o ?e_(@sdZddlZddlmZddlmZddlmZddlm Z ddl m Z ddl m Zdd lmZdd lmZdd lmZd d ZedddgdejdddZdddZedddgdejdddZdS)zDiscrete Cosine Transform ops.N)dtypes)ops) smart_cond) tensor_shape) array_ops)math_ops)fft_ops)dispatch) tf_exportcCs|dkr td||dur|dkrtd|dvrtd|dkr<|dkr*td |jddur<|jdd krChecks that DCT/IDCT arguments are compatible and well formed.zaxis must be -1. Got: %sNz&n should be a positive integer or Noner z-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)Z input_tensorZdct_typenaxisnormre/home/www/facesmatcher.com/pyenv/lib/python3.10/site-packages/tensorflow/python/ops/signal/dct_ops.py_validate_dct_argumentss$ rz signal.dctz spectral.dct)v1rr cCs"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)inputtyperrrnamerrrdct2s.r!c st|dguttjdjd}tjdp%tddurBfdd}fdd }tk||tjdpPtd} t | j} |d kr}tj d d d dfgdd} t t | } | WdS|dkrdt t |t |  tjd| } t t jd| gdd d| f| }|dkrdt | }|td}tjt|d d | d gg|d}||9}|WdS|dkrC|dkrt | }|td}tjt|d d | d gg|d}|9n| 9dt t |t | tjd| } t t j| t |d| gdd d| f}|WdS|dkrvtdd| |dd}|d d ddf}|dkrm|tdt | 9}|WdSWddS1swYdS)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 NcsddfS)N.rrr)rrrrtruncate_inputsz%_dct_internal..truncate_inputcsNtj}ddt|D}||dd<tj|tjd}tj|dS)NcSsg|]}ddgqS)rr).0_rrr sz4_dct_internal..pad_input..r r")Zpaddings) lenrrange_opsconvert_to_tensor_dtypesZint32 _array_opspad)ZrankpaddingrrZseq_lenrr pad_inputs z _dct_internal..pad_inputr .r)rrg@g?)Z fft_lengthr)Zconstant_valuesrr)rrrr)r*Z name_scoper+r#rZdimension_valuerr-r _math_opscastconcatrealrZrfftexpcomplexr)_mathpiZrsqrtsqrtr.Z expand_dimsZirfftr)rrrrrr zeror$r1Zaxis_dimZaxis_dim_floatZ dct1_inputZdct1scaleZdct2Zn1Zn2weightsZdct3Zdct4rr0rrds       5     L L$rz signal.idctz spectral.idctcCs6t|||||ddddd|}t||||||dS)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 r rrrr )rrrrr r)rrrrrr Z inverse_typerrridcts ) r?)rNr NN)__doc__mathr9Ztensorflow.python.frameworkrr,rr*rrZtensorflow.python.opsrr-rr3Ztensorflow.python.ops.signalrZtensorflow.python.utilr Z tensorflow.python.util.tf_exportr rZadd_dispatch_supportr!rr?rrrrs&          0p