U
    9%e'                     @   s   d dl Z d dlZd dlZd dlmZ dd Zdd Zdd Zd	d
 Z	dd Z
dd Zd"ddZdd Zdd Zdd Zdd Zdd Zdd Zdd Zd d! Ze ZdS )#    N)_find_builtinc                 C   s   |  do|  d S )N___)
startswith)name r   V/var/www/html/Darija-Ai-API/env/lib/python3.8/site-packages/torch/jit/supported_ops.py_hidden   s    r	   c                 C   s   t | S N)str)typer   r   r   
_emit_type   s    r   c                 C   sT   |j  dt|j }|j}|d k	r6| dt| }|dkrPdd|   | }|S )Nz : =r   
 )r   r   r   default_valuer   )indentiargvdefaultr   r   r   	_emit_arg   s    r   c                    s   d  fddt|D S )N,c                 3   s   | ]\}}t  ||V  qd S r
   )r   ).0r   r   r   r   r   	<genexpr>   s     z_emit_args.<locals>.<genexpr>)join	enumerate)r   	argumentsr   r   r   
_emit_args   s    r   c                 C   s
   t | jS r
   )r   r   )retr   r   r   	_emit_ret"   s    r!   c                 C   s4   t | dkrt| d S dddd | D  dS )N   r   zTuple[z, c                 s   s   | ]}t |V  qd S r
   )r!   )r   rr   r   r   r   )   s     z_emit_rets.<locals>.<genexpr>])lenr!   r   )returnsr   r   r   
_emit_rets&   s    r'      c                 C   sP   | d kr|}n|  d| }d |tt|d | |j|d  t|j}|S )N.z{}({}) -> {}r"   )formatr   r%   r   r'   r&   )modr   schema	arg_startpaddingZqualified_name
schema_strr   r   r   _emit_schema,   s    r0   c               
   C   sd   dd } g }t tjD ]D}t|stjd| }|D ]"}| |r6|td||dd q6qd|fS )Nc                 S   sF   t | jdkrdS | jd }|jdkr*dS |jtjj sBdS dS )Nr   FselfT)	r%   r   r   r   ZisSubtypeOftorch_CZ
TensorTypeget)r,   r1   r   r   r   is_tensor_method:   s    

z)_get_tensor_ops.<locals>.is_tensor_methodaten::Tensorr"   )r-   zSupported Tensor Methods)dirr2   r7   r	   r3   _jit_get_schemas_for_operatorappendr0   )r5   methodselemschemasr,   r   r   r   _get_tensor_ops9   s    
r>   c            
   	   C   s  g } t jj}|j}tt jjD ]}t||}t|rt|d rDqt	|}|sbt
d| dd|jkrnqz(t j|}|j}| t||| W q   Y qX qt jjjD ]^}|j}t|D ]J}tt||}|d k	rt j|}	|	D ]}t|s| t||| qqqd| fS )Nr   Module for 
 not foundztorch.nn.functionalzSupported PyTorch Functions)r2   nnZ
functional__name__r8   getattrinspect
isfunctionr	   	getmoduleRuntimeErrorjitscriptr,   r:   r0   	_builtinsZ_modules_containing_builtinsr   r3   r9   )
	functionsr+   r   r<   attrZattr_moduleZscriptedr,   builtinr=   r   r   r   _get_nn_functional_opsP   s8    


rN   c                  C   sr   g } t jjjD ]^\}}t|}t|ds,q|s2qt|jst|j	st|jrRqd|jkr^q| 
||f q| S )NrB   ztorch._C)r2   rH   rJ   Z_builtin_opsrD   rF   hasattrr	   rB   __qualname__r:   )builtinsfn_builtin_namer+   r   r   r   _get_builtins_helper{   s    


rT   c                 C   s(   t | }|std|  d|jdkS )Nr?   r@   math)rD   rF   rG   rB   )rR   r+   r   r   r   _is_math_fn   s    
rV   c            	      C   s   g } t dd t }t|}|D ]b\}}t|}|sFtd| dt|}|d k	r tj	|}|D ]}| 
t|j|j| qfq d| fS )Nc                 S   s   t | d  S Nr   rV   rR   r   r   r   <lambda>       z+_get_torchscript_builtins.<locals>.<lambda>r?   r@   zTorchScript Builtin Functions)filterrT   listrD   rF   rG   r   r2   r3   r9   r:   r0   rB   )	rK   rQ   builtins_listrR   rS   r+   rM   r=   r,   r   r   r   _get_torchscript_builtins   s    
r_   c            
      C   s   g } t dd t }t|}|D ]p\}}t|}|sFtd| dt|}|d k	r tj	|}|D ](}t
|j|j|}	d|	krqf| | qfq d| fS )Nc                 S   s   t | d S rW   rX   rY   r   r   r   rZ      r[   z$_get_math_builtins.<locals>.<lambda>r?   r@   r7   z``math`` Module)r\   rT   r]   rD   rF   rG   r   r2   r3   r9   r0   rB   r:   )
rK   rQ   r^   rR   rS   r+   rM   r=   r,   r/   r   r   r   _get_math_builtins   s"    

r`   c                  C   s  ddddddddd	d
ddddddddddddddddddg} dddd d!d"d#d$d%}d&d'd(d(d)d*d*d+d,}d-d.d/d0d1d2d3d4g}g }|D ] \}}| d5| d6| d7 qg }g }| D ]}d8| }	||kr|| }	tj|	}
|
D ]}| td ||d9d: qt|
d9kr| d; qd<| d=||  d5}| | qd>|}d>|}d>|}t|d?}t|d?}t|d?}d@| dA| dB| dC}dD|fS )ENprinttuplefloatcomplexintboolr   rC   rO   
isinstancer%   hexoctroundhashminmaxabsalldivmodr]   ordchrbinrangezipr   sortedz
aten::Boolz	aten::Intzaten::Floatzaten::Complexz	prim::absz	prim::maxz	prim::minzfake::does_not_exist)rf   re   rc   rd   rn   rm   rl   rt   zPrint any valuez]Lists cannot be converted to tuples with this method since their size is not statically knownz'Attribute name must be a literal stringzResult is staticzMArguments must be iterable. See :ref:`Iterables <jit_iterables>` for details.z-Can only be used as an iterator in a for loop)ra   rb   rC   rO   rg   ru   r   rt   )rd   __complex__)rc   	__float__)re   __int__)rf   __bool__)r   __str__)r%   __len__)rh   Z__hex__)ri   Z__oct__"z", "``z``"r6   r   )r.    z":any:`z`", "r   	z
The functions in the following table are supported but do not have a static schema

.. csv-table::
    :header: "Function", "Note"

z

The following functions will use the corresponding magic method on :any:`TorchScript classes`

.. csv-table::
    :header: "Function", "Magic Method"

zX

These built-in functions use the schema

.. rst-class:: codeblock-height-limiter

::

z
    zPython Built-in Functions)	r:   r2   r3   r9   r0   r%   r   textwrapr   )Zsupported_builtinsZ
op_renamesZschemaless_op_explanationsZmagic_methodsZmagic_methods_rowsrR   Zmagic_methodZschematized_opsZschemaless_opsZop_namer=   sZ	table_rowZschematized_ops_strZschemaless_ops_strZmagic_methods_rows_strsectionr   r   r   _get_global_builtins   s     



r   c                  C   s   dd } d}t ttttf}|D ]}| \}}|dddd dd}t|trv| ddt	|  d| d}n | ddt	|  d| | }d	| d
d | }||7 }q|S )Nc                 S   s   d ddd | D S )Nz1
.. rst-class:: codeblock-height-limiter

::

{}
r~   c                 s   s   | ]}d | dV  qdS )z    

Nr   )r   dr   r   r   r   >  s     z:_list_supported_ops.<locals>.emit_block.<locals>.<genexpr>)r*   r   )Zdeclsr   r   r   
emit_block<  s    z'_list_supported_ops.<locals>.emit_blockr~   `-r   r   ~z.. _:r   )
r>   rN   r_   r   r`   replacelowerrg   r   r%   )r   bodyZop_gathering_fnsrR   headeritemsZlink_targetr   r   r   r   _list_supported_ops;  s"    
 
  
r   )r   r(   )rD   r   Z	torch.jitr2   Ztorch.jit._builtinsr   r	   r   r   r   r!   r'   r0   r>   rN   rT   rV   r_   r`   r   r   __doc__r   r   r   r   <module>   s&   

+w