AVh_(dZddlZddlmZddlmZddlmZddlm Z ddl m Z ddl m Zdd lmZdd lmZdd lmZd Zed d dgej,ddZddZedddgej,ddZy)zDiscrete Cosine Transform ops.N)dtypes)ops) smart_cond) tensor_shape) array_ops)math_ops)fft_ops)dispatch) tf_exportc|dk7rtd|z||dkr td|dvr td|dk(r<|dk(r td |jd|jdd kr td |d vrtd |zy)z>Checks that DCT/IDCT arguments are compatible and well formed.zaxis must be -1. Got: %sNz&n should be a positive integer or Nonerz-Types I, II, III and IV (I)DCT are supported.orthoz2Normalization is not supported for the Type-I DCT.rz9Type-I DCT requires the dimension to be greater than one.)Nrz8Unknown normalization. Expected None or 'ortho', got: %s)NotImplementedError ValueErrorshape) input_tensordct_typenaxisnorms T/home/dcms/DCMS/lib/python3.12/site-packages/tensorflow/python/ops/signal/dct_ops.py_validate_dct_argumentsrs RZ 84? @@]q1u = >> \! D EE ] w K LL")l.@.@.Dq.H  E GG  BTI KK!z signal.dctz spectral.dct)v1c@t|||||t||||||S)aEComputes the 1D [Discrete Cosine Transform (DCT)][dct] of `input`. Types I, II, III and IV are supported. Type I is implemented using a length `2N` padded `tf.signal.rfft`. Type II is implemented using a length `2N` padded `tf.signal.rfft`, as described here: [Type 2 DCT using 2N FFT padded (Makhoul)] (https://dsp.stackexchange.com/a/10606). Type III is a fairly straightforward inverse of Type II (i.e. using a length `2N` padded `tf.signal.irfft`). Type IV is calculated through 2N length DCT2 of padded signal and picking the odd indices. @compatibility(scipy) Equivalent to [scipy.fftpack.dct] (https://docs.scipy.org/doc/scipy-1.4.0/reference/generated/scipy.fftpack.dct.html) for Type-I, Type-II, Type-III and Type-IV DCT. @end_compatibility Args: input: A `[..., samples]` `float32`/`float64` `Tensor` containing the signals to take the DCT of. type: The DCT type to perform. Must be 1, 2, 3 or 4. n: The length of the transform. If length is less than sequence length, only the first n elements of the sequence are considered for the DCT. If n is greater than the sequence length, zeros are padded and then the DCT is computed as usual. axis: For future expansion. The axis to compute the DCT along. Must be `-1`. norm: The normalization to apply. `None` for no normalization or `'ortho'` for orthonormal normalization. name: An optional name for the operation. Returns: A `[..., samples]` `float32`/`float64` `Tensor` containing the DCT of `input`. Raises: ValueError: If `type` is not `1`, `2`, `3` or `4`, `axis` is not `-1`, `n` is not `None` or greater than 0, or `norm` is not `None` or `'ortho'`. ValueError: If `type` is `1` and `norm` is `ortho`. [dct]: https://en.wikipedia.org/wiki/Discrete_cosine_transform r _dct_internal)inputtyperrrnames rdctr&2s*\%q$5 udAtT4 88rc "tj|dg5tjtjdj}t j j dxstj d'fd}fd}tjk||t j j dxstj d} tj| j} |dk(rTtjd d d dfgd } tjtj| } | cdddS|d k(rdtjtj |tj"|  t$j&zdz| z z} tjtjd | zgd d| f| z}|dk(rgdtj(| z}|t%j*dz}tj,tj.|d d | dz gg|}||z}|cdddS|dk(r|dk(retj*| }|t%j*dz}tj,tj.|d d | dz gg|}|zn| zdtjtj |tj"| t$j&zdz| z z} tjtj0| tj |zd | zgd d| f}|cdddS|dk(r[t3d d | z|d}|d ddd f}|dk(r.|t%j*dtj(| zz}|cdddS dddy#1swYyxYw)aComputes the 1D Discrete Cosine Transform (DCT) of `input`. This internal version of `dct` does not perform any validation and accepts a dynamic value for `n` in the form of a rank 0 tensor. Args: input: A `[..., samples]` `float32`/`float64` `Tensor` containing the signals to take the DCT of. type: The DCT type to perform. Must be 1, 2, 3 or 4. n: The length of the transform. If length is less than sequence length, only the first n elements of the sequence are considered for the DCT. If n is greater than the sequence length, zeros are padded and then the DCT is computed as usual. Can be an int or rank 0 tensor. axis: For future expansion. The axis to compute the DCT along. Must be `-1`. norm: The normalization to apply. `None` for no normalization or `'ortho'` for orthonormal normalization. name: An optional name for the operation. Returns: A `[..., samples]` `float32`/`float64` `Tensor` containing the DCT of `input`. r&gdtyper NcddfS)N.r)r#rsrtruncate_inputz%_dct_internal..truncate_inputsS!A#Xrctj}t|Dcgc]}ddg}}z ||dz d<tj|t j }tj|Scc}w)Nrrr()paddings) lenrrange_opsconvert_to_tensor_dtypesint32 _array_opspad)rank_paddingr#rseq_lens r pad_inputz _dct_internal..pad_inputso5;;#(;/aAq6// 7{q!(( F~~eg660s A;r.r)rrg@g?) fft_lengthr)constant_valuesrr)r$rrr)r1 name_scoper2r)rdimension_valuerr5r _math_opscastconcatrealr rfftexpcomplexr0_mathpirsqrtsqrtr6 expand_dimsirfftr")r#r$rrrr%zeror,r;axis_dimaxis_dim_float dct1_inputdct1scaledct2n1n2weightsdct3dct4r:s` ` @rr"r"ds. tUUG,U  " "5 )E  ! !#U[[ 9D $$U[[_5 $#  }7##AL.)Le,,U[[_=/##E*2. ^^Hekk:N qy$$eU31R<-@%AKj ^^GLL4 5d 9UU< qyIMM   Y__^44uxx?#E e^^ ,,X 003YhY @BG HId  9??>2 2 %**S/ !..  " "2q )Q1 ,=+>   gUUj   ^^N + %**S/ !..  " "2q )Q1 ,=+>   IMM   oon-83> e ^^ --i''t44h, )*+.yy.:d UUUX  5qAhJT Md#qt!t)_d   3)//."AAA kUUX YUUUs!EP-DP9DPAPPz signal.idctz spectral.idctcVt|||||ddddd|}t||||||S)aComputes the 1D [Inverse Discrete Cosine Transform (DCT)][idct] of `input`. Currently Types I, II, III, IV are supported. Type III is the inverse of Type II, and vice versa. Note that you must re-normalize by 1/(2n) to obtain an inverse if `norm` is not `'ortho'`. That is: `signal == idct(dct(signal)) * 0.5 / signal.shape[-1]`. When `norm='ortho'`, we have: `signal == idct(dct(signal, norm='ortho'), norm='ortho')`. @compatibility(scipy) Equivalent to [scipy.fftpack.idct] (https://docs.scipy.org/doc/scipy-1.4.0/reference/generated/scipy.fftpack.idct.html) for Type-I, Type-II, Type-III and Type-IV DCT. @end_compatibility Args: input: A `[..., samples]` `float32`/`float64` `Tensor` containing the signals to take the DCT of. type: The IDCT type to perform. Must be 1, 2, 3 or 4. n: For future expansion. The length of the transform. Must be `None`. axis: For future expansion. The axis to compute the DCT along. Must be `-1`. norm: The normalization to apply. `None` for no normalization or `'ortho'` for orthonormal normalization. name: An optional name for the operation. Returns: A `[..., samples]` `float32`/`float64` `Tensor` containing the IDCT of `input`. Raises: ValueError: If `type` is not `1`, `2` or `3`, `n` is not `None, `axis` is not `-1`, or `norm` is not `None` or `'ortho'`. [idct]: https://en.wikipedia.org/wiki/Discrete_cosine_transform#Inverse_transforms rrrrr)r$rrrr%r!)r#r$rrrr% inverse_types ridctr\sDR%q$51q)$/,  ,!$T FFr)rNr NN)__doc__mathrHtensorflow.python.frameworkrr3rr1rrtensorflow.python.opsrr5rrAtensorflow.python.ops.signalr tensorflow.python.utilr tensorflow.python.util.tf_exportr radd_dispatch_supportr&r"r\r+rrres%9324970+6K* <\>:; -9<-9`l` =m_=> *F?*Fr