# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import collections import copy import functools import logging import inspect import pdb import re import types import numpy import builtins from paddle.fluid.dygraph.container import Sequential from .convert_operators import ( convert_len, convert_zip, convert_range, convert_enumerate, ) from paddle.fluid.dygraph.dygraph_to_static.logging_utils import ( TranslatorLogger, ) from paddle.fluid.dygraph.dygraph_to_static.utils import is_paddle_func, unwrap from paddle.fluid.dygraph.layers import Layer __all__ = ["convert_call"] # The api(s) should be considered as plain function and convert # them into static layer code. PADDLE_NEED_CONVERT_APIS = [Sequential] translator_logger = TranslatorLogger() CONVERSION_OPTIONS = "An attribute for a function that indicates conversion flags of the function in dynamic-to-static." class ConversionOptions: """ A container for conversion flags of a function in dynamic-to-static. Attributes: not_convert(bool): An attribute indicates that the function won't be converted in dynamic-to-static. NOTE(liym27): More attributes and methods can be added in this class. """ def __init__(self, not_convert=False): self.not_convert = not_convert def is_builtin(func, name=None): """predict whether a function is a builtin function with name={name}. if name == None, then any builtin function will return True """ def name_judge(): return name is None or func.__name__ == name if isinstance(func, types.BuiltinFunctionType) and name_judge(): return True elif func in builtins.__dict__.values() and name_judge(): return True else: return False def builtin_modules(): """ Return builtin modules. """ modules = [ collections, pdb, copy, inspect, re, numpy, logging, ] try: import six modules.append(six) except ImportError: pass # do nothing return modules BUILTIN_LIKELY_MODULES = builtin_modules() def is_unsupported(func): """ Checks whether the func is supported by dygraph to static graph. """ for m in BUILTIN_LIKELY_MODULES: for v in m.__dict__.values(): func_in_dict = func == v if isinstance(func_in_dict, (list, numpy.ndarray)): func_in_dict = numpy.array(func_in_dict).any() if func_in_dict: translator_logger.log( 2, "Whitelist: {} is part of built-in module and does not have to be transformed.".format( func ), ) return True # NOTE: should be placed before `is_paddle_func` if type(func) in PADDLE_NEED_CONVERT_APIS: return False if is_paddle_func(func): translator_logger.log( 2, "Whitelist: {} is part of Paddle module and does not have to be transformed.".format( func ), ) return True def convert_call(func): """ Converts a function call which needs to be transformed to static function. Args: func (callable): A callable function or method to convert. Returns: Callable: A converted function. Examples: .. code-block:: python import paddle from paddle.jit.dy2static import Call paddle.enable_static() def dyfunc(x): if paddle.mean(x) < 0: x_v = x - 1 else: x_v = x + 1 return x_v new_func = Call(dyfunc) x = paddle.tensor.manipulation.fill_constant(shape=[3, 3], value=0, dtype='float64') x_v = new_func(x) exe = paddle.static.Executor(paddle.CPUPlace()) out = exe.run(fetch_list=[x_v]) print(out[0]) # [[1. 1. 1.] # [1. 1. 1.] # [1. 1. 1.]] """ # NOTE(Aurelius84): Fix it after all files migrating into jit. from paddle.jit.dy2static.program_translator import ( convert_to_static, unwrap_decorators, StaticFunction, ) translator_logger.log( 1, "Convert callable object: convert {}.".format(func) ) func_self = None converted_call = None # Function in convert_call may be decorated by another `@to_static`, # in this case, unwraps it into a raw method or function. _, func = unwrap_decorators(func) options = getattr(func, CONVERSION_OPTIONS, None) if options is not None and options.not_convert: translator_logger.log( 2, "{} is not converted when it is decorated by 'paddle.jit.not_to_static'.".format( func ), ) return func if is_builtin(func, "len"): return convert_len if is_builtin(func, "zip"): return convert_zip if is_builtin(func, "range"): return convert_range if is_builtin(func, "enumerate"): return convert_enumerate if is_builtin(func) or is_unsupported(func): return func if inspect.isgeneratorfunction(func): # NOTE(xiongkun03): inspect.isfunction() will return True even though func is a generator function. # If we don't deal generatorfunction here, we will regard it as normal function and get errors in some # occasion. number_of_stars = 30 translator_logger.warn( "\n\n" + "*" * number_of_stars + "\nYour function:`{}` doesn't support to transform to static function because it is a generator function, it will be run as-is.".format( func.__name__ ) + "\n" + "*" * number_of_stars + "\n\n" ) return func if inspect.isfunction(func): # TODO(liym27): If func is a lambda function, special conversion is needed. if func.__name__ == '': return func try: # Note(Aurelius84): Because `@declarative` returns a class instance instead of # a function. This will modify the value referring to itself in `__globals__`. # For example: # # @declarative # def foo(x): # return x # # `foo` will be converted into a wrapper class, suppose as `StaticFunction`. # And `foo.__globals__['foo']` will still return this `StaticFunction` instead of # `foo` function. So `isinstance(fn, StaticFunction)` is added here. _origfunc = unwrap(func) global_functions = set() for fn in _origfunc.__globals__.values(): if inspect.isfunction(fn): global_functions.add(fn) elif isinstance(fn, StaticFunction): _, fn = unwrap_decorators(fn) global_functions.add(fn) elif inspect.isclass(fn): if isinstance( fn.__dict__.get(func.__name__, None), staticmethod ): global_functions.add( func ) # Add func to ensure that we will convert if func in global_functions: converted_call = convert_to_static(func) func_self = getattr(func, '__self__', None) else: # NOTE: # If func is not in __globals__, it does not need to be transformed # because it has been transformed before. translator_logger.warn( "{} doesn't have to be transformed to static function because it has been transformed before, it will be run as-is.".format( func ) ) converted_call = func except AttributeError: # NOTE: # If func is not in __globals__, it does not need to be transformed # because it has been transformed before. converted_call = None except (IOError, OSError): # NOTE: # If func has been decorated, its source code can not be get # so that it can not be transformed to static function. converted_call = None elif inspect.ismethod(func): try: converted_call = convert_to_static(func) func_self = getattr(func, '__self__', None) except (IOError, OSError): # NOTE: func may have been decorated. converted_call = None elif hasattr(func, '__class__') and hasattr(func.__class__, '__call__'): if hasattr(func, 'forward') and isinstance(func, Layer): try: _, forward_func = unwrap_decorators(func.forward) func._original_funcs['forward'] = forward_func.__func__ forward_func = convert_to_static(forward_func) # Bound mothod will be convert into plain function after `convert_to_static`. # So descriptor mechanism is used to bound `self` instance on function to # keep it as bound method. setattr(func, 'forward', forward_func.__get__(func)) except (IOError, OSError, TypeError): # NOTE: func.forward may have been decorated. func_self = None if func_self else func_self converted_call = func else: try: call_func = func.__class__.__call__ converted_call = convert_to_static(call_func) func_self = func except (IOError, OSError, TypeError): # NOTE: # If `func` is a class which is being initialized, for example `convert_call(Foo)()`, # it doesn't need to be transformed func_self = None if func_self else func_self else: raise NotImplementedError( "Callable {} can not be transformed at present.".format(func) ) if converted_call is None: translator_logger.warn( "{} doesn't have to be transformed to static function, and it will be run as-is.".format( func ) ) return func if func_self: converted_call = functools.partial(converted_call, func_self) return converted_call