AVh dZddlZddlmZddlmZddlmZddlm Z ddl m Z ddlmZdd l mZdd l mZdd l mZdd lmZdd lmZddlmZddlmZm Z m!Z!ddl"m#Z#gdfde#e!ejHffdZ%edejLe%Z'de#e!ejHffdZ(dMde#e!ejHffdZ)edejLe)Z*de#e!ejHffdZ+edZ,dMde,de#e!e,ffdZ-edejLe-Z.de,de#e!e,ffdZ/dMde#e!ejHfde#e!ejHfd e#e!ejHffd!Z0ed"ejLe0Z1de#e!ejHfde#e!ejHfd e#e!ejHffd#Z2ed$Z3gdfd%e#e!e3ffd&Z4ed'ejLe4Z5d%e#e!e3ffd(Z6dNd)e7d*e7d+e7fd,Z8ed-ejLe8Z9d)e7d*e7d+e7fd.Z:dMd/e#e!ejvffd0Z<ed1ejLe<Z=d/e#e!ejvffd2Z>dNd)e7d*e7d+e7fd3Z?ed4ejLe?Z@d)e7d*e7d+e7fd5ZAgdfde#e!ejHffd6ZBed7ejLeBZCde#e!ejHffd8ZDed9ZEgdfd%e#e!eEffd:ZFed;ejLeFZGd%e#e!eEffd<ZHgd=dfd>eIfd?ZJed@ejLeJZKd>eIfdAZLdMdBZMedCejLeMZNdDZOedEZPdMdFe#e!ePfde#e!ejffdGZRedHejLeRZSdFe#e!ePfde#e!ejffdIZTgd=dfd>eIfdJZUedKejLeUZVd>eIfdLZWy)OzUPython wrappers around TensorFlow ops. This file is MACHINE GENERATED! Do not edit. N) pywrap_tfe)context)core)execute)dtypes)annotation_types)op_def_registry)ops)op_def_library)deprecated_endpoints)dispatch) tf_export)TypeVarListAny) Annotated branch_indexc tjxstj}|j}|jr" t j |d|||d|d|d| }|St|ttfst!d|z|D cgc]} t#j$| d}} t|ttfst!d|z|g}t|ttfst!d |z|D cgc]} t#j&| d}} t)j*d|||||| \} } } }|dd}|s| St#j,rjd | j/d d| j/dd| j/dd| j/df}| j0}t#j2d||||S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t|||||||S#t j$rYwxYwcc} wcc} w) aAn n-way switch statement which calls a single branch function. An n-way switch statement, implementing the following: ``` switch (branch_index) { case 0: output = branches[0](input); break; case 1: output = branches[1](input); break; ... case [[nbranches-1]]: default: output = branches[nbranches-1](input); break; } ``` Args: branch_index: A `Tensor` of type `int32`. The branch selector, an int32 Tensor. input: A list of `Tensor` objects. A list of input tensors passed to the branch function. Tout: A list of `tf.DTypes`. A list of output types. branches: A list of functions decorated with @Defun that has length `>= 1`. A list of functions each of which takes 'inputs' and returns a list of tensors, whose types are the same as what every other branch returns. output_shapes: An optional list of shapes (each a `tf.TensorShape` or list of `ints`). Defaults to `[]`. name: A name for the operation (optional). Returns: A list of `Tensor` objects of type `Tout`. CaseToutbranches output_shapesNrrrnamectx7Expected list for 'Tout' argument to 'case' Op, not %r.;Expected list for 'branches' argument to 'case' Op, not %r.@Expected list for 'output_shapes' argument to 'case' Op, not %r.rinputrrrrTin)_contextr_thread_local_datais_eagerrTFE_Py_FastPathExecute_core_NotOkStatusException_opsraise_from_not_ok_status_FallbackExceptioncase_eager_fallback_SymbolicException isinstancelisttuple TypeError_execute make_type make_shape_op_def_library_apply_op_helpermust_record_gradientget_attrinputsrecord_gradientrr rrrr_ctxtld_resulte_t_s__op_outputs_attrs _inputs_flats X/home/dcms/DCMS/lib/python3.12/site-packages/tensorflow/python/ops/gen_functional_ops.pycaserGsbF    0h..0$ #\\ 11 fdL%z/=2gn D4- (  # $ %%48 8R(  R ( 8$ 8 HtUm ,  ' ( ))M MD%= 1  , - ..GTT8&&r?;T-T'88\T!TK!QX QK'  J ""$S\\%(&#,,v2F#,,z2Oll?+-F::L  fg/ .Q  & &- ##At,,  # #    D8%Dd<<  # #    9Us< G H88H=HG//HH HH54H5z raw_ops.Casect|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|g}t|ttfstd|z|Dcgc]}t j |d}}t j||\} }tj|tj}|gt|z} d| d|d|d|f} t jdt|| | || } t jrt jd | | | | Scc}wcc}w) Nrrrrrr!rsCaser8attrsrrrr-r.r/r0r1r2r3convert_to_mixed_eager_tensorsr(convert_to_tensor_dtypesint32rlenr6r9 rr rrrrrr?r@ _attr_TinrErDr=s rFr+r+qsw D4- (  # $ %%48 8R(  R ( 8$ 8 HtUm ,  ' ( ))M MD%= 1  , - ..GTT8&&r?;T-T<r@rArBrCrDrEs rF device_indexr[s    0h..0$ #\\ 11 mT><Ag n L4- 0  %'3 4 55COOB(##B7O,O'88Lt=!QX QK' ""$cll>: ;F::L |VW6 (' .1  & &- ##At,,  # #    (#$D::  # #   Ps6DFE(EEE E..FFzraw_ops.DeviceIndexc@t|ttfstd|z|Dcgc]}t j |d}}g}d|f}t j dd||||}t jrt jd||||\}|Scc}w)NrXrWs DeviceIndexrIrV) r-r.r/r0r1rZrr6r9)rWrrr@rErDr=s rFrYrYs L4- 0  %'3 4 55COOB(##B7O,O, L )&   ^Q|#)s ?' ""$ |VW6 (' .PsB) TV_FakeParam_dtype_atypes.BFloat16 _atypes.Bool_atypes.Complex128_atypes.Complex64_atypes.Float16_atypes.Float32_atypes.Float64_atypes.Float8e4m3b11fnuz_atypes.Float8e4m3fn_atypes.Float8e4m3fnuz_atypes.Float8e5m2_atypes.Float8e5m2fnuz _atypes.Half _atypes.Int16 _atypes.Int32 _atypes.Int4 _atypes.Int64 _atypes.Int8_atypes.QInt16_atypes.QInt32 _atypes.QInt8_atypes.QUInt16_atypes.QUInt8_atypes.Resource_atypes.String_atypes.UInt16_atypes.UInt32 _atypes.UInt4_atypes.UInt64 _atypes.UInt8_atypes.Variantdtypec tjxstj}|j}|jr t j |d|d|d|}|Stj|d}tj|d}t!j"d|||\}}}} | dd}tj$rHd|j'dd|j)df} |j*} tj,d| | ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t||||S#t j$rY!wxYw)a This op is used as a placeholder in If branch functions. It doesn't provide a valid output when run, so must either be removed (e.g. replaced with a function input) or guaranteed not to be used (e.g. if mirroring an intermediate output needed for the gradient computation of the other branch). Args: dtype: A `tf.DType`. The type of the output. shape: A `tf.TensorShape` or list of `ints`. The purported shape of the output. This is only used for shape inference; the output will not necessarily have this shape. Can be a partial shape. name: A name for the operation (optional). Returns: A `Tensor` of type `dtype`. FakeParamr~shapeN)r~rrr)r~rr)r"rr#r$rr%r&r'r(r)r*fake_param_eager_fallbackr,r1r2r3r4r5r6_get_attr_typer7r8r9) r~rrr;r<r=r>rArBrCrDrEs rF fake_paramrsv    0h..0$ #\\ 11 k4%%Ag n   UG ,%   eW -%'885D:!QX QK' ""$s))'2Gll7#%F::L \674 (' .-  & &- ##At,,  # #    &U499  # #   s0DE!D<<EEE((E?>E?zraw_ops.FakeParamctj|d}tj|d}g}d|d|f}tjdd||||}tjrtj d||||\}|S)Nr~rs FakeParamr]rIr)r1r2r3rr6r9)r~rrrrErDr=s rFrrs   UG ,%   eW -%, UGU +&   \1\#)s ?' ""$ \674 (' .startlimitdeltac tjxstj}|j}|jr t j |d|||||d| }|Stjd||||||\} } } } | dd}tj rHd| j#dd| j#df} | j$}tj&d|| ||S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t|||||||S#t j$rYwxYw)aApplies a for loop. ```python output = input; for i in range(start, limit, delta) output = body(i, output); ``` Args: start: A `Tensor` of type `int32`. The lower bound. An int32 limit: A `Tensor` of type `int32`. The upper bound. An int32 delta: A `Tensor` of type `int32`. The increment. An int32 input: A list of `Tensor` objects. A list of input tensors whose types are T. body: A function decorated with @Defun. A function that takes a list of tensors (int32, T) and returns another list of tensors (T). name: A name for the operation (optional). Returns: A list of `Tensor` objects. Has the same type as `input`. ForbodyN)rrr)rrrr rrT)r"rr#r$rr%r&r'r(r)r*_for_eager_fallbackr,r4r5r1r6r7r8r9)rrrr rrr;r<r=r>rArBrCrDrEs rF_forrs[.    0h..0$ #\\ 11 eT5%vtEg n(88 U%uE!QX QK' ""$3<<$fcll6.B CF::L  |VW. .'  & &- ##At,,  # #    u4dFF  # #   s0C##D*6DD*)D*.EEEz raw_ops.Forctj||\}}tj|tj }tj|tj }tj|tj }|||gt |z}d|d|f} tjdt||| ||} tjrtjd|| | | S)NrrsForrIr) r1rLr(rMrNrOr.rrPr6r9) rrrr rrr_attr_TrErDr=s rFrrKs::5#F.'5   6%   6%   6%&e4, &$ '&   VSZ #)s ?' ""$  |VW. .r) TV_If_Tcondr_r`rarbrcrdrerfrgrhrirjrkrlrmrnrorprqrrrsrtrurvrwrxryrzr{r|r}condctjxstj}|j}|jr$ t j |d|||d|d|d|d| } | St|ttfst!d|z|D cgc]} t#j$| d}} |g}t|ttfst!d |z|D cgc]} t#j&| d}} t)j*d||||||| \} } }}|dd} | s|St#j,rd |j/d d |j1d d|j1dd|j1dd|j1dd|j1df }|j2}t#j4d||| | S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t||||||||S#t j$rYwxYwcc} wcc} w) aoutput = cond ? then_branch(input) : else_branch(input) Args: cond: A `Tensor`. A Tensor. If the tensor is a scalar of non-boolean type, the scalar is converted to a boolean according to the following rule: if the scalar is a numerical value, non-zero means `True` and zero means False; if the scalar is a string, non-empty means `True` and empty means `False`. If the tensor is not a scalar, being empty means False and being non-empty means True. input: A list of `Tensor` objects. A list of input tensors. Tout: A list of `tf.DTypes`. A list of output types. then_branch: A function decorated with @Defun. A function that takes 'inputs' and returns a list of tensors, whose types are the same as what else_branch returns. else_branch: A function decorated with @Defun. A function that takes 'inputs' and returns a list of tensors, whose types are the same as what then_branch returns. 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 list of `Tensor` objects of type `Tout`. Ifr then_branch else_branchrNrrrrrr5Expected list for 'Tout' argument to 'if' Op, not %r.>Expected list for 'output_shapes' argument to 'if' Op, not %r.rr rrrrrTcondr!)r"rr#r$rr%r&r'r(r)r*_if_eager_fallbackr,r-r.r/r0r1r2r3r4r5r6rr7r8r9rr rrrrrr;r<r=r>r?r@rArBrCrDrEs rF_ifr\s_2    0h..0$ #\\  11 dD$vt]]Kgn D4- (  ! " ##48 8R(  R ( 8$ 8M MD%= 1  * + ,,GTT8&&r?;T-T'88 4u4[%]O!QX QK'  J ""$s))'2Ell5!63<<+?S\\-8-ll=)?ll?+ -F ::L  lFG- .O  & &- ##At,,  # #     Dk!T  # #    9Us<"G H:H?H G00H H  H H76H7z raw_ops.Ifc t|ttfstd|z|Dcgc]}t j |d}}|g}t|ttfstd|z|D cgc]} t j | d}} t j|g|g\} \}t j||\} }|gt|z} d| d| d|d|d|d|f } t jd t|| | || }t jrt jd | | ||Scc}wcc} w) Nrrrrrr!rrsIfrIr r-r.r/r0r1r2r3args_to_matching_eagerrLrrPr6r9rr rrrrrrr?r@ _attr_TcondrRrErDr=s rFrrs_ D4- (  ! " ##48 8R(  R ( 8$ 8M MD%= 1  * + ,,GTT8&&r?;T-T!88$bI+w<r?rArBrCrDrEs rFpartitioned_callrsP.    0h..0$ #\\ 11 tVT38 o}Ngn D4- (  )+/ 0 1148 8R(  R ( 8$ 8 ^ F   VX .&L""<@,M##M?C-'8841V(4)6TC!QX QK' ""$S\\%(&#,,v2Fll33<<+Acll>:Oll?+-F::L <: .M  & &- ##At,,  # #    , TQvL%Dd<<  # #    9s6#G H:H G00H H  H H76H7zraw_ops.PartitionedCallc >t|ttfstd|z|Dcgc]}t j |d}}|d}t j |d}|d}t j |d}|d}t j |d}t j||\} }t|} d| d|d|d|d|d|f } t jd t|| | || } t jrt jd | | | | Scc}w) Nrrrrrrr!rsPartitionedCallrIr r-r.r/r0r1r2rZrLrrPr6r9 rrrrrrrrr?rRrErDr=s rFrrs5 D4- (  )+/ 0 1148 8R(  R ( 8$ 8 ^ F   VX .&L""<@,M##M?C-;;D#F/)Td, 9fdCHf, @&   /T$0C"& ('""$ <: .) 9Dtargetc rtjxstj}|j}|jr t j |d|||d|d| }|St|ttfst!d|z|D cgc]} t#j$| d}} t'j(d|||||\} } } } | dd}|s| St#j*rYd| j-dd| j-dd| j-df} | j.}t#j0d|| ||S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t||||||S#t j$rYQwxYwcc} w) aRuns function `f` on a remote device indicated by `target`. Args: target: A `Tensor` of type `string`. A fully specified device name where we want to run the function. args: A list of `Tensor` objects. A list of arguments for the function. Tout: A list of `tf.DTypes` that has length `>= 1`. The type list for the return values. f: A function decorated with @Defun. The function to run remotely. name: A name for the operation (optional). Returns: A list of `Tensor` objects of type `Tout`. RemoteCallrrNrrrr>Expected list for 'Tout' argument to 'remote_call' Op, not %r.)rrrrrr!)r"rr#r$rr%r&r'r(r)r*remote_call_eager_fallbackr,r-r.r/r0r1r2r4r5r6r7r8r9)rrrrrr;r<r=r>r?rArBrCrDrEs rF remote_callr+s    0h..0$ #\\ 11 lD&$c1Fg n D4- (  $&* + ,,48 8R(  R ( 8$ 8'88V$TQTK!QX QK'  J ""$S\\%(&#,,v2Fll3!F::L lFG5 .5  & &- ##At,,  # #    ' $TQTt==  # #    9s6D>F4>FE,,FF FF10F1zraw_ops.RemoteCallct|ttfstd|z|Dcgc]}t j |d}}t j ||\}}tj|tj}|gt|z}d|d|d|f} t jdt||| ||} t jrt jd|| | | Scc}w)Nrrr!rs RemoteCallrIr)r-r.r/r0r1r2rLr(rMrNstringrrPr6r9) rrrrrrr?rRrErDr=s rFrr`s D4- (  $&* + ,,48 8R(  R ( 8$ 8;;D#F/)T  ! !&'.. 9&DJ&, 9fdC 3&   ]CIl#)s ?' ""$ lFG5 . 9sC.ctjxstj}|j}|jr% t j |d||d|d|d|d|d|} | St|ttfst!d |z|D cgc]} t#j$| d}} |d }t#j&|d}|d }t#j&|d}|d }t#j&|d}t)j*d||||||| \} } } }|dd} | s| St#j,rd | j/d d| j/dd| j/dd| j/dd| j/dd| j/df }| j0}t#j2d||| | S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t||||||||S#t j$rYwxYwcc} w) aareturns `f(inputs)`, where `f`'s body is placed and partitioned. Args: args: A list of `Tensor` objects. A list of input tensors. Tout: A list of `tf.DTypes`. A list of output types. f: A function decorated with @Defun. A function that takes 'args', a list of tensors, and returns 'output', another list of tensors. Input and output types are specified by 'Tin' and 'Tout'. The function body of f will be placed and partitioned across devices, setting this op apart from the regular Call op. This op is stateful. config: An optional `string`. Defaults to `""`. config_proto: An optional `string`. Defaults to `""`. executor_type: An optional `string`. Defaults to `""`. name: A name for the operation (optional). Returns: A list of `Tensor` objects of type `Tout`. StatefulPartitionedCallrrrrrNrLExpected list for 'Tout' argument to 'stateful_partitioned_call' Op, not %r.rrr!)r"rr#r$rr%r&r'r(r)r*(stateful_partitioned_call_eager_fallbackr,r-r.r/r0r1r2rZr4r5r6r7r8r9rs rFstateful_partitioned_callrrsY(    0h..0$ #\\  11 'tVT3&.,gn D4- (  248 9 ::48 8R(  R ( 8$ 8 ^ F   VX .&L""<@,M##M?C-'88!41V0<1>TK!QX QK'  J ""$S\\%(&#,,v2Fll33<<+Acll>:Oll?+-F::L !<B .Q  & &- ##At,,  # #    5 TQvL%Dd<<  # #    9s6#G H>H G44H  H H$$H;:H;zraw_ops.StatefulPartitionedCallc >t|ttfstd|z|Dcgc]}t j |d}}|d}t j |d}|d}t j |d}|d}t j |d}t j||\} }t|} d| d|d|d|d|d|f } t jd t|| | || } t jrt jd | | | | Scc}w) Nrrrrrrr!rsStatefulPartitionedCallrIrrrs rFrrs6 D4- (  248 9 ::48 8R(  R ( 8$ 8 ^ F   VX .&L""<@,M##M?C-;;D#F/)Td, 9fdCHf, @&   7T$0C"& ('""$ !<B .) 9rc |tjxstj}|j}|jr" t j |d|||d|d|d| }|St|ttfst!d|z|D cgc]} t#j$| d}} t|ttfst!d|z|g}t|ttfst!d |z|D cgc]} t#j&| d}} t)j*d|||||| \} } } }|dd}t#j,rjd | j/d d| j/dd| j/dd| j/df}| j0}t#j2d||||S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t|||||||S#t j$rYwxYwcc} wcc} w) aAn n-way switch statement which calls a single branch function. An n-way switch statement, implementing the following: ``` switch (branch_index) { case 0: output = branches[0](input); break; case 1: output = branches[1](input); break; ... case [[nbranches-1]]: default: output = branches[nbranches-1](input); break; } ``` This should only be used when the none of branches has stateful ops. Args: branch_index: A `Tensor` of type `int32`. The branch selector, an int32 Tensor. input: A list of `Tensor` objects. A list of input tensors passed to the branch function. Tout: A list of `tf.DTypes`. A list of output types. branches: A list of functions decorated with @Defun that has length `>= 1`. A list of functions each of which takes 'inputs' and returns a list of tensors, whose types are the same as what every other branch returns. 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 list of `Tensor` objects of type `Tout`. StatelessCaserrrNrAExpected list for 'Tout' argument to 'stateless_case' Op, not %r.EExpected list for 'branches' argument to 'stateless_case' Op, not %r.JExpected list for 'output_shapes' argument to 'stateless_case' Op, not %r.rr!)r"rr#r$rr%r&r'r(r)r*stateless_case_eager_fallbackr,r-r.r/r0r1r2r3r4r5r6r7r8r9r:s rFstateless_casersZJ    0h..0$ #\\ 11 ot\5&$Ho}>gn D4- (  ')- . //48 8R(  R ( 8$ 8 HtUm ,  ')1 2 33M MD%= 1  ')6 7 88GTT8&&r?;T-T'88l%d"*-"$!QX QK' ""$S\\%(&#,,v2F#,,z2Oll?+-F::L vw8 .O  & &- ##At,,  # #    * D8%Dd<<  # #    9Us< F= H48H9=HG++HHHH10H1zraw_ops.StatelessCasect|ttfstd|z|Dcgc]}t j |d}}t|ttfstd|z|g}t|ttfstd|z|Dcgc]}t j |d}}t j||\} }tj|tj}|gt|z} d| d|d|d|f} t jdt|| | || } t jrt jd | | | | Scc}wcc}w) Nrrrrrr!rs StatelessCaserIrrKrQs rFrr1sx D4- (  ')- . //48 8R(  R ( 8$ 8 HtUm ,  ')1 2 33M MD%= 1  ')6 7 88GTT8&&r?;T-T< H6H;>HG,,HH HH32H3zraw_ops.StatelessIfc t|ttfstd|z|Dcgc]}t j |d}}|g}t|ttfstd|z|D cgc]} t j | d}} t j|g|g\} \}t j||\} }|gt|z} d| d| d|d|d|d|f } t jd t|| | || }t jrt jd | | ||Scc}wcc} w) Nrrrrrr!rrs StatelessIfrIrrrs rFrrs_ D4- (  %'+ , --48 8R(  R ( 8$ 8M MD%= 1  %'4 5 66GTT8&&r?;T-T!88$bI+w<r@rArBrCrDrEs rFstateless_whilers8    0h..0$ #\\  11 eVT64(=gnM MD%= 1  (*7 8 99GTT8&&r?;T-T  ))*=?TU'88Dt(5.AN!QX QK' ""$3<<$fcll6.BFll6"Oll?+-B 568F::L ,9 .E  & &- ##At,,  # #    + d]1$HH  # #   Us6!E>G5>GF,,GG GG21G2zraw_ops.StatelessWhilec |g}t|ttfstd|z|Dcgc]}t j |d}}|d}t j |d}t j||\}}t|} d|d|d|d|d|f } t jdt|| | || } t jrt jd | | | | Scc}w) NrrrrrrrsStatelessWhilerIr r-r.r/r0r1r3rrLrrPr6r9 r rrrrrrr@rrErDr=s rFrrs M MD%= 1  (*7 8 99GTT8&&r?;T-T  ))*=?TU::5#F.'5e, &$o&(; =&   .E $0C"& ('""$ ,9 .UC(c dtjxstj}|j}|jr t j |d||d|d|}|St|ttfst!d|z|Dcgc]}t#j$|d}}t'j(d||||\} } } } | dd}t#j*rYd| j-dd| j-dd| j-df} | j.} t#j0d| | ||S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t|||||S#t j$rYKwxYwcc}w) aComputes the gradient function for function f via backpropagation. Args: input: A list of `Tensor` objects. a list of input tensors of size N + M; Tout: A list of `tf.DTypes` that has length `>= 1`. the type list for the input list. f: A function decorated with @Defun. The function we want to compute the gradient for. The function 'f' must be a numerical function which takes N inputs and produces M outputs. Its gradient function 'g', which is computed by this SymbolicGradient op is a function taking N + M inputs and produces N outputs. I.e. if we have (y1, y2, ..., y_M) = f(x1, x2, ..., x_N), then, g is (dL/dx1, dL/dx2, ..., dL/dx_N) = g(x1, x2, ..., x_N, dL/dy1, dL/dy2, ..., dL/dy_M), where L is a scalar-value function of (x1, x2, ..., xN) (e.g., the loss function). dL/dx_i is the partial derivative of L with respect to x_i. (Needs some math expert to say the comment above better.) name: A name for the operation (optional). Returns: A list of `Tensor` objects of type `Tout`. SymbolicGradientrrNrDExpected list for 'Tout' argument to 'symbolic_gradient' Op, not %r.)r rrrr!)r"rr#r$rr%r&r'r(r)r* symbolic_gradient_eager_fallbackr,r-r.r/r0r1r2r4r5r6r7r8r9)r rrrr;r<r=r>r?rArBrCrDrEs rFsymbolic_gradientr s>    0h..0$ #\\ 11  $vtS!Eg n D4- (  *,0 1 2248 8R(  R ( 8$ 8'88%dadD!QX QK' ""$S\\%(&#,,v2Fll3!F::L L&'; .1  & &- ##At,,  # #    - dad66  # #    9s6D8F-8E? E&&E?>E?FF*)F*zraw_ops.SymbolicGradientct|ttfstd|z|Dcgc]}t j |d}}t j ||\}}t|}d|d|d|f}t jdt|||||} t jrt jd||| | Scc}w)Nrrr!rsSymbolicGradientrIr) r-r.r/r0r1r2rLrrPr6r9) r rrrrr?rRrErDr=s rFrrcs D4- (  *,0 1 2248 8R(  R ( 8$ 8<0D tensors, truthiness is determined by looking at the number of elements. If has zero elements, then the result is false. Otherwise the result is true. This matches the behavior of If and While for determining if a tensor counts as true/false for a branch condition. Args: input: A `Tensor`. name: A name for the operation (optional). Returns: A `Tensor` of type `bool`. ToBoolN)rr)r rr)r"rr#r$rr%r&r'r(r)r*to_bool_eager_fallbackr,r4r5r1r6rr8r9) r rr;r<r=r>rArBrCrDrEs rFto_boolrws7.    0h..0$ #\\ 11 he%g n(88D*!QX QK' ""$3%%c* +F::L ,1 (' .'  & &- ##At,,  # #    # d&&  # #   s0C D C;;DD D&&D<;D<zraw_ops.ToBoolctj|g|g\}\}|g}d|f}tjdd||||}tjrtjd||||\}|S)NrsToBoolr]rIr)r1rrr6r9)r rrrrErDr=s rFrrs{55ugsBG'8E, >&   Y,f!$4 1' ""$ ,1 (' .rctjxstj}|j}|jr# t j |d||d|d|d|d| }|S|g}t|ttfst!d|z|D cgc]} t#j$| d}} |d }t#j&|d}t)j*d|||||| \} } } } | dd}|s| St#j,r{d | j/d d| j/dd| j/dd| j/dd| j1df }| j2}t#j4d||||S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t|||||||S#t j$rYwxYwcc} w) aoutput = input; While (Cond(output)) { output = Body(output) } Args: input: A list of `Tensor` objects. A list of input tensors whose types are T. cond: A function decorated with @Defun. A function takes 'input' and returns a tensor. If the tensor is a scalar of non-boolean, the scalar is converted to a boolean according to the following rule: if the scalar is a numerical value, non-zero means True and zero means False; if the scalar is a string, non-empty means True and empty means False. If the tensor is not a scalar, non-emptiness means True and False otherwise. body: A function decorated with @Defun. A function that takes a list of tensors and returns another list of tensors. Both lists have the same types as specified by T. output_shapes: An optional list of shapes (each a `tf.TensorShape` or list of `ints`). Defaults to `[]`. parallel_iterations: An optional `int`. Defaults to `10`. name: A name for the operation (optional). Returns: A list of `Tensor` objects. Has the same type as `input`. WhilerrrrNrAExpected list for 'output_shapes' argument to 'while' Op, not %r.rrr)r"rr#r$rr%r&r'r(r)r*_while_eager_fallbackr,r-r.r/r0r1r3rr4r5r6r7rr8r9rs rF_whilers"2    0h..0$ #\\  11 gtUFD&$(=gnM MD%= 1   - . //GTT8&&r?;T-T  ))*=?TU'88u4d,%8tE!QX QK'  J ""$3<<$fcll6.BFll6"Oll?+-B 568F::L vw0 .I  & &- ##At,,  # #    " d]1$HH  # #   Us6!FG9G F00G G  GG65G6z raw_ops.Whilec |g}t|ttfstd|z|Dcgc]}t j |d}}|d}t j |d}t j||\}}t|} d|d|d|d|d|f } t jdt|| | || } t jrt jd | | | | Scc}w) NrrrrrrrsWhilerIrrrs rFrrsM MD%= 1   - . //GTT8&&r?;T-T  ))*=?TU::5#F.'5e, &$o&(; =&   Xs5z,#)s ?' ""$ vw0 .Ur)N)rrrN)X__doc__ collectionstensorflow.pythonrtensorflow.python.eagerrr"rr&rr1tensorflow.python.frameworkrrNtensorflow.security.fuzzing.pyr_atypesr _op_def_registryr r(r r4"tensorflow.python.util.deprecationr tensorflow.python.utilr _dispatch tensorflow.python.util.tf_exportrtypingrrrtyping_extensionsrInt32rG to_raw_oprr+r[rVrYr^rrrrrrrrrrstrrrrStringrrrrrrrrrrrrrintrrrrrrrBoolrrrrrrrrFrs 67179FK3IC86%%'[]dhSygmm!34Sj!y !56iW]]0B&C<.YsGMM7I-J.`/i-.~t~~l/KL Ic7==FX4>>*+E F  %7 iX[]oXoNp 1 #w}},-1iW]]@R6S1\efikrkxkxfx\y1fi ~t~~d34 ygmm);< YsT[TaTaOaEb ktux{B{H{HvHlI z `bimIi[()IVY|^T^^C01YsK'786E3EEVYEN7)56~t~~FV7WX3cbe80 #w~~"560d-Y+ ,^T^^K-H I ygnn1D'E$ECEE_bENG)$EF~t~~VoGpqCWZkn8fhnrT3 +=!>Tl3 12>4>>.3QR  #w}}:L0M<L rt{Ky&:!:;KZ/i-.~t~~l/KL i5I0I&J668QSZ^GSGR534^T^^O5TUZ]0>@9978HY9Z[$z 19S+-.1iW\\HY>Z1f %# $^T^^G%< = )C,<"= YWZ\c\h\hWhMi -/QUFCFP # /">4>> :QTr