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dŅdӄZµedŌej!ej"ej#ej$ej%ej&ej'ej(ej)ej*ej+ej,ej-ej.ej/ej0ej1ej2ej3ej4ej5ej6ej7ej8ƒZ¶edÕej!ej"ej#ej$ej%ej&ej'ej(ej)ej*ej+ej,ej-ej.ej/ej0ej1ej2ej3ej4ej5ej6ej7ej8ƒZ·d7d7d8gdfde¶de·d9eSd:eSd;eTdej;ej2f dÖdׄZøedŲƒe =eø”ƒZ¹de¶de·d9eSd:eSd;eTdej;ej2f dŁdŚ„ZŗedŪej!ej"ej#ej$ej%ej&ej'ej(ej)ej*ej+ej,ej-ej.ej/ej0ej1ej2ej3ej4ej5ej6ej7ej8ƒZ»edÜej!ej"ej#ej$ej%ej&ej'ej(ej)ej*ej+ej,ej-ej.ej/ej0ej1ej2ej3ej4ej5ej6ej7ej8ƒZ¼dćde»de¼d9eSd:eSd;eTdej;ej2f dŻdŽ„Z½ed߃e =e½”ƒZ¾de»de¼d9eSd:eSd;eTdej;ej2f dądį„ZædS)åzUPython wrappers around TensorFlow ops. This file is MACHINE GENERATED! Do not edit. éN)Ś pywrap_tfe)Ścontext)Ścore)Śexecute)Śdtypes)Śannotation_types)Śop_def_registry)Śops)Śop_def_library)Śdeprecated_endpoints)Śdispatch)Ś tf_export)ŚTypeVarŚListŚTV_AnonymousHashTable_key_dtypeŚ!TV_AnonymousHashTable_value_dtypeŚ key_dtypeŚ value_dtypeŚreturnc Có"tjpt ”}|j}|jrRzt |d|d|d|”}|WStjy4}z t  ||”WYd}~nd}~wtj y=Ynwz t ||||dWStj yQYnwt  |d”}t  |d”}tjd|||d\}}}} | dd…}t  ”rŒd| d”d| d”f} |j} t  d| | |”|\}|S)a!Creates a uninitialized anonymous hash table. This op creates a new anonymous hash table (as a resource) everytime it is executed, with the specified dtype of its keys and values, returning the resource handle. Before using the table you will have to initialize it. After initialization the table will be immutable. The table is anonymous in the sense that it can only be accessed by the returned resource handle (e.g. it cannot be looked up by a name in a resource manager). The table will be automatically deleted when all resource handles pointing to it are gone. Args: key_dtype: A `tf.DType`. Type of the table keys. value_dtype: A `tf.DType`. Type of the table values. name: A name for the operation (optional). Returns: A `Tensor` of type `resource`. ŚAnonymousHashTablerrN©rrŚnameŚctx©rrr)Ś_contextrŚ_thread_local_dataŚis_eagerrŚTFE_Py_FastPathExecuteŚ_coreŚ_NotOkStatusExceptionŚ_opsŚraise_from_not_ok_statusŚ_FallbackExceptionŚ#anonymous_hash_table_eager_fallbackŚ_SymbolicExceptionŚ_executeŚ make_typeŚ_op_def_libraryŚ_apply_op_helperŚmust_record_gradientŚ_get_attr_typeŚinputsŚrecord_gradient© rrrŚ_ctxŚtldŚ_resultŚeŚ_Ś_opŚ_outputsŚ_attrsŚ _inputs_flat©r8śe/home/www/facesmatcher.com/pyenv/lib/python3.10/site-packages/tensorflow/python/ops/gen_lookup_ops.pyŚanonymous_hash_tablesN ž€’’’  ž  ’’r:zraw_ops.AnonymousHashTablecCó`t |d”}t |d”}g}d|d|f}tjdd||||d}t ”r+t d|||”|\}|S)NrrsAnonymousHashTableé©r,Śattrsrrr©r&r'rr*r-©rrrrr7r6r1r8r8r9r$Ss    ’’r$Ś+TV_AnonymousMutableDenseHashTable_key_dtypeŚ-TV_AnonymousMutableDenseHashTable_value_dtypeéēš™™™™™é?Ś empty_keyŚ deleted_keyŚinitial_num_bucketsŚmax_load_factorcCs˜tjpt ”}|j}|jr\zt |d|||d|d|d|d|” } | WStjy:} z t  | |”WYd} ~ nd} ~ wtj yCYnwz t ||||||||dWStj y[Ynwt  |d”}|durhg}t  |d”}|durtd}t  |d”}|dur€d }t  |d”}tjd|||||||d \} } } } | dd…} t  ”rĒd |  d ”d|  d”d|  d”d|  d”d|  d”f }| j}t  d||| ”| \} | S) a&Creates an empty anonymous mutable hash table that uses tensors as the backing store. This op creates a new anonymous mutable hash table (as a resource) everytime it is executed, with the specified dtype of its keys and values, returning the resource handle. Each value must be a scalar. Data can be inserted into the table using the insert operations. It does not support the initialization operation. It uses "open addressing" with quadratic reprobing to resolve collisions. The table is anonymous in the sense that it can only be accessed by the returned resource handle (e.g. it cannot be looked up by a name in a resource manager). The table will be automatically deleted when all resource handles pointing to it are gone. Args: empty_key: A `Tensor`. The key used to represent empty key buckets internally. Must not be used in insert or lookup operations. deleted_key: A `Tensor`. Must have the same type as `empty_key`. value_dtype: A `tf.DType`. Type of the table values. value_shape: An optional `tf.TensorShape` or list of `ints`. Defaults to `[]`. The shape of each value. initial_num_buckets: An optional `int`. Defaults to `131072`. The initial number of hash table buckets. Must be a power to 2. max_load_factor: An optional `float`. Defaults to `0.8`. The maximum ratio between number of entries and number of buckets before growing the table. Must be between 0 and 1. name: A name for the operation (optional). Returns: A `Tensor` of type `resource`. ŚAnonymousMutableDenseHashTablerŚ value_shaperGrHN)rrJrGrHrrrCrD)rErFrrJrGrHrr)rrrrrrrr r!r"r#Ś1anonymous_mutable_dense_hash_table_eager_fallbackr%r&r'Ś make_shapeŚmake_intŚ make_floatr(r)r*r+Śget_attrŚ _get_attr_intr,r-)rErFrrJrGrHrr/r0r1r2r3r4r5r6r7r8r8r9Ś"anonymous_mutable_dense_hash_tabledsv$ ü€’ż’    ł     ü’rQz&raw_ops.AnonymousMutableDenseHashTablec CsŹt |d”}|dur g}t |d”}|durd}t |d”}|dur$d}t |d”}t ||g|g”\}} | \}}||g} d|d|d|d|d|f } tjdd | | ||d } t ”r`t d | | | ”| \} | S) NrrJrCrGrDrHrsAnonymousMutableDenseHashTabler<r=rI) r&r'rLrMrNŚargs_to_matching_eagerrr*r-) rErFrrJrGrHrrŚ_attr_key_dtypeŚ_inputs_key_dtyper7r6r1r8r8r9rKĄs6    žž’rKŚ&TV_AnonymousMutableHashTable_key_dtypeŚ(TV_AnonymousMutableHashTable_value_dtypec Cr)aQCreates an empty anonymous mutable hash table. This op creates a new anonymous mutable hash table (as a resource) everytime it is executed, with the specified dtype of its keys and values, returning the resource handle. Each value must be a scalar. Data can be inserted into the table using the insert operations. It does not support the initialization operation. The table is anonymous in the sense that it can only be accessed by the returned resource handle (e.g. it cannot be looked up by a name in a resource manager). The table will be automatically deleted when all resource handles pointing to it are gone. Args: key_dtype: A `tf.DType`. Type of the table keys. value_dtype: A `tf.DType`. Type of the table values. name: A name for the operation (optional). Returns: A `Tensor` of type `resource`. ŚAnonymousMutableHashTablerrNrr)rrrrrrrr r!r"r#Ś+anonymous_mutable_hash_table_eager_fallbackr%r&r'r(r)r*r+r,r-r.r8r8r9Śanonymous_mutable_hash_tableŽsN ž€’’’  ž  ’’rYz!raw_ops.AnonymousMutableHashTablecCr;)NrrsAnonymousMutableHashTabler<r=rWr?r@r8r8r9rXs   ž’rXŚ/TV_AnonymousMutableHashTableOfTensors_key_dtypeŚ1TV_AnonymousMutableHashTableOfTensors_value_dtypec CsLtjpt ”}|j}|jrUzt |d|d|d|d|” }|WStjy6}z t  ||”WYd}~nd}~wtj y?Ynwz t |||||dWStj yTYnwt  |d”}t  |d”}|durgg}t  |d”}tjd||||d\}}} } | dd…}t  ”r”d|  d”d|  d”d|  d”f} | j} t  d| | |”|\}|S)aµCreates an empty anonymous mutable hash table of vector values. This op creates a new anonymous mutable hash table (as a resource) everytime it is executed, with the specified dtype of its keys and values, returning the resource handle. Each value must be a vector. Data can be inserted into the table using the insert operations. It does not support the initialization operation. The table is anonymous in the sense that it can only be accessed by the returned resource handle (e.g. it cannot be looked up by a name in a resource manager). The table will be automatically deleted when all resource handles pointing to it are gone. Args: key_dtype: A `tf.DType`. Type of the table keys. value_dtype: A `tf.DType`. Type of the table values. value_shape: An optional `tf.TensorShape` or list of `ints`. Defaults to `[]`. name: A name for the operation (optional). Returns: A `Tensor` of type `resource`. Ś"AnonymousMutableHashTableOfTensorsrrrJN)rrrJrr)rrrJr)rrrrrrrr r!r"r#Ś6anonymous_mutable_hash_table_of_tensors_eager_fallbackr%r&r'rLr(r)r*r+rOr,r-) rrrJrr/r0r1r2r3r4r5r6r7r8r8r9Ś'anonymous_mutable_hash_table_of_tensors)s\ ž€’ž’   ü   ž’r^z*raw_ops.AnonymousMutableHashTableOfTensorscCs|t |d”}t |d”}|durg}t |d”}g}d|d|d|f}tjdd||||d}t ”r9t d|||”|\}|S)NrrrJs"AnonymousMutableHashTableOfTensorsr<r=r\)r&r'rLrr*r-)rrrJrrr7r6r1r8r8r9r]js&    ’ž’r]ŚTV_HashTable_key_dtypeŚTV_HashTable_value_dtypeŚFŚ containerŚ shared_nameŚuse_node_name_sharingc Có tjpt ”}|j}|jrtdƒ‚t |d”}t |d”}|dur#d}t |d”}|dur/d}t |d”}|dur;d}t |d ”}t j d ||||||d \}}} } | dd…} t  ”rd|   d”d|   d”d |   d ”d|  d”d|  d”f } | j} t d | | | ”| \} | S) a–Creates a non-initialized hash table. This op creates a hash table, specifying the type of its keys and values. Before using the table you will have to initialize it. After initialization the table will be immutable. Args: key_dtype: A `tf.DType`. Type of the table keys. value_dtype: A `tf.DType`. Type of the table values. container: An optional `string`. Defaults to `""`. If non-empty, this table is placed in the given container. Otherwise, a default container is used. shared_name: An optional `string`. Defaults to `""`. If non-empty, this table is shared under the given name across multiple sessions. use_node_name_sharing: An optional `bool`. Defaults to `False`. If true and shared_name is empty, the table is shared using the node name. name: A name for the operation (optional). Returns: A `Tensor` of type mutable `string`. śLhash_table op does not support eager execution. Arg 'table_handle' is a ref.rrNrarbrcFrdŚ HashTable©rrrbrcrdr©rrrrŚ RuntimeErrorr&r'Śmake_strŚ make_boolr(r)r*rOŚ_get_attr_boolr+r,r-©rrrbrcrdrr/r0r3r4r5r1r6r7r8r8r9Ś hash_table€sD     ż     ü’rozraw_ops.HashTablecCótdƒ‚)Nrf©rj©rrrbrcrdrrr8r8r9Śhash_table_eager_fallback¼órsŚTV_HashTableV2_key_dtypeŚTV_HashTableV2_value_dtypecCó tjpt ”}|j}|jr[zt |d|d|d|d|d|d|” }|WStjy:} z t  | |”WYd} ~ nd} ~ wtj yCYnwz t |||||||dWStj yZYnwt  |d”}t  |d”}|durmd }t  |d”}|duryd }t  |d”}|dur…d }t  |d”}tjd||||||d \} } } } | dd…}t  ”rĖd|  d”d|  d”d|  d”d|  d”d|  d”f } | j}t  d|| |”|\}|S) aCreates a non-initialized hash table. This op creates a hash table, specifying the type of its keys and values. Before using the table you will have to initialize it. After initialization the table will be immutable. Args: key_dtype: A `tf.DType`. Type of the table keys. value_dtype: A `tf.DType`. Type of the table values. container: An optional `string`. Defaults to `""`. If non-empty, this table is placed in the given container. Otherwise, a default container is used. shared_name: An optional `string`. Defaults to `""`. If non-empty, this table is shared under the given name across multiple sessions. use_node_name_sharing: An optional `bool`. Defaults to `False`. If true and shared_name is empty, the table is shared using the node name. name: A name for the operation (optional). Returns: A `Tensor` of type `resource`. Ś HashTableV2rbrcrdrrN©rbrcrdrrrrraFrh)rrrrrrrr r!r"r#Śhash_table_v2_eager_fallbackr%r&r'rkrlr(r)r*rOrmr+r,r-©rrrbrcrdrr/r0r1r2r3r4r5r6r7r8r8r9Ś hash_table_v2Āsn ż€’ż’     ż     ü’r|zraw_ops.HashTableV2c Có“t |d”}t |d”}|durd}t |d”}|durd}t |d”}|dur*d}t |d”}g}d|d|d|d|d|f }tjdd ||||d } t ”rUt d ||| ”| \} | S) NrrrarbrcFrds HashTableV2r<r=rx©r&r'rkrlrr*r-© rrrbrcrdrrr7r6r1r8r8r9rzó2     ž ’’rzŚTV_InitializeTable_TkeyŚTV_InitializeTable_TvalŚ table_handleŚkeysŚvaluesc CóBtjpt ”}|j}|jrtdƒ‚tjd||||d\}}}}|S)alTable initializer that takes two tensors for keys and values respectively. Args: table_handle: A `Tensor` of type mutable `string`. Handle to a table which will be initialized. keys: A `Tensor`. Keys of type Tkey. values: A `Tensor`. Values of type Tval. name: A name for the operation (optional). Returns: The created Operation. śRinitialize_table op does not support eager execution. Arg 'table_handle' is a ref.ŚInitializeTable©rƒr„r…r©rrrrrjr(r)© rƒr„r…rr/r0r3r4r5r8r8r9Śinitialize_table*s žrŒzraw_ops.InitializeTablecCrp)Nr‡rq©rƒr„r…rrr8r8r9Śinitialize_table_eager_fallbackCrtrŽé’’’’ś ŚfilenameŚ key_indexŚ value_indexŚ vocab_sizeŚ delimiterŚoffsetc CsŖtjpt ”}|j} | jrtdƒ‚t |d”}t |d”}|dur#d}t |d”}|dur/d}t |d”}|dur;d }t |d ”}tj d ||||||||d  \} } } } | S) a”Initializes a table from a text file. It inserts one key-value pair into the table for each line of the file. The key and value is extracted from the whole line content, elements from the split line based on `delimiter` or the line number (starting from zero). Where to extract the key and value from a line is specified by `key_index` and `value_index`. - A value of -1 means use the line number(starting from zero), expects `int64`. - A value of -2 means use the whole line content, expects `string`. - A value >= 0 means use the index (starting at zero) of the split line based on `delimiter`. Args: table_handle: A `Tensor` of type mutable `string`. Handle to a table which will be initialized. filename: A `Tensor` of type `string`. Filename of a vocabulary text file. key_index: An `int` that is `>= -2`. Column index in a line to get the table `key` values from. value_index: An `int` that is `>= -2`. Column index that represents information of a line to get the table `value` values from. vocab_size: An optional `int` that is `>= -1`. Defaults to `-1`. Number of elements of the file, use -1 if unknown. delimiter: An optional `string`. Defaults to `"\t"`. Delimiter to separate fields in a line. offset: An optional `int`. Defaults to `0`. name: A name for the operation (optional). Returns: The created Operation. śainitialize_table_from_text_file op does not support eager execution. Arg 'table_handle' is a ref.r’r“Nrr”rr•rr–ŚInitializeTableFromTextFile©rƒr‘r’r“r”r•r–r) rrrrrjr&rMrkr(r)) rƒr‘r’r“r”r•r–rr/r0r3r4r5r8r8r9Śinitialize_table_from_text_fileFs0!     śršz#raw_ops.InitializeTableFromTextFilec Crp)Nr—rq) rƒr‘r’r“r”r•r–rrr8r8r9Ś.initialize_table_from_text_file_eager_fallback‚rtr›cCsFtjpt ”}|j} | jr_zt |d|||d|d|d|d|d|”} | WStjy<} z t  | |”WYd} ~ nd} ~ wtj yEYnwzt |||||||||d WStj y^Ynwt  |d”}t  |d”}|durqd }t  |d”}|dur}d }t  |d”}|dur‰d }t  |d”}tjd||||||||d  \} } } }| S) aŽInitializes a table from a text file. It inserts one key-value pair into the table for each line of the file. The key and value is extracted from the whole line content, elements from the split line based on `delimiter` or the line number (starting from zero). Where to extract the key and value from a line is specified by `key_index` and `value_index`. - A value of -1 means use the line number(starting from zero), expects `int64`. - A value of -2 means use the whole line content, expects `string`. - A value >= 0 means use the index (starting at zero) of the split line based on `delimiter`. Args: table_handle: A `Tensor` of type `resource`. Handle to a table which will be initialized. filename: A `Tensor` of type `string`. Filename of a vocabulary text file. key_index: An `int` that is `>= -2`. Column index in a line to get the table `key` values from. value_index: An `int` that is `>= -2`. Column index that represents information of a line to get the table `value` values from. vocab_size: An optional `int` that is `>= -1`. Defaults to `-1`. Number of elements of the file, use -1 if unknown. delimiter: An optional `string`. Defaults to `"\t"`. Delimiter to separate fields in a line. offset: An optional `int`. Defaults to `0`. name: A name for the operation (optional). Returns: The created Operation. ŚInitializeTableFromTextFileV2r’r“r”r•r–N)r’r“r”r•r–rrrrrr™)rrrrrrrr r!r"r#Ś1initialize_table_from_text_file_v2_eager_fallbackr%r&rMrkr(r))rƒr‘r’r“r”r•r–rr/r0r1r2r3r4r5r8r8r9Ś"initialize_table_from_text_file_v2…s\!   ż€’ż’     łržz%raw_ops.InitializeTableFromTextFileV2c Csŗt |d”}t |d”}|durd}t |d”}|durd}t |d”}|dur*d}t |d”}t |tj”}t |tj”}||g} d|d|d|d|d|f } tjd d| | ||d } d} | S) Nr’r“rr”rr•rr–sInitializeTableFromTextFileV2r=) r&rMrkr!Śconvert_to_tensorŚ_dtypesŚresourceŚstringr) rƒr‘r’r“r”r•r–rrr7r6r1r8r8r9rŅs.       ’žrŚTV_InitializeTableV2_TkeyŚTV_InitializeTableV2_Tvalc CóÄtjpt ”}|j}|jrRz t |d||||”}|WStjy3}z t  ||”WYd}~nd}~wtj y<Ynwz t |||||dWStj yQYnwt jd||||d\}}} } | S)afTable initializer that takes two tensors for keys and values respectively. Args: table_handle: A `Tensor` of type `resource`. Handle to a table which will be initialized. keys: A `Tensor`. Keys of type Tkey. values: A `Tensor`. Values of type Tval. name: A name for the operation (optional). Returns: The created Operation. ŚInitializeTableV2N©rrr‰)rrrrrrrr r!r"r#Ś"initialize_table_v2_eager_fallbackr%r(r)© rƒr„r…rr/r0r1r2r3r4r5r8r8r9Śinitialize_table_v2ķs4  ’€’ ’’žrŖzraw_ops.InitializeTableV2c Cónt |g|g”\}\}t |g|g”\}\}t |tj”}|||g}d|d|f}tjdd||||d} d} | S)NZTkeyZTvalsInitializeTableV2rr=©r&rRr!rŸr r”r) rƒr„r…rrZ _attr_TkeyZ _attr_Tvalr7r6r1r8r8r9rØó   ’rØŚLookupTableExportŚTV_LookupTableExport_TkeysŚTV_LookupTableExport_TvaluesŚTkeysŚTvaluesc Cs¦tjpt ”}|j}|jrtdƒ‚t |d”}t |d”}tjd||||d\}}}}|dd…} t  ”rLd|  d”d|  d”f} |j } t  d| | | ”t  | ”} | S)aqOutputs all keys and values in the table. Args: table_handle: A `Tensor` of type mutable `string`. Handle to the table. Tkeys: A `tf.DType`. Tvalues: A `tf.DType`. name: A name for the operation (optional). Returns: A tuple of `Tensor` objects (keys, values). keys: A `Tensor` of type `Tkeys`. values: A `Tensor` of type `Tvalues`. śUlookup_table_export op does not support eager execution. Arg 'table_handle' is a ref.r±r²r®©rƒr±r²rN)rrrrrjr&r'r(r)r*r+r,r-Ś_LookupTableExportOutputŚ_make) rƒr±r²rr/r0r3r4r5r1r6r7r8r8r9Ślookup_table_export%s*  ž  ’’ r·zraw_ops.LookupTableExportcCrp)Nr³rq)rƒr±r²rrr8r8r9Ś"lookup_table_export_eager_fallbackKrtrøŚLookupTableExportV2ŚTV_LookupTableExportV2_TkeysŚTV_LookupTableExportV2_Tvaluesc Cs6tjpt ”}|j}|jrYzt |d||d|d|”}t |”}|WStj y:}z t   ||”WYd}~nd}~wtj yCYnwz t |||||dWStjyXYnwt |d”}t |d”}tjd||||d\}}} } | dd…}t ”r”d|  d”d|  d”f} | j} t d| | |”t |”}|S)akOutputs all keys and values in the table. Args: table_handle: A `Tensor` of type `resource`. Handle to the table. Tkeys: A `tf.DType`. Tvalues: A `tf.DType`. name: A name for the operation (optional). Returns: A tuple of `Tensor` objects (keys, values). keys: A `Tensor` of type `Tkeys`. values: A `Tensor` of type `Tvalues`. r¹r±r²N)r±r²rrr“)rrrrrrŚ_LookupTableExportV2Outputr¶rr r!r"r#Ś%lookup_table_export_v2_eager_fallbackr%r&r'r(r)r*r+r,r-) rƒr±r²rr/r0r1r2r3r4r5r6r7r8r8r9Ślookup_table_export_v2UsP ž €’ ’’  ž  ’’ r¾zraw_ops.LookupTableExportV2cCstt |d”}t |d”}t |tj”}|g}d|d|f}tjdd||||d}t ”r3t d|||”t   |”}|S)Nr±r²sLookupTableExportV2ér=r¹) r&r'r!rŸr r”rr*r-r¼r¶)rƒr±r²rrr7r6r1r8r8r9r½‰s    ’’ r½ŚTV_LookupTableFind_TinŚTV_LookupTableFind_ToutŚ default_valuec CsŠtjpt ”}|j}|jrtdƒ‚tjd||||d\}}}}|dd…} t ”r@d|  d”d|  d”f} |j } t  d| | | ”| \} | S)abLooks up keys in a table, outputs the corresponding values. The tensor `keys` must of the same type as the keys of the table. The output `values` is of the type of the table values. The scalar `default_value` is the value output for keys not present in the table. It must also be of the same type as the table values. Args: table_handle: A `Tensor` of type mutable `string`. Handle to the table. keys: A `Tensor`. Any shape. Keys to look up. default_value: A `Tensor`. name: A name for the operation (optional). Returns: A `Tensor`. Has the same type as `default_value`. śSlookup_table_find op does not support eager execution. Arg 'table_handle' is a ref.ŚLookupTableFind©rƒr„rĀrNŚTinŚTout) rrrrrjr(r)r&r*r+r,r-) rƒr„rĀrr/r0r3r4r5r1r6r7r8r8r9Ślookup_table_find›s&ž  ’’rČzraw_ops.LookupTableFindcCrp)NrĆrq)rƒr„rĀrrr8r8r9Ś lookup_table_find_eager_fallbackĀrtrÉŚTV_LookupTableFindV2_TinŚTV_LookupTableFindV2_Toutc Cs tjpt ”}|j}|jrRz t |d||||”}|WStjy3}z t  ||”WYd}~nd}~wtj y<Ynwz t |||||dWStj yQYnwt jd||||d\}}} } | dd…}t ”rd|  d”d|  d”f} | j} t d| | |”|\}|S)a\Looks up keys in a table, outputs the corresponding values. The tensor `keys` must of the same type as the keys of the table. The output `values` is of the type of the table values. The scalar `default_value` is the value output for keys not present in the table. It must also be of the same type as the table values. Args: table_handle: A `Tensor` of type `resource`. Handle to the table. keys: A `Tensor`. Any shape. Keys to look up. default_value: A `Tensor`. name: A name for the operation (optional). Returns: A `Tensor`. Has the same type as `default_value`. ŚLookupTableFindV2Nr§rÅrĘrĒ)rrrrrrrr r!r"r#Ś#lookup_table_find_v2_eager_fallbackr%r(r)r&r*r+r,r-) rƒr„rĀrr/r0r1r2r3r4r5r6r7r8r8r9Ślookup_table_find_v2ČsH ’€’ ’’ž  ’’rĪzraw_ops.LookupTableFindV2c Csˆt |g|g”\}\}t |g|g”\}\}t |tj”}|||g}d|d|f}tjdd||||d} t ”r?t d||| ”| \} | S)NrĘrĒsLookupTableFindV2r<r=rĢ) r&rRr!rŸr r”rr*r-) rƒr„rĀrrŚ _attr_TinŚ _attr_Toutr7r6r1r8r8r9rĶūs   ’’rĶŚTV_LookupTableImport_TinŚTV_LookupTableImport_Toutc Cr†)aåReplaces the contents of the table with the specified keys and values. The tensor `keys` must be of the same type as the keys of the table. The tensor `values` must be of the type of the table values. Args: table_handle: A `Tensor` of type mutable `string`. Handle to the table. keys: A `Tensor`. Any shape. Keys to look up. values: A `Tensor`. Values to associate with keys. name: A name for the operation (optional). Returns: The created Operation. śUlookup_table_import op does not support eager execution. Arg 'table_handle' is a ref.ŚLookupTableImportr‰rŠr‹r8r8r9Ślookup_table_import óžrÕzraw_ops.LookupTableImportcCrp)NrÓrqrr8r8r9Ś"lookup_table_import_eager_fallback(rtr׌TV_LookupTableImportV2_TinŚTV_LookupTableImportV2_Toutc Cr„)aßReplaces the contents of the table with the specified keys and values. The tensor `keys` must be of the same type as the keys of the table. The tensor `values` must be of the type of the table values. Args: table_handle: A `Tensor` of type `resource`. Handle to the table. keys: A `Tensor`. Any shape. Keys to look up. values: A `Tensor`. Values to associate with keys. name: A name for the operation (optional). Returns: The created Operation. ŚLookupTableImportV2Nr§r‰)rrrrrrrr r!r"r#Ś%lookup_table_import_v2_eager_fallbackr%r(r)r©r8r8r9Ślookup_table_import_v2.ó4 ’€’ ’’žrÜzraw_ops.LookupTableImportV2c Cr«)NrĘrĒsLookupTableImportV2rr=r¬© rƒr„r…rrrĻrŠr7r6r1r8r8r9rŪUr­rŪŚTV_LookupTableInsert_TinŚTV_LookupTableInsert_Toutc Cr†)aŠUpdates the table to associates keys with values. The tensor `keys` must be of the same type as the keys of the table. The tensor `values` must be of the type of the table values. Args: table_handle: A `Tensor` of type mutable `string`. Handle to the table. keys: A `Tensor`. Any shape. Keys to look up. values: A `Tensor`. Values to associate with keys. name: A name for the operation (optional). Returns: The created Operation. śUlookup_table_insert op does not support eager execution. Arg 'table_handle' is a ref.ŚLookupTableInsertr‰rŠr‹r8r8r9Ślookup_table_insertdrÖrćzraw_ops.LookupTableInsertcCrp)Nrįrqrr8r8r9Ś"lookup_table_insert_eager_fallbackrträŚTV_LookupTableInsertV2_TinŚTV_LookupTableInsertV2_Toutc Cr„)aŹUpdates the table to associates keys with values. The tensor `keys` must be of the same type as the keys of the table. The tensor `values` must be of the type of the table values. Args: table_handle: A `Tensor` of type `resource`. Handle to the table. keys: A `Tensor`. Any shape. Keys to look up. values: A `Tensor`. Values to associate with keys. name: A name for the operation (optional). Returns: The created Operation. ŚLookupTableInsertV2Nr§r‰)rrrrrrrr r!r"r#Ś%lookup_table_insert_v2_eager_fallbackr%r(r)r©r8r8r9Ślookup_table_insert_v2…rŻrézraw_ops.LookupTableInsertV2c Cr«)NrĘrĒsLookupTableInsertV2rr=r¬rŽr8r8r9rč¬r­rčŚTV_LookupTableRemoveV2_Tinc Cs¾tjpt ”}|j}|jrPz t |d|||”}|WStjy2}z t  ||”WYd}~nd}~wtj y;Ynwz t ||||dWStj yOYnwt jd|||d\}}}} |S)a™Removes keys and its associated values from a table. The tensor `keys` must of the same type as the keys of the table. Keys not already in the table are silently ignored. Args: table_handle: A `Tensor` of type `resource`. Handle to the table. keys: A `Tensor`. Any shape. Keys of the elements to remove. name: A name for the operation (optional). Returns: The created Operation. ŚLookupTableRemoveV2Nr§)rƒr„r)rrrrrrrr r!r"r#Ś%lookup_table_remove_v2_eager_fallbackr%r(r)) rƒr„rr/r0r1r2r3r4r5r8r8r9Ślookup_table_remove_v2ŗs4 ’€’’’žrķzraw_ops.LookupTableRemoveV2cCsRt |g|g”\}\}t |tj”}||g}d|f}tjdd||||d}d}|S)NrĘsLookupTableRemoveV2rr=r¬)rƒr„rrrĻr7r6r1r8r8r9rģąs ’rģc Csrtjpt ”}|j}|jrtdƒ‚tjd||d\}}}}|dd…}t ”r4d}|j } t  d| ||”|\}|S)zęComputes the number of elements in the given table. Args: table_handle: A `Tensor` of type mutable `string`. Handle to the table. name: A name for the operation (optional). Returns: A `Tensor` of type `int64`. śSlookup_table_size op does not support eager execution. Arg 'table_handle' is a ref.ŚLookupTableSize©rƒrNr8) rrrrrjr(r)r&r*r,r-) rƒrr/r0r3r4r5r1r6r7r8r8r9Ślookup_table_sizeės  ’ ’rńzraw_ops.LookupTableSizecCrp)Nrīrq)rƒrrr8r8r9Ś lookup_table_size_eager_fallbackrtrņc Csģtjpt ”}|j}|jrNz t |d||”}|WStjy1}z t  ||”WYd}~nd}~wtj y:Ynwzt |||dWStj yMYnwt jd||d\}}}}|dd…}t ”rqd} |j} t d| | |”|\}|S)ząComputes the number of elements in the given table. Args: table_handle: A `Tensor` of type `resource`. Handle to the table. name: A name for the operation (optional). Returns: A `Tensor` of type `int64`. ŚLookupTableSizeV2Nr§ršr8)rrrrrrrr r!r"r#Ś#lookup_table_size_v2_eager_fallbackr%r(r)r&r*r,r-) rƒrr/r0r1r2r3r4r5r6r7r8r8r9Ślookup_table_size_v2 sB ’€’’’’ ’rõzraw_ops.LookupTableSizeV2cCsPt |tj”}|g}d}tjdd||||d}t ”r#t d|||”|\}|S)NsLookupTableSizeV2r<r=ró)r!rŸr r”r&rr*r-)rƒrrr7r6r1r8r8r9rō4s ’’rōŚ"TV_MutableDenseHashTable_key_dtypeŚ$TV_MutableDenseHashTable_value_dtypec Csltjpt ”} | j} | jrtdƒ‚t |d”}|durd}t |d”}|dur)d}t |d”}|dur5d}t |d”}|durAg}t  |d ”}|durMd }t  |d ”}|durYd }t  |d ”}t j d|||||||||d \} } } } | dd…}t ”r±d|  d”d|  d”d|  d”d|  d”d|  d”d |  d ”d |  d ”d |  d ”f}| j}t d|||”|\}|S)aóCreates an empty hash table that uses tensors as the backing store. It uses "open addressing" with quadratic reprobing to resolve collisions. This op creates a mutable hash table, specifying the type of its keys and values. Each value must be a scalar. Data can be inserted into the table using the insert operations. It does not support the initialization operation. Args: empty_key: A `Tensor`. The key used to represent empty key buckets internally. Must not be used in insert or lookup operations. value_dtype: A `tf.DType`. Type of the table values. container: An optional `string`. Defaults to `""`. If non-empty, this table is placed in the given container. Otherwise, a default container is used. shared_name: An optional `string`. Defaults to `""`. If non-empty, this table is shared under the given name across multiple sessions. use_node_name_sharing: An optional `bool`. Defaults to `False`. value_shape: An optional `tf.TensorShape` or list of `ints`. Defaults to `[]`. The shape of each value. initial_num_buckets: An optional `int`. Defaults to `131072`. The initial number of hash table buckets. Must be a power to 2. max_load_factor: An optional `float`. Defaults to `0.8`. The maximum ratio between number of entries and number of buckets before growing the table. Must be between 0 and 1. name: A name for the operation (optional). Returns: A `Tensor` of type mutable `string`. śZmutable_dense_hash_table op does not support eager execution. Arg 'table_handle' is a ref.rNrarbrcFrdrJrCrGrDrHŚMutableDenseHashTable) rErrbrcrdrJrGrHrr)rrrrrjr&r'rkrlrLrMrNr(r)r*rOrmr+rPr,r-)rErrbrcrdrJrGrHrr/r0r3r4r5r1r6r7r8r8r9Śmutable_dense_hash_tableDs`#       ś        ł’rśzraw_ops.MutableDenseHashTablec Crp)Nrųrq) rErrbrcrdrJrGrHrrr8r8r9Ś'mutable_dense_hash_table_eager_fallback™rtrūŚ$TV_MutableDenseHashTableV2_key_dtypeŚ&TV_MutableDenseHashTableV2_value_dtypec Cstjpt ”} | j} | jrezt | d| ||d|d|d|d|d|d|d|”} | WStjy@} z t  | | ”WYd } ~ nd } ~ wtj yIYnwzt |||||||||| | d  WStj ydYnwt  |d”}|d urqd }t  |d”}|d ur}d }t  |d”}|d ur‰d }t  |d”}|d ur•g}t  |d”}|d ur”d }t  |d”}|d ur­d}t  |d”}tjd|||||||||| d \}}}}|d d …} t  ”rd| d”d| d”d| d”d| d”d| d”d| d”d| d”d| d”f}|j}t  d||| ”| \} | S)a2Creates an empty hash table that uses tensors as the backing store. It uses "open addressing" with quadratic reprobing to resolve collisions. This op creates a mutable hash table, specifying the type of its keys and values. Each value must be a scalar. Data can be inserted into the table using the insert operations. It does not support the initialization operation. Args: empty_key: A `Tensor`. The key used to represent empty key buckets internally. Must not be used in insert or lookup operations. deleted_key: A `Tensor`. Must have the same type as `empty_key`. value_dtype: A `tf.DType`. Type of the table values. container: An optional `string`. Defaults to `""`. If non-empty, this table is placed in the given container. Otherwise, a default container is used. shared_name: An optional `string`. Defaults to `""`. If non-empty, this table is shared under the given name across multiple sessions. use_node_name_sharing: An optional `bool`. Defaults to `False`. value_shape: An optional `tf.TensorShape` or list of `ints`. Defaults to `[]`. The shape of each value. initial_num_buckets: An optional `int`. Defaults to `131072`. The initial number of hash table buckets. Must be a power to 2. max_load_factor: An optional `float`. Defaults to `0.8`. The maximum ratio between number of entries and number of buckets before growing the table. Must be between 0 and 1. name: A name for the operation (optional). Returns: A `Tensor` of type `resource`. ŚMutableDenseHashTableV2rbrcrdrrJrGrHN) rbrcrdrrJrGrHrrraFrCrD) rErFrrbrcrdrJrGrHrr)rrrrrrrr r!r"r#Ś*mutable_dense_hash_table_v2_eager_fallbackr%r&r'rkrlrLrMrNr(r)r*rOrmr+rPr,r-)rErFrrbrcrdrJrGrHrr/r0r1r2r3r4r5r6r7r8r8r9Śmutable_dense_hash_table_v2Ÿsš$ ū€’ś’       ÷        ł’rzraw_ops.MutableDenseHashTableV2c Cst |d”}|dur d}t |d”}|durd}t |d”}|dur$d}t |d”}|dur0g}t |d”}|durs*            hh 5hh@Y6hh 6hh$>hh,9*hh,I*hh,*8968J6hh,"* žhh #žhh 1hh6$4hh604hh,*hh,$*h h,*hh,$*h "# $ "$&"h hHR8hhRkBh&h,:*hh6?*hh6Q*hh,K.