o i eE@sdZddlZddlmZddlmZddlmZddlm Z ddl m Z ddlmZdd l mZdd l mZdd l mZdd lmZdd lmZddlmZddlmZm Z e!dgdZ"edej#ej$Z%edej&ej'ej#ej$Z(d2dej)e%dej)e(de*de+de+f ddZ,ede-e,Z.dej)e%dej)e(de*de+de+f ddZ/e!dgdZ0ed ej#ej$Z1ed!ej&ej'ej#ej$Z2d2d"ej)ej$dej)e1dej)e2de*de+de+f d#d$Z3ed%e-e3Z4d"ej)ej$dej)e1dej)e2de*de+de+f d&d'Z5e!d(gdZ6ed)ej#ej$Z7ed*ej&ej'ej#ej$Z8d2d+ej)ej$dej)e7d,ej)ej$dej)e8de*de+de+fd-d.Z9ed/e-e9Z:d+ej)ej$dej)e7d,ej)ej$dej)e8de*de+de+fd0d1Z;dS)3zUPython 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)TypeVarListDenseCountSparseOutput)output_indices output_valuesoutput_dense_shapeTV_DenseCountSparseOutput_T%TV_DenseCountSparseOutput_output_typevaluesweights binary_output minlength maxlengthc Cstjpt}|j}|jr^zt|d|||d|d|d| }t|}|WStj y=} z t | |WYd} ~ nd} ~ wtj yFYnwz t |||||||dWStjy]Ynwt|d}|durjd}t|d}|durvd}t|d}tjd||||||d\} } } } | dd}trd | d d| dd| dd| dd | d f } | j}td|| |t|}|S) aPerforms sparse-output bin counting for a tf.tensor input. Counts the number of times each value occurs in the input. Args: values: A `Tensor`. Must be one of the following types: `int32`, `int64`. Tensor containing data to count. weights: A `Tensor`. Must be one of the following types: `int32`, `int64`, `float32`, `float64`. A Tensor of the same shape as indices containing per-index weight values. May also be the empty tensor if no weights are used. binary_output: A `bool`. Whether to output the number of occurrences of each value or 1. minlength: An optional `int` that is `>= -1`. Defaults to `-1`. Minimum value to count. Can be set to -1 for no minimum. maxlength: An optional `int` that is `>= -1`. Defaults to `-1`. Maximum value to count. Can be set to -1 for no maximum. name: A name for the operation (optional). Returns: A tuple of `Tensor` objects (output_indices, output_values, output_dense_shape). output_indices: A `Tensor` of type `int64`. output_values: A `Tensor`. Has the same type as `weights`. output_dense_shape: A `Tensor` of type `int64`. rrrrNrrrnamectxr)rrrrrrT output_type)_contextr_thread_local_datais_eagerrTFE_Py_FastPathExecute_DenseCountSparseOutputOutput_make_core_NotOkStatusException_opsraise_from_not_ok_status_FallbackException(dense_count_sparse_output_eager_fallback_SymbolicException_execute make_boolmake_int_op_def_library_apply_op_helpermust_record_gradient_get_attr_type _get_attr_int_get_attr_boolinputsrecord_gradient)rrrrrr_ctxtld_resulte__op_outputs_attrs _inputs_flatrBR/var/www/myenv/lib/python3.10/site-packages/tensorflow/python/ops/gen_count_ops.pydense_count_sparse_outputsf            rDzraw_ops.DenseCountSparseOutputc Cst|d}|dur d}t|d}|durd}t|d}t|g|tjtjg\}\}t|g|tjtjtjtjg\}\}||g} d|d|d|d|d|f } tj dd| | ||d } t rgt d | | | t | } | S) Nrrrrrr sDenseCountSparseOutputr7attrsrrr)r.r/r0args_to_matching_eager_dtypesint32int64float32float64rr3r8r%r&) rrrrrrr_attr_T_attr_output_typerAr@r;rBrBrCr,is.   &  r,RaggedCountSparseOutputTV_RaggedCountSparseOutput_T&TV_RaggedCountSparseOutput_output_typesplitscCstjpt}|j}|jr`zt|d||||d|d|d| } t| } | WStj y>} z t | |WYd} ~ nd} ~ wtj yGYnwz t ||||||||dWStjy_Ynwt|d}|durld}t|d}|durxd}t|d}tjd|||||||d\} } } } | dd} trd | d d| dd| dd| dd | d f }| j}td||| t| } | S) aPerforms sparse-output bin counting for a ragged tensor input. Counts the number of times each value occurs in the input. Args: splits: A `Tensor` of type `int64`. Tensor containing the row splits of the ragged tensor to count. values: A `Tensor`. Must be one of the following types: `int32`, `int64`. Tensor containing values of the sparse tensor to count. weights: A `Tensor`. Must be one of the following types: `int32`, `int64`, `float32`, `float64`. A Tensor of the same shape as indices containing per-index weight values. May also be the empty tensor if no weights are used. binary_output: A `bool`. Whether to output the number of occurrences of each value or 1. minlength: An optional `int` that is `>= -1`. Defaults to `-1`. Minimum value to count. Can be set to -1 for no minimum. maxlength: An optional `int` that is `>= -1`. Defaults to `-1`. Maximum value to count. Can be set to -1 for no maximum. name: A name for the operation (optional). Returns: A tuple of `Tensor` objects (output_indices, output_values, output_dense_shape). output_indices: A `Tensor` of type `int64`. output_values: A `Tensor`. Has the same type as `weights`. output_dense_shape: A `Tensor` of type `int64`. rPrrrNrr)rSrrrrrrrr )r!rr"r#rr$_RaggedCountSparseOutputOutputr&r'r(r)r*r+)ragged_count_sparse_output_eager_fallbackr-r.r/r0r1r2r3r4r5r6r7r8)rSrrrrrrr9r:r;r<r=r>r?r@rArBrBrCragged_count_sparse_outputsj             rVzraw_ops.RaggedCountSparseOutputc Cst|d}|dur d}t|d}|durd}t|d}t|g|tjtjg\}\}t|g|tjtjtjtjg\} \}t |tj}|||g} d|d|d|d|d| f } tj dd| | ||d } t rot d | | | t| } | S) Nrrrrrr sRaggedCountSparseOutputrErFrP)r.r/r0rHrIrJrKrLrMr)convert_to_tensorrr3r8rTr&) rSrrrrrrrrNrOrAr@r;rBrBrCrUs0   &   rUSparseCountSparseOutputTV_SparseCountSparseOutput_T&TV_SparseCountSparseOutput_output_typeindices dense_shapecCstjpt}|j} | jrbzt|d|||||d|d|d| } t| } | WStj y?} z t | |WYd} ~ nd} ~ wtj yHYnwzt |||||||||d WStjyaYnwt|d}|durnd}t|d}|durzd}t|d}tjd||||||||d \} } } }|dd} trd | d d| dd| dd| dd | d f }| j}td||| t| } | S) aPerforms sparse-output bin counting for a sparse tensor input. Counts the number of times each value occurs in the input. Args: indices: A `Tensor` of type `int64`. Tensor containing the indices of the sparse tensor to count. values: A `Tensor`. Must be one of the following types: `int32`, `int64`. Tensor containing values of the sparse tensor to count. dense_shape: A `Tensor` of type `int64`. Tensor containing the dense shape of the sparse tensor to count. weights: A `Tensor`. Must be one of the following types: `int32`, `int64`, `float32`, `float64`. A Tensor of the same shape as indices containing per-index weight values. May also be the empty tensor if no weights are used. binary_output: A `bool`. Whether to output the number of occurrences of each value or 1. minlength: An optional `int` that is `>= -1`. Defaults to `-1`. Minimum value to count. Can be set to -1 for no minimum. maxlength: An optional `int` that is `>= -1`. Defaults to `-1`. Maximum value to count. Can be set to -1 for no maximum. name: A name for the operation (optional). Returns: A tuple of `Tensor` objects (output_indices, output_values, output_dense_shape). output_indices: A `Tensor` of type `int64`. output_values: A `Tensor`. Has the same type as `weights`. output_dense_shape: A `Tensor` of type `int64`. rXrrrNrr)r[rr\rrrrrrr )r!rr"r#rr$_SparseCountSparseOutputOutputr&r'r(r)r*r+)sparse_count_sparse_output_eager_fallbackr-r.r/r0r1r2r3r4r5r6r7r8)r[rr\rrrrrr9r:r;r<r=r>r?r@rArBrBrCsparse_count_sparse_outputsl             r_zraw_ops.SparseCountSparseOutputc  Cst|d}|dur d}t|d}|durd}t|d}t|g|tjtjg\} \}t|g|tjtjtjtjg\} \}t |tj}t |tj}||||g} d| d|d|d|d| f } tj dd| | ||d } t rwt d | | | t| } | S) Nrrrrrr sSparseCountSparseOutputrErFrX)r.r/r0rHrIrJrKrLrMr)rWrr3r8r]r&)r[rr\rrrrrrrNrOrAr@r;rBrBrCr^Es2   &   r^)rrN)<__doc__ collectionstensorflow.pythonrtensorflow.python.eagerrr!rr'rr.tensorflow.python.frameworkrrItensorflow.security.fuzzing.pyr_atypesr_op_def_registryr r)r r1"tensorflow.python.util.deprecationr tensorflow.python.utilr _dispatch tensorflow.python.util.tf_exportr typingrr namedtupler%Int32Int64rFloat32Float64rTensorFuzzingAnnotationboolintrD to_raw_oprr,rTrQrRrVrPrUr]rYrZr_rXr^rBrBrBrCsT            ,G*8K6DNF