func),
        six.get_function_globals(original_func),
        name=name,
        argdefs=six.get_function_defaults(original_func)
    )

    for key, val in original_func.__dict__.items():
        if key != 'build_data':
            new_func.__dict__[key] = val

    # Support either an arg list or kwarg dict for our data
    build_args = build_params if isinstance(build_params, list) else []
    build_kwargs = build_params if isinstance(build_params, dict) else {}

    # Build a test wrapper to execute with our kwargs
    def test_wrapper(func, test_args, test_kwargs):
        @functools.wraps(func)
        def wrapper(self):
            return func(self, *test_args, **test_kwargs)
        return wrapper

    return test_wrapper(new_func, build_args, build_kwargs) 

# 需要導入模塊: import six [as 別名]
# 或者: from six import get_function_globals [as 別名]
def test_get_function_globals():
    def f():
        pass
    assert six.get_function_globals(f) is globals() 

# 需要導入模塊: import six [as 別名]
# 或者: from six import get_function_globals [as 別名]
def construct_new_test_function(original_func, name, build_params):
    """Builds a new test function based on parameterized data.

    :param original_func: The original test function that is used as a template
    :param name: The fullname of the new test function
    :param build_params: A dictionary or list containing args or kwargs
        for the new test
    :return: A new function object
    """
    new_func = types.FunctionType(
        six.get_function_code(original_func),
        six.get_function_globals(original_func),
        name=name,
        argdefs=six.get_function_defaults(original_func)
    )

    # Support either an arg list or kwarg dict for our data
    build_args = build_params if isinstance(build_params, list) else []
    build_kwargs = build_params if isinstance(build_params, dict) else {}

    # Build a test wrapper to execute with our kwargs
    def test_wrapper(func, test_args, test_kwargs):
        @functools.wraps(func)
        def wrapper(self):
            return func(self, *test_args, **test_kwargs)
        return wrapper

    return test_wrapper(new_func, build_args, build_kwargs) 

# 需要導入模塊: import six [as 別名]
# 或者: from six import get_function_globals [as 別名]
def construct_new_test_function(original_func, name, build_params):
    """Builds a new test function based on parameterized data.

    :param original_func: The original test function that is used as a template
    :param name: The fullname of the new test function
    :param build_params: A dictionary or list containing args or kwargs
        for the new test
    :return: A new function object
    """
    new_func = types.FunctionType(
        six.get_function_code(original_func),
        six.get_function_globals(original_func),
        name=name,
        argdefs=six.get_function_defaults(original_func),
        closure=six.get_function_closure(original_func)
    )

    for key, val in original_func.__dict__.items():
        if key != 'build_data':
            new_func.__dict__[key] = val

    # Support either an arg list or kwarg dict for our data
    build_args = build_params if isinstance(build_params, list) else []
    build_kwargs = build_params if isinstance(build_params, dict) else {}

    # Build a test wrapper to execute with our kwargs
    def test_wrapper(func, test_args, test_kwargs):
        @functools.wraps(func)
        def wrapper(self):
            return func(self, *test_args, **test_kwargs)
        return wrapper

    return test_wrapper(new_func, build_args, build_kwargs) 

# 需要導入模塊: import six [as 別名]
# 或者: from six import get_function_globals [as 別名]
def autodiff_tree(func, wrt, motion, mode, preserve_result, check_dims,
                  verbose):
  """Perform AD on all functions in a call tree.

  This function walks the call tree and differentiates each function in it. It
  also ensures that the global namespaces that each function in the call tree
  was in are merged.

  The `tangent` and `numpy` packages are added to the namespace here, so that
  the gradient templates can assume that they are present.

  Args:
    See `grad`.

  Returns:
    final: A single module which contains the primals and adjoints of all the
        functions in the call tree.
    namespace: A merged dictionary with all the variables in the global
        namespaces of each function. The primals and adjoints need access to
        these in order to execute.
  """
  # Imported here to avoid circular imports
  import tangent
  namespace = {'tangent': tangent, 'numpy': numpy}

  done = set()
  final = gast.Module(body=[])
  namespace.update(six.get_function_globals(func))

  node, required = autodiff_ast(func, wrt, motion, mode, preserve_result,
                                check_dims, verbose)
  final.body.extend(node.body)

  to_do = set(required)
  if motion == 'split' and mode == 'reverse':
    done.add((func, wrt))
    to_do -= done

  while to_do:
    func, wrt = to_do.pop()
    namespace.update(six.get_function_globals(func))

    node, required = autodiff_ast(
        func=func,
        wrt=wrt,
        motion='split',
        mode=mode,
        preserve_result=True,
        check_dims=False,
        verbose=verbose)

    final.body.extend(node.body)
    done.add((func, wrt))
    to_do.update(required)
    to_do -= done

  return final, namespace