o ?ed@sxdZddlmZddlmZddlmZddZddZd d Z d d Z dddZ ddZ ddZ dddZddZdS)zDContains layer utilities for input validation and format conversion.) smart_cond)cond) variablescCs|dkr|dkr dS|dkrdS|dkrdStd|d |d kr<|dkr(d S|dkr.d S|dkr4d Std|d td|d)N channels_lastZNWCZNHWCZNDHWCz Input rank: z5 not supported. We only support input rank 3, 4 or 5.channels_firstZNCWZNCHWZNCDHWzInvalid data_format: z5. We only support "channels_first" or "channels_last") ValueError) data_formatndimr _/home/www/facesmatcher.com/pyenv/lib/python3.10/site-packages/tensorflow/python/layers/utils.pyconvert_data_formats"rcCst|tr |f|Szt|}Wnty(td|dt|dt|wt||kr@td|dt|dt||D].}zt|WqBttfyptd|dt|dt|dt|dtt| w|S)aTransforms a single integer or iterable of integers into an integer tuple. Args: value: The value to validate and convert. Could an int, or any iterable of ints. n: The size of the tuple to be returned. name: The name of the argument being validated, e.g. "strides" or "kernel_size". This is only used to format error messages. Returns: A tuple of n integers. Raises: ValueError: If something else than an int/long or iterable thereof was passed. z Argument `z` must be a tuple of z integers. Received: z including element z of type ) isinstanceinttuple TypeErrorr strlentype)valuennameZ value_tupleZ single_valuer r rnormalize_tuple0s4       rcCs(|}|dvrtdt|d|S)N>rr zWThe `data_format` argument must be one of "channels_first", "channels_last". Received: .lowerr r)rr r r rnormalize_data_formatWs  rcCs(|}|dvrtdt|d|S)N>samevalidzAThe `padding` argument must be one of "valid", "same". Received: rr)rpaddingr r rnormalize_padding`s  r"cCst|durdS|dvs J||d|d}|dkr|}n|dkr(||d}n |dkr2||d}||d|S)aDetermines output length of a convolution given input length. Args: input_length: integer. filter_size: integer. padding: one of "same", "valid", "full". stride: integer. dilation: dilation rate, integer. Returns: The output length (integer). N>fullrr r#rr r$r ) input_length filter_sizer!strideZdilationZdilated_filter_size output_lengthr r rconv_output_lengthhs   r)cCs`|durdS|dvs J|dkr|d}n|dkrd}n|dkr$|d}|d|d||S) zDetermines input length of a convolution given output length. Args: output_length: integer. filter_size: integer. padding: one of "same", "valid", "full". stride: integer. Returns: The input length (integer). N>r$rr rr rr$r#r )r(r&r!r'padr r rconv_input_lengths   r,cCsN|durdS||9}|dkr|t||d7}|S|dkr%|||d8}|S)aDetermines output length of a transposed convolution given input length. Args: input_length: integer. filter_size: integer. padding: one of "same", "valid", "full". stride: integer. Returns: The output length (integer). Nr rr$r*)max)r%r&r!r'r r rdeconv_output_lengths r.NcCs0t|tjrtj||||dStj||||dS)aReturn either `true_fn()` if predicate `pred` is true else `false_fn()`. If `pred` is a bool or has a constant value, we return either `true_fn()` or `false_fn()`, otherwise we use `tf.cond` to dynamically route to both. Args: pred: A scalar determining whether to return the result of `true_fn` or `false_fn`. true_fn: The callable to be performed if pred is true. false_fn: The callable to be performed if pred is false. name: Optional name prefix when using `tf.cond`. Returns: Tensors returned by the call to either `true_fn` or `false_fn`. Raises: TypeError: If `true_fn` or `false_fn` is not callable. )true_fnfalse_fnr)rrVariabler smart_moduler)predr/r0rr r rrs rcCs>t|tr|dkr d}n|dkrd}t|tjrdSt|S)aReturn the bool value for `pred`, or None if `pred` had a dynamic value. Args: pred: A scalar, either a Python bool or a TensorFlow boolean variable or tensor, or the Python integer 1 or 0. Returns: True or False if `pred` has a constant boolean value, None otherwise. Raises: TypeError: If `pred` is not a Variable, Tensor or bool, or Python integer 1 or 0. r#TrFN)rrrr1r2Zsmart_constant_value)r3r r rconstant_values   r4)r#)NNN)__doc__Ztensorflow.python.frameworkrr2Ztensorflow.python.opsrrrrrr"r)r,r.r4r r r rs   '