a 0Sic|@sxdZddlmZddlmZddlmZddZddZd d Z d d Z dddZ ddZ ddZ dddZddZdS)zDContains layer utilities for input validation and format conversion.) smart_cond)control_flow_ops) variablescCs|dkr>|dkrdS|dkr dS|dkr,dStd|d nN|d kr||dkrRd S|dkr^d S|dkrjd Std|d ntd|ddS)N channels_lastNWCNHWCNDHWCz Input rank: z5 not supported. We only support input rank 3, 4 or 5.channels_firstNCWNCHWNCDHWzInvalid data_format: z5. We only support "channels_first" or "channels_last") ValueError) data_formatndimrZ/var/www/html/django/DPS/env/lib/python3.9/site-packages/tensorflow/python/layers/utils.pyconvert_data_formats"rcCst|tr|f|Sz t|}Wn4tyTtd|dt|dt|Yn0t||krtd|dt|dt||D]b}z t|Wqttfytd|dt|dt|dt|dtt| Yq0q|SdS)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 N) isinstanceinttuple TypeErrorrstrlentype)valuenname value_tuple single_valuerrrnormalize_tuple0s0       r"cCs(|}|dvr$tdt|d|S)N>r rzWThe `data_format` argument must be one of "channels_first", "channels_last". Received: .lowerrr)rrrrrnormalize_data_formatWs  r&cCs(|}|dvr$tdt|d|S)N>validsamezAThe `padding` argument must be one of "valid", "same". Received: r#r$)rpaddingrrrnormalize_padding`s  r*cCst|dur dS|dvsJ||d|d}|dkr:|}n*|dkrP||d}n|dkrd||d}||d|S)aDetermines output length of a convolution given input length. Args: input_length: integer. filter_size: integer. padding: one of "same", "valid", "full". stride: integer. dilation: dilation rate, integer. Returns: The output length (integer). N>r'r(fullr+r(r'r,r) input_length filter_sizer)stridedilationdilated_filter_size output_lengthrrrconv_output_lengthhs   r3cCs`|dur dS|dvsJ|dkr*|d}n|dkr8d}n|dkrH|d}|d|d||S) zDetermines input length of a convolution given output length. Args: output_length: integer. filter_size: integer. padding: one of "same", "valid", "full". stride: integer. Returns: The input length (integer). N>r'r(r,r(r'rr,r+r)r2r.r)r/padrrrconv_input_lengths   r6cCsL|dur dS||9}|dkr0|t||d7}n|dkrH|||d8}|S)aDetermines output length of a transposed convolution given input length. Args: input_length: integer. filter_size: integer. padding: one of "same", "valid", "full". stride: integer. Returns: The output length (integer). Nr'rr,r4)max)r-r.r)r/rrrdeconv_output_lengths r8NcCs0t|tjrtj||||dStj||||dS)aReturn either `true_fn()` if predicate `pred` is true else `false_fn()`. If `pred` is a bool or has a constant value, we return either `true_fn()` or `false_fn()`, otherwise we use `tf.cond` to dynamically route to both. Args: pred: A scalar determining whether to return the result of `true_fn` or `false_fn`. true_fn: The callable to be performed if pred is true. false_fn: The callable to be performed if pred is false. name: Optional name prefix when using `tf.cond`. Returns: Tensors returned by the call to either `true_fn` or `false_fn`. Raises: TypeError: If `true_fn` or `false_fn` is not callable. )true_fnfalse_fnr)rrVariablercond smart_moduler)predr9r:rrrrrs rcCs>t|tr$|dkrd}n |dkr$d}t|tjr4dSt|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)rrrr;r=smart_constant_value)r>rrrconstant_values  r@)r+)NNN)__doc__tensorflow.python.frameworkrr=tensorflow.python.opsrrrr"r&r*r3r6r8r@rrrrs   '