BVhRAdZddlZddlZddlZddlmZddlmZddl m Z ddl m Z ddl m Z ddl mZdd l mZdd l mZdd l mZdd l mZdd l mZddl mZddlmZddlmZddlmZddlmZddlmZGdde j>Z edGddejBejDe jFZ!ejHdgdZ%edGddejLZ'ejPejRe'ejTjVedgd$dZ, d%dZ- d%d Z.d$d!Z/d"Z0d%d#Z1ejde!e1y)&zIndexed slices.N) struct_pb2)tf2)context)composite_tensor)composite_tensor_gradient)dtypes)ops)tensor_conversion_registry) tensor_shape) tensor_spec) tensor_util) type_spec) gen_math_ops)nested_structure_coder)internal)collections_abc) tf_exportceZdZdZdZdZy)$IndexedSlicesCompositeTensorGradientz*CompositeTensorGradient for IndexedSlices.c|SNselfvalues Z/home/dcms/DCMS/lib/python3.12/site-packages/tensorflow/python/framework/indexed_slices.pyget_gradient_componentsz> D0`. The values in `indices` are the indices in the first dimension of the slices that have been extracted from the larger tensor. The dense tensor `dense` represented by an `IndexedSlices` `slices` has ```python dense[slices.indices[i], :, :, :, ...] = slices.values[i, :, :, :, ...] ``` The `IndexedSlices` class is used principally in the definition of gradients for operations that have sparse gradients (e.g. `tf.gather`). >>> v = tf.Variable([[0.,1, 2], [2, 3, 4], [4, 5, 6], [6, 7, 8]]) >>> with tf.GradientTape() as tape: ... r = tf.gather(v, [1,3]) >>> index_slices = tape.gradient(r,v) >>> index_slices <...IndexedSlices object ...> >>> index_slices.indices.numpy() array([1, 3], dtype=int32) >>> index_slices.values.numpy() array([[1., 1., 1.], [1., 1., 1.]], dtype=float32) Contrast this representation with `tf.sparse.SparseTensor`, which uses multi-dimensional indices and scalar values. Nc.||_||_||_y)zCreates an `IndexedSlices`.N)_values_indices _dense_shape)rvaluesindices dense_shapes r__init__zIndexedSlices.__init__bsDLDM#Drc|jS)z/A `Tensor` containing the values of the slices.)r)rs rr,zIndexedSlices.valueshs <<rc|jS)z4A 1-D `Tensor` containing the indices of the slices.)r*r1s rr-zIndexedSlices.indicesms ==rc|jS)zFA 1-D `Tensor` containing the shape of the corresponding dense tensor.)r+r1s rr.zIndexedSlices.dense_shapers   rc|jtjdStj|jS)zyGets the `tf.TensorShape` representing the shape of the dense tensor. Returns: A `tf.TensorShape` object. N)r+r TensorShaper constant_value_as_shaper1s rshapezIndexedSlices.shapews8   % %d ++  . .t/@/@ AArc.|jjS)z!The name of this `IndexedSlices`.)r,namer1s rr9zIndexedSlices.names ;;  rc.|jjS)zEThe name of the device on which `values` will be produced, or `None`.)r,devicer1s rr;zIndexedSlices.devices ;;  rreturnc.|jjS)z4The `Operation` that produces `values` as an output.)r,opr1s rr>zIndexedSlices.ops ;;>>rc.|jjS)z'The `DType` of elements in this tensor.)r,dtyper1s rr@zIndexedSlices.dtypes ;;  rc.|jjS)zAThe `Graph` that contains the values, indices, and shape tensors.)r)graphr1s rrBzIndexedSlices.graphs <<  rc|d|jd|j|jd|jdSddS)NzIndexedSlices(indices=z , values=z, dense_shape=))r*r)r+r1s r__str__zIndexedSlices.__str__sS t||"&"3"3"?$    H IIFH H IIrcZt|j |j|jSr)r&r,r-r.r1s r__neg__zIndexedSlices.__neg__s! $++t||T5E5E FFrc|jjj|jjdd}t j dgj |jjdd}|jE|jj}|jtj|j}nd}t||j|jj||SN) r*r7 merge_withr)r r5 concatenater+r@r r6IndexedSlicesSpec)r indices_shaper.dense_shape_dtypes r _type_speczIndexedSlices._type_specsMM''224<<3E3Ebq3IJM**D62>> 12 K $++11**  - -d.?.? @Bk [$**dmm6I6I.  ??rc|dd}tjdgj|dd}|jd}n|jj}t ||j|j j||SrJ)r r5rMr+r@rNr*)rr7rOr.rPs r_shape_invariant_to_type_specz+IndexedSlices._shape_invariant_to_type_specs| "1IM**D62>>uQRyIK  ++11 [$**dmm6I6I.  ??rc"|jSr) _consumersr1s r consumerszIndexedSlices.consumerss ?? rr)r"r#r$r%r/propertyr,r-r.r7r9r;r Operationr>r@GraphrBrFrHr__composite_gradient__rQrSrVrrrr&r&6s  %N$         B  B     #--    SYY I G@A  ?  ? ?rIndexedSlicesValue)r,r-r.rNceZdZdZgdZedZdejejddfdZ dZ edZ dZ d Zy) rNz,Type specification for a `tf.IndexedSlices`._shape _values_dtype_indices_dtype_dense_shape_dtype_indices_shapectSr)r&r1s rzIndexedSlicesSpec.s]rNc:tj||_tj||_tj||_|d|_ntj||_tj|jd|_ y)aConstructs a type specification for a `tf.IndexedSlices`. Args: shape: The dense shape of the `IndexedSlices`, or `None` to allow any dense shape. dtype: `tf.DType` of values in the `IndexedSlices`. indices_dtype: `tf.DType` of the `indices` in the `IndexedSlices`. One of `tf.int32` or `tf.int64`. dense_shape_dtype: `tf.DType` of the `dense_shape` in the `IndexedSlices`. One of `tf.int32`, `tf.int64`, or `None` (if the `IndexedSlices` has no `dense_shape` tensor). indices_shape: The shape of the `indices` component, which indicates how many slices are in the `IndexedSlices`. NrK) r as_shaper^ras_dtyper_r`ra with_rankrb)rr7r@ indices_dtyperPrOs rr/zIndexedSlicesSpec.__init__sv"''.DK/D //-8D $d &0A Bd&// >HHKDrct|j|j|j|j|jfSrr]r1s r _serializezIndexedSlicesSpec._serializes4 KK++T-@-@  # #T%8%8 ::rc|jj|jdd}tj||j tj|j|j g}|jD|jtj|jjg|jt|SrJ) rbrMr^r TensorSpecr_r`raappendndimstuple)r value_shapespecss r_component_specsz"IndexedSlicesSpec._component_specss%%11$++ab/BK{D,>,>?t22D4G4GH JE * ll  $++"3"3!4d6M6M NP <rc|j|j|jfS|j|j|jfSr)r.r,r-rs r_to_componentsz IndexedSlicesSpec._to_componentss<  llEMM **llEMM5+<+< ==rctd|Dr=tjs)t|dk(rt |d|ddSt |St |S)Nc3PK|]}t|tj ywr) isinstancenpndarray).0ts r z5IndexedSlicesSpec._from_components..s ;!Jq"** % ;s$&rrK)allrenabledlenr[r&)r tensor_lists r_from_componentsz"IndexedSlicesSpec._from_componentssS ;{ ;; KKM [ Q !+a.+a.$GG!;// K ((r)r"r#r$r% __slots__rW value_typerfloat32int64r/rkrsrurrrrrNrNsW47)23*v~~#\\T!L4:  > )r#convert_to_tensor_or_indexed_slices)v1c t|||dS)aConverts the given object to a `Tensor` or an `IndexedSlices`. If `value` is an `IndexedSlices` or `SparseTensor` it is returned unmodified. Otherwise, it is converted to a `Tensor` using `convert_to_tensor()`. Args: value: An `IndexedSlices`, `SparseTensor`, or an object that can be consumed by `convert_to_tensor()`. dtype: (Optional.) The required `DType` of the returned `Tensor` or `IndexedSlices`. name: (Optional.) A name to use if a new `Tensor` is created. Returns: A `Tensor`, `IndexedSlices`, or `SparseTensor` based on `value`. Raises: ValueError: If `dtype` does not match the element type of `value`. Frr@r9as_ref),internal_convert_to_tensor_or_indexed_slices)rr@r9s rrrs* 6 T% 99rc t|tjr-tjstj ||||St|t jrx|rttj|j|jsFtdtj|jd|d|jjd|Stj ||||S)aConverts the given object to a `Tensor` or an `IndexedSlices`. If `value` is an `IndexedSlices` or `SparseTensor` it is returned unmodified. Otherwise, it is converted to a `Tensor` using `convert_to_tensor()`. Args: value: An `IndexedSlices`, `SparseTensor`, or an object that can be consumed by `convert_to_tensor()`. dtype: (Optional.) The required `DType` of the returned `Tensor` or `IndexedSlices`. name: (Optional.) A name to use if a new `Tensor` is created. as_ref: True if the caller wants the results as ref tensors. Returns: A `Tensor`, `IndexedSlices`, or `SparseTensor` based on `value`. Raises: ValueError: If `dtype` does not match the element type of `value`. r@r9r4Incompatible tensor conversion requested to `dtype` z for `value` ( ) with dtype .)rxr EagerTensorrexecuting_eagerlyconvert_to_tensorr NativeObjectrrgis_compatible_withr@ ValueErrorr9rs rrr.s0s'0I0I0K  e$v NN%../ V__U+>>u{{K  @ __U # ( ( )w?kk q " ## L  e$v NNrc t|tjs tdg}t |D]B\}}||j ||dnd||fz}|j t ||||D|S)auConverts `values` to a list of `Tensor` or `IndexedSlices` objects. Any `IndexedSlices` or `SparseTensor` objects in `values` are returned unmodified. Args: values: An iterable of `None`, `IndexedSlices`, `SparseTensor`, or objects that can be consumed by `convert_to_tensor()`. dtype: (Optional.) The required `DType` of the returned `Tensor` or `IndexedSlices`. name: (Optional.) A name prefix to used when a new `Tensor` is created, in which case element `i` will be given the name `name + '_' + i`. as_ref: True if the caller wants the results as ref tensors. Returns: A list of `Tensor`, `IndexedSlices`, `SparseTensor` and/or `None` objects. Raises: TypeError: If no conversion function is registered for an element in `values`. RuntimeError: If a registered conversion function returns an invalid value. z#Argument `values` must be iterable.Nz%s_%dr)rxrIterable TypeError enumeraternr)r,r@r9rretirns r.internal_convert_n_to_tensor_or_indexed_slicesrTs6 FO44 5 9 :: #F#:ha } jj,$GtQi$7a jj 65q 9: : *rc t|||dS)a%Converts `values` to a list of `Output` or `IndexedSlices` objects. Any `IndexedSlices` or `SparseTensor` objects in `values` are returned unmodified. Args: values: A list of `None`, `IndexedSlices`, `SparseTensor`, or objects that can be consumed by `convert_to_tensor()`. dtype: (Optional.) The required `DType` of the returned `Tensor` `IndexedSlices`. name: (Optional.) A name prefix to used when a new `Tensor` is created, in which case element `i` will be given the name `name + '_' + i`. Returns: A list of `Tensor`, `IndexedSlices`, and/or `SparseTensor` objects. Raises: TypeError: If no conversion function is registered for an element in `values`. RuntimeError: If a registered conversion function returns an invalid value. F)r,r@r9r)r)r,r@r9s r%convert_n_to_tensor_or_indexed_slicesr}s. 8 5tE ;;ric"|}|rM|j|js2td|jd|d|jj|jtd|t j sWtj|j}|6tj|}|tk\rtjd|ztj|j |j"|jd|S)aConverts an IndexedSlices object `value` to a Tensor. NOTE(mrry): This function is potentially expensive. Args: value: An ops.IndexedSlices object. dtype: The dtype of the Tensor to be returned. name: Optional name to use for the returned Tensor. as_ref: True if a ref is requested. Returns: A dense Tensor representing the values in the given IndexedSlices. Raises: ValueError: If the IndexedSlices does not have the same dtype. rz for IndexedSlices (rzXTensor conversion requested for IndexedSlices for argument `value` without dense_shape: znConverting sparse IndexedSlices to a dense Tensor with %d elements. This may consume a large amount of memory.r)r9)rr@rr9r.rrr constant_valueryprod_LARGE_SPARSE_NUM_ELEMENTSwarningswarnrunsorted_segment_sumr,r-)rr@r9r_dense_shape_value num_elementss r_indexed_slices_to_tensorrs" ! 5++EKK8  >uzzlK ekk.>.>-? A BB   %y * ++  " " $#2253D3DE$WW./l 3 3  C     * * llEMM5#4#4Q#7d DDr)NN)NNF)3r% collectionsrnumpyrytensorflow.core.protobufrtensorflow.pythonrtensorflow.python.eagerrtensorflow.python.frameworkrrrr r r r r rtensorflow.python.opsrtensorflow.python.saved_modelrtensorflow.python.typesrtensorflow.python.util.compatr tensorflow.python.util.tf_exportrCompositeTensorGradientrr&rCompositeTensor namedtupler[TypeSpecrNregister_codecBuiltInTypeSpecCodec TypeSpecProtoINDEXED_SLICES_SPECrrrrrr#register_tensor_conversion_functionrrrrs~/!+8A.+B4331.@,9655 ?M  $$MM`,[++>@ ?) **?) ?)D&%%///:33GG 45697928<6:8=#ON:>8<:?& R;:'&DR?>>,.r