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numpy_pickle_compat.cpython-35.pyc
���W� � @ s d Z d d l Z d d l Z d d l Z d d l m Z d d l m Z d d l m Z d d l m Z d d � Z e r� d d � Z n e Z e e d � � Z d Z d d � Z d d d � Z Gd d � d e � Z Gd d � d e � Z Gd d � d e � Z d d � Z d S) z%Numpy pickle compatibility functions.� N)�BytesIO� )� PY3_OR_LATER)� _ZFILE_PREFIX)� Unpicklerc C s d j | � S)z(Convert an int to an hexadecimal string.z{0:#x})�format)Zan_int� r �/numpy_pickle_compat.py�hex_str s r c C s t | t � r | S| j d � S)N�latin1)� isinstance�bytes�encode)�sr r r �asbytes s r � �@ i c C s� | j d � t t � t } | j | � } | t t � d � } t | d � } | j d � } | d k ry | j | � t j | j � d | � } t | � | k s� t d | � � | S)z�Read the z-file and return the content as a string. Z-files are raw data compressed with zlib used internally by joblib for persistence. Backward compatibility is not guaranteed. Do not use for external purposes. r N� r � � zIIncorrect data length while decompressing %s.The file could be corrupted.) �seek�lenr �_MAX_LEN�read�int�zlib� decompress�AssertionError)� file_handleZ header_length�lengthZ next_byte�datar r r � read_zfile s r! c C s^ | j t � t t | � � } | j t | j t � � � | j t j t | � | � � d S)z�Write the data in the given file as a Z-file. Z-files are raw data compressed with zlib used internally by joblib for persistence. Backward compatibility is not guarantied. Do not use for external purposes. N) �writer r r r �ljustr r �compress)r r r$ r r r r � write_zfile> s r% c @ s1 e Z d Z d Z d d d � Z d d � Z d S)�NDArrayWrapperz�An object to be persisted instead of numpy arrays. The only thing this object does, is to carry the filename in which the array has been persisted, and the array subclass. Tc C s | | _ | | _ | | _ d S)z4Constructor. Store the useful information for later.N)�filename�subclass� allow_mmap)�selfr' r( r) r r r �__init__V s zNDArrayWrapper.__init__c C s� t j j | j | j � } t | d d � } | s9 i n d | j i } | j j | | � } t | d � r� | j | j j | j j f k r� | j j j j | j d d � } | j | � S| Sd S) zReconstruct the array.r) T� mmap_mode�__array_prepare__r �bN)r )�os�path�join�_dirnamer' �getattrr, �np�load�hasattrr( ZndarrayZmemmap�core� multiarray� _reconstructr- )r* � unpicklerr' r) Z memmap_kwargs�arrayZ new_arrayr r r r \ s zNDArrayWrapper.readN)�__name__� __module__� __qualname__�__doc__r+ r r r r r r& O s r& c @ s. e Z d Z d Z d d � Z d d � Z d S)�ZNDArrayWrapperaU An object to be persisted instead of numpy arrays. This object store the Zfile filename in which the data array has been persisted, and the meta information to retrieve it. The reason that we store the raw buffer data of the array and the meta information, rather than array representation routine (tostring) is that it enables us to use completely the strided model to avoid memory copies (a and a.T store as fast). In addition saving the heavy information separately can avoid creating large temporary buffers when unpickling data with large arrays. c C s | | _ | | _ | | _ d S)z4Constructor. 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We capture it to replace our place-holder objects, NDArrayWrapper, by the array we are interested in. We replace them directly in the stack of pickler. r Nz@Trying to unpickle an ndarray, but numpy didn't import correctly���) r � load_buildr �stackr& r4 rK �popr �append)r* Znd_array_wrapperr; r r r rM � s z ZipNumpyUnpickler.load_buildr ) r< r= r> r? r �dispatch�copyr+ rJ rM r �pickle�BUILDr r r r rG � s rG c C s� t | d � �� } t | d | �} z] y | j � } WnF t k r } z& t rm t d � } | | _ | � WYd d } ~ Xn XWd t | d � r� | j j � X| SWd QRXd S)a' Reconstruct a Python object from a file persisted with joblib.dump. This function ensures the compatibility with joblib old persistence format (<= 0.9.3). Parameters ----------- filename: string The name of the file from which to load the object Returns ------- result: any Python object The object stored in the file. See Also -------- joblib.dump : function to save an object Notes ----- This function can load numpy array files saved separately during the dump. rC r zyYou may be trying to read with python 3 a joblib pickle generated with python 2. This feature is not supported by joblib.N) rD rG r5 �UnicodeDecodeErrorr � ValueError� __cause__r6 r �close)r' r r: �obj�exc�new_excr r r �load_compatibility� s r\ l i )r? rS r/ r �ior Z_compatr Znumpy_pickle_utilsr r r r �strr r � _CHUNK_SIZEr! r% �objectr& r@ rG r\ r r r r �<module> s& !$",
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__init__.cpython-35.opt-1.pyc
4779 bytes
0644
__init__.cpython-35.pyc
4779 bytes
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_compat.cpython-35.opt-1.pyc
677 bytes
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_compat.cpython-35.pyc
677 bytes
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_memory_helpers.cpython-35.opt-1.pyc
3223 bytes
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_memory_helpers.cpython-35.pyc
3223 bytes
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_multiprocessing_helpers.cpython-35.opt-1.pyc
922 bytes
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_multiprocessing_helpers.cpython-35.pyc
922 bytes
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_parallel_backends.cpython-35.opt-1.pyc
12908 bytes
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_parallel_backends.cpython-35.pyc
12908 bytes
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disk.cpython-35.opt-1.pyc
2571 bytes
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disk.cpython-35.pyc
2571 bytes
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format_stack.cpython-35.opt-1.pyc
9075 bytes
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format_stack.cpython-35.pyc
9123 bytes
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func_inspect.cpython-35.opt-1.pyc
9763 bytes
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func_inspect.cpython-35.pyc
9763 bytes
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hashing.cpython-35.opt-1.pyc
6653 bytes
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hashing.cpython-35.pyc
6653 bytes
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logger.cpython-35.opt-1.pyc
4184 bytes
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logger.cpython-35.pyc
4184 bytes
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memory.cpython-35.opt-1.pyc
28122 bytes
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memory.cpython-35.pyc
28122 bytes
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my_exceptions.cpython-35.opt-1.pyc
2750 bytes
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my_exceptions.cpython-35.pyc
2750 bytes
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numpy_pickle.cpython-35.opt-1.pyc
15536 bytes
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numpy_pickle.cpython-35.pyc
15536 bytes
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numpy_pickle_compat.cpython-35.opt-1.pyc
7262 bytes
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numpy_pickle_compat.cpython-35.pyc
7393 bytes
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numpy_pickle_utils.cpython-35.opt-1.pyc
16434 bytes
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numpy_pickle_utils.cpython-35.pyc
16434 bytes
0644
parallel.cpython-35.opt-1.pyc
25898 bytes
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parallel.cpython-35.pyc
25898 bytes
0644
pool.cpython-35.opt-1.pyc
18841 bytes
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pool.cpython-35.pyc
18841 bytes
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testing.cpython-35.opt-1.pyc
2657 bytes
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testing.cpython-35.pyc
2657 bytes
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