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dӐdԄZd5dDej!ejDdej!ej;d5ej!ej;d6ej!ej;dej!ej"deIdFeEdej!ejDfdՐdքZed׃e$eZdDej!ejDdej!ej;d5ej!ej;d6ej!ej;dej!ej"deIdFeEdej!ejDfdؐdلZd'dDej!ejDdej!ej;dFeEdej!ejDfdڐdۄZed܃e$eZdDej!ejDdej!ej;dFeEdej!ejDfdݐdބZedejej@ejejejejejejej ejej;ej!ej"ej#ej$ej%ej&ej"ejMej'ej(ej)ej*ejDZ+d&dej!ej;dej!e+dej!ej;dej!ejDfddZ,ede$e,Z-dej!ej;dej!e+dej!ej;dej!ejDfddZ.d'dej!ejMdej!ejMdej!ej;dFeEdej!ejDf ddZ/ede$e/Z0dej!ejMdej!ejMdej!ej;dFeEdej!ejDf ddZ1d'dej!ejMdej!ejMdej!ej;dej!ej;dFeEdej!ejDf ddZ2ede$e2Z3dej!ejMdej!ejMdej!ej;dej!ej;dFeEdej!ejDf ddZ4d'dDej!ejDdej!ej;dFeEdej!ejDfddZ5ede$e5Z6dDej!ejDdej!ej;dFeEdej!ejDfddZ7d'dFeEdej!ejDfddZ8ede$e8Z9dFeEdej!ejDfddZ:d7deIdFeEdeIdej!ejDfddZ;ede$e;Z<deIdFeEdeIdej!ejDfddZ=d'dej!ejMdej!ejMdej!ej;dFeEdej!ejDf ddZ>ede$e>Z?dej!ejMdej!ejMdej!ej;dFeEdej!ejDf ddZ@d&dej!ejDdej!ejDfd d ZAed e$eAZBdej!ejDdej!ejDfd d ZCd'dDej!ejDdej!ej;dej!ej;dej!ej;dMej!ej@dFeEdej!ejDfddZDede$eDZEdDej!ejDdej!ej;dej!ej;dej!ej;dMej!ej@dFeEdej!ejDfddZFd&dej!ejDfddZGede$eGZHdej!ejDfddZId&dej!ejDdej!ejDfddZJede$eJZKdej!ejDdej!ejDfddZLd'd e ej!ejDdFeEdej!ejDfd!d"ZMed#e$eMZNd e ej!ejDdFeEdej!ejDfd$d%ZOdS(8zUPython 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)TypeVarListreturnc CZtjpt}|j}|jrRzt|d|d|d|}|WStjy4}z t ||WYd}~nd}~wtj y=Ynwz t ||||dWStj yQYnwt |ttfs_td|dd|D}t |ttfsstd |d d|D}tjd|||d \}}}} | dd}trd|dd|df} |j} td| | ||\}|S) 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.cSg|]}t|dqSr_executeZ make_type.0Z_tr f/home/www/facesmatcher.com/pyenv/lib/python3.10/site-packages/tensorflow/python/ops/gen_dataset_ops.py :z&anonymous_iterator..NExpected list for 'output_shapes' argument to 'anonymous_iterator' Op, not %r.cSrrrZ make_shaperZ_sr r r!r"?r#rrr)_contextr_thread_local_datais_eagerrTFE_Py_FastPathExecute_core_NotOkStatusException_opsraise_from_not_ok_status_FallbackException!anonymous_iterator_eager_fallback_SymbolicException isinstancelisttuple TypeError_op_def_library_apply_op_helperrmust_record_gradientget_attrinputsrecord_gradient rrr_ctxtld_resulte__op_outputs_attrs _inputs_flatr r r!anonymous_iteratorh    rHzraw_ops.AnonymousIteratorcCt|ttfs td|dd|D}t|ttfs!td|dd|D}g}d|d|f}tjdd ||||d }trGtd ||||\}|S) NrcSrrrrr r r!r"Ur#z5anonymous_iterator_eager_fallback..r$cSrr%r&r'r r r!r"Zr#rrsAnonymousIteratorr<attrsrrrr4r5r6r7rrr:r=rrrrrGrFrAr r r!r2P2  r2AnonymousIteratorV2handledeleterc Cshtjpt}|j}|jrWzt|d|d|d|}t|}|WStj y9}z t ||WYd}~nd}~wtj yBYnwz t ||||dWStjyVYnwt|ttfsdtd|dd|D}t|ttfsxtd |d d|D}tjd|||d \}}}} | dd}trd|dd|df} |j} td| | |t|}|S) aA container for an iterator resource. Args: output_types: A list of `tf.DTypes` that has length `>= 1`. output_shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`) that has length `>= 1`. name: A name for the operation (optional). Returns: A tuple of `Tensor` objects (handle, deleter). handle: A `Tensor` of type `resource`. deleter: A `Tensor` of type `variant`. rQrrNrPExpected list for 'output_types' argument to 'anonymous_iterator_v2' Op, not %r.cSrrrrr r r!r"r#z)anonymous_iterator_v2..QExpected list for 'output_shapes' argument to 'anonymous_iterator_v2' Op, not %r.cSrr%r&r'r r r!r"r#r()r)rr*r+rr,_AnonymousIteratorV2Output_maker-r.r/r0r1$anonymous_iterator_v2_eager_fallbackr3r4r5r6r7r8r9rr:r;r<r=r>r r r!anonymous_iterator_v2jsj     rYzraw_ops.AnonymousIteratorV2cCst|ttfs td|dd|D}t|ttfs!td|dd|D}g}d|d|f}tjdd ||||d }trGtd |||t |}|S) NrTcSrrrrr r r!r"r#z8anonymous_iterator_v2_eager_fallback..rUcSrr%r&r'r r r!r"r#rrsAnonymousIteratorV2rLrQ) r4r5r6r7rrr:r=rVrWrOr r r!rXs2   rXc Cr) rAnonymousIteratorV3rrNrPExpected list for 'output_types' argument to 'anonymous_iterator_v3' Op, not %r.cSrrrrr r r!r"r#z)anonymous_iterator_v3..QExpected list for 'output_shapes' argument to 'anonymous_iterator_v3' Op, not %r.cSrr%r&r'r r r!r"r#r()r)rr*r+rr,r-r.r/r0r1$anonymous_iterator_v3_eager_fallbackr3r4r5r6r7r8r9rr:r;r<r=r>r r r!anonymous_iterator_v3rIr_zraw_ops.AnonymousIteratorV3cCrJ) Nr\cSrrrrr r r!r"r#z8anonymous_iterator_v3_eager_fallback..r]cSrr%r&r'r r r!r"r#rrsAnonymousIteratorV3rKrLr[rNrOr r r!r^rPr^AnonymousMemoryCachec Cstjpt}|j}|jrQzt|d|}t|}|WStj y5}z t ||WYd}~nd}~wtj y>Ynwzt ||dWStjyPYnwtjd|d\}}}}|dd}trsd}|j} td| ||t|}|S)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`Nrrrr )r)rr*r+rr,_AnonymousMemoryCacheOutputrWr-r.r/r0r1%anonymous_memory_cache_eager_fallbackr3r8r9rr:r<r= rr?r@rArBrCrDrErFrGr r r!anonymous_memory_cachesD    rfzraw_ops.AnonymousMemoryCachecCsDg}d}tjdd||||d}trtd|||t|}|S)NsAnonymousMemoryCacherZrLr`)rrr:r=rcrWrrrGrFrAr r r!rd:s  rdAnonymousMultiDeviceIteratorc Cstjpt}|j}|jrZzt|d|d|d|d| }t|}|WStj y;}z t ||WYd}~nd}~wtj yDYnwz t |||||dWStjyYYnwt|ttfsgtd|dd |D}t|ttfs{td |d d |D}t|ttfstd |d d |D}tjd||||d\}}} } | dd}trd| dd| dd| df} | j} td| | |t|}|S)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`. rhdevicesrrNrirrrrUExpected list for 'devices' argument to 'anonymous_multi_device_iterator' Op, not %r.cSrrirmake_strr'r r r!r"qr#z3anonymous_multi_device_iterator..ZExpected list for 'output_types' argument to 'anonymous_multi_device_iterator' Op, not %r.cSrrrrr r r!r"vr#[Expected list for 'output_shapes' argument to 'anonymous_multi_device_iterator' Op, not %r.cSrr%r&r'r r r!r"{r#rirrr)r)rr*r+rr,#_AnonymousMultiDeviceIteratorOutputrWr-r.r/r0r1.anonymous_multi_device_iterator_eager_fallbackr3r4r5r6r7r8r9rr:r;r<r= rirrrr?r@rArBrCrDrErFrGr r r!anonymous_multi_device_iteratorJs~      ruz$raw_ops.AnonymousMultiDeviceIteratorcCst|ttfs td|dd|D}t|ttfs!td|dd|D}t|ttfs5td|dd|D}g}d|d |d |f}tjd d ||||d }tr]td|||t |}|S)NrkcSrrlrmr'r r r!r"r#zBanonymous_multi_device_iterator_eager_fallback..rocSrrrrr r r!r"r#rpcSrr%r&r'r r r!r"r#rirrsAnonymousMultiDeviceIteratorrZrLrh) r4r5r6r7rrr:r=rrrWrirrrrrGrFrAr r r!rssF  rsc Cstjpt}|j}|jrUzt|d|d|d|d| }|WStjy6}z t ||WYd}~nd}~wtj y?Ynwz t |||||dWStj yTYnwt |ttfsbtd|dd |D}t |ttfsvtd |d d |D}t |ttfstd |d d |D}tjd||||d\}}} } | dd}trd| dd| dd| df} | j} td| | ||\}|S)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`. AnonymousMultiDeviceIteratorV3rirrNrjXExpected list for 'devices' argument to 'anonymous_multi_device_iterator_v3' Op, not %r.cSrrlrmr'r r r!r"r#z6anonymous_multi_device_iterator_v3..]Expected list for 'output_types' argument to 'anonymous_multi_device_iterator_v3' Op, not %r.cSrrrrr r r!r"r#^Expected list for 'output_shapes' argument to 'anonymous_multi_device_iterator_v3' Op, not %r.cSrr%r&r'r r r!r"r#rq)r)rr*r+rr,r-r.r/r0r11anonymous_multi_device_iterator_v3_eager_fallbackr3r4r5r6r7r8r9rr:r;r<r=rtr r r!"anonymous_multi_device_iterator_v3s|     r|z&raw_ops.AnonymousMultiDeviceIteratorV3cCst|ttfs td|dd|D}t|ttfs!td|dd|D}t|ttfs5td|dd|D}g}d|d |d |f}tjd d ||||d }tr]td||||\}|S)NrxcSrrlrmr'r r r!r"r#zEanonymous_multi_device_iterator_v3_eager_fallback..rycSrrrrr r r!r"r#rzcSrr%r&r'r r r!r"r#rirrsAnonymousMultiDeviceIteratorV3rKrLrwrNrvr r r!r{sF r{AnonymousRandomSeedGeneratorseedseed2c Cstjpt}|j}|jrUzt|d|||}t|}|WStj y7}z t ||WYd}~nd}~wtj y@Ynwz t ||||dWStjyTYnwtjd|||d\}}}} | dd}tryd} |j} td| | |t|}|S)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`. r}Nra)r~rrr )r)rr*r+rr,#_AnonymousRandomSeedGeneratorOutputrWr-r.r/r0r1.anonymous_random_seed_generator_eager_fallbackr3r8r9rr:r<r=) r~rrr?r@rArBrCrDrErFrGr r r!anonymous_random_seed_generatorsD    rz$raw_ops.AnonymousRandomSeedGeneratorcCsdt|tj}t|tj}||g}d}tjdd||||d}tr+td|||t |}|S)NsAnonymousRandomSeedGeneratorrZrLr}) r/convert_to_tensor_dtypesint64rrr:r=rrW)r~rrrrGrFrAr r r!r<s rAnonymousSeedGenerator reshufflec Cstjpt}|j}|jrWzt|d||||}t|}|WStj y8}z t ||WYd}~nd}~wtj yAYnwz t |||||dWStjyVYnwtjd||||d\}}} } | dd}tr|d} | j} td| | |t|}|S)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`. rNra)r~rrrr )r)rr*r+rr,_AnonymousSeedGeneratorOutputrWr-r.r/r0r1'anonymous_seed_generator_eager_fallbackr3r8r9rr:r<r=) r~rrrr?r@rArBrCrDrErFrGr r r!anonymous_seed_generatorOsF     rzraw_ops.AnonymousSeedGeneratorcCstt|tj}t|tj}t|tj}|||g}d}tjdd||||d}tr3td|||t |}|S)NsAnonymousSeedGeneratorrZrLr) r/rrrboolrrr:r=rrW)r~rrrrrGrFrAr r r!rs  r input_dataset batch_sizemetadatac Ctjpt}|j}|jrYzt|d|||d|d|d| }|WStjy8} z t | |WYd} ~ nd} ~ wtj yAYnwz t |||||||dWStj yXYnwt |ttfsftd|dd |D}t |ttfsztd |d d |D}|durd }t|d}tjd||||||d \} } } } | dd}trd| dd| dd| df} | j}td|| ||\}|S)aACreates 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. 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`. BatchDatasetrrrNrrrrrHExpected list for 'output_types' argument to 'batch_dataset' Op, not %r.cSrrrrr r r!r"r#z!batch_dataset..IExpected list for 'output_shapes' argument to 'batch_dataset' Op, not %r.cSrr%r&r'r r r!r"r#r)rrrrrr)r)rr*r+rr,r-r.r/r0r1batch_dataset_eager_fallbackr3r4r5r6r7rrnr8r9r:r;r<r=)rrrrrrr?r@rArBrCrDrErFrGr r r! batch_datasett      rzraw_ops.BatchDatasetc Ct|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}t|tj }t|tj }||g}d|d |d|f}tj d d ||||d } t ret d ||| | \} | S)NrcSrrrrr r r!r"r#z0batch_dataset_eager_fallback..rcSrr%r&r'r r r!r"r#rrrrs BatchDatasetrKrLrr4r5r6r7rrnr/rrvariantrrr:r=) rrrrrrrrGrFrAr r r!r@  rFdrop_remainder parallel_copycCtjpt}|j} | jr^zt|d||||d|d|d|d|} | WStjy;} z t | |WYd} ~ nd} ~ wtj yDYnwzt |||||||||d WStj y]Ynwt |ttfsktd|d d |D}t |ttfstd |d d |D}|durd }t|d}|durd}t|d}tjd||||||||d \} } } }|dd} trd| dd| dd| dd| df}| j}td||| | \} | S)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.cSrrrrr r r!r"r#z$batch_dataset_v2..LExpected list for 'output_shapes' argument to 'batch_dataset_v2' Op, not %r.cSrr%r&r'r r r!r"r#Fr)rrrrrrrr)r)rr*r+rr,r-r.r/r0r1batch_dataset_v2_eager_fallbackr3r4r5r6r7r make_boolrnr8r9r:_get_attr_boolr;r<r=)rrrrrrrrr?r@rArBrCrDrErFrGr r r!batch_dataset_v2s        rzraw_ops.BatchDatasetV2c Cst|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}|dur:d}t|d }t|t j }t|t j }t|t j }|||g} d|d |d |d |f} tj d d | | ||d} tr{td| | | | \} | S)NrcSrrrrr r r!r"Ar#z3batch_dataset_v2_eager_fallback..rcSrr%r&r'r r r!r"Fr#FrrrrrsBatchDatasetV2rKrLrr4r5r6r7rrrnr/rrrrrrr:r=) rrrrrrrrrrGrFrAr r r!r<H    rfilenamec Cr)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.cSrrrrr r r!r"r#z!cache_dataset..IExpected list for 'output_shapes' argument to 'cache_dataset' Op, not %r.cSrr%r&r'r r r!r"r#r)rrrrrr)r)rr*r+rr,r-r.r/r0r1cache_dataset_eager_fallbackr3r4r5r6r7rrnr8r9r:r;r<r=)rrrrrrr?r@rArBrCrDrErFrGr r r! cache_dataset\st      rzraw_ops.CacheDatasetc Cr)NrcSrrrrr r r!r"r#z0cache_dataset_eager_fallback..rcSrr%r&r'r r r!r"r#rrrrs CacheDatasetrKrLr)r4r5r6r7rrnr/rrrstringrr:r=) rrrrrrrrGrFrAr r r!rrrcachecCtjpt}|j}|jr[zt|d||||d|d|d| } | WStjy9} z t | |WYd} ~ nd} ~ wtj yBYnwz t ||||||||dWStj yZYnwt |ttfshtd|dd |D}t |ttfs|td |d d |D}|durd }t|d}tjd|||||||d \} } } } | dd} trd| dd| dd| df}| j}td||| | \} | S)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.cSrrrrr r r!r"r#z$cache_dataset_v2..LExpected list for 'output_shapes' argument to 'cache_dataset_v2' Op, not %r.cSrr%r&r'r r r!r"r#r)rrrrrrr)r)rr*r+rr,r-r.r/r0r1cache_dataset_v2_eager_fallbackr3r4r5r6r7rrnr8r9r:r;r<r=)rrrrrrrr?r@rArBrCrDrErFrGr r r!cache_dataset_v2sv     rzraw_ops.CacheDatasetV2c Ct|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}t|tj }t|tj }t|tj }|||g}d|d |d|f} tj d d || ||d } t rmtd || | | \} | S)NrcSrrrrr r r!r"r#z3cache_dataset_v2_eager_fallback..rcSrr%r&r'r r r!r" r#rrrrsCacheDatasetV2rKrLr)r4r5r6r7rrnr/rrrrresourcerr:r=) rrrrrrrrrGrFrAr r r!rB   ranother_datasetc Cr)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.cSrrrrr r r!r"Fr#z'concatenate_dataset..OExpected list for 'output_shapes' argument to 'concatenate_dataset' Op, not %r.cSrr%r&r'r r r!r"Kr#r)rrrrrr)r)rr*r+rr,r-r.r/r0r1"concatenate_dataset_eager_fallbackr3r4r5r6r7rrnr8r9r:r;r<r=)rrrrrrr?r@rArBrCrDrErFrGr r r!concatenate_dataset sx     rzraw_ops.ConcatenateDatasetc Cst|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}t|tj }t|tj }||g}d|d |d|f}tj d d ||||d } t ret d ||| | \} | S)NrcSrrrrr r r!r"hr#z6concatenate_dataset_eager_fallback..rcSrr%r&r'r r r!r"mr#rrrrsConcatenateDatasetrKrLr) r4r5r6r7rrnr/rrrrr:r=) rrrrrrrrGrFrAr r r!rcrrcardinality_optionsc Ctjpt}|j}|jrQz t|d||d|}|WStjy3}z t ||WYd}~nd}~wtj y<Ynwz t ||||dWStj yPYnw|durWd}t |d}tjd|||d\}}}} | dd}t rd|df} |j} t d| | ||\}|S)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)r)rr*r+rr,r-r.r/r0r1"dataset_cardinality_eager_fallbackr3rrnr8r9r:r;r<r=) rrrr?r@rArBrCrDrErFrGr r r!dataset_cardinalitysP  rzraw_ops.DatasetCardinalitycCl|durd}t|d}t|tj}|g}d|f}tjdd||||d}tr1td||||\}|S)NrrsDatasetCardinalityrKrLr) rrnr/rrrrr:r=)rrrrrGrFrAr r r!r  rallow_statefulstrip_device_assignmentc Cstjpt}|j}|jrWzt|d||d|d|d| }|WStjy7}z t ||WYd}~nd}~wtj y@Ynwz t ||||||dWStj yVYnw|dur]g}t |ttfsjtd|dd |D}|durwd }t|d}|durd }t|d}tjd|||||d \} } } } | dd}trd| dd| dd| df} | j} td| | ||\}|S) 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.cSrrrmr'r r r!r"r#z$dataset_to_graph..F)rrrrr)r)rr*r+rr,r-r.r/r0r1dataset_to_graph_eager_fallbackr3r4r5r6r7rrr8r9r:r;rr<r=)rrrrrr?r@rArBrCrDrErFrGr r r!dataset_to_graphsz      rzraw_ops.DatasetToGraphc Cs|durg}t|ttfstd|dd|D}|dur d}t|d}|dur,d}t|d}t|tj }|g}d|d|d|f}tj dd ||||d }t r[t d ||||\}|S) NrcSrrrmr'r r r!r"r#z3dataset_to_graph_eager_fallback..FrrrsDatasetToGraphrKrLr r4r5r6r7rrr/rrrrr:r=) rrrrrrrGrFrAr r r!r s:   rexternal_state_policyc Cs@tjpt}|j}|jrTzt|d||d|d|}|WStjy5}z t ||WYd}~nd}~wtj y>Ynwz t |||||dWStj ySYnw|durZd}t |d}|durfd}t |d}tjd||||d\}}} } | dd}t rd| dd| df} | j} t d| | ||\}|S) 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)r)rr*r+rr,r-r.r/r0r1"dataset_to_graph_v2_eager_fallbackr3rmake_intrr8r9r: _get_attr_intrr<r=) rrrrr?r@rArBrCrDrErFrGr r r!dataset_to_graph_v2&sd   rzraw_ops.DatasetToGraphV2cCs|durd}t|d}|durd}t|d}t|tj}|g}d|d|f}tjdd||||d}tr?t d||||\}|S) NrrFrsDatasetToGraphV2rKrLr) rrrr/rrrrr:r=)rrrrrrGrFrAr r r!rds(   rdatasetc Cstjpt}|j}|jrWzt|d||d|d|d| }|WStjy7}z t ||WYd}~nd}~wtj y@Ynwz t ||||||dWStj yVYnwt |ttfsdtd|dd |D}t |ttfsxtd |d d |D}|durd }t|d}tjd|||||d \} } } } | dd}|s| Strd| dd| dd| df} | j} td| | ||S)aOutputs the single element from the given dataset. Args: dataset: A `Tensor` of type `variant`. A handle to a dataset that contains a single element. 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 list of `Tensor` objects of type `output_types`. DatasetToSingleElementrrrNrTExpected list for 'output_types' argument to 'dataset_to_single_element' Op, not %r.cSrrrrr r r!r"r#z-dataset_to_single_element..UExpected list for 'output_shapes' argument to 'dataset_to_single_element' Op, not %r.cSrr%r&r'r r r!r"r#r)rrrrr)r)rr*r+rr,r-r.r/r0r1(dataset_to_single_element_eager_fallbackr3r4r5r6r7rrnr8r9r:r;r<r=)rrrrrr?r@rArBrCrDrErFrGr r r!dataset_to_single_elementxst      rzraw_ops.DatasetToSingleElementc Cst|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}t|tj }|g}d|d |d|f}tj d t |||||d }t r_t d ||||S) NrcSrrrrr r r!r"r#z.rcSrr%r&r'r r r!r"r#rrrrsDatasetToSingleElementrLr)r4r5r6r7rrnr/rrrrlenr:r=) rrrrrrrGrFrAr r r!rs>  rc Ctjpt}|j}|jrPz t|d|||}|WStjy2}z t ||WYd}~nd}~wtj y;Ynwz t ||||dWStj yOYnwt jd|||d\}}}} |S)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. DeleteIteratorNrarRrSr)r)rr*r+rr,r-r.r/r0r1delete_iterator_eager_fallbackr3r8r9 rRrSrr?r@rArBrCrDrEr r r!delete_iterator2  rzraw_ops.DeleteIteratorcCFt|tj}t|tj}||g}d}tjdd||||d}d}|S)NsDeleteIteratorrrLr/rrrrrrrRrSrrrGrFrAr r r!r rc Cr)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. DeleteMemoryCacheNrar)r)rr*r+rr,r-r.r/r0r1"delete_memory_cache_eager_fallbackr3r8r9rr r r!delete_memory_cacherrzraw_ops.DeleteMemoryCachecCr)NsDeleteMemoryCacherrLrrr r r!r#rrmulti_device_iterator iteratorsc Cstjpt}|j}|jrRz t|d||||}|WStjy3}z t ||WYd}~nd}~wtj y<Ynwz t |||||dWStj yQYnwt |ttfs_td|t|}tjd||||d\} } } } | S)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. DeleteMultiDeviceIteratorNraTExpected list for 'iterators' argument to 'delete_multi_device_iterator' Op, not %r.)rrrSr)r)rr*r+rr,r-r.r/r0r1+delete_multi_device_iterator_eager_fallbackr3r4r5r6r7rr8r9) rrrSrr?r@rArB_attr_NrCrDrEr r r!delete_multi_device_iterator.sF rz!raw_ops.DeleteMultiDeviceIteratorc Cst|ttfs td|t|}t|tj}t |tj}t|tj }|gt||g}d|f}t j dd||||d}d}|S)NrNsDeleteMultiDeviceIteratorrrL) r4r5r6r7rr/rrrconvert_n_to_tensorrrr) rrrSrrrrGrFrAr r r!r[s$rc Cr)rDeleteRandomSeedGeneratorNrar)r)rr*r+rr,r-r.r/r0r1+delete_random_seed_generator_eager_fallbackr3r8r9rr r r!delete_random_seed_generatorms4  rz!raw_ops.DeleteRandomSeedGeneratorcCr)NsDeleteRandomSeedGeneratorrrLrrr r r!rsrc Cr)rDeleteSeedGeneratorNrar)r)rr*r+rr,r-r.r/r0r1$delete_seed_generator_eager_fallbackr3r8r9rr r r!delete_seed_generatorrrzraw_ops.DeleteSeedGeneratorcCr)NsDeleteSeedGeneratorrrLrrr r r!rrrresource_handle serializedc Cr)aConverts the given variant tensor to an iterator and stores it in the given resource. Args: resource_handle: A `Tensor` of type `resource`. A handle to an iterator resource. serialized: A `Tensor` of type `variant`. A variant tensor storing the state of the iterator contained in the resource. name: A name for the operation (optional). Returns: The created Operation. DeserializeIteratorNra)rrr)r)rr*r+rr,r-r.r/r0r1#deserialize_iterator_eager_fallbackr3r8r9) rrrr?r@rArBrCrDrEr r r!deserialize_iterators4 rzraw_ops.DeserializeIteratorcCr)NsDeserializeIteratorrrLr)rrrrrGrFrAr r r!rrrc Ctjpt}|j}|jrLz t|d|}|WStjy0}z t ||WYd}~nd}~wtj y9Ynwzt ||dWStj yKYnwt jd|d\}}}}|dd}trnd}|j} td| |||\}|S)xTODO: add doc. Args: name: A name for the operation (optional). Returns: A `Tensor` of type `resource`. DummyMemoryCacheNrarbr )r)rr*r+rr,r-r.r/r0r1!dummy_memory_cache_eager_fallbackr3r8r9rr:r<r=rer r r!dummy_memory_cacheB  rzraw_ops.DummyMemoryCachecC@g}d}tjdd||||d}trtd||||\}|S)NsDummyMemoryCacherKrLrrrr:r=rgr r r!r" rc Cr)rDummySeedGeneratorNrarbr )r)rr*r+rr,r-r.r/r0r1#dummy_seed_generator_eager_fallbackr3r8r9rr:r<r=rer r r!dummy_seed_generator.rr zraw_ops.DummySeedGeneratorcCr)NsDummySeedGeneratorrKrLrrrgr r r!r Vrr c C`tjpt}|j}|jrTzt|d||d|d|}|WStjy5}z t ||WYd}~nd}~wtj y>Ynwz t |||||dWStj ySYnwt |ttfsatd|dd|D}t |ttfsutd |d d|D}tjd||||d \}}} } | dd}trd| dd| df} | j} td| | ||\}|S) aCreates a dataset containing elements of first component of `input_dataset` having true in the last component. Args: input_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`. 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.cSrrrrr r r!r"r#z4filter_by_last_component_dataset..\Expected list for 'output_shapes' argument to 'filter_by_last_component_dataset' Op, not %r.cSrr%r&r'r r r!r"r#)rrrr)r)rr*r+rr,r-r.r/r0r1/filter_by_last_component_dataset_eager_fallbackr3r4r5r6r7r8r9rr:r;r<r=) rrrrr?r@rArBrCrDrErFrGr r r! filter_by_last_component_datasetbsl   rz$raw_ops.FilterByLastComponentDatasetcCt|ttfs td|dd|D}t|ttfs!td|dd|D}t|tj}|g}d|d|f}tj dd ||||d }t rOt d ||||\}|S) Nr cSrrrrr r r!r"r#zCfilter_by_last_component_dataset_eager_fallback..rcSrr%r&r'r r r!r"r#rrsFilterByLastComponentDatasetrKrLr ) r4r5r6r7r/rrrrrr:r=)rrrrrrGrFrAr r r!r6 rcCtjpt}|j}|jr\zt|d|||d|d|d|d| } | WStjy:} z t | |WYd} ~ nd} ~ wtj yCYnwz t ||||||||dWStj y[Ynwt |ttfsitd|d d |D}t |ttfs}td |d d |D}|durd }t|d}tjd|||||||d\} } } } | dd} trd| dd| dd| dd| dd| df }| j}td||| | \} | S)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`. 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`. 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`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. FilterDataset predicaterrrN)rrrrrrIExpected list for 'output_types' argument to 'filter_dataset' Op, not %r.cSrrrrr r r!r"r#z"filter_dataset..JExpected list for 'output_shapes' argument to 'filter_dataset' Op, not %r.cSrr%r&r'r r r!r"r#r)rother_argumentsrrrrr Targuments)r)rr*r+rr,r-r.r/r0r1filter_dataset_eager_fallbackr3r4r5r6r7rrnr8r9r:r;r<r=)rrrrrrrr?r@rArBrCrDrErFrGr r r!filter_datasets~        rzraw_ops.FilterDatasetc Ct|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}t||\}}t|t j }|gt|} d|d |d |d |d|f } tj d d | | ||d} t rmt d| | | | \} | S)NrcSrrrrr r r!r" r#z1filter_dataset_eager_fallback..rcSrr%r&r'r r r!r"r#rrrrrrs FilterDatasetrKrLrr4r5r6r7rrnconvert_to_mixed_eager_tensorsr/rrrrr:r=) rrrrrrrr_attr_TargumentsrGrFrAr r r!rsB   rhas_captured_refc Cstjpt}|j}|jrWzt|d||d|d|d| }|WStjy7}z t ||WYd}~nd}~wtj y@Ynwz t ||||||dWStj yVYnwt |ttfsdtd|dd |D}t |ttfsxtd |d d |D}|durd }t|d}tjd|||||d \} } } } | dd}trd| dd| dd| df} | j} td| | ||\}|S)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`. FinalizeDatasetr rrN)r rrrrKExpected list for 'output_types' argument to 'finalize_dataset' Op, not %r.cSrrrrr r r!r"Ir#z$finalize_dataset..LExpected list for 'output_shapes' argument to 'finalize_dataset' Op, not %r.cSrr%r&r'r r r!r"Nr#F)rrrr r)r)rr*r+rr,r-r.r/r0r1finalize_dataset_eager_fallbackr3r4r5r6r7rrr8r9r:rr;r<r=)rrrr rr?r@rArBrCrDrErFrGr r r!finalize_dataset"sx     r%zraw_ops.FinalizeDatasetc Cst|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}t|tj }|g}d|d|d |f}tj d d ||||d }t r]t d ||||\}|S)Nr"cSrrrrr r r!r"jr#z3finalize_dataset_eager_fallback..r#cSrr%r&r'r r r!r"or#Fr rrsFinalizeDatasetrKrLr!r) rrrr rrrGrFrAr r r!r$es>  r$ filenames header_bytes record_bytes footer_bytes buffer_sizec Cs.tjpt}|j}|jrYzt|d||||||d| } | WStjy7} z t | |WYd} ~ nd} ~ wtj y@Ynwz t ||||||||dWStj yXYnw|dur_d}t |d}tjd|||||||d\} } } } | dd} t rd| df}| j}t d||| | \} | S)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)r&r'r(r)r*rr)r)rr*r+rr,r-r.r/r0r1*fixed_length_record_dataset_eager_fallbackr3rrnr8r9r:r;r<r=)r&r'r(r)r*rrr?r@rArBrCrDrErFrGr r r!fixed_length_record_datasetsV     r.z raw_ops.FixedLengthRecordDatasetc Cs|durd}t|d}t|tj}t|tj}t|tj}t|tj}t|tj}|||||g}d|f} tjdd|| ||d} trQt d|| | | \} | S)NrrsFixedLengthRecordDatasetrKrLr+ rrnr/rrrrrr:r=) r&r'r(r)r*rrrrGrFrAr r r!r-s( r-compression_typec Cs4tjpt}|j} | jr[zt|d|||||||d| } | WStjy8} z t | |WYd} ~ nd} ~ wtj yAYnwzt |||||||||d WStj yZYnw|durad}t |d}tjd||||||||d \} } } }|dd} t rd| df}| j}t d||| | \} | S)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)r&r'r(r)r*r0rr)r)rr*r+rr,r-r.r/r0r1-fixed_length_record_dataset_v2_eager_fallbackr3rrnr8r9r:r;r<r=)r&r'r(r)r*r0rrr?r@rArBrCrDrErFrGr r r!fixed_length_record_dataset_v2sZ     r3z"raw_ops.FixedLengthRecordDatasetV2c Cs|durd}t|d}t|tj}t|tj}t|tj}t|tj}t|tj}t|tj}||||||g} d|f} tjdd| | ||d} trYt d| | | | \} | S)NrrsFixedLengthRecordDatasetV2rKrLr1r/) r&r'r(r)r*r0rrrrGrFrAr r r!r2 s* r2cCr)a~Creates a dataset that applies `f` to the outputs of `input_dataset`. Unlike MapDataset, the `f` in FlatMapDataset is expected to return a Dataset variant, and FlatMapDataset will flatten successive results into a single Dataset. Args: input_dataset: A `Tensor` of type `variant`. other_arguments: A list of `Tensor` objects. 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`. FlatMapDatasetfrrrNr5rrrrrKExpected list for 'output_types' argument to 'flat_map_dataset' Op, not %r.cSrrrrr r r!r"T r#z$flat_map_dataset..LExpected list for 'output_shapes' argument to 'flat_map_dataset' Op, not %r.cSrr%r&r'r r r!r"Y r#r)rrr5rrrrr)r)rr*r+rr,r-r.r/r0r1flat_map_dataset_eager_fallbackr3r4r5r6r7rrnr8r9r:r;r<r=)rrr5rrrrr?r@rArBrCrDrErFrGr r r!flat_map_dataset& s|      r:zraw_ops.FlatMapDatasetc Cr)Nr7cSrrrrr r r!r"x r#z3flat_map_dataset_eager_fallback..r8cSrr%r&r'r r r!r"} r#rrr5rrrsFlatMapDatasetrKrLr4r) rrr5rrrrrrrGrFrAr r r!r9s s@    r9c Cstjpt} | j} | jrdzt| d| |||d|d|d|d|d|d|} | WStjy?} z t | | WYd} ~ nd} ~ wtj yHYnwzt |||||||||| | d WStj ycYnwt |ttfsqtd |d d |D}t |ttfstd |dd |D}|durd}t|d}tjd|||||||||| d \}}}}|dd} trd|dd|dd|dd|dd|dd|dd|dd|dd|df}|j}td||| | \} | S)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)r<r=r>rrrrrLExpected list for 'output_types' argument to 'generator_dataset' Op, not %r.cSrrrrr r r!r" r#z%generator_dataset..MExpected list for 'output_shapes' argument to 'generator_dataset' Op, not %r.cSrr%r&r'r r r!r" r#r) init_func_other_argsnext_func_other_argsfinalize_func_other_argsr<r=r>rrrrTinit_func_argsTnext_func_argsTfinalize_func_args)r)rr*r+rr,r-r.r/r0r1 generator_dataset_eager_fallbackr3r4r5r6r7rrnr8r9r:r;r<r=)rArBrCr<r=r>rrrrr?r@rArBrCrDrErFrGr r r!generator_dataset s            rHzraw_ops.GeneratorDatasetc Cst|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}t|| \} }t|| \} }t|| \} }t|t|t|}d|d |d |d | d | d | d|d|d|f}tjdd||| | d}trt d||||\}|S)Nr?cSrrrrr r r!r" r#z4generator_dataset_eager_fallback..r@cSrr%r&r'r r r!r" r#rrr<r=r>rDrErFrrsGeneratorDatasetrKrLr; r4r5r6r7rrnrrr:r=)rArBrCr<r=r>rrrrrZ_attr_Tinit_func_argsZ_attr_Tnext_func_argsZ_attr_Tfinalize_func_argsrGrFrAr r r!rG sH    rGc Ctjpt}|j}|jrNz t|d||}|WStjy1}z t ||WYd}~nd}~wtj y:Ynwzt |||dWStj yMYnwt jd||d\}}}}|dd}trqd} |j} td| | ||\}|S)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`. GetOptionsNra)rrr )r)rr*r+rr,r-r.r/r0r1get_options_eager_fallbackr3r8r9rr:r<r=) rrr?r@rArBrCrDrErFrGr r r! get_options B  rMzraw_ops.GetOptionscCPt|tj}|g}d}tjdd||||d}tr#td||||\}|S)Ns GetOptionsrKrLrKr/rrrrrr:r=)rrrrGrFrAr r r!rL-  rL cycle_length block_lengthc Cstjpt} | j} | jr`zt| d|||||d|d|d|d|} | WStjy<} z t | |WYd} ~ nd} ~ wtj yEYnwzt |||||||||| d WStj y_Ynwt |ttfsmtd|d d |D}t |ttfstd |d d |D}|durd }t|d}tjd|||||||||d \} } }}|dd} trd|dd|dd|dd|dd|df }|j}td||| | \} | S)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`. InterleaveDatasetr5rrrNr6MExpected list for 'output_types' argument to 'interleave_dataset' Op, not %r.cSrrrrr r r!r"m r#z&interleave_dataset..NExpected list for 'output_shapes' argument to 'interleave_dataset' Op, not %r.cSrr%r&r'r r r!r"r r#r) rrrRrSr5rrrrr)r)rr*r+rr,r-r.r/r0r1!interleave_dataset_eager_fallbackr3r4r5r6r7rrnr8r9r:r;r<r=)rrrRrSr5rrrrr?r@rArBrCrDrErFrGr r r!interleave_dataset: s         rXzraw_ops.InterleaveDatasetc  Cst|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}t|| \} }t|t j }t|t j }t|t j }|gt|||g} d|d | d |d |d|f } tj d d | | | |d} t rtd| | | | \} | S)NrUcSrrrrr r r!r" r#z5interleave_dataset_eager_fallback..rVcSrr%r&r'r r r!r" r#rrr5rrrsInterleaveDatasetrKrLrTr4r5r6r7rrnrr/rrrrrr:r=)rrrRrSr5rrrrrrrGrFrAr r r!rW sD    rW shared_name containerc Ctjpt}|j}|jrXzt|d|d|d|d|d| }|WStjy8}z t ||WYd}~nd}~wtj yAYnwz t ||||||dWStj yWYnwt |d}t |d}t|ttfsqtd|d d |D}t|ttfstd |d d |D}tjd|||||d \} } } } | dd}t rd| dd| dd| dd| df} | j} t d| | ||\}|S)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`. IteratorrZr[rrNrZr[rrrrCExpected list for 'output_types' argument to 'iterator' Op, not %r.cSrrrrr r r!r" r#ziterator..DExpected list for 'output_shapes' argument to 'iterator' Op, not %r.cSrr%r&r'r r r!r" r#rZr[rrr)r)rr*r+rr,r-r.r/r0r1iterator_eager_fallbackr3rrnr4r5r6r7r8r9r:r;r<r=rZr[rrrr?r@rArBrCrDrErFrGr r r!iterator v        rdzraw_ops.Iteratorc Ct|d}t|d}t|ttfstd|dd|D}t|ttfs-td|dd|D}g}d|d|d|d |f}tjd d ||||d }trWtd ||||\}|S)NrZr[r_cSrrrrr r r!r" r#z+iterator_eager_fallback..r`cSrr%r&r'r r r!r" r#rrsIteratorrKrLr] rrnr4r5r6r7rr:r= rZr[rrrrrGrFrAr r r!rb :   rb string_handlec Cxtjpt}|j}|jrTzt|d||d|d|}|WStjy5}z t ||WYd}~nd}~wtj y>Ynwz t |||||dWStj ySYnw|durZg}t |ttfsgtd|dd|D}|durtg}t |ttfstd |d d|D}tjd||||d \}}} } | dd}trd| dd| df} | j} td| | ||\}|S) 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.cSrrrrr r r!r"0 r#z/iterator_from_string_handle..WExpected list for 'output_shapes' argument to 'iterator_from_string_handle' Op, not %r.cSrr%r&r'r r r!r"7 r#rjrrr)r)rr*r+rr,r-r.r/r0r1*iterator_from_string_handle_eager_fallbackr3r4r5r6r7r8r9rr:r;r<r= rjrrrr?r@rArBrCrDrErFrGr r r!iterator_from_string_handle sr   rrz raw_ops.IteratorFromStringHandlecC|durg}t|ttfstd|dd|D}|dur g}t|ttfs-td|dd|D}t|tj}|g}d|d|f}tj dd ||||d }t r[t d ||||\}|S) NrmcSrrrrr r r!r"P r#z>iterator_from_string_handle_eager_fallback..rncSrr%r&r'r r r!r"W r#rrsIteratorFromStringHandlerKrLrl r4r5r6r7r/rrrrrr:r=rjrrrrrGrFrAr r r!rpI > rpc Crk) 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.cSrrrrr r r!r" r#z2iterator_from_string_handle_v2..ZExpected list for 'output_shapes' argument to 'iterator_from_string_handle_v2' Op, not %r.cSrr%r&r'r r r!r" r#ro)r)rr*r+rr,r-r.r/r0r1-iterator_from_string_handle_v2_eager_fallbackr3r4r5r6r7r8r9rr:r;r<r=rqr r r!iterator_from_string_handle_v2e sr   r{z"raw_ops.IteratorFromStringHandleV2cCrs) NrxcSrrrrr r r!r" r#zAiterator_from_string_handle_v2_eager_fallback..rycSrr%r&r'r r r!r" r#rrsIteratorFromStringHandleV2rKrLrwrtrur r r!rz rvrzc Cbtjpt}|j}|jrTzt|d||d|d|}|WStjy5}z t ||WYd}~nd}~wtj y>Ynwz t |||||dWStj ySYnwt |ttfsatd|dd|D}t |ttfsutd |d d|D}tjd||||d \}}} } | dd}|s| Strd| dd| df} | j} td| | ||S) 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.cSrrrrr r r!r" r#z%iterator_get_next..MExpected list for 'output_shapes' argument to 'iterator_get_next' Op, not %r.cSrr%r&r'r r r!r" r#rdrrr)r)rr*r+rr,r-r.r/r0r1 iterator_get_next_eager_fallbackr3r4r5r6r7r8r9rr:r;r<r= rdrrrr?r@rArBrCrDrErFrGr r r!iterator_get_next sj    rzraw_ops.IteratorGetNextcCt|ttfs td|dd|D}t|ttfs!td|dd|D}t|tj}|g}d|d|f}tj dt |||||d }t rQt d ||||S) Nr~cSrrrrr r r!r" r#z4iterator_get_next_eager_fallback..rcSrr%r&r'r r r!r" r#rrsIteratorGetNextrLr} r4r5r6r7r/rrrrrrr:r=rdrrrrrGrFrAr r r!r 4  rc Cr ) 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.cSrrrrr r r!r"3 r#z1iterator_get_next_as_optional..YExpected list for 'output_shapes' argument to 'iterator_get_next_as_optional' Op, not %r.cSrr%r&r'r r r!r"8 r#r)r)rr*r+rr,r-r.r/r0r1,iterator_get_next_as_optional_eager_fallbackr3r4r5r6r7r8r9rr:r;r<r=rr r r!iterator_get_next_as_optional sj    rz!raw_ops.IteratorGetNextAsOptionalcCr) NrcSrrrrr r r!r"O r#z@iterator_get_next_as_optional_eager_fallback..rcSrr%r&r'r r r!r"T r#rrsIteratorGetNextAsOptionalrKrLr) r4r5r6r7r/rrrrrr:r=rr r r!rJ rrc Cr|) 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.cSrrrrr r r!r" r#z*iterator_get_next_sync..RExpected list for 'output_shapes' argument to 'iterator_get_next_sync' Op, not %r.cSrr%r&r'r r r!r" r#r)r)rr*r+rr,r-r.r/r0r1%iterator_get_next_sync_eager_fallbackr3r4r5r6r7r8r9rr:r;r<r=rr r r!iterator_get_next_syncb sj   rzraw_ops.IteratorGetNextSynccCr) NrcSrrrrr r r!r" r#z9iterator_get_next_sync_eager_fallback..rcSrr%r&r'r r r!r" r#rrsIteratorGetNextSyncrLrrrr r r!r rrc CrJ)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`. IteratorToStringHandleNra)rrr )r)rr*r+rr,r-r.r/r0r1(iterator_to_string_handle_eager_fallbackr3r8r9rr:r<r=) rrr?r@rArBrCrDrErFrGr r r!iterator_to_string_handle rNrzraw_ops.IteratorToStringHandlecCrO)NsIteratorToStringHandlerKrLrr/rrrrrr:r=)rrrrGrFrAr r r!r rc Cr\)aXTODO: add doc. 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`. IteratorV2rZr[rrNr^FExpected list for 'output_types' argument to 'iterator_v2' Op, not %r.cSrrrrr r r!r" r#ziterator_v2..GExpected list for 'output_shapes' argument to 'iterator_v2' Op, not %r.cSrr%r&r'r r r!r" r#ra)r)rr*r+rr,r-r.r/r0r1iterator_v2_eager_fallbackr3rrnr4r5r6r7r8r9r:r;r<r=rcr r r! iterator_v2 rerzraw_ops.IteratorV2c Crf)NrZr[rcSrrrrr r r!r"8 r#z.iterator_v2_eager_fallback..rcSrr%r&r'r r r!r"= r#rrs IteratorV2rKrLrrgrhr r r!r1 rirc Cr)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. MakeIteratorNra)rrdr)r)rr*r+rr,r-r.r/r0r1make_iterator_eager_fallbackr3r8r9) rrdrr?r@rArBrCrDrEr r r! make_iteratorJ s2 rzraw_ops.MakeIteratorcCr)Ns MakeIteratorrrL)r/rrrrrr)rrdrrrGrFrAr r r!ro rrTuse_inter_op_parallelismpreserve_cardinalityc Cstjpt} | j} | jrbzt| d|||d|d|d|d|d|d|} | WStjy>} z t | |WYd} ~ nd} ~ wtj yGYnwzt |||||||||| d WStj yaYnwt |ttfsotd |d d |D}t |ttfstd |dd |D}|durd}t|d}|durd}t|d}|durd}t|d}tjd|||||||||d \} } }}|dd} trd|dd|dd|dd|dd|dd|dd|df}|j}td||| | \} | S)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`. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. MapDatasetr5rrrrrN)r5rrrrrrrFExpected list for 'output_types' argument to 'map_dataset' Op, not %r.cSrrrrr r r!r" r#zmap_dataset..GExpected list for 'output_shapes' argument to 'map_dataset' Op, not %r.cSrr%r&r'r r r!r" r#TFr) rrr5rrrrrrr)r)rr*r+rr,r-r.r/r0r1map_dataset_eager_fallbackr3r4r5r6r7rrrnr8r9r:r;rr<r=)rrr5rrrrrrr?r@rArBrCrDrErFrGr r r! map_datasetz s         rzraw_ops.MapDatasetc Cst|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}|dur:d}t|d }|durFd }t|d }t|| \} }t |t j }|gt|} d |d | d|d|d|d |d |f} tj dd| | | |d} t rtd| | | | \} | S)NrcSrrrrr r r!r" r#z.map_dataset_eager_fallback..rcSrr%r&r'r r r!r" r#TrFrrrr5rrrs MapDatasetrKrLr)r4r5r6r7rrrnrr/rrrrr:r=)rrr5rrrrrrrrrGrFrAr r r!r sP     rrKmax_intra_op_parallelismcCstjpt}|j}|jr\zt|d|||d|d|d|d| } | WStjy:} z t | |WYd} ~ nd} ~ wtj yCYnwz t ||||||||dWStj y[Ynwt |ttfsitd|d d |D}t |ttfs}td |d d |D}|durd }t|d}tjd|||||||d\} } } } | dd} trd| dd| dd| dd| dd| dd| df }| j}td||| | S)a Maps a function on the list of tensors unpacked from arguments on dimension 0. The function given by `f` is assumed to be stateless, and is executed concurrently on all the slices; up to batch_size (i.e. the size of the 0th dimension of each argument) functions will be scheduled at once. The `max_intra_op_parallelism` attr, which defaults to 1, can be used to limit the intra op parallelism. To limit inter-op parallelism, a user can set a private threadpool on the dataset using `tf.data.Options`'s `ThreadingOptions`. Note that this op is not exposed to users directly, but is invoked in tf.data rewrites. Args: arguments: A list of `Tensor` objects. A list of tensors whose types are `Targuments`, corresponding to the inputs the function should be mapped over. captured_inputs: A list of `Tensor` objects. A list of tensors whose types are `Tcaptured`, corresponding to the captured inputs of the defun. output_types: A list of `tf.DTypes` that has length `>= 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`. MapDefunrrr5rN)rrr5rrrDExpected list for 'output_types' argument to 'map_defun' Op, not %r.cSrrrrr r r!r".r#zmap_defun..EExpected list for 'output_shapes' argument to 'map_defun' Op, not %r.cSrr%r&r'r r r!r"3r#rK) argumentscaptured_inputsrrr5rrr Tcaptured)r)rr*r+rr,r-r.r/r0r1map_defun_eager_fallbackr3r4r5r6r7rrr8r9r:r;rr<r=)rrrrr5rrr?r@rArBrCrDrErFrGr r r! map_defun s~        rzraw_ops.MapDefunc Cst|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}t||\}}t||\} }t|t|} d|d | d |d |d |d|f } tjd t|| | ||d} t rst d| | | | S)NrcSrrrrr r r!r"Qr#z,map_defun_eager_fallback..rcSrr%r&r'r r r!r"Vr#rKrrrrrr5sMapDefunrLr) r4r5r6r7rrrrrr:r=) rrrrr5rrrrZ_attr_TcapturedrGrFrAr r r!rLsB   r algorithm cpu_budget ram_budgetcCstjpt}|j}|jr]zt|d||d|d|d|d|d|} | WStjy;} z t | |WYd} ~ nd} ~ wtj yDYnwz t ||||||||dWStj y\Ynwt |ttfsjtd |d d |D}t |ttfs~td |d d |D}|durd}t|d}|durd}t|d}|durd}t|d}tjd|||||||d\} } } } | dd} trd| dd| dd| dd| dd| df }| j}td||| | \} | S)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.cSrrrrr r r!r"r#z!model_dataset..IExpected list for 'output_shapes' argument to 'model_dataset' Op, not %r.cSrr%r&r'r r r!r"r#r)rrrrrrr)r)rr*r+rr,r-r.r/r0r1model_dataset_eager_fallbackr3r4r5r6r7rrr8r9r:rr;r<r=)rrrrrrrr?r@rArBrCrDrErFrGr r r! model_datasetis          rzraw_ops.ModelDatasetc Cst|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}|dur:d}t|d}|durFd}t|d }t|tj }|g}d|d|d |d |d |f } tj d d || ||d} t ryt d|| | | \} | S)NrcSrrrrr r r!r"r#z0model_dataset_eager_fallback..rcSrr%r&r'r r r!r"r#rrrrrrs ModelDatasetrKrLr) r4r5r6r7rrr/rrrrr:r=) rrrrrrrrrGrFrAr r r!rsJ      rcCstjpt}|j}|jr[zt|d|d|d|d|d|d| }|WStjy:} z t | |WYd} ~ nd} ~ wtj yCYnwz t |||||||dWStj yZYnwt |ttfshtd |d d |D}t|d}t|d}t |ttfstd |d d |D}t |ttfstd|dd |D}tjd||||||d\} } } } | dd}trd| dd| dd| dd| dd| df } | j}td|| ||\}|S)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`. MultiDeviceIteratorrirZr[rrN)rirZr[rrrrKExpected list for 'devices' argument to 'multi_device_iterator' Op, not %r.cSrrlrmr'r r r!r"r#z)multi_device_iterator..PExpected list for 'output_types' argument to 'multi_device_iterator' Op, not %r.cSrrrrr r r!r"r#QExpected list for 'output_shapes' argument to 'multi_device_iterator' Op, not %r.cSrr%r&r'r r r!r"r#)rirZr[rrr)r)rr*r+rr,r-r.r/r0r1$multi_device_iterator_eager_fallbackr3r4r5r6r7rrnr8r9r:r;r<r=)rirZr[rrrr?r@rArBrCrDrErFrGr r r!rs         zraw_ops.MultiDeviceIteratorc Cst|ttfs td|dd|D}t|d}t|d}t|ttfs-td|dd|D}t|ttfsAtd|d d|D}g}d |d|d|d |d |f }tjd d||||d} trmtd||| | \} | S)NrcSrrlrmr'r r r!r".r#z8multi_device_iterator_eager_fallback..rZr[rcSrrrrr r r!r"5r#rcSrr%r&r'r r r!r":r#rirrsMultiDeviceIteratorrKrLr r4r5r6r7rrnrr:r=) rirZr[rrrrrGrFrAr r r!r)sH     rc Crk) 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.cSrrrrr r r!r"or#z.dExpected list for 'output_shapes' argument to 'multi_device_iterator_from_string_handle' Op, not %r.cSrr%r&r'r r r!r"vr#ro)r)rr*r+rr,r-r.r/r0r17multi_device_iterator_from_string_handle_eager_fallbackr3r4r5r6r7r8r9rr:r;r<r=rqr r r!(multi_device_iterator_from_string_handleGst  rz+raw_ops.MultiDeviceIteratorFromStringHandlecCrs) NrcSrrrrr r r!r"r#zKmulti_device_iterator_from_string_handle_eager_fallback..rcSrr%r&r'r r r!r"r#rrs#MultiDeviceIteratorFromStringHandlerKrLrrtrur r r!rrvr shard_numincarnation_idc Csntjpt}|j}|jrXzt|d||||d|d| }|WStjy7} z t | |WYd} ~ nd} ~ wtj y@Ynwz t |||||||dWStj yWYnwt |ttfsetd|dd|D}t |ttfsytd |d d|D}tjd||||||d \} } } } | dd}|s| Strd| dd| df} | j}td|| ||S) 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.cSrrrrr r r!r"r#z=multi_device_iterator_get_next_from_shard..eExpected list for 'output_shapes' argument to 'multi_device_iterator_get_next_from_shard' Op, not %r.cSrr%r&r'r r r!r"r#)rrrrrr)r)rr*r+rr,r-r.r/r0r18multi_device_iterator_get_next_from_shard_eager_fallbackr3r4r5r6r7r8r9rr:r;r<r=)rrrrrrr?r@rArBrCrDrErFrGr r r!)multi_device_iterator_get_next_from_shardsv  rz+raw_ops.MultiDeviceIteratorGetNextFromShardc Cst|ttfs td|dd|D}t|ttfs!td|dd|D}t|tj}t|tj}t|tj }|||g}d|d|f}t j dt |||||d } t rat d ||| | S) NrcSrrrrr r r!r"r#zLmulti_device_iterator_get_next_from_shard_eager_fallback..rcSrr%r&r'r r r!r"r#rrs#MultiDeviceIteratorGetNextFromShardrLr)r4r5r6r7r/rrrint32rrrrr:r=) rrrrrrrrGrFrAr r r!rs8  rmax_buffer_sizec Cstjpt}|j}|jrRz t|d||||}|WStjy3}z t ||WYd}~nd}~wtj y<Ynwz t |||||dWStj yQYnwt jd||||d\}}} } | dd}trwd} | j} td| | ||\}|S)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`. MultiDeviceIteratorInitNra)rrrrr )r)rr*r+rr,r-r.r/r0r1)multi_device_iterator_init_eager_fallbackr3r8r9rr:r<r=) rrrrr?r@rArBrCrDrErFrGr r r!multi_device_iterator_initsJ  rzraw_ops.MultiDeviceIteratorInitcCspt|tj}t|tj}t|tj}|||g}d}tjdd||||d}tr3t d||||\}|S)NsMultiDeviceIteratorInitrKrLr) r/rrrrrrrr:r=)rrrrrrGrFrAr r r!r6s rc CrJ)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`. !MultiDeviceIteratorToStringHandleNra)rrr )r)rr*r+rr,r-r.r/r0r15multi_device_iterator_to_string_handle_eager_fallbackr3r8r9rr:r<r=) rrr?r@rArBrCrDrErFrGr r r!&multi_device_iterator_to_string_handleFsF  rz)raw_ops.MultiDeviceIteratorToStringHandlecCrO)Ns!MultiDeviceIteratorToStringHandlerKrLrr)rrrrGrFrAr r r!rrrrcCstjpt}|j}|jr[zt|d|d|d|d|d|d| }|WStjy:} z t | |WYd} ~ nd} ~ wtj yCYnwz t |||||||dWStj yZYnwt |ttfshtd |d d |D}t |ttfs|td |d d |D}|durd}t|d}|durd}t|d}tjd||||||d\} } } } | dd}trd| dd| dd| dd| dd| df } | j}td|| ||\}|S)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_factoryrrr[rZN)rrrr[rZrrLExpected list for 'output_types' argument to 'one_shot_iterator' Op, not %r.cSrrrrr r r!r"r#z%one_shot_iterator..MExpected list for 'output_shapes' argument to 'one_shot_iterator' Op, not %r.cSrr%r&r'r r r!r"r#r)rrrr[rZr)r)rr*r+rr,r-r.r/r0r1 one_shot_iterator_eager_fallbackr3r4r5r6r7rrnr8r9r:r;r<r=)rrrr[rZrr?r@rArBrCrDrErFrGr r r!one_shot_iterators"        rzraw_ops.OneShotIteratorc Cst|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}|dur:d}t|d}g}d |d |d |d|d|f }tjd d ||||d} tretd||| | \} | S)NrcSrrrrr r r!r"r#z4one_shot_iterator_eager_fallback..rcSrr%r&r'r r r!r"r#rr[rZrrrsOneShotIteratorrKrLrr) rrrr[rZrrrGrFrAr r r!rsD    r optimizationsc Cstjpt}|j}|jrYzt|d|||d|d|d| }|WStjy8} z t | |WYd} ~ nd} ~ wtj yAYnwz t |||||||dWStj yXYnwt |ttfsftd|dd |D}t |ttfsztd |d d |D}|durg}t |ttfstd |d d |D}tjd||||||d\} } } } | dd}trd| dd| dd| df} | j}td|| ||\}|S)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_configsNrrrrrKExpected list for 'output_types' argument to 'optimize_dataset' Op, not %r.cSrrrrr r r!r"%r#z$optimize_dataset..LExpected list for 'output_shapes' argument to 'optimize_dataset' Op, not %r.cSrr%r&r'r r r!r"*r#SExpected list for 'optimization_configs' argument to 'optimize_dataset' Op, not %r.cSrrrmr'r r r!r"1r#)rrrrrr)r)rr*r+rr,r-r.r/r0r1optimize_dataset_eager_fallbackr3r4r5r6r7r8r9rr:r;r<r=)rrrrrrr?r@rArBrCrDrErFrGr r r!optimize_datasets    rzraw_ops.OptimizeDatasetc Cst|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.g}t|ttfs;td|dd|D}t|tj}t|tj}||g}d|d |d |f}t j d d ||||d } t rst d||| | \} | S)NrcSrrrrr r r!r"Lr#z3optimize_dataset_eager_fallback..rcSrr%r&r'r r r!r"Qr#rcSrrrmr'r r r!r"Xr#rrrsOptimizeDatasetrKrLr r4r5r6r7r/rrrrrrr:r=) rrrrrrrrGrFrAr r r!rGsL roptimizations_enabledoptimizations_disabledoptimizations_defaultcCstjpt}|j} | jr]zt|d|||||d|d|d| } | WStjy:} z t | |WYd} ~ nd} ~ wtj yCYnwzt |||||||||d WStj y\Ynwt |ttfsjtd|dd |D}t |ttfs~td |d d |D}|durg}t |ttfstd |d d |D}tjd||||||||d \} } } }|dd} trd| dd| dd| df}| j}td||| | \} | S)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`. OptimizeDatasetV2rrrNrNExpected list for 'output_types' argument to 'optimize_dataset_v2' Op, not %r.cSrrrrr r r!r"r#z'optimize_dataset_v2..OExpected list for 'output_shapes' argument to 'optimize_dataset_v2' Op, not %r.cSrr%r&r'r r r!r"r#VExpected list for 'optimization_configs' argument to 'optimize_dataset_v2' Op, not %r.cSrrrmr'r r r!r"r#)rrrrrrrr)r)rr*r+rr,r-r.r/r0r1"optimize_dataset_v2_eager_fallbackr3r4r5r6r7r8r9rr:r;r<r=)rrrrrrrrr?r@rArBrCrDrErFrGr r r!optimize_dataset_v2gs    rzraw_ops.OptimizeDatasetV2c Cst|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.g}t|ttfs;td|dd|D}t|tj}t|tj}t|tj}t|tj}||||g} d|d |d |f} t j d d | | ||d } t rt d| | | | \} | S)NrcSrrrrr r r!r"r#z6optimize_dataset_v2_eager_fallback..rcSrr%r&r'r r r!r"r#rcSrrrmr'r r r!r"r#rrrsOptimizeDatasetV2rKrLrr) rrrrrrrrrrGrFrAr r r!rsP  rserialized_optionscCstjpt}|j}|jrZzt|d||d|d|d|d| }|WStjy9} z t | |WYd} ~ nd} ~ wtj yBYnwz t |||||||dWStj yYYnwt |d}t|ttfsmtd|d d |D}t|ttfstd |d d |D}|durd }t |d}tjd||||||d\} } } } | dd}t rd| dd| dd| dd| df} | j}t d|| ||\}|S)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`. OptionsDatasetrrrrN)rrrrrrJExpected list for 'output_types' argument to 'options_dataset' Op, not %r.cSrrrrr r r!r"r#z#options_dataset..KExpected list for 'output_shapes' argument to 'options_dataset' Op, not %r.cSrr%r&r'r r r!r" r#r)rrrrrr)r)rr*r+rr,r-r.r/r0r1options_dataset_eager_fallbackr3rrnr4r5r6r7r8r9r:r;r<r=)rrrrrrr?r@rArBrCrDrErFrGr r r!options_datasets~       rzraw_ops.OptionsDatasetc Cst|d}t|ttfstd|dd|D}t|ttfs'td|dd|D}|dur4d}t|d}t|tj }|g}d|d |d |d|f}tj d d ||||d } t ret d||| | \} | S)NrrcSrrrrr r r!r",r#z2options_dataset_eager_fallback..rcSrr%r&r'r r r!r"1r#rrrrsOptionsDatasetrKrLr) rrnr4r5r6r7r/rrrrr:r=) rrrrrrrrGrFrAr r r!r&s@    r padded_shapesc Cstjpt}|j}|jrZzt|d|||||d|d| } | WStjy8} z t | |WYd} ~ nd} ~ wtj yAYnwz t ||||||||dWStj yYYnwt |ttfsgtd|t|} t |ttfsxtd|dd |D}|durd }t|d}tjd|||||||d \} } } }|dd} trd | d d| dd | d d| df}| j}td||| | \} | S)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.cSrr%r&r'r r r!r"vr#z(padded_batch_dataset..r)rrrpadding_valuesrrr Toutput_typesr)r)rr*r+rr,r-r.r/r0r1#padded_batch_dataset_eager_fallbackr3r4r5r6r7rrrnr8r9r:r;rr<r=)rrrrrrrr?r@rArBrrCrDrErFrGr r r!padded_batch_datasetBsz     rzraw_ops.PaddedBatchDatasetc Cst|ttfs td|t|}t|ttfstd|dd|D}|dur+d}t|d}t||\} }t |t j }t |t j }t |t j }||gt|t|} d| d|d |d|f} tjd d | | ||d } tr{td | | | | \} | S)NrrcSrr%r&r'r r r!r"r#z7padded_batch_dataset_eager_fallback..rrrrrsPaddedBatchDatasetrKrLr)r4r5r6r7rrrnrr/rrrrrrr:r=) rrrrrrrrr_attr_Toutput_typesrGrFrAr r r!rsD   rc Cstjpt} | j} | jr_zt| d||||||d|d|d|} | WStjy;} z t | |WYd} ~ nd} ~ wtj yDYnwzt |||||||||| d WStj y^Ynwt |ttfsltd|t|} t |ttfs}td|d d |D}|durd }t|d}|durd }t|d}tjd|||||||||d \}}}}|dd} trd|dd|dd|dd|dd|df }|j}td||| | \} | S)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.cSrr%r&r'r r r!r"r#z+padded_batch_dataset_v2..Fr) rrrrrrrrrrr)r)rr*r+rr,r-r.r/r0r1&padded_batch_dataset_v2_eager_fallbackr3r4r5r6r7rrrrnr8r9r:rr;rr<r=)rrrrrrrrrr?r@rArBrrCrDrErFrGr r r!padded_batch_dataset_v2s        rzraw_ops.PaddedBatchDatasetV2c  Cs0t|ttfs td|t|} t|ttfstd|dd|D}|dur+d}t|d}|dur7d}t|d}t|| \} }t |t j }t |t j }t |t j }t |t j}||gt|t||g} d|d | d |d | d|f } tjd d | | | |d}trtd| | ||\}|S)NrrcSrr%r&r'r r r!r"r#z:padded_batch_dataset_v2_eager_fallback..FrrrrrrsPaddedBatchDatasetV2rKrLr)r4r5r6r7rrrrnrr/rrrrrrrr:r=)rrrrrrrrrrrrrGrFrAr r r!rsN    rdefaultnum_parallel_calls deterministicc Cstjpt} | j} | jrczt| d| ||||d|d|d|d|d|} | WStjy>} z t | | WYd} ~ nd} ~ wtj yGYnwzt |||||||||| | d WStj ybYnwt |ttfsptd |d d |D}t |ttfstd |d d |D}|durd}t|d}|durd}t|d}|durd}t|d}tjd|||||||||| d \}}}}|dd} trd|dd|dd|dd|dd|df }|j}td||| | \} | S)aTODO: add doc. Args: input_dataset: A `Tensor` of type `variant`. batch_size: A `Tensor` of type `int64`. num_parallel_calls: A `Tensor` of type `int64`. drop_remainder: A `Tensor` of type `bool`. 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`. 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`. ParallelBatchDatasetrrrrrN)rrrrrrrQExpected list for 'output_types' argument to 'parallel_batch_dataset' Op, not %r.cSrrrrr r r!r"Ur#z*parallel_batch_dataset..RExpected list for 'output_shapes' argument to 'parallel_batch_dataset' Op, not %r.cSrr%r&r'r r r!r"Zr#Frr) rrrrrrrrrr)r)rr*r+rr,r-r.r/r0r1%parallel_batch_dataset_eager_fallbackr3r4r5r6r7rrrnr8r9r:rr;r<r=)rrrrrrrrrrr?r@rArBrCrDrErFrGr r r!parallel_batch_dataset(s         rzraw_ops.ParallelBatchDatasetc  Cs,t|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}|dur:d}t|d }|durFd }t|d }t|t j }t|t j }t|t j }t|t j }||||g} d|d |d |d |d |f } tj dd| | | | d} trtd| | | | \} | S)NrcSrrrrr r r!r"r#z9parallel_batch_dataset_eager_fallback..rcSrr%r&r'r r r!r"r#FrrrrrrrsParallelBatchDatasetrKrLrr)rrrrrrrrrrrrGrFrAr r r!r~sR      rc Cstjpt} | j} | jrazt| d||||d|d|d|d|d|} | WStjy=} z t | |WYd} ~ nd} ~ wtj yFYnwzt |||||||||| d WStj y`Ynwt |ttfsntd |d d |D}t |ttfstd |d d |D}|durd}t|d}|durd}t|d}tjd|||||||||d \} } }}|dd} trd|dd|dd|dd|dd|dd|df }|j}td||| | \} | S)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`. ParallelFilterDatasetrrrrrN)rrrrrrrRExpected list for 'output_types' argument to 'parallel_filter_dataset' Op, not %r.cSrrrrr r r!r"r#z+parallel_filter_dataset..SExpected list for 'output_shapes' argument to 'parallel_filter_dataset' Op, not %r.cSrr%r&r'r r r!r"r#rr) rrrrrrrrrr)r)rr*r+rr,r-r.r/r0r1¶llel_filter_dataset_eager_fallbackr3r4r5r6r7rrnr8r9r:r;r<r=)rrrrrrrrrr?r@rArBrCrDrErFrGr r r!parallel_filter_datasets$         r zraw_ops.ParallelFilterDatasetc  Cst|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}|dur:d}t|d }t|| \} }t|t j }t|t j }|gt||g} d |d|d | d |d |d |f } tj dd| | | |d} t rtd| | | | \} | S)Nr cSrrrrr r r!r" r#z:parallel_filter_dataset_eager_fallback..r cSrr%r&r'r r r!r"r#rrrrrrrrsParallelFilterDatasetrKrLrrY)rrrrrrrrrrrrGrFrAr r r!r sJ   r sloppyc Cstjpt} | j} | jrezt| d| |||||d|d|d|d|d| } | WStjy?}z t || WYd}~nd}~wtj yHYnwzt |||||||||| | | d WStj ydYnwt |ttfsrtd |d d |D}t |ttfstd |d d |D}|durd}t|d}| durd} t| d} tjd|||||||||| | d \}}}}|dd} trd|dd|dd|dd|dd|dd|df }|j}td||| | \} | S)aR 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 set the `experimental_deterministic` parameter of `tf.data.Options` to `False`, which 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`. 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`. ParallelInterleaveDatasetV2r5rrr rN)r5rrr rrrYExpected list for 'output_types' argument to 'parallel_interleave_dataset_v2' Op, not %r.cSrrrrr r r!r"rr#z2parallel_interleave_dataset_v2..ZExpected list for 'output_shapes' argument to 'parallel_interleave_dataset_v2' Op, not %r.cSrr%r&r'r r r!r"wr#Fr) rrrRrSrr5rrr rrr)r)rr*r+rr,r-r.r/r0r1-parallel_interleave_dataset_v2_eager_fallbackr3r4r5r6r7rrrnr8r9r:r;rr<r=)rrrRrSrr5rrr rrr?r@rArBrCrDrErFrGr r r!parallel_interleave_dataset_v2)s.          rz#raw_ops.ParallelInterleaveDatasetV2c  Cs4t|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}| dur:d} t| d } t|| \} }t |t j }t |t j }t |t j }t |t j }|gt||||g} d |d | d |d |d|d | f }tj dd| || | d}trtd| |||\}|S)NrcSrrrrr r r!r"r#zAparallel_interleave_dataset_v2_eager_fallback..rcSrr%r&r'r r r!r"r#Fr rrr5rrrsParallelInterleaveDatasetV2rKrLrr4r5r6r7rrrnrr/rrrrrr:r=)rrrRrSrr5rrr rrrrrGrFrAr r r!rsP    rc Cstjpt} | j} | jrezt| d| |||||d|d|d|d|d| } | WStjy?}z t || WYd}~nd}~wtj yHYnwzt |||||||||| | | d WStj ydYnwt |ttfsrtd |d d |D}t |ttfstd |d d |D}|durd}t|d}| durd} t| d} tjd|||||||||| | d \}}}}|dd} trd|dd|dd|dd|dd|dd|df }|j}td||| | \} | S)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`. ParallelInterleaveDatasetV3r5rrrrNr5rrrrrrYExpected list for 'output_types' argument to 'parallel_interleave_dataset_v3' Op, not %r.cSrrrrr r r!r" r#z2parallel_interleave_dataset_v3..ZExpected list for 'output_shapes' argument to 'parallel_interleave_dataset_v3' Op, not %r.cSrr%r&r'r r r!r"r#rr) rrrRrSrr5rrrrrr)r)rr*r+rr,r-r.r/r0r1-parallel_interleave_dataset_v3_eager_fallbackr3r4r5r6r7rrnr8r9r:r;r<r=)rrrRrSrr5rrrrrr?r@rArBrCrDrErFrGr r r!parallel_interleave_dataset_v3s4          rz#raw_ops.ParallelInterleaveDatasetV3c  Cs4t|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}| dur:d} t| d } t|| \} }t|t j }t|t j }t|t j }t|t j }|gt||||g} d |d|d | d |d |d | f }tj dd| || | d}t rtd| |||\}|S)NrcSrrrrr r r!r"8r#zAparallel_interleave_dataset_v3_eager_fallback..rcSrr%r&r'r r r!r"=r#rrrrr5rrrsParallelInterleaveDatasetV3rKrLrrY)rrrRrSrr5rrrrrrrrGrFrAr r r!r3sP   rbuffer_output_elementsprefetch_input_elementsc Cstjpt} | j}|jrizt| d| |||||||d|d| d|d| d| }|WStjyA}z t || WYd}~nd}~wtj yJYnwzt ||||||||| || | | | dWStj yhYnwt |ttfsvtd |d d |D}t | ttfstd | d d | D} | durd} t| d} | durd} t| d} tjd|||||||||| | | | d\}}}}|dd}trd|dd|dd|dd|dd|dd|df }|j}td||||\}|S)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`. ParallelInterleaveDatasetV4r5rrrrNrYExpected list for 'output_types' argument to 'parallel_interleave_dataset_v4' Op, not %r.cSrrrrr r r!r"r#z2parallel_interleave_dataset_v4..ZExpected list for 'output_shapes' argument to 'parallel_interleave_dataset_v4' Op, not %r.cSrr%r&r'r r r!r"r#rr) rrrRrSrrrr5rrrrrr)r)rr*r+rr,r-r.r/r0r1-parallel_interleave_dataset_v4_eager_fallbackr3r4r5r6r7rrnr8r9r:r;r<r=)rrrRrSrrrr5rrrrrr?r@rArBrCrDrErFrGr r r!parallel_interleave_dataset_v4Ws:         r z#raw_ops.ParallelInterleaveDatasetV4c CsTt|ttfs td|dd|D}t| ttfs!td| dd| D} | dur.d} t| d} | dur:d} t| d } t|| \}}t|t j }t|t j }t|t j }t|t j }t|t j }t|t j }|gt||||||g}d |d| d |d |d | d | f }tj dd||| | d}t rtd||||\}|S)NrcSrrrrr r r!r"r#zAparallel_interleave_dataset_v4_eager_fallback..rcSrr%r&r'r r r!r"r#rrrrr5rrrsParallelInterleaveDatasetV4rKrLrrY)rrrRrSrrrr5rrrrrrrrGrFrAr r r!rsT   rc Cs2tjpt} | j} | jrgzt| d| |||d|d|d|d|d|d|d| } | WStjyA}z t || WYd }~nd }~wtj yJYnwzt |||||||||| | | d WStj yfYnwt |ttfsttd |d d |D}t |ttfstd|dd |D}|d urd}t|d}|d urd}t|d}|d urd}t|d}| d urd} t| d} tjd|||||||||| | d \}}}}|d d } trd|dd|dd|dd|dd|dd|dd|dd|df}|j}td||| | \} | S)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`. ParallelMapDatasetr5rrrr rrN) r5rrrr rrrrOExpected list for 'output_types' argument to 'parallel_map_dataset' Op, not %r.cSrrrrr r r!r"1r#z(parallel_map_dataset..PExpected list for 'output_shapes' argument to 'parallel_map_dataset' Op, not %r.cSrr%r&r'r r r!r"6r#TFr) rrrr5rrrr rrrr)r)rr*r+rr,r-r.r/r0r1#parallel_map_dataset_eager_fallbackr3r4r5r6r7rrrnr8r9r:r;rr<r=)rrrr5rrrr rrrr?r@rArBrCrDrErFrGr r r!parallel_map_datasets              r%zraw_ops.ParallelMapDatasetc CsLt|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}|dur:d}t|d }|durFd}t|d }| durRd } t| d } t|| \} }t |t j }t |t j }|gt||g} d |d| d|d|d|d |d |d | f}tj dd| || | d}trtd| |||\}|S)Nr"cSrrrrr r r!r"er#z7parallel_map_dataset_eager_fallback..r#cSrr%r&r'r r r!r"jr#TrFr rrrr5rrrsParallelMapDatasetrKrLr!)r4r5r6r7rrrnrr/rrrrrr:r=)rrrr5rrrr rrrrrrGrFrAr r r!r$`sX      r$c Cs2tjpt} | j} | jrgzt| d| |||d|d|d|d|d|d|d| } | WStjyA}z t || WYd }~nd }~wtj yJYnwzt |||||||||| | | d WStj yfYnwt |ttfsttd |d d |D}t |ttfstd|dd |D}|d urd}t|d}|d urd}t|d}|d urd}t|d}| d urd} t| d} tjd|||||||||| | d \}}}}|d d } trd|dd|dd|dd|dd|dd|dd|dd|df}|j}td||| | \} | S)a Creates 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 `int64`. 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`. deterministic: An optional `string`. Defaults to `"default"`. 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`. ParallelMapDatasetV2r5rrrrrrN) r5rrrrrrrrRExpected list for 'output_types' argument to 'parallel_map_dataset_v2' Op, not %r.cSrrrrr r r!r"r#z+parallel_map_dataset_v2..SExpected list for 'output_shapes' argument to 'parallel_map_dataset_v2' Op, not %r.cSrr%r&r'r r r!r"r#TrFr) rrrr5rrrrrrrr)r)rr*r+rr,r-r.r/r0r1¶llel_map_dataset_v2_eager_fallbackr3r4r5r6r7rrrnr8r9r:r;rr<r=)rrrr5rrrrrrrr?r@rArBrCrDrErFrGr r r!parallel_map_dataset_v2s              r*zraw_ops.ParallelMapDatasetV2c CsLt|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}|dur:d}t|d }|durFd }t|d }| durRd } t| d } t|| \} }t |t j }t |t j }|gt||g} d|d| d|d|d|d |d |d | f}tj dd| || | d}trtd| |||\}|S)Nr'cSrrrrr r r!r"r#z:parallel_map_dataset_v2_eager_fallback..r(cSrr%r&r'r r r!r"r#TrrrFrrrr5rrrsParallelMapDatasetV2rKrLr&r)rrrr5rrrrrrrrrrGrFrAr r r!r)sX      r) slack_periodlegacy_autotunebuffer_size_minc Cstjpt} | j} | jrbzt| d|||d|d|d|d|d|d|} | WStjy>} z t | |WYd} ~ nd} ~ wtj yGYnwzt |||||||||| d WStj yaYnwt |ttfsotd |d d |D}t |ttfstd |dd |D}|durd}t|d}|durd}t|d}|durd}t|d}|durd}t|d}tjd|||||||||d \} } }}|dd} trd|dd|dd|dd|dd|dd|df }|j}td||| | \} | S)aCreates a dataset that asynchronously prefetches elements from `input_dataset`. Args: input_dataset: A `Tensor` of type `variant`. buffer_size: A `Tensor` of type `int64`. The maximum number of elements to buffer in an iterator over this 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`. 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`. PrefetchDatasetrrr+r,r-rN)rrr+r,r-rrrKExpected list for 'output_types' argument to 'prefetch_dataset' Op, not %r.cSrrrrr r r!r"Cr#z$prefetch_dataset..LExpected list for 'output_shapes' argument to 'prefetch_dataset' Op, not %r.cSrr%r&r'r r r!r"Hr#rTr) rr*rrr+r,r-rr)r)rr*r+rr,r-r.r/r0r1prefetch_dataset_eager_fallbackr3r4r5r6r7rrrrnr8r9r:r;rrr<r=)rr*rrr+r,r-rrr?r@rArBrCrDrErFrGr r r!prefetch_datasets            r2zraw_ops.PrefetchDatasetc Cs(t|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}|dur:d}t|d }|durFd}t|d }|durRd }t|d }t |t j }t |t j }||g} d |d|d|d |d |d |f } tj dd| | | |d} trtd| | | | \} | S)Nr/cSrrrrr r r!r"sr#z3prefetch_dataset_eager_fallback..r0cSrr%r&r'r r r!r"xr#rr+Tr,r-rrrrsPrefetchDatasetrKrLr.)r4r5r6r7rrrrnr/rrrrrr:r=) rr*rrr+r,r-rrrrGrFrAr r r!r1nsT     r1startstopstepreplicate_on_splitcCstjpt}|j} | jr^zt|d||||d|d|d|d|} | WStjy;} z t | |WYd} ~ nd} ~ wtj yDYnwzt |||||||||d WStj y]Ynwt |ttfsktd|d d |D}t |ttfstd |d d |D}|durd }t|d}|durd}t|d}tjd||||||||d \} } } }|dd} trd| dd| dd| dd| df}| j}td||| | \} | S)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`. RangeDatasetrrrr6N)rrrr6rrHExpected list for 'output_types' argument to 'range_dataset' Op, not %r.cSrrrrr r r!r"r#z!range_dataset..IExpected list for 'output_shapes' argument to 'range_dataset' Op, not %r.cSrr%r&r'r r r!r"r#rF)r3r4r5rrrr6r)r)rr*r+rr,r-r.r/r0r1range_dataset_eager_fallbackr3r4r5r6r7rrnrr8r9r:r;rr<r=)r3r4r5rrrr6rr?r@rArBrCrDrErFrGr r r! range_datasets       r;zraw_ops.RangeDatasetc Cst|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}|dur:d}t|d }t|t j }t|t j }t|t j }|||g} d |d |d|d |f} tj d d | | ||d} t r{t d| | | | \} | S)Nr8cSrrrrr r r!r"r#z0range_dataset_eager_fallback..r9cSrr%r&r'r r r!r"r#rrFr6rrs RangeDatasetrKrLr7)r4r5r6r7rrnrr/rrrrr:r=) r3r4r5rrrr6rrrGrFrAr r r!r:rr:c Cstjpt} | j} | jrazt| d||||d|d|d|d|d|} | WStjy=} z t | |WYd} ~ nd} ~ wtj yFYnwzt |||||||||| d WStj y`Ynwt |ttfsntd |d d |D}t |ttfstd |d d |D}|durd}t|d}|durd}t|d}tjd|||||||||d \} } }}|dd} | s|Strd|dd|dd|dd|dd|dd|dd|df}|j}td||| | S)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`. ReduceDatasetr5rrrrN)r5rrrrrrIExpected list for 'output_types' argument to 'reduce_dataset' Op, not %r.cSrrrrr r r!r"2r#z"reduce_dataset..JExpected list for 'output_shapes' argument to 'reduce_dataset' Op, not %r.cSrr%r&r'r r r!r"7r#Tr) r initial_staterr5rrrrrTstater)r)rr*r+rr,r-r.r/r0r1reduce_dataset_eager_fallbackr3r4r5r6r7rrrnr8r9r:r;rr<r=)rr?rr5rrrrrr?r@rArBrCrDrErFrGr r r!reduce_datasets         rBzraw_ops.ReduceDatasetc Cst|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}|dur:d}t|d }t|| \} }t|| \} }t |t j }|gt|t|} d |d | d | d |d|d|d |f} tj dt || | | |d}trtd| | ||S)Nr=cSrrrrr r r!r"]r#z1reduce_dataset_eager_fallback..r>cSrr%r&r'r r r!r"br#Trrrr5r@rrrs ReduceDatasetrLr<)r4r5r6r7rrrnrr/rrrrrr:r=)rr?rr5rrrrrrZ _attr_TstaterrGrFrAr r r!rAXsJ    rAcountc Cr)aCreates a dataset that emits the outputs of `input_dataset` `count` times. Args: input_dataset: A `Tensor` of type `variant`. count: A `Tensor` of type `int64`. A scalar representing the number of times that `input_dataset` should be repeated. A value of `-1` indicates that it should be repeated infinitely. 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`. RepeatDatasetrrrNrIExpected list for 'output_types' argument to 'repeat_dataset' Op, not %r.cSrrrrr r r!r"r#z"repeat_dataset..JExpected list for 'output_shapes' argument to 'repeat_dataset' Op, not %r.cSrr%r&r'r r r!r"r#rrrCrrrr)r)rr*r+rr,r-r.r/r0r1repeat_dataset_eager_fallbackr3r4r5r6r7rrnr8r9r:r;r<r=rrCrrrrr?r@rArBrCrDrErFrGr r r!repeat_datasetyrrJzraw_ops.RepeatDatasetc Cr)NrEcSrrrrr r r!r"r#z1repeat_dataset_eager_fallback..rFcSrr%r&r'r r r!r"r#rrrrs RepeatDatasetrKrLrDr rrCrrrrrrGrFrAr r r!rHrrH rewrite_namec Csftjpt}|j}|jrVzt|d|||d|d| }|WStjy6}z t ||WYd}~nd}~wtj y?Ynwz t ||||||dWStj yUYnwt |ttfsctd|dd|D}t |ttfswtd |d d|D}tjd|||||d \} } } } | dd}trd| dd| df} | j} td| | ||\}|S) 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.cSrrrrr r r!r"r#z#rewrite_dataset..KExpected list for 'output_shapes' argument to 'rewrite_dataset' Op, not %r.cSrr%r&r'r r r!r"r#)rrLrrr)r)rr*r+rr,r-r.r/r0r1rewrite_dataset_eager_fallbackr3r4r5r6r7r8r9rr:r;r<r=)rrLrrrr?r@rArBrCrDrErFrGr r r!rewrite_datasetsl    rQzraw_ops.RewriteDatasetc Cst|ttfs td|dd|D}t|ttfs!td|dd|D}t|tj}t|tj}||g}d|d|f}t j dd ||||d }t rWt d ||||\}|S) NrNcSrrrrr r r!r"r#z2rewrite_dataset_eager_fallback..rOcSrr%r&r'r r r!r"r#rrsRewriteDatasetrKrLrMr) rrLrrrrrGrFrAr r r!rPs6  rPc Cr)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)rrr)r)rr*r+rr,r-r.r/r0r1!serialize_iterator_eager_fallbackr3rrr8r9r:rr<r=) rrrr?r@rArBrCrDrErFrGr r r!serialize_iterator,sT   rTzraw_ops.SerializeIteratorcCr)NrrsSerializeIteratorrKrLrR) rrr/rrrrr:r=)rrrrrGrFrAr r r!rS_rrS num_shardsindexrequire_non_emptycCr)aCreates a `Dataset` that includes only 1/`num_shards` of this dataset. Args: input_dataset: A `Tensor` of type `variant`. num_shards: A `Tensor` of type `int64`. An integer representing the number of shards operating in parallel. index: A `Tensor` of type `int64`. An integer representing the current worker index. 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`. 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`. ShardDatasetrWrrrN)rWrrrrrHExpected list for 'output_types' argument to 'shard_dataset' Op, not %r.cSrrrrr r r!r"r#z!shard_dataset..IExpected list for 'output_shapes' argument to 'shard_dataset' Op, not %r.cSrr%r&r'r r r!r"r#Fr)rrUrVrrrWrr)r)rr*r+rr,r-r.r/r0r1shard_dataset_eager_fallbackr3r4r5r6r7rrrnr8r9r:rr;r<r=)rrUrVrrrWrrr?r@rArBrCrDrErFrGr r r! shard_datasetos       r\zraw_ops.ShardDatasetc Cst|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}|dur:d}t|d }t|t j }t|t j }t|t j }|||g} d|d |d |d |f} tj d d | | ||d} t r{td| | | | \} | S)NrYcSrrrrr r r!r"r#z0shard_dataset_eager_fallback..rZcSrr%r&r'r r r!r"r#FrWrrrrs ShardDatasetrKrLrXr4r5r6r7rrrnr/rrrrrr:r=) rrUrVrrrWrrrrGrFrAr r r!r[sH     r[reshuffle_each_iterationc Cstjpt} | j} | jrbzt| d| |||||d|d|d|d|} | WStjy=} z t | | WYd} ~ nd} ~ wtj yFYnwzt |||||||||| | d WStj yaYnwt |ttfsotd|d d |D}t |ttfstd |d d |D}|durd }t|d}|durd}t|d}tjd|||||||||| d \}}}}|dd} trd|dd|dd|dd|df}|j}td||| | \} | S)aCreates a dataset that shuffles and repeats 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. count: A `Tensor` of type `int64`. A scalar representing the number of times the underlying dataset should be repeated. The default is `-1`, which results in infinite repetition. 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`. ShuffleAndRepeatDatasetrrr^rN)rrr^rrrUExpected list for 'output_types' argument to 'shuffle_and_repeat_dataset' Op, not %r.cSrrrrr r r!r"r#z.shuffle_and_repeat_dataset..VExpected list for 'output_shapes' argument to 'shuffle_and_repeat_dataset' Op, not %r.cSrr%r&r'r r r!r"r#Tr) rr*r~rrCrrr^rr)r)rr*r+rr,r-r.r/r0r1)shuffle_and_repeat_dataset_eager_fallbackr3r4r5r6r7rrrnr8r9r:r;rr<r=)rr*r~rrCrrr^rrr?r@rArBrCrDrErFrGr r r!shuffle_and_repeat_datasets         rczraw_ops.ShuffleAndRepeatDatasetc Cs t|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}|dur:d}t|d }t|t j }t|t j }t|t j }t|t j }t|t j }|||||g} d |d |d|d |f} tj d d | | | | d} t rtd| | | | \} | S)Nr`cSrrrrr r r!r";r#z=shuffle_and_repeat_dataset_eager_fallback..racSrr%r&r'r r r!r"@r#Tr^rrrrsShuffleAndRepeatDatasetrKrLr_r])rr*r~rrCrrr^rrrrGrFrAr r r!rb6sN  rbseed_generatorc Cstjpt} | j} | jrdzt| d| ||||||d|d|d|d| } | WStjy>}z t || WYd}~nd}~wtj yGYnwzt |||||||||| | | d WStj ycYnwt |ttfsqtd|d d |D}t |ttfstd |d d |D}|durd }t|d}| durd} t| d} tjd|||||||||| | d \}}}}|dd} trd|dd|dd|dd|df}|j}td||| | \} | S)aTODO: 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`. count: 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`. ShuffleAndRepeatDatasetV2r^rrrNr^rrrrrXExpected list for 'output_types' argument to 'shuffle_and_repeat_dataset_v2' Op, not %r.cSrrrrr r r!r"r#z1shuffle_and_repeat_dataset_v2..YExpected list for 'output_shapes' argument to 'shuffle_and_repeat_dataset_v2' Op, not %r.cSrr%r&r'r r r!r"r#Tr) rr*r~rrCrdrrr^rr)r)rr*r+rr,r-r.r/r0r1,shuffle_and_repeat_dataset_v2_eager_fallbackr3r4r5r6r7rrrnr8r9r:rr;r<r=)rr*r~rrCrdrrr^rrr?r@rArBrCrDrErFrGr r r!shuffle_and_repeat_dataset_v2Ys         rjz!raw_ops.ShuffleAndRepeatDatasetV2c Cs0t|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}| dur:d} t| d } t|t j }t|t j }t|t j }t|t j }t|t j }t|t j }||||||g} d|d |d |d | f} tj d d | | | | d}trtd| | ||\}|S)NrgcSrrrrr r r!r"r#z@shuffle_and_repeat_dataset_v2_eager_fallback..rhcSrr%r&r'r r r!r"r#Tr^rrrrsShuffleAndRepeatDatasetV2rKrLrer4r5r6r7rrrnr/rrrrrrr:r=)rr*r~rrCrdrrr^rrrrGrFrAr r r!risR   ric Cstjpt} | j} | jr`zt| d|||||d|d|d|d|} | WStjy<} z t | |WYd} ~ nd} ~ wtj yEYnwzt |||||||||| d WStj y_Ynwt |ttfsmtd|d d |D}t |ttfstd |d d |D}|durd }t|d}|durd}t|d}tjd|||||||||d \} } }}|dd} trd|dd|dd|dd|df}|j}td||| | \} | S)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`. ShuffleDatasetr^rrrNrfJExpected list for 'output_types' argument to 'shuffle_dataset' Op, not %r.cSrrrrr r r!r"r#z#shuffle_dataset..KExpected list for 'output_shapes' argument to 'shuffle_dataset' Op, not %r.cSrr%r&r'r r r!r" r#Tr) rr*r~rrrr^rr)r)rr*r+rr,r-r.r/r0r1shuffle_dataset_eager_fallbackr3r4r5r6r7rrrnr8r9r:rr;r<r=)rr*r~rrrr^rrr?r@rArBrCrDrErFrGr r r!shuffle_datasets       rpzraw_ops.ShuffleDatasetc Cst|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}|dur:d}t|d }t|t j }t|t j }t|t j }t|t j }||||g} d|d |d |d |f} tj d d | | | |d} t rtd| | | | \} | S)NrmcSrrrrr r r!r"0r#z2shuffle_dataset_eager_fallback..rncSrr%r&r'r r r!r"5r#Tr^rrrrsShuffleDatasetrKrLrlr]) rr*r~rrrr^rrrrGrFrAr r r!ro+sL     rocCr)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.cSrrrrr r r!r"ur#z&shuffle_dataset_v2..NExpected list for 'output_shapes' argument to 'shuffle_dataset_v2' Op, not %r.cSrr%r&r'r r r!r"zr#r)rr*rdrrrr)r)rr*r+rr,r-r.r/r0r1!shuffle_dataset_v2_eager_fallbackr3r4r5r6r7rrnr8r9r:r;r<r=)rr*rdrrrrr?r@rArBrCrDrErFrGr r r!shuffle_dataset_v2Ms|     ruzraw_ops.ShuffleDatasetV2c Cr)NrrcSrrrrr r r!r"r#z5shuffle_dataset_v2_eager_fallback..rscSrr%r&r'r r r!r"r#rrrrsShuffleDatasetV2rKrLrq)r4r5r6r7rrnr/rrrrrrr:r=) rr*rdrrrrrrGrFrAr r r!rtrrtc Cstjpt} | j} | jrbzt| d| |||||d|d|d|d|} | WStjy=} z t | | WYd} ~ nd} ~ wtj yFYnwzt |||||||||| | d WStj yaYnwt |ttfsotd|d d |D}t |ttfstd |d d |D}|durd }t|d}|durd}t|d}tjd|||||||||| d \}}}}|dd} trd|dd|dd|dd|df}|j}td||| | \} | S)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`. ShuffleDatasetV3r^rrrNrfMExpected list for 'output_types' argument to 'shuffle_dataset_v3' Op, not %r.cSrrrrr r r!r"r#z&shuffle_dataset_v3..NExpected list for 'output_shapes' argument to 'shuffle_dataset_v3' Op, not %r.cSrr%r&r'r r r!r"r#Tr) rr*r~rrdrrr^rr)r)rr*r+rr,r-r.r/r0r1!shuffle_dataset_v3_eager_fallbackr3r4r5r6r7rrrnr8r9r:rr;r<r=)rr*r~rrdrrr^rrr?r@rArBrCrDrErFrGr r r!shuffle_dataset_v3s        rzzraw_ops.ShuffleDatasetV3c Cs t|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}|dur:d}t|d }t|t j }t|t j }t|t j }t|t j }t|t j }|||||g} d|d |d |d |f} tj d d | | | | d} trtd| | | | \} | S)NrwcSrrrrr r r!r"r#z5shuffle_dataset_v3_eager_fallback..rxcSrr%r&r'r r r!r" r#Tr^rrrrsShuffleDatasetV3rKrLrvrk)rr*r~rrdrrr^rrrrGrFrAr r r!rysN    ryc Cr)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.cSrrrrr r r!r"Kr#z skip_dataset..HExpected list for 'output_shapes' argument to 'skip_dataset' Op, not %r.cSrr%r&r'r r r!r"Pr#rrG)r)rr*r+rr,r-r.r/r0r1skip_dataset_eager_fallbackr3r4r5r6r7rrnr8r9r:r;r<r=rIr r r! skip_dataset$sr      rzraw_ops.SkipDatasetc Cr)Nr|cSrrrrr r r!r"kr#z/skip_dataset_eager_fallback..r}cSrr%r&r'r r r!r"pr#rrrrs SkipDatasetrKrLr{rrKr r r!r~frr~#TV_SparseTensorSliceDataset_Tvaluesindicesvalues dense_shapec Cstjpt}|j}|jrRz t|d||||}|WStjy3}z t ||WYd}~nd}~wtj y<Ynwz t |||||dWStj yQYnwt jd||||d\}}} } | dd}tr|d| df} | j} td| | ||\}|S)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`. SparseTensorSliceDatasetNra)rrrrTvalues)r)rr*r+rr,r-r.r/r0r1*sparse_tensor_slice_dataset_eager_fallbackr3r8r9rr:Z_get_attr_typer<r=) rrrrr?r@rArBrCrDrErFrGr r r!sparse_tensor_slice_datasetsD    rz raw_ops.SparseTensorSliceDatasetc Cs|t|g|g\}\}t|tj}t|tj}|||g}d|f}tjdd||||d}tr9td||||\}|S)NrsSparseTensorSliceDatasetrKrLr) rZargs_to_matching_eagerr/rrrrr:r=) rrrrrZ _attr_TvaluesrGrFrAr r r!rs rc C"tjpt}|j}|jrUzt|d||||d|}|WStjy5}z t ||WYd}~nd}~wtj y>Ynwz t ||||||dWStj yTYnw|dur[d}t |d}tjd|||||d\} } } } | dd}t rd| df} | j} t d| | ||\}|S)aCreates a dataset that emits the records from one or more TFRecord files. Args: filenames: A `Tensor` of type `string`. A scalar or 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 representing the number of bytes to buffer. A value of 0 means no buffering will be performed. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. TFRecordDatasetrNr,rr&r0r*rr)r)rr*r+rr,r-r.r/r0r1 tf_record_dataset_eager_fallbackr3rrnr8r9r:r;r<r=r&r0r*rrr?r@rArBrCrDrErFrGr r r!tf_record_datasetsR   rzraw_ops.TFRecordDatasetc C|durd}t|d}t|tj}t|tj}t|tj}|||g}d|f}tjdd||||d}trAt d||||\}|S)NrrsTFRecordDatasetrKrLrr/ r&r0r*rrrrGrFrAr r r!r"   r byte_offsetsc Cs(tjpt}|j}|jrWzt|d|||||d| }|WStjy6} z t | |WYd} ~ nd} ~ wtj y?Ynwz t |||||||dWStj yVYnw|dur]d}t |d}tjd||||||d\} } } } | dd}t rd| df} | j}t d|| ||\}|S)aFCreates a dataset that emits the records from one or more TFRecord files. Args: filenames: A `Tensor` of type `string`. A scalar or 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 representing the number of bytes to buffer. A value of 0 means no buffering will be performed. byte_offsets: A `Tensor` of type `int64`. A scalar or vector containing the number of bytes for each file that will be skipped prior to reading. metadata: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. TFRecordDatasetV2rNr,r)r&r0r*rrr)r)rr*r+rr,r-r.r/r0r1#tf_record_dataset_v2_eager_fallbackr3rrnr8r9r:r;r<r=)r&r0r*rrrr?r@rArBrCrDrErFrGr r r!tf_record_dataset_v2 sT   rzraw_ops.TFRecordDatasetV2c Cs|durd}t|d}t|tj}t|tj}t|tj}t|tj}||||g}d|f}tjdd||||d} trIt d||| | \} | S)NrrsTFRecordDatasetV2rKrLrr/) r&r0r*rrrrrGrFrAr r r!rJs$   rc Cr)aCreates a dataset that contains `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 taken. A value of `-1` indicates that all of `input_dataset` is taken. 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`. TakeDatasetrrrNrGExpected list for 'output_types' argument to 'take_dataset' Op, not %r.cSrrrrr r r!r"r#z take_dataset..HExpected list for 'output_shapes' argument to 'take_dataset' Op, not %r.cSrr%r&r'r r r!r"r#rrG)r)rr*r+rr,r-r.r/r0r1take_dataset_eager_fallbackr3r4r5r6r7rrnr8r9r:r;r<r=rIr r r! take_dataset]sr      rzraw_ops.TakeDatasetc Cr)NrcSrrrrr r r!r"r#z/take_dataset_eager_fallback..rcSrr%r&r'r r r!r"r#rrrrs TakeDatasetrKrLrrrKr r r!rrrc CsZtjpt}|j}|jrTzt|d||d|d|}|WStjy5}z t ||WYd}~nd}~wtj y>Ynwz t |||||dWStj ySYnwt |ttfsatd|dd|D}|durnd }t|d}tjd||||d \}}} } | dd}trd | d d| dd| df} | j} td| | ||\}|S) 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`. TensorDatasetrrNrJExpected list for 'output_shapes' argument to 'tensor_dataset' Op, not %r.cSrr%r&r'r r r!r"r#z"tensor_dataset..r) componentsrrrr)r)rr*r+rr,r-r.r/r0r1tensor_dataset_eager_fallbackr3r4r5r6r7rrnr8r9r:r;r<r=) rrrrr?r@rArBrCrDrErFrGr r r!tensor_datasetsb      rzraw_ops.TensorDatasetc Cst|ttfs td|dd|D}|durd}t|d}t||\}}t|}d|d|d|f}tjdd ||||d }trKt d ||||\}|S) NrcSrr%r&r'r r r!r"r#z1tensor_dataset_eager_fallback..rrrrs TensorDatasetrKrLrrI) rrrrrrrGrFrAr r r!rs0  ris_filescCstjpt}|j}|jrZzt|d||d|d|d|d| }|WStjy9} z t | |WYd} ~ nd} ~ wtj yBYnwz t |||||||dWStj yYYnwt |ttfsgtd|d d |D}|durtd }t|d}|durd }t|d}|durd }t|d}tjd||||||d \} } } } | dd}trd| dd| dd| dd| dd| df } | j}td|| ||\}|S)aCreates a dataset that emits each dim-0 slice of `components` 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`. 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`. TensorSliceDatasetrrrr6N)rrrr6rrPExpected list for 'output_shapes' argument to 'tensor_slice_dataset' Op, not %r.cSrr%r&r'r r r!r"1r#z(tensor_slice_dataset..Fr)rrrrr6rr)r)rr*r+rr,r-r.r/r0r1#tensor_slice_dataset_eager_fallbackr3r4r5r6r7rrrnr8r9r:r;rr<r=)rrrrr6rr?r@rArBrCrDrErFrGr r r!tensor_slice_dataset s|          rzraw_ops.TensorSliceDatasetc Cst|ttfs td|dd|D}|durd}t|d}|dur&d}t|d}|dur2d}t|d}t||\}}t|}d |d |d|d|d|f } tjd d || ||d } t rgt d|| | | \} | S)NrcSrr%r&r'r r r!r"Vr#z7tensor_slice_dataset_eager_fallback..Frrrr6rrsTensorSliceDatasetrKrLr) r4r5r6r7rrrnrrr:r=) rrrrr6rrrrGrFrAr r r!rQs>     rc Cr)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)r)rr*r+rr,r-r.r/r0r1 text_line_dataset_eager_fallbackr3rrnr8r9r:r;r<r=rr r r!text_line_datasetnsR   rzraw_ops.TextLineDatasetc Cr)NrrsTextLineDatasetrKrLrr/rr r r!rrr input_handlec CrJ)TODO: add doc. Args: input_handle: A `Tensor` of type `variant`. name: A name for the operation (optional). Returns: A `Tensor` of type `variant`. UnwrapDatasetVariantNrarrr )r)rr*r+rr,r-r.r/r0r1%unwrap_dataset_variant_eager_fallbackr3r8r9rr:r<r= rrr?r@rArBrCrDrErFrGr r r!unwrap_dataset_variantB  rzraw_ops.UnwrapDatasetVariantcCrO)NsUnwrapDatasetVariantrKrLrrPrrrrGrFrAr r r!rrQrsizeshiftstridec Cstjpt} | j} | jr_zt| d||||||d|d|d|} | WStjy;} z t | |WYd} ~ nd} ~ wtj yDYnwzt |||||||||| d WStj y^Ynwt |ttfsltd|dd |D}t |ttfstd |d d |D}|durd }t|d}tjd|||||||||d \} } }}|dd} trd|dd|dd|df}|j}td||| | \} | S)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.cSrrrrr r r!r"Mr#z"window_dataset..JExpected list for 'output_shapes' argument to 'window_dataset' Op, not %r.cSrr%r&r'r r r!r"Rr#r) rrrrrrrrr)r)rr*r+rr,r-r.r/r0r1window_dataset_eager_fallbackr3r4r5r6r7rrnr8r9r:r;r<r=)rrrrrrrrrr?r@rArBrCrDrErFrGr r r!window_datasetszE     rzraw_ops.WindowDatasetc Cst|ttfs td|dd|D}t|ttfs!td|dd|D}|dur.d}t|d}t|tj }t|tj }t|tj }t|tj }t|tj }|||||g} d|d |d|f} tj d d | | | |d } t r}td | | | | \} | S)NrcSrrrrr r r!r"or#z1window_dataset_eager_fallback..rcSrr%r&r'r r r!r"tr#rrrrs WindowDatasetrKrLr)r4r5r6r7rrnr/rrrrrrr:r=) rrrrrrrrrrrGrFrAr r r!rjsF  rc Csjtjpt}|j}|jrTzt|d||d|d|}|WStjy5}z t ||WYd}~nd}~wtj y>Ynwz t |||||dWStj ySYnwt |ttfsatd|dd|D}t |ttfsutd |d d|D}tjd||||d \}}} } | dd}trd| dd| dd | d f} | j} td| | ||\}|S) 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.cSrrrrr r r!r"r#zwindow_op..EExpected list for 'output_shapes' argument to 'window_op' Op, not %r.cSrr%r&r'r r r!r"r#)r<rrrTinputs)r)rr*r+rr,r-r.r/r0r1window_op_eager_fallbackr3r4r5r6r7r8r9rr:r;r<r=) r<rrrr?r@rArBrCrDrErFrGr r r! window_opsj     rzraw_ops.WindowOpc Cst|ttfs td|dd|D}t|ttfs!td|dd|D}t||\}}t|}d|d|d|f}tjd d ||||d }trStd ||||\}|S) NrcSrrrrr r r!r"r#z,window_op_eager_fallback..rcSrr%r&r'r r r!r"r#rrrsWindowOprKrLr) r4r5r6r7rrrr:r=) r<rrrrZ _attr_TinputsrGrFrAr r r!rs8 rc CrJ)rWrapDatasetVariantNrarr )r)rr*r+rr,r-r.r/r0r1#wrap_dataset_variant_eager_fallbackr3r8r9rr:r<r=rr r r!wrap_dataset_variantrrzraw_ops.WrapDatasetVariantcCrO)NsWrapDatasetVariantrKrLrrPrr r r!r rQrinput_datasetsc Cstjpt}|j}|jrWzt|d||d|d|d| }|WStjy7}z t ||WYd}~nd}~wtj y@Ynwz t ||||||dWStj yVYnwt |ttfsdtd|t|} t |ttfsutd|d d |D}t |ttfstd |d d |D}|durd }t|d}tjd|||||d\} } } } | dd}trd| dd| dd| dd| df} | j}td|| ||\}|S)a3Creates a dataset that zips together `input_datasets`. The elements of the resulting dataset are created by zipping corresponding elements from each of the input datasets. The size of the resulting dataset will match the size of the smallest input dataset, and no error will be raised if input datasets have different sizes. Args: input_datasets: A list of at least 1 `Tensor` objects with type `variant`. List of `N` variant Tensors representing datasets to be zipped together. 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`. ZipDatasetrrrNrHExpected list for 'input_datasets' argument to 'zip_dataset' Op, not %r.FExpected list for 'output_types' argument to 'zip_dataset' Op, not %r.cSrrrrr r r!r"A r#zzip_dataset..GExpected list for 'output_shapes' argument to 'zip_dataset' Op, not %r.cSrr%r&r'r r r!r"F r#r)rrrrrr)r)rr*r+rr,r-r.r/r0r1zip_dataset_eager_fallbackr3r4r5r6r7rrrnr8r9r:r;rr<r=)rrrrrr?r@rArBrrCrDrErFrGr r r! zip_dataset s      rzraw_ops.ZipDatasetc Cst|ttfs td|t|}t|ttfstd|dd|D}t|ttfs2td|dd|D}|dur?d}t|d}t|t j }t|}d |d |d |d|f}tj d d ||||d} t rqt d||| | \} | S)NrrcSrrrrr r r!r"f r#z.zip_dataset_eager_fallback..rcSrr%r&r'r r r!r"k r#rrrrrs ZipDatasetrKrLr)r4r5r6r7rrrnr/rrrrr:r=) rrrrrrrrGrFrAr r r!r\ sL   r)N)rN)FrN)rFN)FN)TFrN)rKN)rrrN)rrN)FrrN)rrN)TFFrN)TrFrN)rTrrN)rFN)TrN)rN)FrFN(P__doc__ collectionsZtensorflow.pythonrZtensorflow.python.eagerrr)rr-rrZtensorflow.python.frameworkrrZtensorflow.security.fuzzing.pyrZ_atypesrZ_op_def_registryr r/r r8Z"tensorflow.python.util.deprecationr Ztensorflow.python.utilr _dispatchZ tensorflow.python.util.tf_exportr typingrrZTensorFuzzingAnnotationResourcerHZ to_raw_oprr2 namedtuplerVrYrQrXr_r[r^rcrfr`rdrrrurhrsr|rwr{rZInt64rr}rrZBoolrrrZVariantstrrrrrrrrStringrrrrrrrrrrrrrrrintrrrrrrrrrrrrrrrrrrrrrrrrrrrr rr rr rrrrr%r!r$r.r+r-r3r1r2r:r4r9rHr;rGrMrKrLrXrTrWrdr]rbrrrlrpr{rwrzrr}rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrZInt32rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr rr rrrrrrr rrr%r!r$r*r&r)r2r.r1r;r7r:rBr<rArJrDrHrQrMrPrTrRrSr\rXr[rcr_rbrjrerirprlrorurqrtrzrvryrr{r~ZBFloat16Z Complex128Z Complex64ZFloat16ZFloat32ZFloat64ZHalfZInt16ZInt8ZQInt16ZQInt32ZQInt8ZQUInt16ZQUInt8ZUInt16ZUInt32ZUInt64ZUInt8rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr r r r!s^            5 95 )  B>&+"2-.6@2FKB6 E2B@>6@2*1&4E*.;*>&"& "6 *2& "& "& #" % %& 8"*M&*@&Z=Vf8b*J&Q& '"B Q>">*@"*;"7&7"<*'&&>"*"&: S6$U<M8$!L".?&:D6D.@*)&&Y":J4V RP4"E0LJH\UX^#SZB%b>Z!mVZ$sVv$|rN&aJN(bJL(VHR&IN( U$#?:J)FH7DV;R>@:$5 0D,H6D.&*f xb 7.&*6 H6