AVhT3dZddlZddlmZddlmZddlmZddlmZddlmZddlm Z dd l m Z dd l m Z dd l m Z dd lmZdd lmZej$ej&ddej(e j*fdZedej,ej$ej. ddej(e j*fdZdZdZdZdZdZdZy)z.Concat and stack operations for RaggedTensors.N)ops) tensor_shape) array_ops)array_ops_stack) check_ops)math_ops)ragged_gather_ops) ragged_tensor) ragged_util)dispatch) tf_exportvaluesct|ttfs|g}tj|d|5t ||dcdddS#1swYyxYw)aGConcatenates potentially ragged tensors along one dimension. Given a list of tensors with the same rank `K` (`K >= axis`), returns a rank-`K` `RaggedTensor` `result` such that `result[i0...iaxis]` is the concatenation of `[rt[i0...iaxis] for rt in values]`. Args: values: A list of potentially ragged tensors. May not be empty. All `values` must have the same rank and the same dtype; but unlike `tf.concat`, they can have arbitrary shapes. axis: A python integer, indicating the dimension along which to concatenate. (Note: Unlike `tf.concat`, the `axis` parameter must be statically known.) Negative values are supported only if the rank of at least one `values` value is statically known. name: A name prefix for the returned tensor (optional). Returns: A `RaggedTensor` with rank `K`. `result.ragged_rank=max(axis, max(rt.ragged_rank for rt in values]))`. Raises: ValueError: If `values` is empty, if `axis` is out of bounds or if the input tensors have different ranks. #### Example: >>> t1 = tf.ragged.constant([[1, 2], [3, 4, 5]]) >>> t2 = tf.ragged.constant([[6], [7, 8, 9]]) >>> tf.concat([t1, t2], axis=0) >>> tf.concat([t1, t2], axis=1) RaggedConcatF stack_valuesN isinstancelisttupler name_scope_ragged_stack_concat_helperraxisnames ^/home/dcms/DCMS/lib/python3.12/site-packages/tensorflow/python/ops/ragged/ragged_concat_ops.pyconcatr sOF FT5M *XF ~~dNF3I &vt% HIII A  Az ragged.stackct|ttfs|g}tj|d|5t ||dcdddS#1swYyxYw)aStacks a list of rank-`R` tensors into one rank-`(R+1)` `RaggedTensor`. Given a list of tensors or ragged tensors with the same rank `R` (`R >= axis`), returns a rank-`R+1` `RaggedTensor` `result` such that `result[i0...iaxis]` is `[value[i0...iaxis] for value in values]`. #### Examples: >>> # Stacking two ragged tensors. >>> t1 = tf.ragged.constant([[1, 2], [3, 4, 5]]) >>> t2 = tf.ragged.constant([[6], [7, 8, 9]]) >>> tf.ragged.stack([t1, t2], axis=0) >>> tf.ragged.stack([t1, t2], axis=1) >>> # Stacking two dense tensors with different sizes. >>> t3 = tf.constant([[1, 2, 3], [4, 5, 6]]) >>> t4 = tf.constant([[5], [6], [7]]) >>> tf.ragged.stack([t3, t4], axis=0) Args: values: A list of `tf.Tensor` or `tf.RaggedTensor`. May not be empty. All `values` must have the same rank and the same dtype; but unlike `tf.stack`, they can have arbitrary dimension sizes. axis: A python integer, indicating the dimension along which to stack. (Note: Unlike `tf.stack`, the `axis` parameter must be statically known.) Negative values are supported only if the rank of at least one `values` value is statically known. name: A name prefix for the returned tensor (optional). Returns: A `RaggedTensor` with rank `R+1` (if `R>0`). If `R==0`, then the result will be returned as a 1D `Tensor`, since `RaggedTensor` can only be used when `rank>1`. `result.ragged_rank=1+max(axis, max(rt.ragged_rank for rt in values]))`. Raises: ValueError: If `values` is empty, if `axis` is out of bounds or if the input tensors have different ranks. rTrNrrs rstackr IsO` FT5M *XF ~~dNF3H &vt$ GHHHrc |s td|Dcgc]}tj|d}}tj|ddi\}}t |}t |dk(r|s|dSd}|D]6}||j j}|j j|8||s|n|dz}tj||}|rv|dk(rq|dk(rltjjtj|d tj|Dcgc]}tj |c}d  Std |Dr@|>||dz k(s||dz k(r.|rtj ||Stj||St#t |D]C} tj$|| rtjj'|| d| || <Et)t)d |Dd} |Dcgc]}t+|| |}}|dk(r t-||S|dk(r t/||S|Dcgc]}|j0} }|Dcgc]}|j2g} }t5j6t9j:| 5tjj=t?| |dz || dddcdddScc}wcc}wcc}wcc}wcc}w#1swYyxYw)aHelper function to concatenate or stack ragged tensors. Args: rt_inputs: A list of RaggedTensors or Tensors to combine. axis: The axis along which to concatenate or stack. stack_values: A boolean -- if true, then stack values; otherwise, concatenate them. Returns: A RaggedTensor. Raises: ValueError: If rt_inputs is empty, or if axis is out of range. zrt_inputs may not be empty.rt_input)r return_dtypeTrNr)r row_lengthsc3HK|]}tj| ywN)r is_ragged.0rts r z._ragged_stack_concat_helper..s=R] $ $R ( (=s ") ragged_rankrow_splits_dtypec34K|]}|jywr()r.r*s rr-z._ragged_stack_concat_helper..s;2;sFvalidate) ValueErrorr "convert_to_tensor_or_ragged_tensormatch_row_splits_dtypesrlenshapendimsassert_has_rankrget_positive_axis RaggedTensorfrom_row_lengthsrallrr ranger) from_tensormax_increase_ragged_rank_to_ragged_stack_concat_axis_0_ragged_stack_concat_axis_1r row_splitsrcontrol_dependenciesr assert_splits_matchfrom_row_splitsr) rt_inputsrrr"r/r8r, out_ndimsrir.rsplitss rrrs  2 33 6?)166 %)!. E E!%#!%I9o) ^q Q< % &b }hhnnehhu% &  \e )  $ $T9 5$eqjTQY  % % 6 6 2$$)%LQiooa&8%L*+- 7 .. =9== di!m3tuqy7H $$Y55 400 Y Ja  " "9Q< 0"//;; A,A8H<JilJ C;;;Q?+"$(K9IJ$)$ QY &y, ?? qy &y, ??"+ ,Bbii ,F ,4= >x""# >F > ! !+"A"A&"I J(  ' ' 7 7 %fdQh E )A,8(((u4&M,$- >((s)KK$ K)K.!K36K88Lc F|Dcgc]}|j}}tj|d}|Dcgc]}|j}}|dj}t |Dcgc]}t |Dcgc]}|| c} } }}|rXtj|Dcgc]}|jc}} tj| } | jd| tjj|| dScc}wcc}wcc}wcc}}wcc}w)aHelper function to concatenate or stack ragged tensors along axis 0. Args: rt_inputs: A list of RaggedTensors, all with the same rank and ragged_rank. stack_values: Boolean. If true, then stack values; otherwise, concatenate them. Returns: A RaggedTensor. rr%Fr1) flat_valuesrrnested_row_splitsr.r>_concat_ragged_splitsrr nrowsr lengths_to_splitsinsertr r;from_nested_row_splits) rHrr,rNconcatenated_flat_values nested_splitsr.dimnsconcatenated_nested_splits stack_lengths stack_splitss rrBrBs&+44B4+4&--kB3<rreshape transposer gather_copy_row_shaper r;rGrDr)rHr num_inputs nrows_checksrt_nrowsindexr,concatenated_rt row_indicesrow_index_matrixtransposed_row_index_matrixrow_permutation permuted_rtr[ concat_splitss rrCrCs9~*, q\   !(Yqr]+ ieR  HHJ4U1WI>((      -=1)%PO..J!67K ((z26FG"+"5"56F"G''(CbTJO#**?OLK^^Ax*'Sets splits.shape to [rt[shape[0]+1] for each rt in rt_inputs.rNr$)r7 set_shaper TensorShape)rHrLr,s rrere/sF Bb xx{ |// a@ABc|dkDrntj|s!tjj||}|j|kr)|j t |j|dz |}|S)zGAdds ragged dimensions to `rt_input` so it has the desired ragged rank.r)r/r$)r r)r;r?r. with_valuesrAr)r"r.r/s rrArA6st1_  " "8 ,++77 %587hk)%% "8??K!O#3 56h /rtc|dg}|dd}|ddD]!}|j|dd|z||dz }#tj|dS)zCConcatenates a list of RaggedTensor splits to form a single splits.rr^r$Nr%)r`rr) splits_listpieces splits_offsetrLs rrPrPCsk N &a.$-AB f MM&*},-VBZM    &q ))rtr()rN)__doc__typingtensorflow.python.frameworkrrtensorflow.python.opsrrrrtensorflow.python.ops.raggedr r r tensorflow.python.utilr tensorflow.python.util.tf_exportr dispatch_for_apirList RaggedOrDenseadd_dispatch_supportr rrBrCrerArPrtrrs5 +4+1+*:64+69++,%I6;;}::;%I-%IP > ?0010H&++m99:0H20HfP(f LF7=tB *rt