AVh cdZddlZddlmZddlmZddlmZddlm Z ddl m Z ddlmZdd l mZdd l mZdd l mZdd lmZdd lmZddlmZddlmZm Z m!Z!ddl"m#Z#dxde#e!ejHffdZ%edejLe%Z'de#e!ejHffdZ(ejRdddgZ*dxdZ+edejLe+Z,dZ-dxde#e!ejHffdZ.edejLe.Z/de#e!ejHffdZ0ejRdddgZ1dxdZ2ed ejLe2Z3d!Z4ejRd"ddgZ5dxd#Z6ed$ejLe6Z7d%Z8dxde#e!ejHffd&Z9ed'ejLe9Z:de#e!ejHffd(Z;ejRd)ddgZ<dxd*e#e!ejzfd+e#e!ejzffd,Z>ed-ejLe>Z?d*e#e!ejzfd+e#e!ejzffd.Z@ejRd/ddgZAdxd*e#e!ejzfd+e#e!ejzfd0e#e!ejffd1ZCed2ejLeCZDd*e#e!ejzfd+e#e!ejzfd0e#e!ejffd3ZEdyd4e#e!ejfd5e#e!ejzfd6eGde#e!ejffd7ZHed8ejLeHZId4e#e!ejfd5e#e!ejzfd6eGde#e!ejffd9ZJdzd4e#e!ejfd5e#e!ejzfd;e#e!ejfdejLeLZMd4e#e!ejfd5e#e!ejzfd;e#e!ejfdejLeZd4e#e!ejfde#e!ejzfd*e#e!ejzfd+e#e!ejzfd5eKd6eGde#e!ejffd?Zdyd4e#e!ejfde#e!ejzfd9e#e!ejHfd6eGde#e!ejff d@ZedAejLeZd4e#e!ejfde#e!ejzfd9e#e!ejHfd6eGde#e!ejff dBZdd4e#e!ejfde#e!ejzfd*e#e!ejzfd+e#e!ejzfd9e#e!ejHfd5eKd6eGde#e!ejffdCZedDejLeZd4e#e!ejfde#e!ejzfd*e#e!ejzfd+e#e!ejzfd9e#e!ejHfd5eKd6eGde#e!ejffdEZdyd4e#e!ejfd$e#e!ejzfd6eGde#e!ejffdFZedGejLeZd4e#e!ejfd$e#e!ejzfd6eGde#e!ejffdHZedIZdxdJe#e!ejzfdKe#e!efdLe#e!ejzfde#e!ejffdMZ edNejLe Z!dJe#e!ejzfdKe#e!efdLe#e!ejzfde#e!ejffdOZ"dyde#e!ejfde#e!ejfde#e!ejzfd6eGde#e!ejff dPZ#edQejLe#Z$de#e!ejfde#e!ejfde#e!ejzfd6eGde#e!ejff dRZ%dyde#e!ejfde#e!ejfde#e!ejzfdSe#e!ejzfd6eGde#e!ejff dTZ&edUejLe&Z'de#e!ejfde#e!ejfde#e!ejzfdSe#e!ejzfd6eGde#e!ejff dVZ(dyd4e#e!ejfd$e#e!ejzfd6eGde#e!ejffdWZ)edXejLe)Z*d4e#e!ejfd$e#e!ejzfd6eGde#e!ejffdYZ+dyd6eGde#e!ejffdZZ,ed[ejLe,Z-d6eGde#e!ejffd\Z.dd]eKd6eGdeKde#e!ejffd^Z/ed_ejLe/Z0d]eKd6eGdeKde#e!ejffd`Z1dyde#e!ejfde#e!ejfde#e!ejzfd6eGde#e!ejff daZ2edbejLe2Z3de#e!ejfde#e!ejfde#e!ejzfd6eGde#e!ejff dcZ4dxdde#e!ejfde#e!ejffdeZ5edfejLe5Z6dde#e!ejfde#e!ejffdgZ7dyd4e#e!ejfdhe#e!ejzfdie#e!ejzfdje#e!ejzfd;e#e!ejfd6eGde#e!ejffdkZ8edlejLe8Z9d4e#e!ejfdhe#e!ejzfdie#e!ejzfdje#e!ejzfd;e#e!ejfd6eGde#e!ejffdmZ:dxde#e!ejffdnZ;edoejLe;ZedrejLe>Z?dde#e!ejfde#e!ejffdsZ@dydte#e e!ejfd6eGde#e!ejffduZAedvejLeAZBdte#e e!ejfd6eGde#e!ejffdwZCy(zUPython wrappers around TensorFlow ops. This file is MACHINE GENERATED! Do not edit. N) pywrap_tfe)context)core)execute)dtypes)annotation_types)op_def_registry)ops)op_def_library)deprecated_endpoints)dispatch) tf_export)TypeVarListAny) Annotatedreturnc tjxstj}|j}|jr t j |d|d|d|}|St|ttfst!d|z|Dcgc]}t#j$|d}}t|ttfst!d|z|Dcgc]}t#j&|d}}t)j*d|||\} } } } | dd}t#j,rHd| j/dd| j/df} | j0} t#j2d| | ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t||||S#t j$rYwxYwcc}wcc}w) 7A container for an iterator resource. Args: output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. name: A name for the operation (optional). Returns: A `Tensor` of type `resource`. AnonymousIterator output_types output_shapesNrrnamectxMExpected list for 'output_types' argument to 'anonymous_iterator' Op, not %r.NExpected list for 'output_shapes' argument to 'anonymous_iterator' Op, not %r.rrr)_contextr_thread_local_datais_eagerrTFE_Py_FastPathExecute_core_NotOkStatusException_opsraise_from_not_ok_status_FallbackException!anonymous_iterator_eager_fallback_SymbolicException isinstancelisttuple TypeError_execute make_type make_shape_op_def_library_apply_op_helpermust_record_gradientget_attrinputsrecord_gradientrrr_ctxtld_resulte_t_s__op_outputs_attrs _inputs_flats U/home/dcms/DCMS/lib/python3.12/site-packages/tensorflow/python/ops/gen_dataset_ops.pyanonymous_iteratorrDs    0h..0$ #\\ 11 !4(gn L4- 0  +-9 : ;;DPPR($$R8P,P MD%= 1  +-: ; <<GTT8&&r?;T-T'88,+8tE!QX QK' ""$cll>:Oll?+-F::L \67< (' .A  & &- ##At,,  # #    .#=t  # #   Q U<E0G$ G)0F7FF76F7;G G! G!zraw_ops.AnonymousIteratorct|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j |d}}g}d|d|f}t jdd||||}t jrt jd||||\}|Scc}wcc}w) NrrrrsAnonymousIteratorr5attrsrrr r*r+r,r-r.r/r0rr3r6 rrrrr<r=rBrAr:s rCr(r(Qs L4- 0  +-9 : ;;DPPR($$R8P,P MD%= 1  +-: ; <<GTT8&&r?;T-T, L/= I&   11\#)s ?' ""$ \67< (' .Q U C$0C)AnonymousIteratorV2handledeleterc (tjxstj}|j}|jr3 t j |d|d|d|}t j|}|St|t t"fst%d|z|Dcgc]}t'j(|d}}t|t t"fst%d|z|Dcgc]}t'j*|d}}t-j.d|||\} } } } | dd}t'j0rHd| j3dd| j3df} | j4} t'j6d| | |t j|}|S#tj$r }tj||Yd}~nd}~wtj$rYnwxYw t||||S#tj$rYwxYwcc}wcc}w) aA container for an iterator resource. Args: output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. name: A name for the operation (optional). Returns: A tuple of `Tensor` objects (handle, deleter). handle: A `Tensor` of type `resource`. deleter: A `Tensor` of type `variant`. rMrrNrPExpected list for 'output_types' argument to 'anonymous_iterator_v2' Op, not %r.QExpected list for 'output_shapes' argument to 'anonymous_iterator_v2' Op, not %r.r)rrr r!rr"_AnonymousIteratorV2Output_maker#r$r%r&r'$anonymous_iterator_v2_eager_fallbackr)r*r+r,r-r.r/r0r1r2r3r4r5r6r7s rCanonymous_iterator_v2rVks    0h..0$ #\\  11 #T><(g+009g n L4- 0  .0< = >>DPPR($$R8P,P MD%= 1  .0= > ??GTT8&&r?;T-T'88L-:G!QX QK' ""$cll>:Oll?+-F::L |VW> & , ,W 5' .A  & &- ##At,,  # #    1#=t  # #   Q Us<1FH !HG)GGG!G00HHzraw_ops.AnonymousIteratorV2ct|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j |d}}g}d|d|f}t jdd||||}t jrt jd|||tj|}|Scc}wcc}w) NrQrrRrsAnonymousIteratorV2rHrM) r*r+r,r-r.r/r0rr3r6rSrTrKs rCrUrUs L4- 0  .0< = >>DPPR($$R8P,P MD%= 1  .0= > ??GTT8&&r?;T-T, L/= I&   3Q|#)s ?' ""$ |VW> & , ,W 5' .Q Us C50C:c tjxstj}|j}|jr t j |d|d|d|}|St|ttfst!d|z|Dcgc]}t#j$|d}}t|ttfst!d|z|Dcgc]}t#j&|d}}t)j*d|||\} } } } | dd}t#j,rHd| j/dd| j/df} | j0} t#j2d| | ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t||||S#t j$rYwxYwcc}wcc}w) rAnonymousIteratorV3rrNrPExpected list for 'output_types' argument to 'anonymous_iterator_v3' Op, not %r.QExpected list for 'output_shapes' argument to 'anonymous_iterator_v3' Op, not %r.r)rrr r!rr"r#r$r%r&r'$anonymous_iterator_v3_eager_fallbackr)r*r+r,r-r.r/r0r1r2r3r4r5r6r7s rCanonymous_iterator_v3r^s    0h..0$ #\\ 11 #T><(gn L4- 0  .0< = >>DPPR($$R8P,P MD%= 1  .0= > ??GTT8&&r?;T-T'88L-:G!QX QK' ""$cll>:Oll?+-F::L |VW> (' .A  & &- ##At,,  # #    1#=t  # #   Q UrEzraw_ops.AnonymousIteratorV3ct|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j |d}}g}d|d|f}t jdd||||}t jrt jd||||\}|Scc}wcc}w) Nr[rr\rsAnonymousIteratorV3rGrHrZrJrKs rCr]r]s L4- 0  .0< = >>DPPR($$R8P,P MD%= 1  .0= > ??GTT8&&r?;T-T, L/= I&   3Q|#)s ?' ""$ |VW> (' .Q UrLAnonymousMemoryCachectjxstj}|j}|jr/ t j |d|}t j|}|Stj d|\}}}}|dd}t#j$r&d}|j&} t#j(d| ||t j|}|S#tj$r }tj||Yd}~nd}~wtj$rYnwxYw t||S#tj$rYwxYw)zTODO: add doc. Args: name: A name for the operation (optional). Returns: A tuple of `Tensor` objects (handle, deleter). handle: A `Tensor` of type `resource`. deleter: A `Tensor` of type `variant`. r`Nrrr)rrr r!rr"_AnonymousMemoryCacheOutputrTr#r$r%r&r'%anonymous_memory_cache_eager_fallbackr)r1r2r.r3r5r6 rr8r9r:r;r>r?r@rArBs rCanonymous_memory_cacherhs;    0h..0$ #\\ 11 $d,g+11':g n(88T+!QX QK' ""$ F::L  fg? ' - -g 6' .'  & &- ##At,,  # #    2  # #   s0-C D'3DD'&D'+ D88E Ezraw_ops.AnonymousMemoryCachecg}d}tjdd||||}tjrtjd|||tj |}|S)NsAnonymousMemoryCacherXrHr`)r.rr3r6rerTrrrBrAr:s rCrfrf;sb, &   4a #)s ?' ""$  fg? ' - -g 6' .AnonymousMultiDeviceIteratorc tjxstj}|j}|jr5 t j |d|d|d|d| }t j|}|St|t t"fst%d|z|Dcgc]}t'j(|d}}t|t t"fst%d|z|D cgc]} t'j*| d}} t|t t"fst%d |z|Dcgc]}t'j,|d}}t/j0d|||| \} } } } | dd}t'j2rYd| j5dd| j5dd| j5df} | j6}t'j8d|| |t j|}|S#tj$r }tj||Yd}~nd}~wtj$rYnwxYw t|||||S#tj$rYwxYwcc}wcc} wcc}w) aA container for a multi device iterator resource. Args: devices: A list of `strings` that has length `>= 1`. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. name: A name for the operation (optional). Returns: A tuple of `Tensor` objects (handle, deleter). handle: A `Tensor` of type `resource`. deleter: A `Tensor` of type `variant`. rldevicesrrNrnrrrrUExpected list for 'devices' argument to 'anonymous_multi_device_iterator' Op, not %r.ZExpected list for 'output_types' argument to 'anonymous_multi_device_iterator' Op, not %r.[Expected list for 'output_shapes' argument to 'anonymous_multi_device_iterator' Op, not %r.rnrrr)rrr r!rr"#_AnonymousMultiDeviceIteratorOutputrTr#r$r%r&r'.anonymous_multi_device_iterator_eager_fallbackr)r*r+r,r-r.make_strr/r0r1r2r3r4r5r6rnrrrr8r9r:r;r=r<r>r?r@rArBs rCanonymous_multi_device_iteratorrxKs    0h..0$ #\\  11 ,dIw o}Fg499'Bg n GdE] +  8:A B CC9@ @"X  r9 - @' @ L4- 0  8:F G HHDPPR($$R8P,P MD%= 1  8:G H IIGTT8&&r?;T-T'88&5A6C-1 3!QX QK' ""$i0.ll>*Oll?+-F::L & fgG / 5 5g >' .Q  & &- ##At,,  # #    ; %Dd<<  # #    A Q UsB3G1I&#I+*I01H8HH87H8<I I#"I#z$raw_ops.AnonymousMultiDeviceIteratorct|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j|d}}g}d|d|d|f}t jdd|||| } t jrt jd ||| tj| } | Scc}wcc}wcc}w) NrprnrqrrrrsAnonymousMultiDeviceIteratorrXrHrl) r*r+r,r-r.rvr/r0rr3r6rtrT rnrrrrr=r<rBrAr:s rCrurust GdE] +  8:A B CC9@ @"X  r9 - @' @ L4- 0  8:F G HHDPPR($$R8P,P MD%= 1  8:G H IIGTT8&&r?;T-T, w o &   ' .+ A Q UsD>0E7Ec tjxstj}|j}|jr t j |d|d|d|d| }|St|ttfst!d|z|Dcgc]}t#j$|d}}t|ttfst!d|z|D cgc]} t#j&| d}} t|ttfst!d |z|Dcgc]}t#j(|d}}t+j,d|||| \} } } } | dd}t#j.rYd| j1dd| j1dd| j1df} | j2}t#j4d|| ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t|||||S#t j$rYwxYwcc}wcc} wcc}w) a|A container for a multi device iterator resource. Args: devices: A list of `strings` that has length `>= 1`. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. name: A name for the operation (optional). Returns: A `Tensor` of type `resource`. AnonymousMultiDeviceIteratorV3rnrrNroXExpected list for 'devices' argument to 'anonymous_multi_device_iterator_v3' Op, not %r.]Expected list for 'output_types' argument to 'anonymous_multi_device_iterator_v3' Op, not %r.^Expected list for 'output_shapes' argument to 'anonymous_multi_device_iterator_v3' Op, not %r.rs)rrr r!rr"r#r$r%r&r'1anonymous_multi_device_iterator_v3_eager_fallbackr)r*r+r,r-r.rvr/r0r1r2r3r4r5r6rws rC"anonymous_multi_device_iterator_v3rss    0h..0$ #\\ 11 .i o}Fgn GdE] +  ;=D E FF9@ @"X  r9 - @' @ L4- 0  ;=I J KKDPPR($$R8P,P MD%= 1  ;=J K LLGTT8&&r?;T-T'88('7C8E/3 5!QX QK' ""$i0.ll>*Oll?+-F::L (,I (' .Q  & &- ##At,,  # #    > %Dd<<  # #    A Q UsBG III  HG99HHH&&H=<H=z&raw_ops.AnonymousMultiDeviceIteratorV3cxt|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j|d}}g}d|d|d|f}t jdd|||| } t jrt jd ||| | \} | Scc}wcc}wcc}w) Nr}rnr~rrrsAnonymousMultiDeviceIteratorV3rGrHr| r*r+r,r-r.rvr/r0rr3r6rzs rCrrsk GdE] +  ;=D E FF9@ @"X  r9 - @' @ L4- 0  ;=I J KKDPPR($$R8P,P MD%= 1  ;=J K LLGTT8&&r?;T-T, w o &   >$0C"& ('""$ (,I (' .+ A Q UsD-0D27D7AnonymousRandomSeedGeneratorseedseed2ctjxstj}|j}|jr1 t j |d|||}t j|}|Stj d|||\}}}} | dd}t#j$r&d} |j&} t#j(d| | |t j|}|S#tj$r }tj||Yd}~nd}~wtj$rYnwxYw t||||S#tj$rYwxYw)a,TODO: add doc. Args: seed: A `Tensor` of type `int64`. seed2: A `Tensor` of type `int64`. name: A name for the operation (optional). Returns: A tuple of `Tensor` objects (handle, deleter). handle: A `Tensor` of type `resource`. deleter: A `Tensor` of type `variant`. rNrb)rrrrd)rrr r!rr"#_AnonymousRandomSeedGeneratorOutputrTr#r$r%r&r'.anonymous_random_seed_generator_eager_fallbackr)r1r2r.r3r5r6) rrrr8r9r:r;r>r?r@rArBs rCanonymous_random_seed_generatorrsJ    0h..0$ #\\ 11 ,dD%Ag399'Bg n(88&TTK!QX QK' ""$ F::L & fgG / 5 5g >' .'  & &- ##At,,  # #    ; Dd,,  # #   s0/C$$D+7DD+*D+/D>>EEz$raw_ops.AnonymousRandomSeedGeneratorcZtj|tj}tj|tj}||g}d}t j dd||||}t j rt jd|||tj|}|S)NsAnonymousRandomSeedGeneratorrXrHr) r%convert_to_tensor_dtypesint64r.rr3r6rrT)rrrrrBrAr:s rCrr=s  gmm 4$   6%, &   ' .rkAnonymousSeedGenerator reshufflectjxstj}|j}|jr2 t j |d||||}t j|}|Stj d||||\}}} } | dd}t#j$r&d} | j&} t#j(d| | |t j|}|S#tj$r }tj||Yd}~nd}~wtj$rYnwxYw t|||||S#tj$rYwxYw)aVTODO: add doc. Args: seed: A `Tensor` of type `int64`. seed2: A `Tensor` of type `int64`. reshuffle: A `Tensor` of type `bool`. name: A name for the operation (optional). Returns: A tuple of `Tensor` objects (handle, deleter). handle: A `Tensor` of type `resource`. deleter: A `Tensor` of type `variant`. rNrb)rrrrrd)rrr r!rr"_AnonymousSeedGeneratorOutputrTr#r$r%r&r''anonymous_seed_generator_eager_fallbackr)r1r2r.r3r5r6) rrrrr8r9r:r;r>r?r@rArBs rCanonymous_seed_generatorrPsR    0h..0$ #\\ 11 &dE9Fg-33G= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. BatchDatasetrrrNrrrrrHExpected list for 'output_types' argument to 'batch_dataset' Op, not %r.IExpected list for 'output_shapes' argument to 'batch_dataset' Op, not %r.)rrrrrr)rrr r!rr"r#r$r%r&r'batch_dataset_eager_fallbackr)r*r+r,r-r.r/r0rvr1r2r3r4r5r6)rrrrrrr8r9r:r;r<r=r>r?r@rArBs rC batch_datasetrsB    0h..0$ #\\ 11 ndM:~o}j(Lgn L4- 0  &(4 5 66DPPR($$R8P,P MD%= 1  &(5 6 77GTT8&&r?;T-T H   x 4('88m %1&3h! #!QX QK' ""$cll>:Oll?+Zll:&(F::L  fg7 (' .M  & &- ##At,,  # #    ) ,%tOO  # #   Q U< F" HH"G)5GG)(G)-G??HHzraw_ops.BatchDatasetct|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j |d}}|d}t j|d}tj|tj}tj|tj}||g} d|d|d|f} t jdd| | || } t jrt jd | | | | \} | Scc}wcc}w) Nrrrrrrs BatchDatasetrGrHrr*r+r,r-r.r/r0rvr%rrvariantrrr3r6) rrrrrrrr<r=rBrAr:s rCrrsZ L4- 0  &(4 5 66DPPR($$R8P,P MD%= 1  &(5 6 77GTT8&&r?;T-T H   x 4(((H-%%j'--@*,, L/= h &   _a #)s ?' ""$  fg7 (' .)Q U E 0EFdrop_remainder parallel_copyctjxstj}|j} | jr% t j |d||||d|d|d|d|} | St|ttfst!d|z|D cgc]} t#j$| d}} t|ttfst!d |z|D cgc]} t#j&| d}} |d }t#j(|d}|d }t#j*|d}t-j.d|||||||| \}}}}|dd} t#j0rjd|j3dd|j5dd|j5dd|j5df}|j6}t#j8d||| | \} | S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t||||||||| S#t j$rYwxYwcc} wcc} w) aCreates a dataset that batches `batch_size` elements from `input_dataset`. Args: input_dataset: A `Tensor` of type `variant`. batch_size: A `Tensor` of type `int64`. A scalar representing the number of elements to accumulate in a batch. drop_remainder: A `Tensor` of type `bool`. A scalar representing whether the last batch should be dropped in case its size is smaller than desired. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. parallel_copy: An optional `bool`. Defaults to `False`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. BatchDatasetV2rrrrN)rrrrrrKExpected list for 'output_types' argument to 'batch_dataset_v2' Op, not %r.LExpected list for 'output_shapes' argument to 'batch_dataset_v2' Op, not %r.Fr)rrrrrrrr)rrr r!rr"r#r$r%r&r'batch_dataset_v2_eager_fallbackr)r*r+r,r-r.r/r0 make_boolrvr1r2r3_get_attr_boolr4r5r6)rrrrrrrrr8r9r:r;r<r=r>r?r@rArBs rCbatch_dataset_v2rs&    0h..0$ #\\  11 mZo}j(Lgn L4- 0  )+7 8 99DPPR($$R8P,P MD%= 1  )+8 9 ::GTT8&&r?;T-TM$$]OD- H   x 4('88 *)7'3(5(5# %!QX QK' ""$s11/Bcll>:Oll?+Zll:&(F::L ,9 (' .[  & &- ##At,,  # #    , ^%L%tOO  # #   Q U<#G I IH%HHHH11IIzraw_ops.BatchDatasetV2c *t|ttfstd|z|D cgc]} t j | d}} t|ttfstd|z|D cgc]} t j | d}} |d}t j|d}|d}t j|d}tj|tj}tj|tj}tj|tj}|||g} d|d|d|d|f} t jd d | | || } t j rt j"d | | | | \} | Scc} wcc} w) NrrrrFrrrsBatchDatasetV2rGrHrr*r+r,r-r.r/r0rrvr%rrrrrrr3r6)rrrrrrrrrr<r=rBrAr:s rCrr=s L4- 0  )+7 8 99DPPR($$R8P,P MD%= 1  )+8 9 ::GTT8&&r?;T-TM$$]OD- H   x 4(((H-%%j'--@*)).',,G.^<, ]NL=*h 8&   .,#)s ?' ""$ ,9 (' .1Q U F 0Ffilenamec Ftjxstj}|j}|jr" t j |d|||d|d|d| }|St|ttfst!d|z|D cgc]} t#j$| d}} t|ttfst!d|z|D cgc]} t#j&| d}} |d }t#j(|d}t+j,d|||||| \} } } }|dd}t#j.rYd| j1dd| j1dd| j1df}| j2}t#j4d||||\}|S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t|||||||S#t j$rYwxYwcc} wcc} w) aUCreates a dataset that caches elements from `input_dataset`. A CacheDataset will iterate over the input_dataset, and store tensors. If the cache already exists, the cache will be used. If the cache is inappropriate (e.g. cannot be opened, contains tensors of the wrong shape / size), an error will the returned when used. Args: input_dataset: A `Tensor` of type `variant`. filename: A `Tensor` of type `string`. A path on the filesystem where we should cache the dataset. Note: this will be a directory. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. CacheDatasetrrrNrHExpected list for 'output_types' argument to 'cache_dataset' Op, not %r.IExpected list for 'output_shapes' argument to 'cache_dataset' Op, not %r.r)rrrrrr)rrr r!rr"r#r$r%r&r'cache_dataset_eager_fallbackr)r*r+r,r-r.r/r0rvr1r2r3r4r5r6)rrrrrrr8r9r:r;r<r=r>r?r@rArBs rC cache_datasetr]sB*    0h..0$ #\\ 11 ndM8^o}j(Lgn L4- 0  &(4 5 66DPPR($$R8P,P MD%= 1  &(5 6 77GTT8&&r?;T-T H   x 4('88mh%1&3h! #!QX QK' ""$cll>:Oll?+Zll:&(F::L  fg7 (' .M  & &- ##At,,  # #    )  %tOO  # #   Q Urzraw_ops.CacheDatasetct|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j |d}}|d}t j|d}tj|tj}tj|tj}||g} d|d|d|f} t jdd| | || } t jrt jd | | | | \} | Scc}wcc}w) Nrrrrrrs CacheDatasetrGrHrr*r+r,r-r.r/r0rvr%rrrstringrr3r6) rrrrrrrr<r=rBrAr:s rCrrsZ L4- 0  &(4 5 66DPPR($$R8P,P MD%= 1  &(5 6 77GTT8&&r?;T-T H   x 4(((H-  # #Hgnn =(*, L/= h &   _a #)s ?' ""$  fg7 (' .)Q UrcachecLtjxstj}|j}|jr# t j |d||||d|d|d| } | St|ttfst!d|z|D cgc]} t#j$| d}} t|ttfst!d|z|D cgc]} t#j&| d}} |d }t#j(|d}t+j,d||||||| \} } }}|dd} t#j.rYd|j1dd|j1dd|j1df}|j2}t#j4d||| | \} | S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t||||||||S#t j$rYwxYwcc} wcc} w) aTODO: add doc. Args: input_dataset: A `Tensor` of type `variant`. filename: A `Tensor` of type `string`. cache: A `Tensor` of type `resource`. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. CacheDatasetV2rrrNrKExpected list for 'output_types' argument to 'cache_dataset_v2' Op, not %r.LExpected list for 'output_shapes' argument to 'cache_dataset_v2' Op, not %r.r)rrrrrrr)rrr r!rr"r#r$r%r&r'cache_dataset_v2_eager_fallbackr)r*r+r,r-r.r/r0rvr1r2r3r4r5r6)rrrrrrrr8r9r:r;r<r=r>r?r@rArBs rCcache_dataset_v2rsI    0h..0$ #\\  11 mXu o}Hgn L4- 0  )+7 8 99DPPR($$R8P,P MD%= 1  )+8 9 ::GTT8&&r?;T-T H   x 4('88  %L(5# %!QX QK' ""$cll>:Oll?+Zll:&(F::L ,9 (' .M  & &- ##At,,  # #    , 5|%tOO  # #   Q U<!F$ HH!$G+7GG+*G+/HHHzraw_ops.CacheDatasetV2ct|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|D cgc]} t j | d}} |d}t j|d}tj|tj}tj|tj}tj|tj}|||g} d|d|d|f} t jdd| | || } t jrt j d | | | | \} | Scc}wcc} w) NrrrrrrsCacheDatasetV2rGrHr)r*r+r,r-r.r/r0rvr%rrrrresourcerr3r6) rrrrrrrrr<r=rBrAr:s rCrrsu L4- 0  )+7 8 99DPPR($$R8P,P MD%= 1  )+8 9 ::GTT8&&r?;T-T H   x 4(((H-  # #Hgnn =(  (8(8 9%51, L/= h &   .,#)s ?' ""$ ,9 (' .+Q U E/0E4another_datasetc Ftjxstj}|j}|jr" t j |d|||d|d|d| }|St|ttfst!d|z|D cgc]} t#j$| d}} t|ttfst!d|z|D cgc]} t#j&| d}} |d }t#j(|d}t+j,d|||||| \} } } }|dd}t#j.rYd| j1dd| j1dd| j1df}| j2}t#j4d||||\}|S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t|||||||S#t j$rYwxYwcc} wcc} w) aCreates a dataset that concatenates `input_dataset` with `another_dataset`. Args: input_dataset: A `Tensor` of type `variant`. another_dataset: A `Tensor` of type `variant`. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. ConcatenateDatasetrrrNrNExpected list for 'output_types' argument to 'concatenate_dataset' Op, not %r.OExpected list for 'output_shapes' argument to 'concatenate_dataset' Op, not %r.r)rrrrrr)rrr r!rr"r#r$r%r&r'"concatenate_dataset_eager_fallbackr)r*r+r,r-r.r/r0rvr1r2r3r4r5r6)rrrrrrr8r9r:r;r<r=r>r?r@rArBs rCconcatenate_datasetr!sD    0h..0$ #\\  11 "D- o}Hgn L4- 0  ,.: ; <<DPPR($$R8P,P MD%= 1  ,.; < ==GTT8&&r?;T-T H   x 4('88M.=+7,9H#' )!QX QK' ""$cll>:Oll?+Zll:&(F::L lFG= (' .O  & &- ##At,,  # #    / |%tOO  # #   Q Urzraw_ops.ConcatenateDatasetct|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j |d}}|d}t j|d}tj|tj}tj|tj}||g} d|d|d|f} t jdd| | || } t jrt jd | | | | \} | Scc}wcc}w) NrrrrrrsConcatenateDatasetrGrHr)r*r+r,r-r.r/r0rvr%rrrrr3r6) rrrrrrrr<r=rBrAr:s rCrrds[ L4- 0  ,.: ; <<DPPR($$R8P,P MD%= 1  ,.; < ==GTT8&&r?;T-T H   x 4(((H-**?GOOL/1, L/= h &   2Al#)s ?' ""$ lFG= (' .)Q Urcardinality_optionsctjxstj}|j}|jr t j |d||d|}|S|d}tj|d}tj d|||\}}}} | dd}tj"r7d|j%df} |j&} tj(d| | ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t||||S#t j$rYwxYw)a~Returns the cardinality of `input_dataset`. Returns the cardinality of `input_dataset`. Args: input_dataset: A `Tensor` of type `variant`. A variant tensor representing the dataset to return cardinality for. cardinality_options: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `int64`. DatasetCardinalityrN)rrrr)rrr)rrr r!rr"r#r$r%r&r'"dataset_cardinality_eager_fallbackr)r.rvr1r2r3r4r5r6) rrrr8r9r:r;r>r?r@rArBs rCdataset_cardinalityrsl    0h..0$ #\\ 11 "D-24gn  ))*=?TU'88M2E#')!QX QK' ""$#S\\2G%H IF::L lFG= (' .3  & &- ##At,,  # #    / -@t  # #   0C**D1=DD10D15EEEzraw_ops.DatasetCardinalityc&|d}tj|d}tj|tj }|g}d|f}tj dd||||}tjrtjd||||\}|S)NrrsDatasetCardinalityrGrHr) r.rvr%rrrrr3r6)rrrrrBrAr:s rCrrs  ))*=?TU((H-, !#6 7&   2Al#)s ?' ""$ lFG= (' .rkc\tjxstj}|j}|jr t j |d||}|Stjd||\}}}}|dd}tj r&d} |j"} tj$d| | ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t|||S#t j$rYwxYw)a>Returns the fingerprint of `input_dataset`. Returns the fingerprint of `input_dataset`. Args: input_dataset: A `Tensor` of type `variant`. A variant tensor representing the dataset to return fingerprint for. name: A name for the operation (optional). Returns: A `Tensor` of type `uint64`. DatasetFingerprintNrbrrrd)rrr r!rr"r#r$r%r&r'"dataset_fingerprint_eager_fallbackr)r1r2r.r3r5r6 rrr8r9r:r;r>r?r@rArBs rCdataset_fingerprintrs)    0h..0$ #\\ 11 "D-9g n(88MF!QX QK' ""$ F::L lFG= (' .'  & &- ##At,,  # #    / d..  # #   0B<<DC**DD DD+*D+zraw_ops.DatasetFingerprintctj|tj}|g}d}t j dd||||}t j rt jd||||\}|S)NsDatasetFingerprintrGrHrr%rrrr.rr3r6rrrrBrAr:s rCrrsq((H-, &   2Al#)s ?' ""$ lFG= (' .rkallow_statefulstrip_device_assignmentc tjxstj}|j}|jr! t j |d||d|d|d| }|S|g}t|ttfst!d|z|D cgc]} t#j$| d}} |d}t#j&|d}|d}t#j&|d}t)j*d||||| \} } } } | dd}t#j,rYd| j/dd| j1dd| j1df} | j2}t#j4d|| ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t||||||S#t j$rYwxYwcc} w) a/Returns a serialized GraphDef representing `input_dataset`. Returns a graph representation for `input_dataset`. Args: input_dataset: A `Tensor` of type `variant`. A variant tensor representing the dataset to return the graph representation for. stateful_whitelist: An optional list of `strings`. Defaults to `[]`. allow_stateful: An optional `bool`. Defaults to `False`. strip_device_assignment: An optional `bool`. Defaults to `False`. name: A name for the operation (optional). Returns: A `Tensor` of type `string`. DatasetToGraphstateful_whitelistrrN)rrrrrQExpected list for 'stateful_whitelist' argument to 'dataset_to_graph' Op, not %r.F)rrrrr)rrr r!rr"r#r$r%r&r'dataset_to_graph_eager_fallbackr)r*r+r,r-r.rvrr1r2r3r4rr5r6)rrrrrr8r9r:r;r=r>r?r@rArBs rCdataset_to_graphrs)    0h..0$ #\\  11 m5I,n!#: ??Oaa))".BCaaN%%n6FG.$#$../FHab'88 -?)72I# %!QX QK' ""$"CLL1E$F 2 23C D'  !:;=F::L ,9 (' .U  & &- ##At,,  # #    , ,>'"9   # #   bs6E7 G-7F> F%%F>=F>GG*)G*zraw_ops.DatasetToGraphc|g}t|ttfstd|z|Dcgc]}t j |d}}|d}t j |d}|d}t j |d}tj|tj}|g}d|d|d|f}t jdd||||} t jrt jd ||| | \} | Scc}w) NrrFrrsDatasetToGraphrGrHr)r*r+r,r-r.rvrr%rrrrr3r6) rrrrrrr=rBrAr:s rCrrEs& &u 6  )+= > ??Oaa))".BCaaN%%n6FG.$#$../FHab((H-, "46F+-D F&   .,#)s ?' ""$ ,9 (' .#bsC<external_state_policyc tjxstj}|j}|jr t j |d||d|d|}|S|d}tj|d}|d}tj|d}t!j"d||||\}}} } | dd}tj$rHd| j'dd| j)df} | j*} tj,d| | ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t|||||S#t j$rY+wxYw) aReturns a serialized GraphDef representing `input_dataset`. Returns a graph representation for `input_dataset`. Args: input_dataset: A `Tensor` of type `variant`. A variant tensor representing the dataset to return the graph representation for. external_state_policy: An optional `int`. Defaults to `0`. strip_device_assignment: An optional `bool`. Defaults to `False`. name: A name for the operation (optional). Returns: A `Tensor` of type `string`. DatasetToGraphV2rrN)rrrrrF)rrrr)rrr r!rr"r#r$r%r&r'"dataset_to_graph_v2_eager_fallbackr)r.make_intrr1r2r3 _get_attr_intrr5r6) rrrrr8r9r:r;r>r?r@rArBs rCdataset_to_graph_v2r`s    0h..0$ #\\  11  $ !6!#:= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A list of `Tensor` objects of type `output_types`. DatasetToSingleElementrrrNrTExpected list for 'output_types' argument to 'dataset_to_single_element' Op, not %r.UExpected list for 'output_shapes' argument to 'dataset_to_single_element' Op, not %r.r)rrrrr)rrr r!rr"r#r$r%r&r'(dataset_to_single_element_eager_fallbackr)r*r+r,r-r.r/r0rvr1r2r3r4r5r6)rrrrrr8r9r:r;r<r=r>r?r@rArBs rCdataset_to_single_elementrsC    0h..0$ #\\ 11 &g~o}j(Lgn L4- 0  24@ A BBDPPR($$R8P,P MD%= 1  24A B CCGTT8&&r?;T-T H   x 4('88 ' 0=+3$@!QX QK'  J ""$cll>:Oll?+Zll:&(F::L  ,A .M  & &- ##At,,  # #    5  M$D22  # #   Q U<F HH G'3GG'&G'+G<<HHzraw_ops.DatasetToSingleElementcht|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j |d}}|d}t j|d}tj|tj}|g}d|d|d|f} t jdt||| ||} t jrt jd || | | Scc}wcc}w) NrrrrrrsDatasetToSingleElementrHr)r*r+r,r-r.r/r0rvr%rrrrlenr3r6) rrrrrrr<r=rBrAr:s rCrrsJ L4- 0  24@ A BBDPPR($$R8P,P MD%= 1  24A B CCGTT8&&r?;T-T H   x 4(  " "7GOO <', L/= h &   6L8I$0C"& ('""$  ,A .'Q Us D*0D/ctjxstj}|j}|jr t j |d|||}|Stjd|||\}}}} |S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t||||S#t j$rYwxYw)aA container for an iterator resource. Args: handle: A `Tensor` of type `resource`. A handle to the iterator to delete. deleter: A `Tensor` of type `variant`. A variant deleter. name: A name for the operation (optional). Returns: The created Operation. DeleteIteratorNrbrNrOr)rrr r!rr"r#r$r%r&r'delete_iterator_eager_fallbackr)r1r2 rNrOrr8r9r:r;r>r?r@s rCdelete_iteratorrs    0h..0$ #\\ 11 fg7g n(88tE!QX *  & &- ##At,,  # #    + '$00  # #   0A;;CB))CCCC+*C+zraw_ops.DeleteIteratorctj|tj}tj|tj}||g}d}t j dd||||}d}|S)NsDeleteIteratorrrHr%rrrrr.rrNrOrrrBrAr:s rCrr0sg  ! !&'*:*: ;&  " "7GOO <''", &   .,#)s ?' ' .rkctjxstj}|j}|jr t j |d|||}|Stjd|||\}}}} |S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t||||S#t j$rYwxYw)TODO: add doc. Args: handle: A `Tensor` of type `resource`. deleter: A `Tensor` of type `variant`. name: A name for the operation (optional). Returns: The created Operation. DeleteMemoryCacheNrbr)rrr r!rr"r#r$r%r&r'"delete_memory_cache_eager_fallbackr)r1r2rs rCdelete_memory_cacher ;s    0h..0$ #\\ 11 !4:g n(88FG$H!QX *  & &- ##At,,  # #    / '$00  # #   rzraw_ops.DeleteMemoryCachectj|tj}tj|tj}||g}d}t j dd||||}d}|S)NsDeleteMemoryCacherrHrrs rCr r ]sg  ! !&'*:*: ;&  " "7GOO <''", &   11\#)s ?' ' .rkmulti_device_iterator iteratorsc@tjxstj}|j}|jr t j |d||||}|St|ttfst!d|zt#|}t%j&d||||\} } } } | S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t|||||S#t j$rYwxYw)a@A container for an iterator resource. Args: multi_device_iterator: A `Tensor` of type `resource`. A handle to the multi device iterator to delete. iterators: A list of `Tensor` objects with type `resource`. A list of iterator handles (unused). This is added so that automatic control dependencies get added during function tracing that ensure this op runs after all the dependent iterators are deleted. deleter: A `Tensor` of type `variant`. A variant deleter. name: A name for the operation (optional). Returns: The created Operation. DeleteMultiDeviceIteratorNrbTExpected list for 'iterators' argument to 'delete_multi_device_iterator' Op, not %r.)rrrOr)rrr r!rr"r#r$r%r&r'+delete_multi_device_iterator_eager_fallbackr)r*r+r,r-rr1r2) rrrOrr8r9r:r;_attr_Nr>r?r@s rCdelete_multi_device_iteratorrhs4    0h..0$ #\\ 11 )41F7gn Ie} -  57@ A BB  N''88#;P/8'*.0!QX *'  & &- ##At,,  # #    8 G$DJJ  # #   s0B,,C3?CC32C37DDDz!raw_ops.DeleteMultiDeviceIteratorct|ttfstd|zt |}t j |tj}t j|tj}t j |tj}|gt|z|gz}d|f}tjdd||||}d}|S)NrNsDeleteMultiDeviceIteratorrrH) r*r+r,r-rr%rrrconvert_n_to_tensorrr.r) rrrOrrrrBrAr:s rCrrs Ie} -  57@ A BB  N'001FHXHXY&&y'2B2BC)  " "7GOO <''(4 ?:gYF, >&   91$0C"& (' ' .rkctjxstj}|j}|jr t j |d|||}|Stjd|||\}}}} |S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t||||S#t j$rYwxYw)r DeleteRandomSeedGeneratorNrbr)rrr r!rr"r#r$r%r&r'+delete_random_seed_generator_eager_fallbackr)r1r2rs rCdelete_random_seed_generatorrs    0h..0$ #\\ 11 )4Bg n(88#FG*.0!QX *  & &- ##At,,  # #    8 '$00  # #   rz!raw_ops.DeleteRandomSeedGeneratorctj|tj}tj|tj}||g}d}t j dd||||}d}|S)NsDeleteRandomSeedGeneratorrrHrrs rCrrsj  ! !&'*:*: ;&  " "7GOO <''", &   91$0C"& (' ' .rkctjxstj}|j}|jr t j |d|||}|Stjd|||\}}}} |S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t||||S#t j$rYwxYw)r DeleteSeedGeneratorNrbr)rrr r!rr"r#r$r%r&r'$delete_seed_generator_eager_fallbackr)r1r2rs rCdelete_seed_generatorr!s    0h..0$ #\\ 11 #T67r?r@s rCdeserialize_iteratorr(s    0h..0$ #\\ 11 #T?JHg n(88*44A!QX *  & &- ##At,,  # #    0 :Dd<<  # #   rzraw_ops.DeserializeIteratorctj|tj}tj|tj}||g}d}t j dd||||}d}|S)NsDeserializeIteratorrrHr)r#r$rrrBrAr:s rCr'r')sg**?G= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. FilterByLastComponentDatasetrrNr[Expected list for 'output_types' argument to 'filter_by_last_component_dataset' Op, not %r.\Expected list for 'output_shapes' argument to 'filter_by_last_component_dataset' Op, not %r.)rrrr)rrr r!rr"r#r$r%r&r'/filter_by_last_component_dataset_eager_fallbackr)r*r+r,r-r.r/r0r1r2r3r4r5r6)rrrrr8r9r:r;r<r=r>r?r@rArBs rC filter_by_last_component_datasetr<s     0h..0$ #\\ 11 ,dM o}Fgn L4- 0  9;G H IIDPPR($$R8P,P MD%= 1  9;H I JJGTT8&&r?;T-T'88&m5A6C-1 3!QX QK' ""$cll>:Oll?+-F::L & fgG (' .E  & &- ##At,,  # #    < l%Dd<<  # #   Q U<E2G' G,2F9F  F98F9=G G$#G$z$raw_ops.FilterByLastComponentDatasetc&t|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j |d}}tj|tj}|g}d|d|f}t jdd||||} t jrt jd||| | \} | Scc}wcc}w) Nr9rr:rsFilterByLastComponentDatasetrGrHr8)r*r+r,r-r.r/r0r%rrrrr3r6) rrrrrr<r=rBrAr:s rCr;r;s( L4- 0  9;G H IIDPPR($$R8P,P MD%= 1  9;H I JJGTT8&&r?;T-T((H-, L/= I&   = 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. FilterDataset predicaterrrN)rBrrrrrIExpected list for 'output_types' argument to 'filter_dataset' Op, not %r.JExpected list for 'output_shapes' argument to 'filter_dataset' Op, not %r.r)rother_argumentsrBrrrr Targuments)rrr r!rr"r#r$r%r&r'filter_dataset_eager_fallbackr)r*r+r,r-r.r/r0rvr1r2r3r4r5r6)rrErBrrrrr8r9r:r;r<r=r>r?r@rArBs rCfilter_datasetrHsf0    0h..0$ #\\  11 ot]OY oz8-gn L4- 0  ')5 6 77DPPR($$R8P,P MD%= 1  ')6 7 88GTT8&&r?;T-T H   x 4('88})8I&2'4x" $!QX QK' ""$3<< 4lll<(.ll>*Oll?+Zll:& (F ::L vw8 (' .U  & &- ##At,,  # #    * I#=$D22  # #   Q U<"G H?IHG55H HH%%H<;H<zraw_ops.FilterDatasetc t|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|D cgc]} t j | d}} |d}t j|d}t j||\} }tj|tj}|gt|z} d|d| d|d|d|f } t jd d | | || } t jrt jd | | | | \} | Scc}wcc} w) NrCrrDrrrrBrFs FilterDatasetrGrHrAr*r+r,r-r.r/r0rvconvert_to_mixed_eager_tensorsr%rrrrr3r6)rrErBrrrrrr<r=_attr_TargumentsrBrAr:s rCrGrG?sq L4- 0  ')5 6 77DPPR($$R8P,P MD%= 1  ')6 7 88GTT8&&r?;T-T H   x 4(&.&M&Mo_b&c#O((H-4#88, L2B,   &   -q#)s ?' ""$ vw8 (' .+Q U E0Ehas_captured_refc @tjxstj}|j}|jr! t j |d||d|d|d| }|St|ttfst!d|z|D cgc]} t#j$| d}} t|ttfst!d|z|D cgc]} t#j&| d}} |d }t#j(|d}t+j,d||||| \} } } } | dd}t#j.rYd| j1dd| j3dd| j3df}| j4}t#j6d||||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t||||||S#t j$rYwxYwcc} wcc} w) aCreates a dataset by applying `tf.data.Options` to `input_dataset`. Args: input_dataset: A `Tensor` of type `variant`. A variant tensor representing the input dataset. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. has_captured_ref: An optional `bool`. Defaults to `False`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. FinalizeDatasetrOrrN)rOrrrrKExpected list for 'output_types' argument to 'finalize_dataset' Op, not %r.LExpected list for 'output_shapes' argument to 'finalize_dataset' Op, not %r.F)rrrrOr)rrr r!rr"r#r$r%r&r'finalize_dataset_eager_fallbackr)r*r+r,r-r.r/r0rr1r2r3rr4r5r6)rrrrOrr8r9r:r;r<r=r>r?r@rArBs rCfinalize_datasetrU\sF    0h..0$ #\\  11 }6H.,gn L4- 0  )+7 8 99DPPR($$R8P,P MD%= 1  )+8 9 ::GTT8&&r?;T-T''(8:LM'88(4)6,<4 I!QX QK' ""$ #"4"45G"Hcll>:Oll?+-F::L <: (' .O  & &- ##At,,  # #    , *:#=t  # #   Q Urzraw_ops.FinalizeDatasetc^t|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j |d}}|d}t j|d}tj|tj}|g}d|d|d|f} t jdd|| || } t jrt jd || | | \} | Scc}wcc}w) NrRrrSrFrOsFinalizeDatasetrGrHrQ)r*r+r,r-r.r/r0rr%rrrrr3r6) rrrrOrrr<r=rBrAr:s rCrTrTsG L4- 0  )+7 8 99DPPR($$R8P,P MD%= 1  )+8 9 ::GTT8&&r?;T-T''(8:LM((H-,  0. 0&   /<#)s ?' ""$ <: (' .'Q Us D%0D* filenames header_bytes record_bytes footer_bytes buffer_sizec tjxstj}|j}|jr! t j |d||||||d| } | S|d}tj|d}tj d|||||||\} } } } | dd} tj"r7d| j%df}| j&}tj(d||| | \} | S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t||||||||S#t j$rYwxYw)aRCreates a dataset that emits the records from one or more binary files. Args: filenames: A `Tensor` of type `string`. A scalar or a vector containing the name(s) of the file(s) to be read. header_bytes: A `Tensor` of type `int64`. A scalar representing the number of bytes to skip at the beginning of a file. record_bytes: A `Tensor` of type `int64`. A scalar representing the number of bytes in each record. footer_bytes: A `Tensor` of type `int64`. A scalar representing the number of bytes to skip at the end of a file. buffer_size: A `Tensor` of type `int64`. A scalar representing the number of bytes to buffer. Must be > 0. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. FixedLengthRecordDatasetrNrrrr)rWrXrYrZr[rr)rrr r!rr"r#r$r%r&r'*fixed_length_record_dataset_eager_fallbackr)r.rvr1r2r3r4r5r6)rWrXrYrZr[rrr8r9r:r;r>r?r@rArBs rCfixed_length_record_datasetr`s.    0h..0$ #\\ 11 ($ <lKXGgnH   x 4('88"i1=1=1=0;-5D B!QX QK' ""$#,,z2 3F::L "L&'C (' .9  & &- ##At,,  # #    7 \<{$D22  # #   s0C22D9D  D98D9=EE'&E'z raw_ops.FixedLengthRecordDatasetcN|d}tj|d}tj|tj }tj|tj }tj|tj }tj|tj }tj|tj }|||||g}d|f} tjdd|| ||} tjrtjd|| | | \} | S)NrrsFixedLengthRecordDatasetrGrHr] r.rvr%rrrrrr3r6) rWrXrYrZr[rrrrBrAr:s rCr_r_s H   x 4($$Y?)'' gmmD,'' gmmD,'' gmmD,&&{GMMB+\<{S,  !&   8!$0C"& ('""$ "L&'C (' .rkcompression_typec tjxstj}|j} | jr" t j |d|||||||d| } | S|d}tj|d}tj d|||||||| \} } } }|dd} tj"r7d| j%df}| j&}tj(d||| | \} | S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t||||||||| S#t j$rYwxYw)aTODO: add doc. Args: filenames: A `Tensor` of type `string`. header_bytes: A `Tensor` of type `int64`. record_bytes: A `Tensor` of type `int64`. footer_bytes: A `Tensor` of type `int64`. buffer_size: A `Tensor` of type `int64`. compression_type: A `Tensor` of type `string`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. FixedLengthRecordDatasetV2rNr^r)rWrXrYrZr[rcrr)rrr r!rr"r#r$r%r&r'-fixed_length_record_dataset_v2_eager_fallbackr)r.rvr1r2r3r4r5r6)rWrXrYrZr[rcrrr8r9r:r;r>r?r@rArBs rCfixed_length_record_dataset_v2rg s    0h..0$ #\\  11 *D)\lK1A:gnH   x 4('88$ 3?3?3?2=7G/7dD!QX QK' ""$#,,z2 3F::L $lFGE (' .;  & &- ##At,,  # #    : \<{ XDdDD  # #   s0 C44D;D""D;:D;?EE*)E*z"raw_ops.FixedLengthRecordDatasetV2c |d}tj|d}tj|tj }tj|tj }tj|tj }tj|tj }tj|tj }tj|tj }||||||g} d|f} tjdd| | ||} tjrtjd| | | | \} | S)NrrsFixedLengthRecordDatasetV2rGrHrerb) rWrXrYrZr[rcrrrrBrAr:s rCrfrfJ s H   x 4($$Y?)'' gmmD,'' gmmD,'' gmmD,&&{GMMB+++,= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. FlatMapDatasetfrrrNrkrrrrrKExpected list for 'output_types' argument to 'flat_map_dataset' Op, not %r.LExpected list for 'output_shapes' argument to 'flat_map_dataset' Op, not %r.r)rrErkrrrrrF)rrr r!rr"r#r$r%r&r'flat_map_dataset_eager_fallbackr)r*r+r,r-r.r/r0rvr1r2r3r4r5r6)rrErkrrrrr8r9r:r;r<r=r>r?r@rArBs rCflat_map_datasetrp` sh,    0h..0$ #\\  11 m_c1 o}Hgn L4- 0  )+7 8 99DPPR($$R8P,P MD%= 1  )+8 9 ::GTT8&&r?;T-T H   x 4('88 *9Q'3(5# %!QX QK' ""$3<<$lll<(.ll>*Oll?+Zll:& (F ::L ,9 (' .S  & &- ##At,,  # #    , AL%tOO  # #   Q UrIzraw_ops.FlatMapDatasetc t|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|D cgc]} t j | d}} |d}t j|d}t j||\} }tj|tj}|gt|z} d|d| d|d|d|f } t jd d | | || } t jrt jd | | | | \} | Scc}wcc} w) NrmrrnrrrrkrFsFlatMapDatasetrGrHrjrK)rrErkrrrrrr<r=rMrBrAr:s rCroro so L4- 0  )+7 8 99DPPR($$R8P,P MD%= 1  )+8 9 ::GTT8&&r?;T-T H   x 4(&.&M&Mo_b&c#O((H-4#88, L"2N H F&   .,#)s ?' ""$ ,9 (' .)Q UrNc 0tjxstj} | j} | jr) t j | d| |||d|d|d|d|d|d|} | St|ttfst!d |z|Dcgc]}t#j$|d}}t|ttfst!d |z|Dcgc]}t#j&|d}}|d }t#j(|d}t+j,d|||||||||| \}}}}|dd} t#j.rd|j1dd|j1dd|j1dd|j1dd|j1dd|j1dd|j1dd|j1dd|j1df}|j2}t#j4d||| | \} | S#t j$r } tj| | Yd} ~ nd} ~ wt j$rYnwxYw t|||||||||| | S#t j$rY"wxYwcc}wcc}w)aCreates a dataset that invokes a function to generate elements. Args: init_func_other_args: A list of `Tensor` objects. next_func_other_args: A list of `Tensor` objects. finalize_func_other_args: A list of `Tensor` objects. init_func: A function decorated with @Defun. next_func: A function decorated with @Defun. finalize_func: A function decorated with @Defun. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. GeneratorDataset init_func next_func finalize_funcrrrN)rtrurvrrrrrLExpected list for 'output_types' argument to 'generator_dataset' Op, not %r.MExpected list for 'output_shapes' argument to 'generator_dataset' Op, not %r.r) init_func_other_argsnext_func_other_argsfinalize_func_other_argsrtrurvrrrrTinit_func_argsTnext_func_argsTfinalize_func_args)rrr r!rr"r#r$r%r&r' generator_dataset_eager_fallbackr)r*r+r,r-r.r/r0rvr1r2r3r4r5r6)ryrzr{rtrurvrrrrr8r9r:r;r<r=r>r?r@rArBs rCgenerator_datasetr s$    0h..0$ #\\  11  $(<6 ; ?M o}H g n L4- 0  *,8 9 ::DPPR($$R8P,P MD%= 1  *,9 : ;;GTT8&&r?;T-T H   x 4('881E1E5M&/9*7)5*7(!%'!QX QK' ""$3<< 4kll;'ll?+->ll,-/@ll,-/Dll01>ll>*Oll?+Zll:&(F::L L&'; (' .e  & &- ##At,,  # #    -  4 "i9%L%t OO  # #   Q Us<'HJJI&IIII44J  J zraw_ops.GeneratorDatasetc t|ttfstd|z|D cgc]} t j | d}} t|ttfstd|z|D cgc]} t j | d}} |d}t j|d}t j|| \} }t j|| \}}t j|| \}}t|t|zt|z}d|d|d |d | d |d |d|d|d|f}t jd d||| | }t jrt jd||||\}|Scc} wcc} w)Nrwrrxrrrrtrurvr|r}r~sGeneratorDatasetrGrHrs) r*r+r,r-r.r/r0rvrLrr3r6)ryrzr{rtrurvrrrrrr<r=_attr_Tinit_func_args_attr_Tnext_func_args_attr_Tfinalize_func_argsrBrAr:s rCrr s L4- 0  *,8 9 ::DPPR($$R8P,P MD%= 1  *,9 : ;;GTT8&&r?;T-T H   x 4(080W0WXlnq0r--080W0WXlnq0r--8@8_8_`xz}8~55*+d3G.HH4PhKii, KO"$9;L.0I,   &   0!L#)s ?' ""$ L&'; (' .1Q Us E80E=c\tjxstj}|j}|jr t j |d||}|Stjd||\}}}}|dd}tj r&d} |j"} tj$d| | ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t|||S#t j$rYwxYw)a Returns the `tf.data.Options` attached to `input_dataset`. Args: input_dataset: A `Tensor` of type `variant`. A variant tensor representing the input dataset. name: A name for the operation (optional). Returns: A `Tensor` of type `string`. GetOptionsNrbrrd)rrr r!rr"r#r$r%r&r'get_options_eager_fallbackr)r1r2r.r3r5r6rs rC get_optionsr= s'    0h..0$ #\\ 11 lD-1g n(88M>!QX QK' ""$ F::L lFG5 (' .'  & &- ##At,,  # #    ' d..  # #   rzraw_ops.GetOptionsctj|tj}|g}d}t j dd||||}t j rt jd||||\}|S)Ns GetOptionsrGrHrrrs rCrrg sp((H-, &   ]Al#)s ?' ""$ lFG5 (' .rk cycle_length block_lengthc tjxstj} | j} | jr& t j | d|||||d|d|d|d|} | St|ttfst!d|z|D cgc]} t#j$| d}} t|ttfst!d |z|Dcgc]}t#j&|d}}|d }t#j(|d}t+j,d||||||||| \}}}}|dd} t#j.r{d|j1dd |j1d d|j1dd|j1dd|j1df }|j2}t#j4d||| | \} | S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t||||||||||  S#t j$rYwxYwcc} wcc}w) axCreates a dataset that applies `f` to the outputs of `input_dataset`. Unlike MapDataset, the `f` in InterleaveDataset is expected to return a Dataset variant, and InterleaveDataset will flatten successive results into a single Dataset. Unlike FlatMapDataset, InterleaveDataset will interleave sequences of up to `block_length` consecutive elements from `cycle_length` input elements. Args: input_dataset: A `Tensor` of type `variant`. other_arguments: A list of `Tensor` objects. cycle_length: A `Tensor` of type `int64`. block_length: A `Tensor` of type `int64`. f: A function decorated with @Defun. A function mapping elements of `input_dataset`, concatenated with `other_arguments`, to a Dataset variant that contains elements matching `output_types` and `output_shapes`. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. InterleaveDatasetrkrrrNrlMExpected list for 'output_types' argument to 'interleave_dataset' Op, not %r.NExpected list for 'output_shapes' argument to 'interleave_dataset' Op, not %r.r) rrErrrkrrrrrF)rrr r!rr"r#r$r%r&r'!interleave_dataset_eager_fallbackr)r*r+r,r-r.r/r0rvr1r2r3r4r5r6)rrErrrkrrrrr8r9r:r;r<r=r>r?r@rArBs rCinterleave_datasetrt su4    0h..0$ #\\  11 !4lCNL H>gn L4- 0  +-9 : ;;DPPR($$R8P,P MD%= 1  +-: ; <<GTT8&&r?;T-T H   x 4('88=-<*6*6!*6+88"&(!QX QK' ""$3<<$lll<(.ll>*Oll?+Zll:& (F ::L \67< (' .Y  & &- ##At,,  # #    . , #=$D22  # #   Q Us<$G II  HG99HHH++IIzraw_ops.InterleaveDatasetc Jt|ttfstd|z|D cgc]} t j | d}} t|ttfstd|z|D cgc]} t j | d}} |d}t j|d}t j|| \} }tj|tj}tj|tj}tj|tj}|gt|z||gz} d|d| d|d|d|f }t jd d | || | }t jrt j d | |||\}|Scc} wcc} w) NrrrrrrrkrFsInterleaveDatasetrGrHrr*r+r,r-r.r/r0rvrLr%rrrrrr3r6)rrErrrkrrrrrr<r=rMrBrAr:s rCrr s L4- 0  +-9 : ;;DPPR($$R8P,P MD%= 1  +-: ; <<GTT8&&r?;T-T H   x 4(&.&M&Mo_b&c#O((H-'' gmmD,'' gmmD,4#88L,;WW, L"2N H F&   11\#)s ?' ""$ \67< (' .-Q Us F0F  shared_name containerc tjxstj}|j}|jr" t j |d|d|d|d|d| }|Stj|d}tj|d}t|t t"fst%d|z|D cgc]} tj&| d}} t|t t"fst%d |z|D cgc]} tj(| d}} t+j,d||||| \} } } } | dd}tj.rjd| j1dd| j1dd| j1dd| j1df}| j2}tj4d||||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t||||||S#t j$rYwxYwcc} wcc} w) aoA container for an iterator resource. Args: shared_name: A `string`. container: A `string`. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. name: A name for the operation (optional). Returns: A `Tensor` of type `resource`. IteratorrrrrNrrrrrrCExpected list for 'output_types' argument to 'iterator' Op, not %r.DExpected list for 'output_shapes' argument to 'iterator' Op, not %r.rrrrr)rrr r!rr"r#r$r%r&r'iterator_eager_fallbackr)r.rvr*r+r,r-r/r0r1r2r3r4r5r6rrrrrr8r9r:r;r<r=r>r?r@rArBs rCiteratorr sQ    0h..0$ #\\  11 j$ {K><gn!!+}=+ ;7) L4- 0  !#/ 0 11DPPR($$R8P,P MD%= 1  !#0 1 22GTT8&&r?;T-T'88 y!-]!QX QK' ""$S\\-8+ll;'ll>*Oll?+-F::L L&'3 (' .M  & &- ##At,,  # #    $!Y#=t  # #   Q U< G5H:<H?H G22H  H H H76H7zraw_ops.Iteratorc<tj|d}tj|d}t|ttfst d|z|Dcgc]}tj |d}}t|ttfst d|z|Dcgc]}tj|d}}g}d|d|d|d|f} tjdd|| || } tjrtjd || | | \} | Scc}wcc}w) NrrrrrrsIteratorrGrHr r.rvr*r+r,r-r/r0rr3r6 rrrrrrr<r=rBrAr:s rCrr' s5!!+}=+ ;7) L4- 0  !#/ 0 11DPPR($$R8P,P MD%= 1  !#0 1 22GTT8&&r?;T-T, ; Y, @&   [!L#)s ?' ""$ L&'3 (' .Q U DD string_handlec tjxstj}|j}|jr t j |d||d|d|}|S|g}t|ttfst!d|z|Dcgc]}t#j$|d}}|g}t|ttfst!d|z|D cgc]} t#j&| d}} t)j*d||||\} } } } | dd}t#j,rHd| j/dd| j/df} | j0}t#j2d|| ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t|||||S#t j$rYwxYwcc}wcc} w) aConverts the given string representing a handle to an iterator to a resource. Args: string_handle: A `Tensor` of type `string`. A string representation of the given handle. output_types: An optional list of `tf.DTypes`. Defaults to `[]`. If specified, defines the type of each tuple component in an element produced by the resulting iterator. output_shapes: An optional list of shapes (each a `tf.TensorShape` or list of `ints`). Defaults to `[]`. If specified, defines the shape of each tuple component in an element produced by the resulting iterator. name: A name for the operation (optional). Returns: A `Tensor` of type `resource`. IteratorFromStringHandlerrNrVExpected list for 'output_types' argument to 'iterator_from_string_handle' Op, not %r.WExpected list for 'output_shapes' argument to 'iterator_from_string_handle' Op, not %r.rrrr)rrr r!rr"r#r$r%r&r'*iterator_from_string_handle_eager_fallbackr)r*r+r,r-r.r/r0r1r2r3r4r5r6rrrrr8r9r:r;r<r=r>r?r@rArBs rCiterator_from_string_handler@ s""    0h..0$ #\\ 11 ($ ~o}6gnL L4- 0  46B C DDDPPR($$R8P,PM MD%= 1  46C D EEGTT8&&r?;T-T'88"-1=2?dL!QX QK' ""$cll>:Oll?+-F::L "L&'C (' .K  & &- ##At,,  # #    7 l%Dd<<  # #   QU<E: G/G4:G F((GGGG,+G,z raw_ops.IteratorFromStringHandlec6|g}t|ttfstd|z|Dcgc]}t j |d}}|g}t|ttfstd|z|Dcgc]}t j |d}}tj|tj}|g}d|d|f}t jdd||||} t jrt jd||| | \} | Scc}wcc}w) NrrrrsIteratorFromStringHandlerGrHrr*r+r,r-r.r/r0r%rrrrr3r6 rrrrrr<r=rBrAr:s rCrr s>L L4- 0  46B C DDDPPR($$R8P,PM MD%= 1  46C D EEGTT8&&r?;T-T((G-, L/= I&   8!$0C"& ('""$ "L&'C (' .%QU D8Dc tjxstj}|j}|jr t j |d||d|d|}|S|g}t|ttfst!d|z|Dcgc]}t#j$|d}}|g}t|ttfst!d|z|D cgc]} t#j&| d}} t)j*d||||\} } } } | dd}t#j,rHd| j/dd| j/df} | j0}t#j2d|| ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t|||||S#t j$rYwxYwcc}wcc} w) aZTODO: add doc. Args: string_handle: A `Tensor` of type `string`. output_types: An optional list of `tf.DTypes`. Defaults to `[]`. output_shapes: An optional list of shapes (each a `tf.TensorShape` or list of `ints`). Defaults to `[]`. name: A name for the operation (optional). Returns: A `Tensor` of type `resource`. IteratorFromStringHandleV2rrNrYExpected list for 'output_types' argument to 'iterator_from_string_handle_v2' Op, not %r.ZExpected list for 'output_shapes' argument to 'iterator_from_string_handle_v2' Op, not %r.r)rrr r!rr"r#r$r%r&r'-iterator_from_string_handle_v2_eager_fallbackr)r*r+r,r-r.r/r0r1r2r3r4r5r6rs rCiterator_from_string_handle_v2r s#    0h..0$ #\\ 11 *D- o}FgnL L4- 0  79E F GGDPPR($$R8P,PM MD%= 1  79F G HHGTT8&&r?;T-T'88$M3?4AN!QX QK' ""$cll>:Oll?+-F::L $lFGE (' .K  & &- ##At,,  # #    : l%Dd<<  # #   QUrz"raw_ops.IteratorFromStringHandleV2c6|g}t|ttfstd|z|Dcgc]}t j |d}}|g}t|ttfstd|z|Dcgc]}t j |d}}tj|tj}|g}d|d|f}t jdd||||} t jrt jd||| | \} | Scc}wcc}w) NrrrrsIteratorFromStringHandleV2rGrHrrrs rCrr s>L L4- 0  79E F GGDPPR($$R8P,PM MD%= 1  79F G HHGTT8&&r?;T-T((G-, L/= I&   :A$0C"& ('""$ $lFGE (' .%QUrrc tjxstj}|j}|jr t j |d||d|d|}|St|ttfst!d|z|Dcgc]}t#j$|d}}t|ttfst!d|z|D cgc]} t#j&| d}} t)j*d||||\} } } } | dd}|s| St#j,rHd| j/dd| j/df} | j0}t#j2d|| ||S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t|||||S#t j$rYwxYwcc}wcc} w) aGets the next output from the given iterator . Args: iterator: A `Tensor` of type `resource`. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. name: A name for the operation (optional). Returns: A list of `Tensor` objects of type `output_types`. IteratorGetNextrrNrLExpected list for 'output_types' argument to 'iterator_get_next' Op, not %r.MExpected list for 'output_shapes' argument to 'iterator_get_next' Op, not %r.rrrr)rrr r!rr"r#r$r%r&r' iterator_get_next_eager_fallbackr)r*r+r,r-r.r/r0r1r2r3r4r5r6rrrrr8r9r:r;r<r=r>r?r@rArBs rCiterator_get_nextr s    0h..0$ #\\ 11 x(gn L4- 0  *,8 9 ::DPPR($$R8P,P MD%= 1  *,9 : ;;GTT8&&r?;T-T'88H<)6TC!QX QK'  J ""$cll>:Oll?+-F::L <: .C  & &- ##At,,  # #    - ]  # #   Q Ur=zraw_ops.IteratorGetNextc0t|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j |d}}tj|tj}|g}d|d|f}t jdt|||||} t jrt jd||| | Scc}wcc}w)NrrrrsIteratorGetNextrHrr*r+r,r-r.r/r0r%rrrrrr3r6 rrrrrr<r=rBrAr:s rCrr3 s! L4- 0  *,8 9 ::DPPR($$R8P,P MD%= 1  *,9 : ;;GTT8&&r?;T-T  # #Hg.>.> ?(, L/= I&   /\1B$0C"& ('""$ <: .Q U D0Dc tjxstj}|j}|jr t j |d||d|d|}|St|ttfst!d|z|Dcgc]}t#j$|d}}t|ttfst!d|z|D cgc]} t#j&| d}} t)j*d||||\} } } } | dd}t#j,rHd| j/dd| j/df} | j0}t#j2d|| ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t|||||S#t j$rYwxYwcc}wcc} w) aGets the next output from the given iterator as an Optional variant. Args: iterator: A `Tensor` of type `resource`. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. IteratorGetNextAsOptionalrrNrXExpected list for 'output_types' argument to 'iterator_get_next_as_optional' Op, not %r.YExpected list for 'output_shapes' argument to 'iterator_get_next_as_optional' Op, not %r.r)rrr r!rr"r#r$r%r&r',iterator_get_next_as_optional_eager_fallbackr)r*r+r,r-r.r/r0r1r2r3r4r5r6rs rCiterator_get_next_as_optionalrJ s     0h..0$ #\\ 11 )4>o}6gn L4- 0  68D E FFDPPR($$R8P,P MD%= 1  68E F GGGTT8&&r?;T-T'88#h2>3@tM!QX QK' ""$cll>:Oll?+-F::L #\67D (' .C  & &- ##At,,  # #    9 ]  # #   Q Ur=z!raw_ops.IteratorGetNextAsOptionalc&t|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j |d}}tj|tj}|g}d|d|f}t jdd||||} t jrt jd||| | \} | Scc}wcc}w) NrrrrsIteratorGetNextAsOptionalrGrHr)r*r+r,r-r.r/r0r%rrrrr3r6rs rCrr s* L4- 0  68D E FFDPPR($$R8P,P MD%= 1  68E F GGGTT8&&r?;T-T  # #Hg.>.> ?(, L/= I&   91$0C"& ('""$ #\67D (' .!Q Ur?c tjxstj}|j}|jr t j |d||d|d|}|St|ttfst!d|z|Dcgc]}t#j$|d}}t|ttfst!d|z|D cgc]} t#j&| d}} t)j*d||||\} } } } | dd}|s| St#j,rHd| j/dd| j/df} | j0}t#j2d|| ||S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t|||||S#t j$rYwxYwcc}wcc} w) aGets the next output from the given iterator. This operation is a synchronous version IteratorGetNext. It should only be used in situations where the iterator does not block the calling thread, or where the calling thread is not a member of the thread pool used to execute parallel operations (e.g. in eager mode). Args: iterator: A `Tensor` of type `resource`. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. name: A name for the operation (optional). Returns: A list of `Tensor` objects of type `output_types`. IteratorGetNextSyncrrNrQExpected list for 'output_types' argument to 'iterator_get_next_sync' Op, not %r.RExpected list for 'output_shapes' argument to 'iterator_get_next_sync' Op, not %r.r)rrr r!rr"r#r$r%r&r'%iterator_get_next_sync_eager_fallbackr)r*r+r,r-r.r/r0r1r2r3r4r5r6rs rCiterator_get_next_syncr s"    0h..0$ #\\ 11 #T8^o}6gn L4- 0  /1= > ??DPPR($$R8P,P MD%= 1  /1> ? @@GTT8&&r?;T-T'88|-:G!QX QK'  J ""$cll>:Oll?+-F::L |VW> .C  & &- ##At,,  # #    2 ]  # #   Q Ur=zraw_ops.IteratorGetNextSyncc0t|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j |d}}tj|tj}|g}d|d|f}t jdt|||||} t jrt jd||| | Scc}wcc}w)NrrrrsIteratorGetNextSyncrHrrrs rCrr s# L4- 0  /1= > ??DPPR($$R8P,P MD%= 1  /1> ? @@GTT8&&r?;T-T  # #Hg.>.> ?(, L/= I&   3S5F$0C"& ('""$ |VW> .Q Urc\tjxstj}|j}|jr t j |d||}|Stjd||\}}}}|dd}tj r&d} |j"} tj$d| | ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t|||S#t j$rYwxYw)aConverts the given `resource_handle` representing an iterator to a string. Args: resource_handle: A `Tensor` of type `resource`. A handle to an iterator resource. name: A name for the operation (optional). Returns: A `Tensor` of type `string`. IteratorToStringHandleNrb)r#rrd)rrr r!rr"r#r$r%r&r'(iterator_to_string_handle_eager_fallbackr)r1r2r.r3r5r6) r#rr8r9r:r;r>r?r@rArBs rCiterator_to_string_handler s*    0h..0$ #\\ 11 &o?g n(88 /N!QX QK' ""$ F::L  ,A (' .'  & &- ##At,,  # #    5 $00  # #   rzraw_ops.IteratorToStringHandlectj|tj}|g}d}t j dd||||}t j rt jd||||\}|S)NsIteratorToStringHandlerGrHrr%rrrr.rr3r6)r#rrrBrAr:s rCrr sx**?G= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. name: A name for the operation (optional). Returns: A `Tensor` of type `resource`. IteratorV2rrrrNrFExpected list for 'output_types' argument to 'iterator_v2' Op, not %r.GExpected list for 'output_shapes' argument to 'iterator_v2' Op, not %r.r)rrr r!rr"r#r$r%r&r'iterator_v2_eager_fallbackr)r.rvr*r+r,r-r/r0r1r2r3r4r5r6rs rC iterator_v2r* sQ    0h..0$ #\\  11 lD-k><gn!!+}=+ ;7) L4- 0  $&2 3 44DPPR($$R8P,P MD%= 1  $&3 4 55GTT8&&r?;T-T'88+#/}!!QX QK' ""$S\\-8+ll;'ll>*Oll?+-F::L lFG5 (' .M  & &- ##At,,  # #    '!Y#=t  # #   Q Urzraw_ops.IteratorV2c<tj|d}tj|d}t|ttfst d|z|Dcgc]}tj |d}}t|ttfst d|z|Dcgc]}tj|d}}g}d|d|d|d|f} tjdd|| || } tjrtjd || | | \} | Scc}wcc}w) Nrrrrrrs IteratorV2rGrHrrrs rCrrk s5!!+}=+ ;7) L4- 0  $&2 3 44DPPR($$R8P,P MD%= 1  $&3 4 55GTT8&&r?;T-T, ; Y, @&   ]Al#)s ?' ""$ lFG5 (' .Q Urctjxstj}|j}|jr t j |d|||}|Stjd|||\}}}} |S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t||||S#t j$rYwxYw)aMakes a new iterator from the given `dataset` and stores it in `iterator`. This operation may be executed multiple times. Each execution will reset the iterator in `iterator` to the first element of `dataset`. Args: dataset: A `Tensor` of type `variant`. iterator: A `Tensor` of type `resource`. name: A name for the operation (optional). Returns: The created Operation. MakeIteratorNrb)rrr)rrr r!rr"r#r$r%r&r'make_iterator_eager_fallbackr)r1r2) rrrr8r9r:r;r>r?r@s rC make_iteratorr s    0h..0$ #\\ 11 ndGX7g n(88(G!QX *  & &- ##At,,  # #    ) 8$D22  # #   rzraw_ops.MakeIteratorctj|tj}tj|tj}||g}d}t j dd||||}d}|S)Ns MakeIteratorrrH)r%rrrrr.r)rrrrrBrAr:s rCrr sf  " "7GOO <'  # #Hg.>.> ?(8$, &   _a #)s ?' ' .rkuse_inter_op_parallelismpreserve_cardinalityforce_synchronousc tjxstj} | j} | jr* t j | d| ||d|d|d|d|d|d|d|} | St|ttfst!d |z|Dcgc]}t#j$|d}}t|ttfst!d |z|Dcgc]}t#j&|d}}|d }t#j(|d}|d}t#j(|d}|d}t#j(|d}|d}t#j*|d}t-j.d||||||||||  \}}}}|d d } t#j0rd|j3dd|j3dd|j3dd|j3dd|j5dd|j5dd|j5dd|j3df}|j6}t#j8d||| | \} | S#t j$r } tj| | Yd } ~ nd } ~ wt j$rYnwxYw t|||||||||| | S#t j$rY_wxYwcc}wcc}w)aCreates a dataset that applies `f` to the outputs of `input_dataset`. Args: input_dataset: A `Tensor` of type `variant`. other_arguments: A list of `Tensor` objects. f: A function decorated with @Defun. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. use_inter_op_parallelism: An optional `bool`. Defaults to `True`. preserve_cardinality: An optional `bool`. Defaults to `False`. force_synchronous: An optional `bool`. Defaults to `False`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. MapDatasetrkrrrrrrN) rkrrrrrrrrFExpected list for 'output_types' argument to 'map_dataset' Op, not %r.GExpected list for 'output_shapes' argument to 'map_dataset' Op, not %r.TFr) rrErkrrrrrrrrF)rrr r!rr"r#r$r%r&r'map_dataset_eager_fallbackr)r*r+r,r-r.r/r0rrvr1r2r3r4rr5r6)rrErkrrrrrrrr8r9r:r;r<r=r>r?r@rArBs rC map_datasetr s!$    0h..0$ #\\  11 lD-#q o}"$< 46I:x 1g n L4- 0  $&2 3 44DPPR($$R8P,P MD%= 1  $&3 4 55GTT8&&r?;T-T%#%//0HJde! !++,@BXY(():*Oll?+-G  !;<$  !78:M  !45zll:&(F::L lFG5 (' .y  & &- ##At,,  # #     ' AL%#;3-t   # #   Q Us<(IK KJ$I??JJJ22K K zraw_ops.MapDatasetc Xt|ttfstd|z|D cgc]} t j | d}} t|ttfstd|z|D cgc]} t j | d}} |d}t j|d}|d}t j|d}|d}t j|d }|d }t j|d }t j|| \} }tj|tj}|gt|z}d |d | d|d|d|d|d |d |f}t jdd||| | }t jrt j d||||\}|Scc} wcc} w)NrrrrTrFrrrrrkrFs MapDatasetrGrHr)r*r+r,r-r.r/r0rrvrLr%rrrrr3r6)rrErkrrrrrrrrr<r=rMrBrAr:s rCrrs L4- 0  $&2 3 44DPPR($$R8P,P MD%= 1  $&3 4 55GTT8&&r?;T-T%#%//0HJde! !++,@BXY(():= 1`. A list of types. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. A list of shapes. f: A function decorated with @Defun. max_intra_op_parallelism: An optional `int`. Defaults to `1`. name: A name for the operation (optional). Returns: A list of `Tensor` objects of type `output_types`. MapDefunrrrkrN)rrrkrrrDExpected list for 'output_types' argument to 'map_defun' Op, not %r.EExpected list for 'output_shapes' argument to 'map_defun' Op, not %r.rG) argumentscaptured_inputsrrrkrrrF Tcaptured)rrr r!rr"r#r$r%r&r'map_defun_eager_fallbackr)r*r+r,r-r.r/r0rr1r2r3r4rr5r6)rrrrrkrrr8r9r:r;r<r=r>r?r@rArBs rC map_defunr9sw@    0h..0$ #\\  11 j$ ?No}c1"$<>gn L4- 0  "$0 1 22DPPR($$R8P,P MD%= 1  "$1 2 33GTT8&&r?;T-T% %../GIcd'88i!-]2J !QX QK' ""$CLL6 ll;'ll>*Oll?+S#,,s2C( :; =F ::L L&'3 .U  & &- ##At,,  # #    % _<%#;$   # #   Q Us<"G I IH'HHHH22I I zraw_ops.MapDefunc t|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|D cgc]} t j | d}} |d}t j|d}t j||\} }t j||\} }t|t|z} d| d| d|d|d |d|f } t jd t|| | || }t jrt jd | | ||Scc}wcc} w) NrrrrrGrrFrrksMapDefunrHr) r*r+r,r-r.r/r0rrLrrr3r6)rrrrrkrrrr<r=rM_attr_TcapturedrBrAr:s rCrrs~ L4- 0  "$0 1 22DPPR($$R8P,P MD%= 1  "$1 2 33GTT8&&r?;T-T% %../GIcd ( G G SV WI%-%L%L_^a%b"/?i4#88, *K,Q6 8&   [#l*;$0C"& ('""$ L&'3 .+Q Us E0E algorithm cpu_budget ram_budgetctjxstj}|j}|jr% t j |d||d|d|d|d|d|} | St|ttfst!d |z|D cgc]} t#j$| d}} t|ttfst!d |z|D cgc]} t#j&| d}} |d }t#j(|d}|d }t#j(|d}|d }t#j(|d}t+j,d||||||| \} } }}|dd} t#j.r{d|j1dd|j1dd|j1dd|j3dd|j3df }|j4}t#j6d||| | \} | S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t||||||||S#t j$rY wxYwcc} wcc} w) axIdentity transformation that models performance. Identity transformation that models performance. Args: input_dataset: A `Tensor` of type `variant`. A variant tensor representing the input dataset. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. algorithm: An optional `int`. Defaults to `0`. cpu_budget: An optional `int`. Defaults to `0`. ram_budget: An optional `int`. Defaults to `0`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. ModelDatasetrrrrrN)rrrrrrrHExpected list for 'output_types' argument to 'model_dataset' Op, not %r.IExpected list for 'output_shapes' argument to 'model_dataset' Op, not %r.r)rrrrrrr)rrr r!rr"r#r$r%r&r'model_dataset_eager_fallbackr)r*r+r,r-r.r/r0rr1r2r3rr4r5r6)rrrrrrrr8r9r:r;r<r=r>r?r@rArBs rC model_datasetrs$    0h..0$ #\\  11 ndM; j, No}6gn L4- 0  &(4 5 66DPPR($$R8P,P MD%= 1  &(5 6 77GTT8&&r?;T-TI ;7)J  \:*J  \:*'88m%1&3y#-*! #!QX QK' ""$3,,[9< -| -~ll>*Oll?+ -F ::L  fg7 (' .a  & &- ##At,,  # #    ) 9l%Dd<<  # #   Q Us<#G< I4I9<IH**IIII10I1zraw_ops.ModelDatasetc t|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|D cgc]} t j | d}} |d}t j|d}|d}t j|d}|d}t j|d}tj|tj}|g} d|d|d|d|d|f } t jd d | | || } t jrt jd | | | | \} | Scc}wcc} w) Nrrrrrrrrs ModelDatasetrGrHr)r*r+r,r-r.r/r0rr%rrrrr3r6) rrrrrrrrr<r=rBrAr:s rCrrs L4- 0  &(4 5 66DPPR($$R8P,P MD%= 1  &(5 6 77GTT8&&r?;T-TI ;7)J  \:*J  \:*((H-, L*l nlO] L&   _a #)s ?' ""$  fg7 (' .3Q Us E0E"cJtjxstj}|j}|jr$ t j |d|d|d|d|d|d| }|St|ttfst!d |z|D cgc]} t#j$| d}} t#j$|d}t#j$|d}t|ttfst!d |z|D cgc]} t#j&| d}} t|ttfst!d |z|D cgc]} t#j(| d}} t+j,d|||||| \} } } }|dd}t#j.r{d| j1dd| j1dd| j1dd| j1dd| j1df }| j2}t#j4d||||\}|S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t|||||||S#t j$rY/wxYwcc} wcc} wcc} w) a Creates a MultiDeviceIterator resource. Args: devices: A list of `strings` that has length `>= 1`. A list of devices the iterator works across. shared_name: A `string`. If non-empty, this resource will be shared under the given name across multiple sessions. container: A `string`. If non-empty, this resource is placed in the given container. Otherwise, a default container is used. output_types: A list of `tf.DTypes` that has length `>= 1`. The type list for the return values. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. The list of shapes being produced. name: A name for the operation (optional). Returns: A `Tensor` of type `resource`. MultiDeviceIteratorrnrrrrN)rnrrrrrrKExpected list for 'devices' argument to 'multi_device_iterator' Op, not %r.PExpected list for 'output_types' argument to 'multi_device_iterator' Op, not %r.QExpected list for 'output_shapes' argument to 'multi_device_iterator' Op, not %r.)rnrrrrr)rrr r!rr"r#r$r%r&r'$multi_device_iterator_eager_fallbackr)r*r+r,r-r.rvr/r0r1r2r3r4r5r6)rnrrrrrr8r9r:r;r=r<r>r?r@rArBs rCrrs*    0h..0$ #\\  11 #T9g}[)^\(gn GdE] +  .07 8 999@ @"X  r9 - @' @!!+}=+ ;7) L4- 0  .0< = >>DPPR($$R8P,P MD%= 1  .0= > ??GTT8&&r?;T-T'88wK)2-:G!QX QK' ""$i0-ll=);ll;'ll>*Oll?+ -F ::L |VW> (' .Y  & &- ##At,,  # #    1{i#=t  # #    AQ UsB"H J>JJ I&2I  I&%I&*I<<JJzraw_ops.MultiDeviceIteratorc t|ttfstd|z|Dcgc]}t j |d}}t j |d}t j |d}t|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j|d}}g} d|d|d|d|d|f } t jd d | | || } t jrt jd | | | | \} | Scc}wcc}wcc}w) Nrrnrrrrr rsMultiDeviceIteratorrGrHrr) rnrrrrrrr=r<rBrAr:s rCr r ns GdE] +  .07 8 999@ @"X  r9 - @' @!!+}=+ ;7) L4- 0  .0< = >>DPPR($$R8P,P MD%= 1  .0= > ??GTT8&&r?;T-T, w {K ^\?M K&   3Q|#)s ?' ""$ |VW> (' .- AQ UsEE"#E'c tjxstj}|j}|jr t j |d||d|d|}|S|g}t|ttfst!d|z|Dcgc]}t#j$|d}}|g}t|ttfst!d|z|D cgc]} t#j&| d}} t)j*d||||\} } } } | dd}t#j,rHd| j/dd| j/df} | j0}t#j2d|| ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t|||||S#t j$rYwxYwcc}wcc} w) aGenerates a MultiDeviceIterator resource from its provided string handle. Args: string_handle: A `Tensor` of type `string`. String representing the resource. output_types: An optional list of `tf.DTypes`. Defaults to `[]`. The type list for the return values. output_shapes: An optional list of shapes (each a `tf.TensorShape` or list of `ints`). Defaults to `[]`. The list of shapes being produced. name: A name for the operation (optional). Returns: A `Tensor` of type `resource`. #MultiDeviceIteratorFromStringHandlerrNrcExpected list for 'output_types' argument to 'multi_device_iterator_from_string_handle' Op, not %r.dExpected list for 'output_shapes' argument to 'multi_device_iterator_from_string_handle' Op, not %r.r)rrr r!rr"r#r$r%r&r'7multi_device_iterator_from_string_handle_eager_fallbackr)r*r+r,r-r.r/r0r1r2r3r4r5r6rs rC(multi_device_iterator_from_string_handlers%    0h..0$ #\\ 11 3T= o}FgnL L4- 0  ACO P QQDPPR($$R8P,PM MD%= 1  ACP Q RRGTT8&&r?;T-T'88-]:Oll?+-F::L -|VWN (' .M  & &- ##At,,  # #    D l%Dd<<  # #   QUrz+raw_ops.MultiDeviceIteratorFromStringHandlec6|g}t|ttfstd|z|Dcgc]}t j |d}}|g}t|ttfstd|z|Dcgc]}t j |d}}tj|tj}|g}d|d|f}t jdd||||} t jrt jd||| | \} | Scc}wcc}w) Nrrrrs#MultiDeviceIteratorFromStringHandlerGrHr rrs rCrrs@L L4- 0  ACO P QQDPPR($$R8P,PM MD%= 1  ACP Q RRGTT8&&r?;T-T((G-, L/= I&   CQ$0C"& ('""$ -|VWN (' .%QUr shard_numincarnation_idc tjxstj}|j}|jr! t j |d||||d|d| }|St|ttfst!d|z|D cgc]} t#j$| d}} t|ttfst!d|z|D cgc]} t#j&| d}} t)j*d||||||\} } } }|dd}|s| St#j,rHd| j/dd| j/df}| j0}t#j2d||||S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t|||||||S#t j$rYwxYwcc} wcc} w) aGets next element for the provided shard number. Args: multi_device_iterator: A `Tensor` of type `resource`. A MultiDeviceIterator resource. shard_num: A `Tensor` of type `int32`. Integer representing which shard to fetch data for. incarnation_id: A `Tensor` of type `int64`. Which incarnation of the MultiDeviceIterator is running. output_types: A list of `tf.DTypes` that has length `>= 1`. The type list for the return values. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. The list of shapes being produced. name: A name for the operation (optional). Returns: A list of `Tensor` objects of type `output_types`. #MultiDeviceIteratorGetNextFromShardrrNrdExpected list for 'output_types' argument to 'multi_device_iterator_get_next_from_shard' Op, not %r.eExpected list for 'output_shapes' argument to 'multi_device_iterator_get_next_from_shard' Op, not %r.)rrrrrr)rrr r!rr"r#r$r%r&r'8multi_device_iterator_get_next_from_shard_eager_fallbackr)r*r+r,r-r.r/r0r1r2r3r4r5r6)rrrrrrr8r9r:r;r<r=r>r?r@rArBs rC)multi_device_iterator_get_next_from_shardrs &    0h..0$ #\\  11 3Ty..o}6gn L4- 0  BDP Q RRDPPR($$R8P,P MD%= 1  BDQ R SSGTT8&&r?;T-T'88-EZ9B>L:Oll?+-F::L -|VWN .M  & &- ##At,,  # #    E N#=t  # #   Q Us<E6G-G26F= F$$F=<F=GG*)G*z+raw_ops.MultiDeviceIteratorGetNextFromShardct|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j |d}}tj|tj}tj|tj}tj|tj}|||g} d|d|f} t jdt|| | ||} t jrt j d| | | | Scc}wcc}w)Nrrrrs#MultiDeviceIteratorGetNextFromShardrHr)r*r+r,r-r.r/r0r%rrrint32rrrr3r6) rrrrrrrr<r=rBrAr:s rCrr1s] L4- 0  BDP Q RRDPPR($$R8P,P MD%= 1  BDQ R SSGTT8&&r?;T-T001FHXHXY$$Y >))).'--H.'NC, L/= I&   C .|#)s ?'""$ -|VWN .#Q Us E0Emax_buffer_sizechtjxstj}|j}|jr t j |d||||}|Stjd||||\}}} } | dd}tj r&d} | j"} tj$d| | ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t|||||S#t j$rYwxYw)aInitializes the multi device iterator with the given dataset. Args: dataset: A `Tensor` of type `variant`. Dataset to be iterated upon. multi_device_iterator: A `Tensor` of type `resource`. A MultiDeviceIteratorResource. max_buffer_size: A `Tensor` of type `int64`. The maximum size of the host side per device buffer to keep. name: A name for the operation (optional). Returns: A `Tensor` of type `int64`. MultiDeviceIteratorInitNrb)rrrrrd)rrr r!rr"r#r$r%r&r')multi_device_iterator_init_eager_fallbackr)r1r2r.r3r5r6) rrrrr8r9r:r;r>r?r@rArBs rCmulti_device_iterator_initr!JsB    0h..0$ #\\ 11 'w8Mgn(88!79N3BO!QX QK' ""$ F::L !<B (' .-  & &- ##At,,  # #    6 (/  # #   s0CDC..DD DD10D1zraw_ops.MultiDeviceIteratorInitctj|tj}tj|tj}tj|tj }|||g}d}t jdd||||}t jrt jd||||\}|S)NsMultiDeviceIteratorInitrGrHr) r%rrrrrr.rr3r6)rrrrrrBrAr:s rCr r {s  " "7GOO <'001FHXHXY**?GMMJ/0/B, &   7$0C"& ('""$ !<B (' .rkc\tjxstj}|j}|jr t j |d||}|Stjd||\}}}}|dd}tj r&d} |j"} tj$d| | ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t|||S#t j$rYwxYw)aProduces a string handle for the given MultiDeviceIterator. Args: multi_device_iterator: A `Tensor` of type `resource`. A MultiDeviceIterator resource. name: A name for the operation (optional). Returns: A `Tensor` of type `string`. !MultiDeviceIteratorToStringHandleNrb)rrrd)rrr r!rr"r#r$r%r&r'5multi_device_iterator_to_string_handle_eager_fallbackr)r1r2r.r3r5r6) rrr8r9r:r;r>r?r@rArBs rC&multi_device_iterator_to_string_handler&s0    0h..0$ #\\ 11 14gn(88+CX268!QX QK' ""$ F::L +\67L (' .)  & &- ##At,,  # #    B d66  # #   rz)raw_ops.MultiDeviceIteratorToStringHandlectj|tj}|g}d}t j dd||||}t j rt jd||||\}|S)Ns!MultiDeviceIteratorToStringHandlerGrHr$r)rrrrBrAr:s rCr%r%sz001FHXHXY'(, &   A1$0C"& ('""$ +\67L (' .rkctjxstj}|j}|jr$ t j |d|d|d|d|d|d| }|St|ttfst!d |z|D cgc]} t#j$| d}} t|ttfst!d |z|D cgc]} t#j&| d}} |d }t#j(|d}|d }t#j(|d}t+j,d|||||| \} } } }|dd}t#j.r{d| j1dd| j1dd| j1dd| j1dd| j1df }| j2}t#j4d||||\}|S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t|||||||S#t j$rYwxYwcc} wcc} w) aMakes a "one-shot" iterator that can be iterated only once. A one-shot iterator bundles the logic for defining the dataset and the state of the iterator in a single op, which allows simple input pipelines to be defined without an additional initialization ("MakeIterator") step. One-shot iterators have the following limitations: * They do not support parameterization: all logic for creating the underlying dataset must be bundled in the `dataset_factory` function. * They are not resettable. Once a one-shot iterator reaches the end of its underlying dataset, subsequent "IteratorGetNext" operations on that iterator will always produce an `OutOfRange` error. For greater flexibility, use "Iterator" and "MakeIterator" to define an iterator using an arbitrary subgraph, which may capture tensors (including fed values) as parameters, and which may be reset multiple times by rerunning "MakeIterator". Args: dataset_factory: A function decorated with @Defun. A function of type `() -> DT_VARIANT`, where the returned DT_VARIANT is a dataset. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. container: An optional `string`. Defaults to `""`. shared_name: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `resource`. OneShotIteratordataset_factoryrrrrN)r*rrrrrrLExpected list for 'output_types' argument to 'one_shot_iterator' Op, not %r.MExpected list for 'output_shapes' argument to 'one_shot_iterator' Op, not %r.r)r*rrrrr)rrr r!rr"r#r$r%r&r' one_shot_iterator_eager_fallbackr)r*r+r,r-r.r/r0rvr1r2r3r4r5r6)r*rrrrrr8r9r:r;r<r=r>r?r@rArBs rCone_shot_iteratorr.sD    0h..0$ #\\  11 '8/ o}Y {:Oll?+[ll;'ll=) +F ::L <: (' .Y  & &- ##At,,  # #    -) %!$88  # #   Q Us<"G II H'3HH'&H'+H==IIzraw_ops.OneShotIteratorc Pt|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j |d}}|d}t j|d}|d}t j|d}g} d|d|d|d|d|f } t jd d | | || } t jrt jd | | | | \} | Scc}wcc}w) Nr+rr,rrrrr*sOneShotIteratorrGrHr)) r*r+r,r-r.r/r0rvrr3r6) r*rrrrrrr<r=rBrAr:s rCr-r-!sR L4- 0  *,8 9 ::DPPR($$R8P,P MD%= 1  *,9 : ;;GTT8&&r?;T-TI ;7)K!!+}=+,  =+y-  &   /<#)s ?' ""$ <: (' .-Q Us D0D# optimizationsc tjxstj}|j}|jr" t j |d|||d|d|d| }|St|ttfst!d|z|D cgc]} t#j$| d}} t|ttfst!d|z|D cgc]} t#j&| d}} |g}t|ttfst!d |z|D cgc]} t#j(| d}} t+j,d|||||| \} } } }|dd}t#j.rYd| j1dd| j1dd| j1df}| j2}t#j4d||||\}|S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t|||||||S#t j$rYwxYwcc} wcc} wcc} w) aCreates a dataset by applying optimizations to `input_dataset`. Creates a dataset by applying optimizations to `input_dataset`. Args: input_dataset: A `Tensor` of type `variant`. A variant tensor representing the input dataset. optimizations: A `Tensor` of type `string`. A `tf.string` vector `tf.Tensor` identifying optimizations to use. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. optimization_configs: An optional list of `strings`. Defaults to `[]`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. OptimizeDatasetrroptimization_configsNrrr3rrKExpected list for 'output_types' argument to 'optimize_dataset' Op, not %r.LExpected list for 'output_shapes' argument to 'optimize_dataset' Op, not %r.SExpected list for 'optimization_configs' argument to 'optimize_dataset' Op, not %r.)rr0rrr3r)rrr r!rr"r#r$r%r&r'optimize_dataset_eager_fallbackr)r*r+r,r-r.r/r0rvr1r2r3r4r5r6)rr0rrr3rr8r9r:r;r<r=r>r?r@rArBs rCoptimize_datasetr9?s$    0h..0$ #\\  11 }m o} 46gn L4- 0  )+7 8 99DPPR($$R8P,P MD%= 1  )+8 9 ::GTT8&&r?;T-T! (4- 8  )+? @ AASggB(++B0FGgg'88)6(4)60D $ &!QX QK' ""$cll>:Oll?+-Cll124F::L <: (' .[  & &- ##At,,  # #    , \%3$DJJ  # #   Q UhsB G I IIH&HHHH00IIzraw_ops.OptimizeDatasetct|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j |d}}|g}t|ttfstd|z|Dcgc]}t j|d}}tj|tj}tj|tj}||g} d|d|d|f} t jdd| | || } t jrt jd | | | | \} | Scc}wcc}wcc}w) Nr5rr6rr7r3sOptimizeDatasetrGrHr2r) rr0rrr3rrr<r=rBrAr:s rCr8r8s L4- 0  )+7 8 99DPPR($$R8P,P MD%= 1  )+8 9 ::GTT8&&r?;T-T! (4- 8  )+? @ AASggB(++B0FGgg((H-((G-/, L/=. 0&   /<#)s ?' ""$ <: (' .1Q UhsE;0F;Foptimizations_enabledoptimizations_disabledoptimizations_defaultctjxstj}|j} | jr$ t j |d|||||d|d|d| } | St|ttfst!d|z|D cgc]} t#j$| d}} t|ttfst!d|z|D cgc]} t#j&| d}} |g}t|ttfst!d |z|D cgc]} t#j(| d}} t+j,d|||||||| \}}}}|dd} t#j.rYd|j1dd|j1dd|j1df}|j2}t#j4d||| | \} | S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t||||||||| S#t j$rYwxYwcc} wcc} wcc} w) aCreates a dataset by applying related optimizations to `input_dataset`. Creates a dataset by applying related optimizations to `input_dataset`. Args: input_dataset: A `Tensor` of type `variant`. A variant tensor representing the input dataset. optimizations_enabled: A `Tensor` of type `string`. A `tf.string` vector `tf.Tensor` identifying user enabled optimizations. optimizations_disabled: A `Tensor` of type `string`. A `tf.string` vector `tf.Tensor` identifying user disabled optimizations. optimizations_default: A `Tensor` of type `string`. A `tf.string` vector `tf.Tensor` identifying optimizations by default. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. optimization_configs: An optional list of `strings`. Defaults to `[]`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. OptimizeDatasetV2rrr3Nr4NExpected list for 'output_types' argument to 'optimize_dataset_v2' Op, not %r.OExpected list for 'output_shapes' argument to 'optimize_dataset_v2' Op, not %r.VExpected list for 'optimization_configs' argument to 'optimize_dataset_v2' Op, not %r.)rr;r<r=rrr3r)rrr r!rr"r#r$r%r&r'"optimize_dataset_v2_eager_fallbackr)r*r+r,r-r.r/r0rvr1r2r3r4r5r6)rr;r<r=rrr3rr8r9r:r;r<r=r>r?r@rArBs rCoptimize_dataset_v2rDs,    0h..0$ #\\  11 !48M 5~o}6L g n L4- 0  ,.: ; <<DPPR($$R8P,P MD%= 1  ,.; < ==GTT8&&r?;T-T! (4- 8  ,.B C DDSggB(++B0FGgg'88=3H4J3H*6+82F"&(!QX QK' ""$cll>:Oll?+-Cll124F::L \67< (' .a  & &- ##At,,  # #    / .0F l%3$D JJ  # #   Q UhsB"G IIIH*HHH"H66I  I zraw_ops.OptimizeDatasetV2c t|ttfstd|z|D cgc]} t j | d}} t|ttfstd|z|D cgc]} t j | d}} |g}t|ttfstd|z|D cgc]} t j| d}} tj|tj}tj|tj}tj|tj}tj|tj}||||g} d|d|d|f} t jdd| | || } t jrt jd | | | | \} | Scc} wcc} wcc} w) Nr@rrArrBr3sOptimizeDatasetV2rGrHr?r)rr;r<r=rrr3rrr<r=rBrAr:s rCrCrCs L4- 0  ,.: ; <<DPPR($$R8P,P MD%= 1  ,.; < ==GTT8&&r?;T-T! (4- 8  ,.B C DDSggB(++B0FGgg((H-001FW112H'..Y001FW!68NPef, L/=. 0&   11\#)s ?' ""$ \67< (' .5Q UhsG0G ;Gserialized_optionsctjxstj}|j}|jr# t j |d||d|d|d|d| }|Stj|d}t|t t"fst%d|z|D cgc]} tj&| d}} t|t t"fst%d |z|D cgc]} tj(| d}} |d }tj|d}t+j,d|||||| \} } } }|dd}tj.rjd| j1dd| j1dd| j1dd| j1df}| j2}tj4d||||\}|S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t|||||||S#t j$rYwxYwcc} wcc} w) amCreates a dataset by attaching tf.data.Options to `input_dataset`. Args: input_dataset: A `Tensor` of type `variant`. A variant tensor representing the input dataset. serialized_options: A `string`. A `tf.string` scalar `tf.Tensor` of serialized `tf.data.Options` protocol buffer. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. OptionsDatasetrFrrrN)rFrrrrrJExpected list for 'output_types' argument to 'options_dataset' Op, not %r.KExpected list for 'output_shapes' argument to 'options_dataset' Op, not %r.r)rrFrrrr)rrr r!rr"r#r$r%r&r'options_dataset_eager_fallbackr)r.rvr*r+r,r-r/r0r1r2r3r4r5r6)rrFrrrrr8r9r:r;r<r=r>r?r@rArBs rCoptions_datasetrL#sk    0h..0$ #\\  11 m5INL/z8-gn (();=QR L4- 0  (*6 7 88DPPR($$R8P,P MD%= 1  (*7 8 99GTT8&&r?;T-T H   x 4('88 -?'3(5# %!QX QK' ""$"CLL1E$Fcll>:Oll?+Zll:&(F::L ,9 (' .U  & &- ##At,,  # #    + ,>#=$D22  # #   Q Us<!G I'I HG88HHH''H>=H>zraw_ops.OptionsDatasetctj|d}t|ttfst d|z|Dcgc]}tj |d}}t|ttfst d|z|Dcgc]}tj|d}}|d}tj|d}tj|tj}|g} d|d|d|d|f} tjdd | | || } tjrtjd | | | | \} | Scc}wcc}w) NrFrIrrJrrrsOptionsDatasetrGrHrH)r.rvr*r+r,r-r/r0r%rrrrr3r6) rrFrrrrrr<r=rBrAr:s rCrKrKks](();=QR L4- 0  (*6 7 88DPPR($$R8P,P MD%= 1  (*7 8 99GTT8&&r?;T-T H   x 4(((H-, "4n H F&   .,#)s ?' ""$ ,9 (' .'Q Us D=E padded_shapesc 2tjxstj}|j}|jr" t j |d|||||d|d| } | St|ttfst!d|zt#|} t|ttfst!d|z|D cgc]} t%j&| d}} |d}t%j(|d}t+j,d||||||| \} } }}|dd} t%j.rjd |j1d d|j1dd |j3d d|j1df}|j4}t%j6d||| | \} | S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t||||||||S#t j$rYwxYwcc} w) aCreates a dataset that batches and pads `batch_size` elements from the input. Args: input_dataset: A `Tensor` of type `variant`. batch_size: A `Tensor` of type `int64`. A scalar representing the number of elements to accumulate in a batch. padded_shapes: A list of at least 1 `Tensor` objects with type `int64`. A list of int64 tensors representing the desired padded shapes of the corresponding output components. These shapes may be partially specified, using `-1` to indicate that a particular dimension should be padded to the maximum size of all batch elements. padding_values: A list of `Tensor` objects. A list of scalars containing the padding value to use for each of the outputs. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. PaddedBatchDatasetrrNrrrrPExpected list for 'padded_shapes' argument to 'padded_batch_dataset' Op, not %r.PExpected list for 'output_shapes' argument to 'padded_batch_dataset' Op, not %r.r)rrrNpadding_valuesrrr Toutput_typesr)rrr r!rr"r#r$r%r&r'#padded_batch_dataset_eager_fallbackr)r*r+r,r-rr.r0rvr1r2r3r4rr5r6)rrrNrTrrrr8r9r:r;rr=r>r?r@rArBs rCpadded_batch_datasetrWs:.    0h..0$ #\\  11 "D-~ Hgn MD%= 1  -/< = >>  ' MD%= 1  -/< = >>GTT8&&r?;T-T H   x 4('88M)3,9-;,9H#' )!QX QK' ""$s||O>  ' MD%= 1  -/< = >>GTT8&&r?;T-T H   x 4((0(O(OP^`c(d%~((H-%%j'--@***='--H-,tM/BBT.EYY, 0/gz8 5&   2Al#)s ?' ""$ lFG= (' .#UsF c tjxstj} | j} | jr% t j | d||||||d|d|d|} | St|ttfst!d|zt#|} t|ttfst!d|z|Dcgc]}t%j&|d}}|d }t%j(|d}|d }t%j*|d}t-j.d||||||||| \}}}}|dd} t%j0r{d|j3dd |j5d d|j5dd |j7d d|j5df }|j8}t%j:d||| | \} | S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t||||||||||  S#t j$rYwxYwcc}w)aCreates a dataset that batches and pads `batch_size` elements from the input. Args: input_dataset: A `Tensor` of type `variant`. batch_size: A `Tensor` of type `int64`. A scalar representing the number of elements to accumulate in a batch. padded_shapes: A list of at least 1 `Tensor` objects with type `int64`. A list of int64 tensors representing the desired padded shapes of the corresponding output components. These shapes may be partially specified, using `-1` to indicate that a particular dimension should be padded to the maximum size of all batch elements. padding_values: A list of `Tensor` objects. A list of scalars containing the padding value to use for each of the outputs. drop_remainder: A `Tensor` of type `bool`. A scalar representing whether the last batch should be dropped in case its size is smaller than desired. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. parallel_copy: An optional `bool`. Defaults to `False`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. PaddedBatchDatasetV2rrrN)rrrrrSExpected list for 'padded_shapes' argument to 'padded_batch_dataset_v2' Op, not %r.SExpected list for 'output_shapes' argument to 'padded_batch_dataset_v2' Op, not %r.Fr) rrrNrTrrrrrrUr)rrr r!rr"r#r$r%r&r'&padded_batch_dataset_v2_eager_fallbackr)r*r+r,r-rr.r0rrvr1r2r3rr4rr5r6)rrrNrTrrrrrr8r9r:r;rr=r>r?r@rArBs rCpadded_batch_dataset_v2r_s6    0h..0$ #\\  11 $dM:~~ z8Mgn MD%= 1  02? @ AA  ' MD%= 1  02? @ AAGTT8&&r?;T-TM$$]OD- H   x 4('88m+5.;/=/=.;.;)1>!QX QK' ""$s11/Bs||O= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. parallel_copy: An optional `bool`. Defaults to `False`. deterministic: An optional `string`. Defaults to `"default"`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. ParallelBatchDatasetrrrrbrN)rrrrbrrrQExpected list for 'output_types' argument to 'parallel_batch_dataset' Op, not %r.RExpected list for 'output_shapes' argument to 'parallel_batch_dataset' Op, not %r.Fdefaultr) rrrarrrrrbrr)rrr r!rr"r#r$r%r&r'%parallel_batch_dataset_eager_fallbackr)r*r+r,r-r.r/r0rrvr1r2r3rr4r5r6)rrrarrrrrbrrr8r9r:r;r<r=r>r?r@rArBs rCparallel_batch_datasetrims$    0h..0$ #\\  11 $dM:NO] o} H >g n L4- 0  /1= > ??DPPR($$R8P,P MD%= 1  /1> ? @@GTT8&&r?;T-TM$$]OD-M##M?C- H   x 4('88m+53E/=-9.;.;.;)1 >!QX QK' ""$s11/Bcll>:Oll?+_ll?+Zll:& (F ::L  fg? (' .k  & &- ##At,,  # #    2 %7%L%]$D 22  # #   Q Us<&HI=JI H00I I  I##I:9I:zraw_ops.ParallelBatchDatasetc t|ttfstd|z|D cgc]} t j | d}} t|ttfstd|z|D cgc]} t j | d}} |d}t j|d}|d}t j|d}|d }t j|d }tj|tj}tj|tj}tj|tj}tj|tj}||||g} d|d|d|d|d |f }t jd d | || | }t j rt j"d| |||\}|Scc} wcc} w)NrerrfrFrrgrbrrsParallelBatchDatasetrGrHrdr)rrrarrrrrbrrrr<r=rBrAr:s rCrhrhs L4- 0  /1= > ??DPPR($$R8P,P MD%= 1  /1> ? @@GTT8&&r?;T-TM$$]OD-M##M?C- H   x 4(((H-%%j'--@*--.@'--P)).',,G.-?P, ]NL=/=*  &   4a #)s ?' ""$  fg? (' .;Q Us G 0Gc tjxstj} | j} | jr' t j | d||||d|d|d|d|d|} | St|ttfst!d |z|D cgc]} t#j$| d}} t|ttfst!d |z|Dcgc]}t#j&|d}}|d }t#j(|d}|d }t#j(|d}t+j,d||||||||| \}}}}|dd} t#j.rd|j1dd|j1dd|j1dd|j1dd|j1dd|j1df }|j2}t#j4d||| | \} | S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t||||||||||  S#t j$rYwxYwcc} wcc}w)aCreates a dataset containing elements of `input_dataset` matching `predicate`. The `predicate` function must return a scalar boolean and accept the following arguments: * One tensor for each component of an element of `input_dataset`. * One tensor for each value in `other_arguments`. Unlike a "FilterDataset", which applies `predicate` sequentially, this dataset invokes up to `num_parallel_calls` copies of `predicate` in parallel. Args: input_dataset: A `Tensor` of type `variant`. other_arguments: A list of `Tensor` objects. A list of tensors, typically values that were captured when building a closure for `predicate`. num_parallel_calls: A `Tensor` of type `int64`. The number of concurrent invocations of `predicate` that process elements from `input_dataset` in parallel. predicate: A function decorated with @Defun. A function returning a scalar boolean. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. deterministic: An optional `string`. Defaults to `"default"`. A string indicating the op-level determinism to use. Deterministic controls whether the interleave is allowed to return elements out of order if the next element to be returned isn't available, but a later element is. Options are "true", "false", and "default". "default" indicates that determinism should be decided by the `experimental_deterministic` parameter of `tf.data.Options`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. ParallelFilterDatasetrBrbrrrN)rBrbrrrrrRExpected list for 'output_types' argument to 'parallel_filter_dataset' Op, not %r.SExpected list for 'output_shapes' argument to 'parallel_filter_dataset' Op, not %r.rgr) rrErarBrrrbrrrF)rrr r!rr"r#r$r%r&r'¶llel_filter_dataset_eager_fallbackr)r*r+r,r-r.r/r0rvr1r2r3r4r5r6)rrErarBrrrbrrr8r9r:r;r<r=r>r?r@rArBs rCparallel_filter_datasetrpsH    0h..0$ #\\  11 %t]OKO~|_z8 -g n L4- 0  02> ? @@DPPR($$R8P,P MD%= 1  02? @ AAGTT8&&r?;T-TM##M?C- H   x 4('88}1@4F+4.:/*Oll?+Zll:& (F ::L vw@ (' .e  & &- ##At,,  # #    3 *<]#=$D 22  # #   Q Us<%G7I1I67H> H%%H>=H>II.-I.zraw_ops.ParallelFilterDatasetc 8t|ttfstd|z|D cgc]} t j | d}} t|ttfstd|z|D cgc]} t j | d}} |d}t j|d}|d}t j|d}t j|| \} }tj|tj}tj|tj}|gt|z|gz} d |d|d | d|d|d|f }t jd d | || | }t jrt j d| |||\}|Scc} wcc} w)NrmrrnrrgrbrrrBrFsParallelFilterDatasetrGrHrlr)rrErarBrrrbrrrr<r=rMrBrAr:s rCroroMs L4- 0  02> ? @@DPPR($$R8P,P MD%= 1  02? @ AAGTT8&&r?;T-TM##M?C- H   x 4(&.&M&Mo_b&c#O((H---.@'--P4#88= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. sloppy: An optional `bool`. Defaults to `False`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. ParallelInterleaveDatasetV2rkrrrrrN)rkrrrrrrrYExpected list for 'output_types' argument to 'parallel_interleave_dataset_v2' Op, not %r.ZExpected list for 'output_shapes' argument to 'parallel_interleave_dataset_v2' Op, not %r.Fr) rrErrrarkrrrrrrrF)rrr r!rr"r#r$r%r&r'-parallel_interleave_dataset_v2_eager_fallbackr)r*r+r,r-r.r/r0rrvr1r2r3r4rr5r6)rrErrrarkrrrrrrr8r9r:r;r<r=r>r?r@rArBs rCparallel_interleave_dataset_v2rxns\    0h..0$ #\\  11 +T=|5G ><-&*h 0g n L4- 0  79E F GGDPPR($$R8P,P MD%= 1  79F G HHGTT8&&r?;T-T ^ F   fh /& H   x 4('88%]7F4@4@:L)*5B.4x,0 2!QX QK' ""$3<<$lll<(.ll>*Oll?+X  *Jll:& (F ::L %|VWF (' .g  & &- ##At,,  # #    : ,  %fx   # #   Q U<'G;I7I<;IH))IIII43I4z#raw_ops.ParallelInterleaveDatasetV2c t|ttfstd|z|D cgc]} t j | d}} t|ttfstd|z|D cgc]} t j | d}} |d}t j|d}| d} t j| d} t j|| \}}tj|tj}tj|tj}tj|tj}tj|tj}|gt|z|||gz}d |d |d|d|d|d| f }t jd d ||| | }t j rt j"d||||\}|Scc} wcc} w)NrurrvrFrrrrrkrFsParallelInterleaveDatasetV2rGrHrtr*r+r,r-r.r/r0rrvrLr%rrrrrr3r6)rrErrrarkrrrrrrrr<r=rMrBrAr:s rCrwrws L4- 0  79E F GGDPPR($$R8P,P MD%= 1  79F G HHGTT8&&r?;T-T ^ F   fh /& H   x 4(&.&M&Mo_b&c#O((H-'' gmmD,'' gmmD,--.@'--P4#88L,Xj;kk, L"2N&*  &   ;Q$0C"& ('""$ %|VWF (' .9Q U G0G!c tjxstj} | j} | jr) t j | d| |||||d|d|d|d|d| } | St|ttfst!d |z|Dcgc]}t#j$|d}}t|ttfst!d |z|Dcgc]}t#j&|d}}|d }t#j(|d}| d } t#j(| d} t+j,d|||||||||| | \}}}}|dd} t#j.rd|j1dd|j1dd|j1dd|j1dd|j1dd|j1df }|j2}t#j4d||| | \} | S#t j$r }tj|| Yd}~nd}~wt j$rYnwxYw t|||||||||| | |  S#t j$rY wxYwcc}wcc}w)aQ Creates a dataset that applies `f` to the outputs of `input_dataset`. The resulting dataset is similar to the `InterleaveDataset`, except that the dataset will fetch records from the interleaved datasets in parallel. The `tf.data` Python API creates instances of this op from `Dataset.interleave()` when the `num_parallel_calls` parameter of that method is set to any value other than `None`. By default, the output of this dataset will be deterministic, which may result in the dataset blocking if the next data item to be returned isn't available. In order to avoid head-of-line blocking, one can either set the `deterministic` attribute to "false", or leave it as "default" and set the `experimental_deterministic` parameter of `tf.data.Options` to `False`. This can improve performance at the expense of non-determinism. Args: input_dataset: A `Tensor` of type `variant`. Dataset that produces a stream of arguments for the function `f`. other_arguments: A list of `Tensor` objects. Additional arguments to pass to `f` beyond those produced by `input_dataset`. Evaluated once when the dataset is instantiated. cycle_length: A `Tensor` of type `int64`. Number of datasets (each created by applying `f` to the elements of `input_dataset`) among which the `ParallelInterleaveDatasetV2` will cycle in a round-robin fashion. block_length: A `Tensor` of type `int64`. Number of elements at a time to produce from each interleaved invocation of a dataset returned by `f`. num_parallel_calls: A `Tensor` of type `int64`. Determines the number of threads that should be used for fetching data from input datasets in parallel. The Python API `tf.data.experimental.AUTOTUNE` constant can be used to indicate that the level of parallelism should be autotuned. f: A function decorated with @Defun. A function mapping elements of `input_dataset`, concatenated with `other_arguments`, to a Dataset variant that contains elements matching `output_types` and `output_shapes`. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. deterministic: An optional `string`. Defaults to `"default"`. A string indicating the op-level determinism to use. Deterministic controls whether the interleave is allowed to return elements out of order if the next element to be returned isn't available, but a later element is. Options are "true", "false", and "default". "default" indicates that determinism should be decided by the `experimental_deterministic` parameter of `tf.data.Options`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. ParallelInterleaveDatasetV3rkrbrrrNrkrbrrrrrYExpected list for 'output_types' argument to 'parallel_interleave_dataset_v3' Op, not %r.ZExpected list for 'output_shapes' argument to 'parallel_interleave_dataset_v3' Op, not %r.rgr) rrErrrarkrrrbrrrF)rrr r!rr"r#r$r%r&r'-parallel_interleave_dataset_v3_eager_fallbackr)r*r+r,r-r.r/r0rvr1r2r3r4r5r6)rrErrrarkrrrbrrr8r9r:r;r<r=r>r?r@rArBs rCparallel_interleave_dataset_v3rsh    0h..0$ #\\  11 +T=|5G ?M>< H >g n L4- 0  79E F GGDPPR($$R8P,P MD%= 1  79F G HHGTT8&&r?;T-TM##M?C- H   x 4('88%]7F4@4@:L)*5B5B08t E!QX QK' ""$3<<$oll?+\ll<(.ll>*Oll?+Zll:& (F ::L %|VWF (' .g  & &- ##At,,  # #    : , #=$D 22  # #   Q Uryz#raw_ops.ParallelInterleaveDatasetV3c t|ttfstd|z|D cgc]} t j | d}} t|ttfstd|z|D cgc]} t j | d}} |d}t j|d}| d} t j| d} t j|| \}}tj|tj}tj|tj}tj|tj}tj|tj}|gt|z|||gz}d |d|d |d|d|d| f }t jd d ||| | }t jrt j d||||\}|Scc} wcc} w)NrrrrrgrbrrrkrFsParallelInterleaveDatasetV3rGrHr~r)rrErrrarkrrrbrrrr<r=rMrBrAr:s rCrrxs L4- 0  79E F GGDPPR($$R8P,P MD%= 1  79F G HHGTT8&&r?;T-TM##M?C- H   x 4(&.&M&Mo_b&c#O((H-'' gmmD,'' gmmD,--.@'--P4#88L,Xj;kk, O]LNL/X '&   ;Q$0C"& ('""$ %|VWF (' .9Q Ur|buffer_output_elementsprefetch_input_elementsc tjxstj} | j}|jr+ t j | d| |||||||d|d| d|d| d| }|St|ttfst!d |z|Dcgc]}t#j$|d}}t| ttfst!d | z| Dcgc]}t#j&|d} }| d } t#j(| d} | d } t#j(| d} t+j,d|||||||||| | | | \}}}}|dd}t#j.rd|j1dd|j1dd|j1dd|j1dd|j1dd|j1df }|j2}t#j4d||||\}|S#t j$r }tj|| Yd}~nd}~wt j$rYnwxYw t||||||||| || | | | S#t j$rYwxYwcc}wcc}w)a Creates a dataset that applies `f` to the outputs of `input_dataset`. The resulting dataset is similar to the `InterleaveDataset`, except that the dataset will fetch records from the interleaved datasets in parallel. The `tf.data` Python API creates instances of this op from `Dataset.interleave()` when the `num_parallel_calls` parameter of that method is set to any value other than `None`. By default, the output of this dataset will be deterministic, which may result in the dataset blocking if the next data item to be returned isn't available. In order to avoid head-of-line blocking, one can either set the `deterministic` attribute to "false", or leave it as "default" and set the `experimental_deterministic` parameter of `tf.data.Options` to `False`. This can improve performance at the expense of non-determinism. Args: input_dataset: A `Tensor` of type `variant`. Dataset that produces a stream of arguments for the function `f`. other_arguments: A list of `Tensor` objects. Additional arguments to pass to `f` beyond those produced by `input_dataset`. Evaluated once when the dataset is instantiated. cycle_length: A `Tensor` of type `int64`. Number of datasets (each created by applying `f` to the elements of `input_dataset`) among which the `ParallelInterleaveDatasetV2` will cycle in a round-robin fashion. block_length: A `Tensor` of type `int64`. Number of elements at a time to produce from each interleaved invocation of a dataset returned by `f`. buffer_output_elements: A `Tensor` of type `int64`. The number of elements each iterator being interleaved should buffer (similar to the `.prefetch()` transformation for each interleaved iterator). prefetch_input_elements: A `Tensor` of type `int64`. Determines the number of iterators to prefetch, allowing buffers to warm up and data to be pre-fetched without blocking the main thread. num_parallel_calls: A `Tensor` of type `int64`. Determines the number of threads that should be used for fetching data from input datasets in parallel. The Python API `tf.data.experimental.AUTOTUNE` constant can be used to indicate that the level of parallelism should be autotuned. f: A function decorated with @Defun. A function mapping elements of `input_dataset`, concatenated with `other_arguments`, to a Dataset variant that contains elements matching `output_types` and `output_shapes`. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. deterministic: An optional `string`. Defaults to `"default"`. A string indicating the op-level determinism to use. Deterministic controls whether the interleave is allowed to return elements out of order if the next element to be returned isn't available, but a later element is. Options are "true", "false", and "default". "default" indicates that determinism should be decided by the `experimental_deterministic` parameter of `tf.data.Options`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. ParallelInterleaveDatasetV4rkrbrrrNrYExpected list for 'output_types' argument to 'parallel_interleave_dataset_v4' Op, not %r.ZExpected list for 'output_shapes' argument to 'parallel_interleave_dataset_v4' Op, not %r.rgr) rrErrrrrarkrrrbrrrF)rrr r!rr"r#r$r%r&r'-parallel_interleave_dataset_v4_eager_fallbackr)r*r+r,r-r.r/r0rvr1r2r3r4r5r6)rrErrrrrarkrrrbrrr8r9r:r;r<r=r>r?r@rArBs rCparallel_interleave_dataset_v4rst    0h..0$ #\\  11 +T=|5K!3S!_~|_z8 -g n L4- 0  79E F GGDPPR($$R8P,P MD%= 1  79F G HHGTT8&&r?;T-TM##M?C- H   x 4('88%]7F4@4@>T?V:L)*5B5B08t E!QX QK' ""$3<<$oll?+\ll<(.ll>*Oll?+Zll:& (F ::L %|VWF (' .k  & &- ##At,,  # #    : , "9;M ]%t OO  # #   Q Us<)G?I=J?IH--II I##I:9I:z#raw_ops.ParallelInterleaveDatasetV4c `t|ttfstd|z|Dcgc]}t j |d}}t| ttfstd| z| Dcgc]}t j |d} }| d} t j| d} | d} t j| d} t j|| \}}tj|tj}tj|tj}tj|tj}tj|tj}tj|tj}tj|tj}|gt|z|||||gz}d |d| d |d|d| d| f }t jd d ||| | }t jrt j d||||\}|Scc}wcc}w)NrrrrrgrbrrrkrFsParallelInterleaveDatasetV4rGrHrr)rrErrrrrarkrrrbrrrr<r=rMrBrAr:s rCrrs0 L4- 0  79E F GGDPPR($$R8P,P MD%= 1  79F G HHGTT8&&r?;T-TM##M?C- H   x 4(&.&M&Mo_b&c#O((H-'' gmmD,'' gmmD,112H'--X 223JGMMZ--.@'--P4#88L,XnqHJ\<]], O]LNL/X '&   ;Q$0C"& ('""$ %|VWF (' .=Q Us H&0H+c tjxstj} | j} | jr+ t j | d| |||d|d|d|d|d|d|d| } | St|ttfst!d |z|Dcgc]}t#j$|d}}t|ttfst!d |z|Dcgc]}t#j&|d}}|d }t#j(|d}|d}t#j(|d}|d}t#j(|d}| d} t#j*| d} t-j.d|||||||||| |  \}}}}|d d } t#j0rd|j3dd|j3dd|j3dd|j3dd|j5dd|j5dd|j5dd|j3df}|j6}t#j8d||| | \} | S#t j$r }tj|| Yd }~nd }~wt j$rYnwxYw t|||||||||| | | S#t j$rYawxYwcc}wcc}w)aCreates a dataset that applies `f` to the outputs of `input_dataset`. Unlike a "MapDataset", which applies `f` sequentially, this dataset invokes up to `num_parallel_calls` copies of `f` in parallel. Args: input_dataset: A `Tensor` of type `variant`. other_arguments: A list of `Tensor` objects. num_parallel_calls: A `Tensor` of type `int32`. The number of concurrent invocations of `f` that process elements from `input_dataset` in parallel. f: A function decorated with @Defun. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. use_inter_op_parallelism: An optional `bool`. Defaults to `True`. sloppy: An optional `bool`. Defaults to `False`. preserve_cardinality: An optional `bool`. Defaults to `False`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. ParallelMapDatasetrkrrrrrrrN) rkrrrrrrrrrOExpected list for 'output_types' argument to 'parallel_map_dataset' Op, not %r.PExpected list for 'output_shapes' argument to 'parallel_map_dataset' Op, not %r.TFr) rrErarkrrrrrrrrrF)rrr r!rr"r#r$r%r&r'#parallel_map_dataset_eager_fallbackr)r*r+r,r-r.r/r0rrvr1r2r3r4rr5r6)rrErarkrrrrrrrrr8r9r:r;r<r=r>r?r@rArBs rCparallel_map_datasetrAs"0    0h..0$ #\\  11 "D-CNL(B (F4Jj( 4g n L4- 0  -/; < ==DPPR($$R8P,P MD%= 1  -/< = >>GTT8&&r?;T-T%#%//0HJde ^ F   fh /&! !++,@BXY H   x 4('88M.=1Cq+7,97O%+3G'/d <!QX QK' ""$3<<$lll<(.ll>*Oll?+-G  !;>GTT8&&r?;T-T%#%//0HJde ^ F   fh /&! !++,@BXY H   x 4(&.&M&Mo_b&c#O((H---.@'--P4#88= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. use_inter_op_parallelism: An optional `bool`. Defaults to `True`. deterministic: An optional `string`. Defaults to `"default"`. preserve_cardinality: An optional `bool`. Defaults to `False`. use_unbounded_threadpool: An optional `bool`. Defaults to `False`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. ParallelMapDatasetV2rkrrrrbrrrN) rkrrrrbrrrrrRExpected list for 'output_types' argument to 'parallel_map_dataset_v2' Op, not %r.SExpected list for 'output_shapes' argument to 'parallel_map_dataset_v2' Op, not %r.TrgFr) rrErarkrrrrbrrrrrF)rrr r!rr"r#r$r%r&r'¶llel_map_dataset_v2_eager_fallbackr)r*r+r,r-r.r/r0rrvr1r2r3r4rr5r6)rrErarkrrrrbrrrrr8r9r:r;r<r=r>r?r@rArBs rCparallel_map_dataset_v2rsg2    0h..0$ #\\  11 $dM?CNL(B /= 4"$ ? @@DPPR($$R8P,P MD%= 1  02? @ AAGTT8&&r?;T-T%#%//0HJdeM##M?C-! !++,@BXY%$%//0HJde H   x 4('88m0?3E-9.;9Q.;5I9Q)1 >!QX QK' ""$3<<$lll<(.ll>*Oll?+-G  !;LKJ//KK K$$K;:K;zraw_ops.ParallelMapDatasetV2c t|ttfstd|z|D cgc]} t j | d}} t|ttfstd|z|Dcgc]}t j |d}}|d}t j|d}|d}t j|d}|d }t j|d }| d } t j| d } | d } t j| d } t j|| \}}tj|tj}tj|tj}|gt|z|gz}d|d|d|d|d|d|d |d | d | f}t jdd||| | }t j rt j"d||||\}|Scc} wcc}w)NrrrrTrrgrbFrrrrrkrFsParallelMapDatasetV2rGrHrr{)rrErarkrrrrbrrrrrr<r=rMrBrAr:s rCrr<s- L4- 0  02> ? @@DPPR($$R8P,P MD%= 1  02? @ AAGTT8&&r?;T-T%#%//0HJdeM##M?C-! !++,@BXY%$%//0HJde H   x 4(&.&M&Mo_b&c#O((H---.@'--P4#88= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. slack_period: An optional `int`. Defaults to `0`. legacy_autotune: An optional `bool`. Defaults to `True`. buffer_size_min: An optional `int`. Defaults to `0`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. PrefetchDatasetrrrrrrN)rrrrrrrrKExpected list for 'output_types' argument to 'prefetch_dataset' Op, not %r.LExpected list for 'output_shapes' argument to 'prefetch_dataset' Op, not %r.rTr) rr[rrrrrrr)rrr r!rr"r#r$r%r&r'prefetch_dataset_eager_fallbackr)r*r+r,r-r.r/r0rrrvr1r2r3r4rrr5r6)rr[rrrrrrrr8r9r:r;r<r=r>r?r@rArBs rCprefetch_datasetrhs&    0h..0$ #\\  11 }k o} &7?J Bg n L4- 0  )+7 8 99DPPR($$R8P,P MD%= 1  )+8 9 ::GTT8&&r?;T-TL""<@,O&&8IJ/O%%o7HI/ H   x 4('88'2)6(4+:+:X $&!QX QK' ""$cll>:Oll?+^/1B  !235F 12Jll:& (F ::L <: (' .o  & &- ##At,,  # #    , <%L)?$D 22  # #   Q Us<&H,J&J+,I3?II32I37J J#"J#zraw_ops.PrefetchDatasetc Pt|ttfstd|z|D cgc]} t j | d}} t|ttfstd|z|D cgc]} t j | d}} |d}t j|d}|d}t j|d}|d}t j|d }|d }t j|d }tj|tj}tj|tj}||g} d|d|d|d|d |d |f } t jd d | | | |}t j rt j"d| | ||\}|Scc} wcc} w)NrrrrrrTrrrrsPrefetchDatasetrGrHr)r*r+r,r-r.r/r0rrrvr%rrrrrr3r6)rr[rrrrrrrrr<r=rBrAr:s rCrrs L4- 0  )+7 8 99DPPR($$R8P,P MD%= 1  )+8 9 ::GTT8&&r?;T-TL""<@,O&&8IJ/O%%o7HI/ H   x 4(((H-&&{GMMB+-, L/=, 1?_j( <&   /<#)s ?' ""$ <: (' .=Q Us F0F#startstopstepreplicate_on_splitctjxstj}|j} | jr% t j |d||||d|d|d|d|} | St|ttfst!d|z|D cgc]} t#j$| d}} t|ttfst!d |z|D cgc]} t#j&| d}} |d }t#j(|d}|d }t#j*|d}t-j.d|||||||| \}}}}|dd} t#j0rjd|j3dd|j3dd|j3dd|j5df}|j6}t#j8d||| | \} | S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t||||||||| S#t j$rYwxYwcc} wcc} w) aCreates a dataset with a range of values. Corresponds to python's xrange. Args: start: A `Tensor` of type `int64`. corresponds to start in python's xrange(). stop: A `Tensor` of type `int64`. corresponds to stop in python's xrange(). step: A `Tensor` of type `int64`. corresponds to step in python's xrange(). output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. metadata: An optional `string`. Defaults to `""`. replicate_on_split: An optional `bool`. Defaults to `False`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. RangeDatasetrrrrN)rrrrrrHExpected list for 'output_types' argument to 'range_dataset' Op, not %r.IExpected list for 'output_shapes' argument to 'range_dataset' Op, not %r.rF)rrrrrrrr)rrr r!rr"r#r$r%r&r'range_dataset_eager_fallbackr)r*r+r,r-r.r/r0rvrr1r2r3r4rr5r6)rrrrrrrrr8r9r:r;r<r=r>r?r@rArBs rC range_datasetrs&    0h..0$ #\\  11 ndE4~o}j(02gn L4- 0  &(4 5 66DPPR($$R8P,P MD%= 1  &(5 6 77GTT8&&r?;T-T H   x 4())*<>RS'88e$T%1&3h+=D J!QX QK' ""$cll>:Oll?+Zll:&(<  !568F::L  fg7 (' .W  & &- ##At,,  # #    ) t,%/dFF  # #   Q Urzraw_ops.RangeDatasetc *t|ttfstd|z|D cgc]} t j | d}} t|ttfstd|z|D cgc]} t j | d}} |d}t j|d}|d}t j|d}tj|tj}tj|tj}tj|tj}|||g} d|d|d|d|f} t jd d | | || } t jrt jd | | | | \} | Scc} wcc} w) NrrrrrrFrs RangeDatasetrGrHr)r*r+r,r-r.r/r0rvrr%rrrrr3r6)rrrrrrrrrr<r=rBrAr:s rCrr3s L4- 0  &(4 5 66DPPR($$R8P,P MD%= 1  &(5 6 77GTT8&&r?;T-T H   x 4())*<>RS   6%  gmm 4$  gmm 4$t$, L/= h,.@ B&   _a #)s ?' ""$  fg7 (' .1Q Urc tjxstj} | j} | jr' t j | d||||d|d|d|d|d|} | St|ttfst!d |z|D cgc]} t#j$| d}} t|ttfst!d |z|Dcgc]}t#j&|d}}|d }t#j(|d}|d }t#j*|d}t-j.d||||||||| \}}}}|dd} | s|St#j0rd|j3dd|j3dd|j3dd|j3dd|j3dd|j5dd|j3df}|j6}t#j8d||| | S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t||||||||||  S#t j$rYwxYwcc} wcc}w)aReduces the input dataset to a singleton using a reduce function. Args: input_dataset: A `Tensor` of type `variant`. A variant tensor representing the input dataset. initial_state: A list of `Tensor` objects. A nested structure of tensors, representing the initial state of the transformation. other_arguments: A list of `Tensor` objects. f: A function decorated with @Defun. A function that maps `(old_state, input_element)` to `new_state`. It must take two arguments and return a nested structures of tensors. The structure of `new_state` must match the structure of `initial_state`. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. use_inter_op_parallelism: An optional `bool`. Defaults to `True`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A list of `Tensor` objects of type `output_types`. ReduceDatasetrkrrrrN)rkrrrrrrIExpected list for 'output_types' argument to 'reduce_dataset' Op, not %r.JExpected list for 'output_shapes' argument to 'reduce_dataset' Op, not %r.Tr) r initial_staterErkrrrrrTstaterF)rrr r!rr"r#r$r%r&r'reduce_dataset_eager_fallbackr)r*r+r,r-r.r/r0rrvr1r2r3r4rr5r6)rrrErkrrrrrr8r9r:r;r<r=r>r?r@rArBs rCreduce_datasetrSs.    0h..0$ #\\  11 ot]Ma(B *h 8g n L4- 0  ')5 6 77DPPR($$R8P,P MD%= 1  ')6 7 88GTT8&&r?;T-T%#%//0HJde H   x 4('88}'4)8A&2'42J"*7!QX QK'  J ""$3<<$h X0FCLL6ll>*Oll?+-G  !;I?zraw_ops.ReduceDatasetc @t|ttfstd|z|D cgc]} t j | d}} t|ttfstd|z|D cgc]} t j | d}} |d}t j|d}|d}t j|d}t j|| \} }t j|| \} }tj|tj}|gt|zt|z}d |d | d | d|d|d|d|f}t jd t|||| | }t j rt j"d||||Scc} wcc} w)NrrrrTrrrrkrrFs ReduceDatasetrHr)r*r+r,r-r.r/r0rrvrLr%rrrrrr3r6)rrrErkrrrrrrr<r= _attr_TstaterMrBrAr:s rCrrs L4- 0  ')5 6 77DPPR($$R8P,P MD%= 1  ')6 7 88GTT8&&r?;T-T%#%//0HJde H   x 4( ( G G WZ [, &.&M&Mo_b&c#O((H-4 #66o9NN, HlL:J,6 H N&   -s= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. RepeatDatasetrrrNrIExpected list for 'output_types' argument to 'repeat_dataset' Op, not %r.JExpected list for 'output_shapes' argument to 'repeat_dataset' Op, not %r.rrrrrrr)rrr r!rr"r#r$r%r&r'repeat_dataset_eager_fallbackr)r*r+r,r-r.r/r0rvr1r2r3r4r5r6rrrrrrr8r9r:r;r<r=r>r?r@rArBs rCrepeat_datasetrsB    0h..0$ #\\ 11 ot]E>o}j(Lgn L4- 0  ')5 6 77DPPR($$R8P,P MD%= 1  ')6 7 88GTT8&&r?;T-T H   x 4('88}E&2'4x" $!QX QK' ""$cll>:Oll?+Zll:&(F::L vw8 (' .M  & &- ##At,,  # #    * \%tOO  # #   Q Urzraw_ops.RepeatDatasetct|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j |d}}|d}t j|d}tj|tj}tj|tj}||g} d|d|d|f} t jdd| | || } t jrt jd | | | | \} | Scc}wcc}w) Nrrrrrrs RepeatDatasetrGrHrr rrrrrrrr<r=rBrAr:s rCrrs[ L4- 0  ')5 6 77DPPR($$R8P,P MD%= 1  ')6 7 88GTT8&&r?;T-T H   x 4(((H-   6%', L/= h &   -q#)s ?' ""$ vw8 (' .)Q Ur rewrite_namec tjxstj}|j}|jr t j |d|||d|d| }|St|ttfst!d|z|D cgc]} t#j$| d}} t|ttfst!d|z|D cgc]} t#j&| d}} t)j*d|||||\} } } } | dd}t#j,rHd| j/dd| j/df}| j0}t#j2d||||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t||||||S#t j$rYwxYwcc} wcc} w) aTODO: add doc. Args: input_dataset: A `Tensor` of type `variant`. rewrite_name: A `Tensor` of type `string`. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. RewriteDatasetrrNrJExpected list for 'output_types' argument to 'rewrite_dataset' Op, not %r.KExpected list for 'output_shapes' argument to 'rewrite_dataset' Op, not %r.)rrrrr)rrr r!rr"r#r$r%r&r'rewrite_dataset_eager_fallbackr)r*r+r,r-r.r/r0r1r2r3r4r5r6)rrrrrr8r9r:r;r<r=r>r?r@rArBs rCrewrite_datasetr+s     0h..0$ #\\ 11 m\ o}Fgn L4- 0  (*6 7 88DPPR($$R8P,P MD%= 1  (*7 8 99GTT8&&r?;T-T'88 '3'3(5D B!QX QK' ""$cll>:Oll?+-F::L ,9 (' .E  & &- ##At,,  # #    + L%Dd<<  # #   Q Us<E4G*G/4F;F""F;:F;?GG'&G'zraw_ops.RewriteDatasetcpt|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j |d}}tj|tj}tj|tj}||g}d|d|f} t jdd|| ||} t jrt jd|| | | \} | Scc}wcc}w) NrrrrsRewriteDatasetrGrHr)r*r+r,r-r.r/r0r%rrrrrr3r6) rrrrrrr<r=rBrAr:s rCrrgs7 L4- 0  (*6 7 88DPPR($$R8P,P MD%= 1  (*7 8 99GTT8&&r?;T-T((H-'' gnnE,., L/= I&   .,#)s ?' ""$ ,9 (' .!Q Us D.0D3ctjxstj}|j}|jr t j |d||d|}|S|d}tj|d}tj d|||\}}}} | dd}tj"r7d|j%df} |j&} tj(d| | ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t||||S#t j$rYwxYw)aVConverts the given `resource_handle` representing an iterator to a variant tensor. Args: resource_handle: A `Tensor` of type `resource`. A handle to an iterator resource. external_state_policy: An optional `int`. Defaults to `0`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. SerializeIteratorrN)rrrr)r#rr)rrr r!rr"r#r$r%r&r'!serialize_iterator_eager_fallbackr)r.rr1r2r3rr5r6) r#rrr8r9r:r;r>r?r@rArBs rCserialize_iteratorrsq    0h..0$ #\\ 11 !4!68gn""++,ACZ['88_3H"&(!QX QK' ""$% 78:F::L \67< (' .5  & &- ##At,,  # #    . 1F  # #   rzraw_ops.SerializeIteratorc&|d}tj|d}tj|tj }|g}d|f}tj dd||||}tjrtjd||||\}|S)NrrsSerializeIteratorrGrHr) r.rr%rrrrr3r6)r#rrrrBrAr:s rCrrs""++,ACZ[**?G= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. require_non_empty: An optional `bool`. Defaults to `False`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. ShardDatasetrrrrN)rrrrrrHExpected list for 'output_types' argument to 'shard_dataset' Op, not %r.IExpected list for 'output_shapes' argument to 'shard_dataset' Op, not %r.Fr)rrrrrrrr)rrr r!rr"r#r$r%r&r'shard_dataset_eager_fallbackr)r*r+r,r-r.r/r0rrvr1r2r3rr4r5r6)rrrrrrrrr8r9r:r;r<r=r>r?r@rArBs rC shard_datasetrs$    0h..0$ #\\  11 ndM:u.  H>gn L4- 0  &(4 5 66DPPR($$R8P,P MD%= 1  &(5 6 77GTT8&&r?;T-T(()::Oll?+Zll:&(F::L  fg7 (' .Y  & &- ##At,,  # #    ) U-L%tOO  # #   Q Urzraw_ops.ShardDatasetc *t|ttfstd|z|D cgc]} t j | d}} t|ttfstd|z|D cgc]} t j | d}} |d}t j|d}|d}t j|d}tj|tj}tj|tj}tj|tj}|||g} d|d|d|d|f} t jd d | | || } t jrt j d | | | | \} | Scc} wcc} w) NrrrrFrrrs ShardDatasetrGrHrr*r+r,r-r.r/r0rrvr%rrrrrr3r6)rrrrrrrrrr<r=rBrAr:s rCrrs L4- 0  &(4 5 66DPPR($$R8P,P MD%= 1  &(5 6 77GTT8&&r?;T-T(():= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. reshuffle_each_iteration: An optional `bool`. Defaults to `True`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. ShuffleAndRepeatDatasetrrrrN)rrrrrrUExpected list for 'output_types' argument to 'shuffle_and_repeat_dataset' Op, not %r.VExpected list for 'output_shapes' argument to 'shuffle_and_repeat_dataset' Op, not %r.Tr) rr[rrrrrrrr)rrr r!rr"r#r$r%r&r')shuffle_and_repeat_dataset_eager_fallbackr)r*r+r,r-r.r/r0rrvr1r2r3r4rr5r6)rr[rrrrrrrrr8r9r:r;r<r=r>r?r@rArBs rCshuffle_and_repeat_datasetr.s:    0h..0$ #\\  11 '}k eUNL/13KH g n L4- 0  35A B CCDPPR($$R8P,P MD%= 1  35B C DDGTT8&&r?;T-T%#%//0HJde H   x 4('88!/:).e0<1>:Oll?+-G  !;= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. reshuffle_each_iteration: An optional `bool`. Defaults to `True`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. ShuffleAndRepeatDatasetV2rrrrNrrrrrrXExpected list for 'output_types' argument to 'shuffle_and_repeat_dataset_v2' Op, not %r.YExpected list for 'output_shapes' argument to 'shuffle_and_repeat_dataset_v2' Op, not %r.Tr) rr[rrrrrrrrr)rrr r!rr"r#r$r%r&r',shuffle_and_repeat_dataset_v2_eager_fallbackr)r*r+r,r-r.r/r0rrvr1r2r3rr4r5r6)rr[rrrrrrrrrr8r9r:r;r<r=r>r?r@rArBs rCshuffle_and_repeat_dataset_v2rs&    0h..0$ #\\  11 )4  eUN,F ., H >g n L4- 0  68D E FFDPPR($$R8P,P MD%= 1  68E F GGGTT8&&r?;T-T%#%//0HJde H   x 4('88#=1<4+04B2>3@>V.6TC!QX QK' ""$(  !;*Oll?+Zll:& (F ::L #\67D (' .c  & &- ##At,,  # #    9 dE5.#;#=$D 22  # #   Q Us<&GIIH+HHH#H::IIz!raw_ops.ShuffleAndRepeatDatasetV2c t|ttfstd|z|D cgc]} t j | d}} t|ttfstd|z|D cgc]} t j | d}} |d}t j|d}| d} t j| d} tj|tj}tj|tj}tj|tj}tj|tj}tj|tj}tj|tj}||||||g}d|d|d|d| f}t jd d ||| | }t j rt j"d ||||\}|Scc} wcc} w) NrrrrTrrrsShuffleAndRepeatDatasetV2rGrHrr*r+r,r-r.r/r0rrvr%rrrrrrr3r6)rr[rrrrrrrrrrr<r=rBrAr:s rCrrs L4- 0  68D E FFDPPR($$R8P,P MD%= 1  68E F GGGTT8&&r?;T-T%#%//0HJde H   x 4(((H-&&{GMMB+  gmm 4$   6%   6%)).':J:JK.dE5.Q, &(@,   &   91$0C"& ('""$ #\67D (' .;Q Us G:0G?c tjxstj} | j} | jr& t j | d|||||d|d|d|d|} | St|ttfst!d|z|D cgc]} t#j$| d}} t|ttfst!d |z|Dcgc]}t#j&|d}}|d }t#j(|d}|d }t#j*|d}t-j.d||||||||| \}}}}|dd} t#j0rjd|j3dd|j5dd|j5dd|j5df}|j6}t#j8d||| | \} | S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t||||||||||  S#t j$rYwxYwcc} wcc}w) aCreates a dataset that shuffles elements from `input_dataset` pseudorandomly. Args: input_dataset: A `Tensor` of type `variant`. buffer_size: A `Tensor` of type `int64`. The number of output elements to buffer in an iterator over this dataset. Compare with the `min_after_dequeue` attr when creating a `RandomShuffleQueue`. seed: A `Tensor` of type `int64`. A scalar seed for the random number generator. If either `seed` or `seed2` is set to be non-zero, the random number generator is seeded by the given seed. Otherwise, a random seed is used. seed2: A `Tensor` of type `int64`. A second scalar seed to avoid seed collision. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. reshuffle_each_iteration: An optional `bool`. Defaults to `True`. If true, each iterator over this dataset will be given a different pseudorandomly generated seed, based on a sequence seeded by the `seed` and `seed2` inputs. If false, each iterator will be given the same seed, and repeated iteration over this dataset will yield the exact same sequence of results. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. ShuffleDatasetrrrrNrJExpected list for 'output_types' argument to 'shuffle_dataset' Op, not %r.KExpected list for 'output_shapes' argument to 'shuffle_dataset' Op, not %r.Tr) rr[rrrrrrr)rrr r!rr"r#r$r%r&r'shuffle_dataset_eager_fallbackr)r*r+r,r-r.r/r0rrvr1r2r3rr4r5r6)rr[rrrrrrrr8r9r:r;r<r=r>r?r@rArBs rCshuffle_datasetr$s:    0h..0$ #\\  11 m[$"$*Oll?+Zll:& (F ::L ,9 (' ._  & &- ##At,,  # #    + dE#;#=$D 22  # #   Q Us<$G IIH'HHHH44I  I zraw_ops.ShuffleDatasetc tt|ttfstd|z|D cgc]} t j | d}} t|ttfstd|z|D cgc]} t j | d}} |d}t j|d}|d}t j|d}tj|tj}tj|tj}tj|tj}tj|tj}||||g} d|d|d|d|f} t jd d | | | | }t jrt j d | | ||\}|Scc} wcc} w) NrrrrTrrrsShuffleDatasetrGrHrr)rr[rrrrrrrrr<r=rBrAr:s rCrr~s L4- 0  (*6 7 88DPPR($$R8P,P MD%= 1  (*7 8 99GTT8&&r?;T-T%#%//0HJde H   x 4(((H-&&{GMMB+  gmm 4$   6%dE:, &(@,   &   .,#)s ?' ""$ ,9 (' .5Q Us F00F5cLtjxstj}|j}|jr# t j |d||||d|d|d| } | St|ttfst!d|z|D cgc]} t#j$| d}} t|ttfst!d|z|D cgc]} t#j&| d}} |d }t#j(|d}t+j,d||||||| \} } }}|dd} t#j.rYd|j1dd|j1dd|j1df}|j2}t#j4d||| | \} | S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t||||||||S#t j$rYwxYwcc} wcc} w) aTODO: add doc. Args: input_dataset: A `Tensor` of type `variant`. buffer_size: A `Tensor` of type `int64`. seed_generator: A `Tensor` of type `resource`. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. ShuffleDatasetV2rrrNrMExpected list for 'output_types' argument to 'shuffle_dataset_v2' Op, not %r.NExpected list for 'output_shapes' argument to 'shuffle_dataset_v2' Op, not %r.r)rr[rrrrr)rrr r!rr"r#r$r%r&r'!shuffle_dataset_v2_eager_fallbackr)r*r+r,r-r.r/r0rvr1r2r3r4r5r6)rr[rrrrrr8r9r:r;r<r=r>r?r@rArBs rCshuffle_dataset_v2rsJ    0h..0$ #\\  11  $ { oz8-gn L4- 0  +-9 : ;;DPPR($$R8P,P MD%= 1  +-: ; <<GTT8&&r?;T-T H   x 4('88-(3+9)5*7(!% '!QX QK' ""$cll>:Oll?+Zll:&(F::L L&'; (' .S  & &- ##At,,  # #    . n#=$D22  # #   Q Urzraw_ops.ShuffleDatasetV2ct|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|D cgc]} t j | d}} |d}t j|d}tj|tj}tj|tj}tj|tj}|||g} d|d|d|f} t jdd| | || } t jrt j d | | | | \} | Scc}wcc} w) NrrrrrrsShuffleDatasetV2rGrHr)r*r+r,r-r.r/r0rvr%rrrrrrr3r6) rr[rrrrrrr<r=rBrAr:s rCrrsu L4- 0  +-9 : ;;DPPR($$R8P,P MD%= 1  +-: ; <<GTT8&&r?;T-T H   x 4(((H-&&{GMMB+)).':J:JK.n=, L/= h &   0!L#)s ?' ""$ L&'; (' .+Q Urc tjxstj} | j} | jr' t j | d| |||||d|d|d|d|} | St|ttfst!d|z|Dcgc]}t#j$|d}}t|ttfst!d |z|Dcgc]}t#j&|d}}|d }t#j(|d}|d }t#j*|d}t-j.d|||||||||| \}}}}|dd} t#j0rjd|j3dd|j5dd|j5dd|j5df}|j6}t#j8d||| | \} | S#t j$r } tj| | Yd} ~ nd} ~ wt j$rYnwxYw t|||||||||| |  S#t j$rYwxYwcc}wcc}w) ayTODO: add doc. Args: input_dataset: A `Tensor` of type `variant`. buffer_size: A `Tensor` of type `int64`. seed: A `Tensor` of type `int64`. seed2: A `Tensor` of type `int64`. seed_generator: A `Tensor` of type `resource`. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. reshuffle_each_iteration: An optional `bool`. Defaults to `True`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. ShuffleDatasetV3rrrrNrMExpected list for 'output_types' argument to 'shuffle_dataset_v3' Op, not %r.NExpected list for 'output_shapes' argument to 'shuffle_dataset_v3' Op, not %r.Tr) rr[rrrrrrrr)rrr r!rr"r#r$r%r&r'!shuffle_dataset_v3_eager_fallbackr)r*r+r,r-r.r/r0rrvr1r2r3rr4r5r6)rr[rrrrrrrrr8r9r:r;r<r=r>r?r@rArBs rCshuffle_dataset_v3rs$    0h..0$ #\\  11  $ {D ~9 ., H >g n L4- 0  +-9 : ;;DPPR($$R8P,P MD%= 1  +-: ; <<GTT8&&r?;T-T%#%//0HJde H   x 4('88-(3$e+9)5*75M%-D:!QX QK' ""$(  !;*Oll?+Zll:& (F ::L L&'; (' .a  & &- ##At,,  # #    . dE>#;#=$D 22  # #   Q Urzraw_ops.ShuffleDatasetV3c t|ttfstd|z|D cgc]} t j | d}} t|ttfstd|z|D cgc]} t j | d}} |d}t j|d}|d}t j|d}tj|tj}tj|tj}tj|tj}tj|tj}tj|tj}|||||g} d|d|d|d|f}t jd d | || | }t j rt j"d | |||\}|Scc} wcc} w) NrrrrTrrrsShuffleDatasetV3rGrHrr)rr[rrrrrrrrrr<r=rBrAr:s rCrrTs L4- 0  +-9 : ;;DPPR($$R8P,P MD%= 1  +-: ; <<GTT8&&r?;T-T%#%//0HJde H   x 4(((H-&&{GMMB+  gmm 4$   6%)).':J:JK.dE>J, &(@,   &   0!L#)s ?' ""$ L&'; (' .7Q Urc Ftjxstj}|j}|jr" t j |d|||d|d|d| }|St|ttfst!d|z|D cgc]} t#j$| d}} t|ttfst!d|z|D cgc]} t#j&| d}} |d }t#j(|d}t+j,d|||||| \} } } }|dd}t#j.rYd| j1dd| j1dd| j1df}| j2}t#j4d||||\}|S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t|||||||S#t j$rYwxYwcc} wcc} w) asCreates a dataset that skips `count` elements from the `input_dataset`. Args: input_dataset: A `Tensor` of type `variant`. count: A `Tensor` of type `int64`. A scalar representing the number of elements from the `input_dataset` that should be skipped. If count is -1, skips everything. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. SkipDatasetrrrNrGExpected list for 'output_types' argument to 'skip_dataset' Op, not %r.HExpected list for 'output_shapes' argument to 'skip_dataset' Op, not %r.rr)rrr r!rr"r#r$r%r&r'skip_dataset_eager_fallbackr)r*r+r,r-r.r/r0rvr1r2r3r4r5r6rs rC skip_datasetr wsA    0h..0$ #\\ 11 mT=%o}j(Lgn L4- 0  %'3 4 55DPPR($$R8P,P MD%= 1  %'4 5 66GTT8&&r?;T-T H   x 4('88]%$0 (t5!QX QK' ""$cll>:Oll?+Zll:&(F::L |VW6 (' .K  & &- ##At,,  # #    ( \%tOO  # #   Q Urzraw_ops.SkipDatasetct|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j |d}}|d}t j|d}tj|tj}tj|tj}||g} d|d|d|f} t jdd| | || } t jrt jd | | | | \} | Scc}wcc}w) Nr rr rrrs SkipDatasetrGrHr rrs rCr r Z L4- 0  %'3 4 55DPPR($$R8P,P MD%= 1  %'4 5 66GTT8&&r?;T-T H   x 4(((H-   6%', L/= h &   ^Q|#)s ?' ""$ |VW6 (' .)Q Ur) #TV_SparseTensorSliceDataset_Tvaluesz_atypes.BFloat16z _atypes.Boolz_atypes.Complex128z_atypes.Complex64z_atypes.Float16z_atypes.Float32z_atypes.Float64z_atypes.Float8e4m3b11fnuzz_atypes.Float8e4m3fnz_atypes.Float8e4m3fnuzz_atypes.Float8e5m2z_atypes.Float8e5m2fnuzz _atypes.Halfz _atypes.Int16z _atypes.Int32z _atypes.Int4z _atypes.Int64z _atypes.Int8z_atypes.QInt16z_atypes.QInt32z _atypes.QInt8z_atypes.QUInt16z_atypes.QUInt8z_atypes.Resourcez_atypes.Stringz_atypes.UInt16z_atypes.UInt32z _atypes.UInt4z_atypes.UInt64z _atypes.UInt8z_atypes.Variantindicesvalues dense_shapectjxstj}|j}|jr t j |d||||}|Stjd||||\}}} } | dd}tj r7d| j#df} | j$} tj&d| | ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t|||||S#t j$rYwxYw)aCreates a dataset that splits a SparseTensor into elements row-wise. Args: indices: A `Tensor` of type `int64`. values: A `Tensor`. dense_shape: A `Tensor` of type `int64`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. SparseTensorSliceDatasetNrb)rrrrTvalues)rrr r!rr"r#r$r%r&r'*sparse_tensor_slice_dataset_eager_fallbackr)r1r2r.r3_get_attr_typer5r6) rrrrr8r9r:r;r>r?r@rArBs rCsparse_tensor_slice_datasetrsJ    0h..0$ #\\ 11 ($Ng n(88"GF0;$H!QX QK' ""$++I6 7F::L "L&'C (' .)  & &- ##At,,  # #    7 6;Tt==  # #   s0CD$C??DDD,,EEz raw_ops.SparseTensorSliceDatasetcxtj|g|g\}\}tj|tj }tj|tj }|||g}d|f}tj dd||||}tjrtjd||||\}|S)NrsSparseTensorSliceDatasetrGrHr) r.args_to_matching_eagerr%rrrrr3r6) rrrrr _attr_TvaluesrBrAr:s rCrrs%<r?r@rArBs rCtf_record_datasetr"st&    0h..0$ #\\ 11 y2BZ+gnH   x 4('88Y,<'2X $ &!QX QK' ""$#,,z2 3F::L <: (' .5  & &- ##At,,  # #    - %{X  # #   0C..D5DD54D59E E! E!zraw_ops.TFRecordDatasetc|d}tj|d}tj|tj }tj|tj }tj|tj }|||g}d|f}tjdd||||}tjrtjd||||\}|S)NrrsTFRecordDatasetrGrHrrb rWrcr[rrrrBrAr:s rCr r M H   x 4($$Y?)++,r?r@rArBs rCtf_record_dataset_v2r+_s{,    0h..0$ #\\ 11 !44D\:x9gnH   x 4('88y.>)4*6"& (!QX QK' ""$#,,z2 3F::L \67< (' .7  & &- ##At,,  # #    0 %{L$D22  # #   s0C00D7DD76D7;E E$#E$zraw_ops.TFRecordDatasetV2c|d}tj|d}tj|tj }tj|tj }tj|tj }tj|tj }||||g}d|f}tjdd||||} tjrtjd||| | \} | S)NrrsTFRecordDatasetV2rGrHr)rb) rWrcr[r'rrrrBrAr:s rCr*r*s H   x 4($$Y?)++,= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. TakeDatasetrrrNrGExpected list for 'output_types' argument to 'take_dataset' Op, not %r.HExpected list for 'output_shapes' argument to 'take_dataset' Op, not %r.rr)rrr r!rr"r#r$r%r&r'take_dataset_eager_fallbackr)r*r+r,r-r.r/r0rvr1r2r3r4r5r6rs rC take_datasetr2sA"    0h..0$ #\\ 11 mT=%o}j(Lgn L4- 0  %'3 4 55DPPR($$R8P,P MD%= 1  %'4 5 66GTT8&&r?;T-T H   x 4('88]%$0 (t5!QX QK' ""$cll>:Oll?+Zll:&(F::L |VW6 (' .K  & &- ##At,,  # #    ( \%tOO  # #   Q Urzraw_ops.TakeDatasetct|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j |d}}|d}t j|d}tj|tj}tj|tj}||g} d|d|d|f} t jdd| | || } t jrt jd | | | | \} | Scc}wcc}w) Nr/rr0rrrs TakeDatasetrGrHr.rrs rCr1r1rrc tjxstj}|j}|jr t j |d||d|d|}|St|ttfst!d|z|Dcgc]}t#j$|d}}|d}t#j&|d}t)j*d||||\} } } } | dd}t#j,rYd | j/d d| j/dd| j/df} | j0} t#j2d| | ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t|||||S#t j$rYiwxYwcc}w) axCreates a dataset that emits `components` as a tuple of tensors once. Args: components: A list of `Tensor` objects. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. TensorDatasetrrNrQJExpected list for 'output_shapes' argument to 'tensor_dataset' Op, not %r.r) componentsrrrrU)rrr r!rr"r#r$r%r&r'tensor_dataset_eager_fallbackr)r*r+r,r-r.r0rvr1r2r3r4r5r6)r7rrrr8r9r:r;r=r>r?r@rArBs rCtensor_datasetr9s    0h..0$ #\\ 11 otZz8-gn MD%= 1  ')6 7 88GTT8&&r?;T-T H   x 4('88Jm"*7!QX QK' ""$s||O= 1`. is_files: An optional `bool`. Defaults to `False`. metadata: An optional `string`. Defaults to `""`. replicate_on_split: An optional `bool`. Defaults to `False`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. TensorSliceDatasetrr;rrN)rr;rrrrPExpected list for 'output_shapes' argument to 'tensor_slice_dataset' Op, not %r.Fr)r7rr;rrrrU)rrr r!rr"r#r$r%r&r'#tensor_slice_dataset_eager_fallbackr)r*r+r,r-r.r0rrvr1r2r3r4rr5r6)r7rr;rrrr8r9r:r;r=r>r?r@rArBs rCtensor_slice_datasetr@]sU    0h..0$ #\\  11 "D*oz8Z02gn MD%= 1  -/< = >>GTT8&&r?;T-T H   * 5( H   x 4())*<>RS'88,9H'/1C#' )!QX QK' ""$s||OrFr;rrrrUsTensorSliceDatasetrGrHr=) r*r+r,r-r.r0rrvrLrr3r6) r7rr;rrrrr=rYrBrAr:s rCr?r?sA MD%= 1  -/< = >>GTT8&&r?;T-T H   * 5( H   x 4())*<>RS$,$K$KJX[$\!zj!, 0/Xz8* ,&   2Al#)s ?' ""$ lFG= (' .+UsDc tjxstj}|j}|jr t j |d||||d|}|S|d}tj|d}tj d|||||\} } } } | dd}tj"r7d| j%df} | j&} tj(d| | ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t||||||S#t j$rYwxYw)adCreates a dataset that emits the lines of one or more text files. Args: filenames: A `Tensor` of type `string`. A scalar or a vector containing the name(s) of the file(s) to be read. compression_type: A `Tensor` of type `string`. A scalar containing either (i) the empty string (no compression), (ii) "ZLIB", or (iii) "GZIP". buffer_size: A `Tensor` of type `int64`. A scalar containing the number of bytes to buffer. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. TextLineDatasetrNr^rr)rrr r!rr"r#r$r%r&r' text_line_dataset_eager_fallbackr)r.rvr1r2r3r4r5r6r!s rCtext_line_datasetrEst$    0h..0$ #\\ 11 y2BZ+gnH   x 4('88Y,<'2X $ &!QX QK' ""$#,,z2 3F::L <: (' .5  & &- ##At,,  # #    - %{X  # #   r#zraw_ops.TextLineDatasetc|d}tj|d}tj|tj }tj|tj }tj|tj }|||g}d|f}tjdd||||}tjrtjd||||\}|S)NrrsTextLineDatasetrGrHrCrbr%s rCrDrDr&rk input_handlec\tjxstj}|j}|jr t j |d||}|Stjd||\}}}}|dd}tj r&d} |j"} tj$d| | ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t|||S#t j$rYwxYw)TODO: add doc. Args: input_handle: A `Tensor` of type `variant`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. UnwrapDatasetVariantNrbrGrrd)rrr r!rr"r#r$r%r&r'%unwrap_dataset_variant_eager_fallbackr)r1r2r.r3r5r6 rGrr8r9r:r;r>r?r@rArBs rCunwrap_dataset_variantrN s)    0h..0$ #\\ 11 $dL:g n(88\F!QX QK' ""$ F::L  fg? (' .'  & &- ##At,,  # #    2 Tt--  # #   rzraw_ops.UnwrapDatasetVariantctj|tj}|g}d}t j dd||||}t j rt jd||||\}|S)NsUnwrapDatasetVariantrGrHrJrrGrrrBrAr:s rCrLrL5sq'' gooF,, &   4a #)s ?' ""$  fg? (' .rksizeshiftstridec Xtjxstj} | j} | jr% t j | d||||||d|d|d|} | St|ttfst!d|z|D cgc]} t#j$| d}} t|ttfst!d|z|Dcgc]}t#j&|d}}|d }t#j(|d}t+j,d||||||||| \}}}}|dd} t#j.rYd|j1dd|j1dd|j1df}|j2}t#j4d||| | \} | S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t||||||||||  S#t j$rYwxYwcc} wcc}w) a/ Combines (nests of) input elements into a dataset of (nests of) windows. A "window" is a finite dataset of flat elements of size `size` (or possibly fewer if there are not enough input elements to fill the window and `drop_remainder` evaluates to false). The `shift` argument determines the number of input elements by which the window moves on each iteration. The first element in the `k`th window will be element ``` 1 + (k-1) * shift ``` of the input dataset. In particular, the first element of the first window will always be the first element of the input dataset. If the `stride` parameter is greater than 1, then each window will skip `(stride - 1)` input elements between each element that appears in the window. Output windows will still contain `size` elements regardless of the value of `stride`. The `stride` argument determines the stride of the input elements, and the `shift` argument determines the shift of the window. For example, letting `{...}` to represent a Dataset: - `tf.data.Dataset.range(7).window(2)` produces `{{0, 1}, {2, 3}, {4, 5}, {6}}` - `tf.data.Dataset.range(7).window(3, 2, 1, True)` produces `{{0, 1, 2}, {2, 3, 4}, {4, 5, 6}}` - `tf.data.Dataset.range(7).window(3, 1, 2, True)` produces `{{0, 2, 4}, {1, 3, 5}, {2, 4, 6}}` Note that when the `window` transformation is applied to a dataset of nested elements, it produces a dataset of nested windows. For example: - `tf.data.Dataset.from_tensor_slices((range(4), range(4))).window(2)` produces `{({0, 1}, {0, 1}), ({2, 3}, {2, 3})}` - `tf.data.Dataset.from_tensor_slices({"a": range(4)}).window(2)` produces `{{"a": {0, 1}}, {"a": {2, 3}}}` Args: input_dataset: A `Tensor` of type `variant`. size: A `Tensor` of type `int64`. An integer scalar, representing the number of elements of the input dataset to combine into a window. Must be positive. shift: A `Tensor` of type `int64`. An integer scalar, representing the number of input elements by which the window moves in each iteration. Defaults to `size`. Must be positive. stride: A `Tensor` of type `int64`. An integer scalar, representing the stride of the input elements in the sliding window. Must be positive. The default value of 1 means "retain every input element". drop_remainder: A `Tensor` of type `bool`. A Boolean scalar, representing whether the last window should be dropped if its size is smaller than `window_size`. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. WindowDatasetrrrNrIExpected list for 'output_types' argument to 'window_dataset' Op, not %r.JExpected list for 'output_shapes' argument to 'window_dataset' Op, not %r.r) rrQrRrSrrrrr)rrr r!rr"r#r$r%r&r'window_dataset_eager_fallbackr)r*r+r,r-r.r/r0rvr1r2r3r4r5r6)rrQrRrSrrrrrr8r9r:r;r<r=r>r?r@rArBs rCwindow_datasetrYBsUJ    0h..0$ #\\  11 ot]D% oz8-gn L4- 0  ')5 6 77DPPR($$R8P,P MD%= 1  ')6 7 88GTT8&&r?;T-T H   x 4('88}4u &~&2'4x" $!QX QK' ""$cll>:Oll?+Zll:&(F::L vw8 (' .Q  & &- ##At,,  # #    * ufn#=$D22  # #   Q Us<#F( H"H'(G/;GG/.G/3HHHzraw_ops.WindowDatasetc t|ttfstd|z|D cgc]} t j | d}} t|ttfstd|z|D cgc]} t j | d}} |d}t j|d}tj|tj}tj|tj}tj|tj}tj|tj}tj|tj}|||||g} d|d|d|f} t jdd| | | | }t jrt j d | | ||\}|Scc} wcc} w) NrVrrWrrrs WindowDatasetrGrHrU)r*r+r,r-r.r/r0rvr%rrrrrrr3r6)rrQrRrSrrrrrrr<r=rBrAr:s rCrXrXs L4- 0  ')5 6 77DPPR($$R8P,P MD%= 1  ')6 7 88GTT8&&r?;T-T H   x 4(((H-  gmm 4$   6%  ! !&'-- 8&)).',,G.ufnE, L/= h &   -q#)s ?' ""$ vw8 (' ./Q Us F90F>c tjxstj}|j}|jr t j |d||d|d|}|St|ttfst!d|z|Dcgc]}t#j$|d}}t|ttfst!d|z|D cgc]} t#j&| d}} t)j*d||||\} } } } | dd}t#j,rYd| j/dd| j/dd | j/d f} | j0}t#j2d|| ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t|||||S#t j$rYwxYwcc}wcc} w) aGTODO: add doc. Args: inputs: A list of `Tensor` objects. output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. WindowOprrNrDExpected list for 'output_types' argument to 'window_op' Op, not %r.EExpected list for 'output_shapes' argument to 'window_op' Op, not %r.)r5rrrTinputs)rrr r!rr"r#r$r%r&r'window_op_eager_fallbackr)r*r+r,r-r.r/r0r1r2r3r4r5r6)r5rrrr8r9r:r;r<r=r>r?r@rArBs rC window_opras    0h..0$ #\\ 11 j$ (gn L4- 0  "$0 1 22DPPR($$R8P,P MD%= 1  "$1 2 33GTT8&&r?;T-T'886 "/d<!QX QK' ""$cll>:Oll?+Yll9%'F::L L&'3 (' .C  & &- ##At,,  # #    % |=  # #   Q Us<FG8 G=G F11G  G GG54G5zraw_ops.WindowOpc$t|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j |d}}t j||\}}t|}d|d|d|f} t jdd|| ||} t jrt jd || | | \} | Scc}wcc}w) Nr]rr^rr_sWindowOprGrHr\) r*r+r,r-r.r/r0rLrr3r6) r5rrrrr<r= _attr_TinputsrBrAr:s rCr`r` s' L4- 0  "$0 1 22DPPR($$R8P,P MD%= 1  "$1 2 33GTT8&&r?;T-T"AA&#N-f, L/= ] &   [!L#)s ?' ""$ L&'3 (' .!Q Us D0D c\tjxstj}|j}|jr t j |d||}|Stjd||\}}}}|dd}tj r&d} |j"} tj$d| | ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t|||S#t j$rYwxYw)rIWrapDatasetVariantNrbrKrd)rrr r!rr"r#r$r%r&r'#wrap_dataset_variant_eager_fallbackr)r1r2r.r3r5r6rMs rCwrap_dataset_variantrg. s)    0h..0$ #\\ 11 "D,8g n(88= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. ZipDatasetrrrNrHExpected list for 'input_datasets' argument to 'zip_dataset' Op, not %r.FExpected list for 'output_types' argument to 'zip_dataset' Op, not %r.GExpected list for 'output_shapes' argument to 'zip_dataset' Op, not %r.r)rirrrrr)rrr r!rr"r#r$r%r&r'zip_dataset_eager_fallbackr)r*r+r,r-rr.r/r0rvr1r2r3r4rr5r6)rirrrrr8r9r:r;rr<r=r>r?r@rArBs rC zip_datasetrpd s~(    0h..0$ #\\ 11 lD..o}j(Lgn NT5M 2  $&4 5 66  ' L4- 0  $&2 3 44DPPR($$R8P,P MD%= 1  $&3 4 55GTT8&&r?;T-T H   x 4('88^#/}'d4!QX QK' ""$cll>:Oll?+S#2C2CC2H#,,z24F::L lFG5 (' .U  & &- ##At,,  # #    ' |%tOO  # #   Q Us<G 7I>I H'3HH'&H'+H<<IIzraw_ops.ZipDatasetct|ttfstd|zt |}t|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|Dcgc]}t j|d}}|d}t j|d}tj|tj}t|} d|d|d|d|f} t jd d | | || } t jrt jd | | | | \} | Scc}wcc}w) Nrlrmrrnrrrrs ZipDatasetrGrHrk)r*r+r,r-rr.r/r0rvr%rrrrr3r6) rirrrrrrr<r=rBrAr:s rCroro s| NT5M 2  $&4 5 66  ' L4- 0  $&2 3 44DPPR($$R8P,P MD%= 1  $&3 4 55GTT8&&r?;T-T H   x 4(++NGOOL.n%, L/=# :x !&   ]Al#)s ?' ""$ lFG5 (' .'Q Us EE#)N)rN)FrN)rFN)FN)TFFrN)rGN)rrrN)rrN)FrgrN)rgrN)TrgFFrN)rTrrN)rFN)TrN)rN)FrFN(D__doc__ collectionstensorflow.pythonrtensorflow.python.eagerrrrr#rr.tensorflow.python.frameworkrrtensorflow.security.fuzzing.pyr_atypesr _op_def_registryr r%r r1"tensorflow.python.util.deprecationr tensorflow.python.utilr _dispatch tensorflow.python.util.tf_exportrtypingrrrtyping_extensionsrResourcerD to_raw_oprr( namedtuplerSrVrMrUr^rZr]rerhr`rfrtrxrlrurr|rrInt64rrrrBoolrrrVariantstrrrrrrrrStringrrrrrrrrrrrrUInt64rrrrrrintrrrrrrrrrr r r rrrrrrr!rr r(r&r'r.r,r-r5r3r4r<r8r;rHrArGrUrQrTr`r]r_rgrerfrprjrorrsrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr rr rInt32rrrr!rr r&r$r%r.r)r-r9r2r8rDr?rCrLrHrKrWrPrVr_r[r^rirdrhrprlrorxrtrwrr~rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr r r rrrrr"rr r+r)r*r2r.r1r9r5r8r@r=r?rErCrDrNrJrLrYrUrXrar\r`rgrerfrprkrordrkrCrs d 67179FK3IC86%%'3)CQXQaQaLaBb3j;I9:>4>>J\;]^QZ[^`g`p`p[pQq*4[33 y 7r?i =>~t~~Nc?de,3YsT[TdTdOdEe3j?i =>~t~~Nc?deT]^acjcscs^sTt*5k44 y 'RAy!?@PfAgh '=k&<&<" y'# @D Qy)OPQ_QUQ_Q_`RA B:<[dehjqjzjzez[{<|"U+S!TUcUYUcUceGVH"IjstwzAzJzJuJkK8'=k&<&<" y'# ))C4F*G)PYZ]_f_l_lZlPm)V Qy)OPQ_QUQ_Q_`RA B 3 CU9V _hilnun{n{i{_| !7 6 6 y! +9S'---?#@+SVX_XeXeSeIf+s|~ACJCOCO~OtP+ZE#CD^T^^TlEmn )C3+?!@>iX[]d]j]jXjNk>TW>jstwy@yHyHtHjI>@1y/0 1NO  #w:N0O]fgjlslylygy]zdgw@ADFMFUFUAUwV8IIc7??.B$CIQZ[^`g`m`m[mQnIAJKNPWP\P\K\A]IJNI_bIu~BDKDSDSSuTIV534^T^^DT5UV9S'//=Q3R`ijmovo|o|j|`}PYZ]_f_k_kZkPlZ^jm}FGJLSL[L[G[}\@C3+?!@CIVY[b[i[iViLjCSVCirsvxxGxGsGiHCJ1y/0 1NO  #w:N0O[dehjqjxjxex[ycfv@CELETET@TvU8>Ic7??.B$C>yY\^e^l^lYlOm>vADFMFVFVAVwW>B>U^_bdkdsds_sUt>@534^T^^DT5UV9S'//=Q3R^ghkmtm{m{h{^|FOPSU\UeUePeFfORbkloqxq@q@l@bA:>ygoo1E'F>YbcfhohwhwcwYx>ad>w@ADFMFUFUAUwV>@=Y;<^T^^L_=`aiW__@T6Uhqruw~xGxGsGiHqtDMNQSZSbSbNbDc8/ygoo1E'F/\_/r{|BIBOBO}OsP/b=Y;<^T^^L_=`a iW__@T6U lo @IJMOVO\O\J\@]  'ygoo1E'F'V_`celeses`sVt'R=Y;<^T^^L_=`a iW__@T6U enort{uCuCpCfD Y[puUZaeCIc7??.B$CCkoCPTCjstwy@yGyGtGjHCJ534^T^^DT5UV9S'//=Q3Rx|X\luvy{B{I{IvIlJ69ygoo1E'F9^a9~B9XabegngugubuXv9v9978H[9\]iW__@T6UnqMQajknpwp~p~k~a(<ygoo1E'F<nq<|E#CD^T^^TmEnoiW__@T6UB6 Ic7+;+;&;< yQTV]VeVeQeGf >534^T^^O5TU9S':J:J5J+KV_`celetet`tVu #w/?/?*? @ 9UXZaZiZiUiKj >;I9:>4>>J];^_yg>N>N9N/OZcdgipixixdxZy) #wGWGWBW8X) enostwox{B{K{KpKfL) W`adfmfufuauWv) TKI&IJ>4>>ZvKwxyQTV]VfVfQfGgt}CDGHJQJZJZZu[fopsu|uDuDpDfE$ 38H8H3H)I T]^acjcrcr^rTs @KI&IJ>4>>ZvKwx  #wGWGWBW8X clmprysBsBnBdC  )C1A1A,A"B YWZ\c\k\kWkMl >?i =>~t~~Nc?de3@P@P;P1Q\efikrkzkzfz\{" )C9I9I4I*J" XabegngvgvbvXw" F?i =>~t~~Nb?cd3HXHXCX9Ygpqtv}wFwFrFhG#YsG4D4D/D%E#J9978HZ9[\ Ic7CSCS>S4T #yg6F6F1F'G#J=Y;<^T^^L`=ab iWEUEU@U6V 6Ic7??>R4S6AJKNPWP_P_K_A`6p Qy)OPQ_QUQ_Q_aARB C9SRYRaRaMaCbPYZ]_f_n_nZnPo0K)C,@"AKFIK\efikrkzkzfz\{KZ3 12>4>>.3QR 3;O1PVYirsvxxGxGsGiH:>Ic7??.B$C>sw>NWX[]d]l]lXlNm>@7)56~t~~FV7WX9S'//=Q3RDHXabegngvgvbvXw6;9S'..5H+I;YbcfhohuhucuYv;GPQTV]VcVcQcGd;t}~ACJCPCP~PtQ;`ijmovo|o|j|`};HK;^ghkmtm|m|h|^};zI9%GHXsItu)CDW:Xhqruw~xExEsEiFV_`celerer`rVsCLMPRYR_R_M_C`oxy|~E~K~KyKoLX[ktuxzAzIzIuIkJ*6iW^^8K.L6\efikrkxkxfx\y6JSTWY`YfYfTfJg6w@ADFMFSFSASwT6clmpryrrmc@6T]^acjcqcq^qTr6}@6S\]`bibqbq]qSr6pMY'KL^T^^\zM{|YsGNNGZ=[ktux{B{H{HvHlIYbcfhohuhucuYvFOPSU\UbUbPbFcr{|AHANAN|NrOclmpryr@r@m@cAMP`ijmovo~o~j~`,HIc7??.B$CH@CHV_`celetet`tVuHT534^T^^DT5UV9S'//=Q3RPSclmpryrArAmAcB8OhkO~GHKMTM\M\H\~]Ob9978HY9Z[x{KTUXZaZiZiUiKj@%ygoo)=>%iX[]d]k]kXkNl%N-Y+ ,^T^^K-H I  iW__8L.M ]fgjlslzlzgz]{ OiW__0D&EOfopsu|vCvCqCgDOT]^acjcpcp^pTqO\_Or{|AHAPAP|PrQOb;I9:>4>>J\;]^YsGOO?S5Tu~@CELERER@RvSclmpryrrmc@loHILNUN]N]I]^<<#<#<ZcdgipiyiydyZz<| )9' ()A BirsvxyIyItIjJ2]_npw{>ygnn9L/M>AJKNPWP`P`K`Aa>@I9%GHXsItuiW^^H[>\JSTWY`YiYiTiJj8`bqsz~9)CN>N9N/O.5Ic7;K;K6K,L5zCDGIPIXIXDXzY5nKI&IJ>4>>ZwKxy9S'JZJZEZ;[IRSVX_XgXgSgIh0:YsG4D4D/D%E:x?i =>~t~~Nd?efIc7CSCS>S4T.%yg>N>N9N/O%_hilnun|n|i|_}%NE#CD^T^^TmEno iWM]M]H]>^ nwx{~E~L~LyLoM <S<S<]fgjlsl|l|g|]}<|-Y+ ,^T^^K-H I CCluvy|C|L|LwLmM2! 9S'//%9:! iPSU\UeUePeFf! D1y/0 1NO )C4H*IU^_bdkdtdt_tUuYygoo)=>YKOYkoYIMY^aYt}~ACJCRCR~RtSYv-Y+ ,^T^^K-H I $iW__8L.M$[_$w{$PT$`c$s|}@BIBQBQ}QsR$NScfSj )9' ( )B Csv:K3+?!@KilK{~KNQKclmpryrArAmAcBKZ1y/0 1NO  #w:N0Oy|KN\_oxy|~E~M~MyMoNBJJJpyz}@G@P@P{PqQJX?i =>~t~~Nc?dess@IJMOVO_O_J_@`<jl{}EI=Ic7>>FY4>>J];^_iW__@T6Unwx{~E~L~LyLoMgpqtv}vDvDqDgE^ghkmtm{m{h{^|HILNUN]N]I]^DC9S'//-A#BCX[CDGCZcdgipixixdxZyCJ534^T^^O5TU)C4>>RiCjk)CDX:YAJKNPWP]P]K]A^WZfiyBCFHOHWHWCWyXBk)C[GclmpryrrmdAGilGDHG^ghkmtm|m|h|^}GR1y/0 1NO  #w}}2D(EYWZ\c\i\iWiMjr{|BIBOBO}OsPy|RVfopsu|uDuDpDfE@S)C,@"AS]aSqtSj3 12>4>>.3QR 3;O1Pmq}@B>)C,@"A>)TWY`YfYfTfJg>PS>fopsu|uDuDpDfE>@3 12>4>>.3QR 3;O1PYbcfhohuhucuYv`cs|}@BIBQBQ}QsR879S'//-A#B7R[\_ahaoao\oRp7^ghkmtm|m|h|^}7r534^T^^O5TU)C4>>J\;]^ ygFVFVAV7W ps DMNQSZSbSbNbDc  G3+?!@GiX[]d]j]jXjNkGt}BDKDQDQQuRGCGGX[Gnwx{}D}L}LxLnMGR1y/0 1NO  #w:N0O]fgjlslylygy]zDMNQSZS`S`N`DaSWcfv@CELETET@TvU@ViW__8L.MV\efikrkxkxfx\yVBKLOQXQ^Q^L^B_Vhqruw~wDwDrDhEVNWX[]d]j]jXjNkVcgVwzVMVWZ\c\k\kWkMlVpG)$EF~t~~VpGqr YsGOOG[=\ ktux{B{H{HvHlI QZ[^`g`m`m[mQn w@ADFMFSFSASwT ]fgjlslylygy]z sw CF V_`celetet`tVu FN3;O1PN_hilnun{n{i{_|NENORT[TaTaOaEbNktuxzAzGzGuGkHNQZ[^`g`m`m[mQnN@IJMOVO_O_J_@`NX\NloNBKLOQXQ`Q`L`BaN`KI&IJ>4>>ZwKxy" #wJ^@_"nwx{~E~K~KyKoL"T]^acjcpcp^pTq"zCDGIPIVIVDVzW"`ijmovo|o|j|`}"OXY\^e^n^nYnOo"hl"x{"KTUXZaZiZiUiKj"JU9S'//-A#BUQZ[^`g`m`m[mQnUvADFMFSFSASwTU]fgjlslylygy]zUrvUFIU\efikrkzkzfz\{Un534^T^^O5TU)C ?= RUW^WdWdRdHe=NQ=dmnqszsBsBnBdC=~/i-.~t~~l/KL ygoo9M/NW`adfmfsfsasWt^aqz{~@G@O@O{OqP8'.'j #'3 3E)F'PYZ]`C[CQD'S\]`bibobo]oSp'@IJMOVO^O^J^@_'RI9%GHXsItu  #w}}BT8U _hiloRjR`S bkloqxq~q~l~b OXY\^e^m^mYmOn  53+>!?5S\]`bibpbp]pSq5AJKNPWP]P]K]A^5il5HILNUN]N]I]^5n7)56~t~~FW7XY #w~~:M0NbkloqxqqlcAPYZ]_f_l_lZlPmy|LUVY[b[j[jVjLk$9Ic7>>.A$B9V_`celeses`sVt9DMNQSZS`S`N`Da9qz{~@G@M@M{MqN9Y\9oxy|~E~M~MyMoN9v;I9:>4>>J^;_`9S'..=P3Qenort{uCuCpCfDS\]`bibobo]oSp@IJMOVO\O\J\@]il|EFIKRKZKZFZ|[&> #w*> ?> RUW^WdWdRdHe>NQ>dmnqszsBsBnBdC>@/i-.~t~~l/KL ygoo9M/NW`adfmfsfsasWt^aqz{~@G@O@O{OqP83s3YWZ\c\k\kWkMl3j3 12>4>>.3QR sZcdgipixixdxZy,BTBRUBmqBHQRUW^WfWfRfHgBH=Y;<^T^^L`=abT]`vzKTUXZaZiZiUiKj:43+>!?4S\]`bibpbp]pSq4AJKNPWP]P]K]A^4il4HILNUN]N]I]^4l7)56~t~~FW7XY #w~~:M0NbkloqxqqlcAPYZ]_f_l_lZlPmy|LUVY[b[j[jVjLk$$33G)H$XabegngvgvbvXw$LAy!?@PfAgh  #wBV8W gpqtv}wFwFrFhG v)C,@"AvSVX_XeXeSeIfvoxy|FLLzLpMvW`adfmfsfsasWtvFOPSU\UaUaPaFbvJMv`ijmovo~o~j~`vp3 12>4>>.3QR 3;O1PXabegngtgtbtXuHILNUN[N[I[\fopsu|uBuBpBfCU^_bdkdpdp_pUqZ]mvwz|C|K|KwKmL>53PWP_P_K_A`5n )9' ( )B CPYZ]_f_n_nZnPo0$ygoo1E'F$V_`celetet`tVu$L=Y;<^T^^L`=ab iW__@T6U enort{uDuDpDfE F $s)W__*D EFmpFDMNQSZSbSbNbDcFP-Y+ ,^T^^K-H I ycGOO9S/T~AQZ[^`g`o`o[oQprk