コード例 #1
0
  def visit_Call(self, node):
    # If the function call is wrapped by one of the marker decorators,
    # consider it graph ready.
    if anno.hasanno(node.func, 'live_val'):
      target_entity = anno.getanno(node.func, 'live_val')
      if target_entity in self.ctx.program.autograph_decorators:
        if len(node.args) < 1:
          raise ValueError(
              'Found call to decorator function "%s", but it had no arguments. '
              'A decorator needs at least one positional argument.' %
              target_entity)
        anno.setanno(node.args[0], 'graph_ready', True)

    self.generic_visit(node)
    if anno.hasanno(node.func, 'live_val'):
      target_entity = anno.getanno(node.func, 'live_val')
      if anno.hasanno(node.func, 'fqn'):
        target_fqn = anno.getanno(node.func, 'fqn')
      else:
        target_fqn = None
      if self._function_is_compilable(target_entity):
        node = self._rename_compilable_function(node)
      elif target_fqn and target_fqn in KNOWN_NUMPY_FUNCTIONS:
        # TODO(mdan): Should we replace these with equivalent TF ops instead?
        node = self._wrap_to_py_func_single_return(
            node, KNOWN_NUMPY_FUNCTIONS[target_fqn].dtype)
      else:
        raise NotImplementedError(
            'py_func with return values (unknown function)')
    else:
      if anno.hasanno(node.func, anno.Basic.QN):
        # Special-case a few builtins that otherwise go undetected. This
        # normally doesn't pose a problem, but the dict built-in doesn't
        # work with inspect.getargspec which is required for dynamic functions.
        # Note: expecting this is resilient to aliasing (e.g.
        # dict = an_evil_dict), because in those cases the regular mechanisms
        # process a simple user function.
        qn = anno.getanno(node.func, anno.Basic.QN)
        # Add items to this list as needed.
        if str(qn) in ('dict',):
          return node

      if ast_util.matches(node, 'super(_)'):
        # super() calls are preserved. The class conversion mechanism will
        # ensure that they return the correct value.
        return node

      if self.ctx.program.recursive:
        node = self._insert_dynamic_conversion(node)
    return node
コード例 #2
0
ファイル: call_trees.py プロジェクト: ZhangXinNan/tensorflow
  def visit_Call(self, node):
    # If the function call is wrapped by one of the marker decorators,
    # consider it graph ready.
    if anno.hasanno(node.func, 'live_val'):
      target_entity = anno.getanno(node.func, 'live_val')
      if target_entity in self.ctx.program.autograph_decorators:
        if len(node.args) < 1:
          raise ValueError(
              'Found call to decorator function "%s", but it had no arguments. '
              'A decorator needs at least one positional argument.' %
              target_entity)
        anno.setanno(node.args[0], 'graph_ready', True)

    self.generic_visit(node)
    if anno.hasanno(node.func, 'live_val'):
      target_entity = anno.getanno(node.func, 'live_val')
      if anno.hasanno(node.func, 'fqn'):
        target_fqn = anno.getanno(node.func, 'fqn')
      else:
        target_fqn = None
      if self._function_is_compilable(target_entity):
        node = self._rename_compilable_function(node)
      elif target_fqn and target_fqn in KNOWN_NUMPY_FUNCTIONS:
        # TODO(mdan): Should we replace these with equivalent TF ops instead?
        node = self._wrap_to_py_func_single_return(
            node, KNOWN_NUMPY_FUNCTIONS[target_fqn].dtype)
      else:
        raise NotImplementedError(
            'py_func with return values (unknown function)')
    else:
      if anno.hasanno(node.func, anno.Basic.QN):
        # Special-case a few builtins that otherwise go undetected. This
        # normally doesn't pose a problem, but the dict built-in doesn't
        # work with inspect.getargspec which is required for dynamic functions.
        # Note: expecting this is resilient to aliasing (e.g.
        # dict = an_evil_dict), because in those cases the regular mechanisms
        # process a simple user function.
        qn = anno.getanno(node.func, anno.Basic.QN)
        # Add items to this list as needed.
        if str(qn) in ('dict',):
          return node

      if ast_util.matches(node, 'super(_)'):
        # super() calls are preserved. The class conversion mechanism will
        # ensure that they return the correct value.
        return node

      if self.ctx.program.recursive:
        node = self._insert_dynamic_conversion(node)
    return node
コード例 #3
0
    def get_definition_directive(self, node, directive, arg, default):
        """Returns the unique directive for a symbol, or a default if none exist.

    See lang/directives.py for details on directives.

    Args:
      node: ast.AST
      directive: Callable[..., Any]
      arg: str
      default: Any

    Raises:
      ValueError: if conflicting annotations have been found
    """
        defs = anno.getanno(node, anno.Static.ORIG_DEFINITIONS, ())
        if not defs:
            return default

        # TODO(mdan): Simplify this.
        arg_values = []
        for def_ in defs:
            if (directive not in def_.directives
                    or arg not in def_.directives[directive]):
                continue
            arg_value = def_.directives[directive][arg]
            for prev_value in arg_values:
                if not ast_util.matches(arg_value, prev_value):
                    qn = anno.getanno(node, anno.Basic.QN)
                    raise ValueError(
                        '%s has ambiguous annotations for %s(%s): %s, %s' %
                        (qn, directive.__name__, arg,
                         compiler.ast_to_source(arg_value).strip(),
                         compiler.ast_to_source(prev_value).strip()))
            arg_values.append(arg_value)

        if not arg_values:
            return default

        arg_value, = arg_values
        return arg_value
コード例 #4
0
ファイル: call_trees.py プロジェクト: imdone/tensorflow
    def visit_Call(self, node):
        # If the function is wrapped by one of the marker decorators,
        # consider it graph ready.
        if anno.hasanno(node.func, 'live_val'):
            target_entity = anno.getanno(node.func, 'live_val')
            if target_entity in self.nocompile_decorators:
                if len(node.args) < 1:
                    raise ValueError(
                        'Found call to decorator function "%s", but it had no arguments. '
                        'A decorator needs at least an argument.')
                anno.setanno(node.args[0], 'graph_ready', True)

        self.generic_visit(node)
        if anno.hasanno(node.func, 'live_val'):
            target_entity = anno.getanno(node.func, 'live_val')
            if anno.hasanno(node.func, 'fqn'):
                target_fqn = anno.getanno(node.func, 'fqn')
            else:
                target_fqn = None
            if self._function_is_compilable(target_entity):
                node = self._rename_compilable_function(node)
            elif target_fqn and target_fqn in KNOWN_NUMPY_FUNCTIONS:
                # TODO (mdan): Should we replace these with equivalent TF ops instead? id:647
                # https://github.com/imdone/tensorflow/issues/648
                node = self._wrap_to_py_func_single_return(
                    node, KNOWN_NUMPY_FUNCTIONS[target_fqn].dtype)
            else:
                raise NotImplementedError(
                    'py_func with return values (unknown function)')
        else:
            if ast_util.matches(node, 'super(_)'):
                # super() calls are preserved. The class conversion mechanism will
                # ensure that they return the correct value.
                pass
            elif self.context.recursive:
                node = self._insert_dynamic_conversion(node)
            else:
                # Unresolved functions are allowed in non-recursive mode.
                pass
        return node
コード例 #5
0
ファイル: converter.py プロジェクト: ZhangXinNan/tensorflow
  def get_definition_directive(self, node, directive, arg, default):
    """Returns the unique directive for a symbol, or a default if none exist.

    See lang/directives.py for details on directives.

    Args:
      node: ast.AST
      directive: Callable[..., Any]
      arg: str
      default: Any

    Raises:
      ValueError: if conflicting annotations have been found
    """
    defs = anno.getanno(node, anno.Static.ORIG_DEFINITIONS, ())
    if not defs:
      return default

    # TODO(mdan): Simplify this.
    arg_values = []
    for def_ in defs:
      if (directive not in def_.directives or
          arg not in def_.directives[directive]):
        continue
      arg_value = def_.directives[directive][arg]
      for prev_value in arg_values:
        if not ast_util.matches(arg_value, prev_value):
          qn = anno.getanno(node, anno.Basic.QN)
          raise ValueError('%s has ambiguous annotations for %s(%s): %s, %s' %
                           (qn, directive.__name__, arg,
                            compiler.ast_to_source(arg_value).strip(),
                            compiler.ast_to_source(prev_value).strip()))
      arg_values.append(arg_value)

    if not arg_values:
      return default

    arg_value, = arg_values
    return arg_value
コード例 #6
0
ファイル: call_trees.py プロジェクト: Jackiefan/tensorflow
  def visit_Call(self, node):
    # If the function is wrapped by one of the marker decorators,
    # consider it graph ready.
    if anno.hasanno(node.func, 'live_val'):
      target_entity = anno.getanno(node.func, 'live_val')
      if target_entity in self.nocompile_decorators:
        if len(node.args) < 1:
          raise ValueError(
              'Found call to decorator function "%s", but it had no arguments. '
              'A decorator needs at least an argument.')
        anno.setanno(node.args[0], 'graph_ready', True)

    self.generic_visit(node)
    if anno.hasanno(node.func, 'live_val'):
      target_entity = anno.getanno(node.func, 'live_val')
      if anno.hasanno(node.func, 'fqn'):
        target_fqn = anno.getanno(node.func, 'fqn')
      else:
        target_fqn = None
      if self._function_is_compilable(target_entity):
        node = self._rename_compilable_function(node)
      elif target_fqn and target_fqn in KNOWN_NUMPY_FUNCTIONS:
        # TODO(mdan): Should we replace these with equivalent TF ops instead?
        node = self._wrap_to_py_func_single_return(
            node, KNOWN_NUMPY_FUNCTIONS[target_fqn].dtype)
      else:
        raise NotImplementedError(
            'py_func with return values (unknown function)')
    else:
      if ast_util.matches(node, 'super(_)'):
        # super() calls are preserved. The class conversion mechanism will
        # ensure that they return the correct value.
        pass
      elif self.context.recursive:
        node = self._insert_dynamic_conversion(node)
      else:
        # Unresolved functions are allowed in non-recursive mode.
        pass
    return node
コード例 #7
0
 def assertNoMatch(self, target_str, pattern_str):
   node = parser.parse_expression(target_str)
   pattern = parser.parse_expression(pattern_str)
   self.assertFalse(ast_util.matches(node, pattern))
コード例 #8
0
 def assertNoMatch(self, target_str, pattern_str):
     node = parser.parse_expression(target_str)
     pattern = parser.parse_expression(pattern_str)
     self.assertFalse(ast_util.matches(node, pattern))