o i e"@sdZddlmZddlmZddlmZddlZddlZddlmm Z ddl m Z ddl mZGdd d e Zd d Zd d ZddZdS)z+This API defines FeatureColumn abstraction.)absolute_import)division)print_functionN)Layer)serialization_libcsjeZdZdZ dfdd ZfddZddZd d Zd d Zd dZ fddZ e dddZ Z S)_BaseFeaturesLayerahBase class for DenseFeatures and SequenceFeatures. Defines common methods and helpers. Args: feature_columns: An iterable containing the FeatureColumns to use as inputs to your model. expected_column_type: Expected class for provided feature columns. trainable: Boolean, whether the layer's variables will be updated via gradient descent during training. name: Name to give to the DenseFeatures. **kwargs: Keyword arguments to construct a layer. Raises: ValueError: if an item in `feature_columns` doesn't match `expected_column_type`. Nc sftjd||d|t||_tjj||j|_ ||_ |jD]}t ||s0t d ||q!dS)N)name trainablezItems of feature_columns must be a {}. You can wrap a categorical column with an embedding_column or indicator_column. Given: {})super__init___normalize_feature_columns_feature_columnstf __internal__feature_column StateManagerr _state_manager _partitioner isinstance ValueErrorformat)selffeature_columnsexpected_column_typer r partitionerkwargscolumn __class__r Z/var/www/myenv/lib/python3.10/site-packages/keras/src/feature_column/base_feature_layer.pyr 4s    z_BaseFeaturesLayer.__init__c s|jD]=}tjjj|j|jd(tjjt|j||j Wdn1s,wYWdn1s;wYqt ddS)N)r) rrcompatv1variable_scoperr(_sanitize_column_name_for_variable_scope create_staterr build)r_rrr r r&Ms z_BaseFeaturesLayer.buildcCstd)aComputes expected output shape of the dense tensor of the layer. Args: input_shape: Tensor or array with batch shape. num_elements: Size of the last dimension of the output. Returns: Tuple with output shape. zCalling an abstract method.)NotImplementedError)r input_shape num_elementsr r r _output_shapeXs z _BaseFeaturesLayer._output_shapecCs*d}|jD] }||j7}q|||S)Nr)rvariable_shaper* _target_shape)rr)total_elementsrr r r compute_output_shapeds  z'_BaseFeaturesLayer.compute_output_shapecCs*|j}|t||}tj||dS)aReshapes the dense tensor output of a column based on expected shape. Args: column: A DenseColumn or SequenceDenseColumn object. tensor: A dense tensor obtained from the same column. Returns: Reshaped dense tensor. )shape)r,r*r-rr0reshape)rrtensorr* target_shaper r r _process_dense_tensorjs z(_BaseFeaturesLayer._process_dense_tensorcCst||jt|dS)z>Verifies and concatenates the dense output of several columns.)"_verify_static_batch_size_equalityrrconcat)routput_tensorsr r r _verify_and_concat_tensorsxs z-_BaseFeaturesLayer._verify_and_concat_tensorscsNdd|jD}d|i}t|j|d<t}tt|t|S)NcSsg|] }tjj|qSr )rrrserialize_feature_column).0fcr r r s z1_BaseFeaturesLayer.get_config..rr) rrserialize_keras_objectrr get_configdictlistitems)rcolumn_configsconfig base_configrr r r?s z_BaseFeaturesLayer.get_configcsJ|}ifdd|dD|d<t|d|d<|di|S)Ncsg|] }tjj|qSr )rrrdeserialize_feature_column)r;ccolumns_by_namecustom_objectsr r r=s z2_BaseFeaturesLayer.from_config..rrr )copyrdeserialize_keras_object)clsrDrJ config_cpr rHr from_configs  z_BaseFeaturesLayer.from_configN)__name__ __module__ __qualname____doc__r r&r+r/r4r9r? classmethodrO __classcell__r r rr r!s     rcCstd}|d|S)zASanitizes user-provided feature names for use as variable scopes.z[^A-Za-z0-9_.\-]r')recompilesub)r invalid_charr r r r$s  r$cCsd}tdt|D]5}tjjtj||jd}|jdur>|dur)|}|}q | |s>t d ||j ||j ||q dS)zVerify equality between static batch sizes. Args: tensors: iterable of input tensors. columns: Corresponding feature columns. Raises: ValueError: in case of mismatched batch sizes. NrzcBatch size (first dimension) of each feature must be same. Batch size of columns ({}, {}): ({}, {})) rangelenrr!r" Dimensiondimension_valuer0valueis_compatible_withrrr)tensorscolumnsexpected_batch_sizei batch_sizebath_size_column_indexr r r r6s*   r6cCst|tjjjr |g}t|tjjrt|}t|t rt d|D]}t|tjjjs5t d t ||q!|ssz,_normalize_feature_columns..)key)rrrr FeatureColumn collectionsabcIteratorrAr@rrtypersorted)rrname_to_columnr r r r s4     r )rT __future__rrrrkrWtensorflow.compat.v2r!v2rkeras.src.engine.base_layerrkeras.src.savingrrr$r6r r r r r s     |