AVh dZddlZddlmZddlmZddlmZddlm Z ddl m Z ddlmZdd l mZdd l mZdd l mZdd lmZdd lmZddlmZddlmZm Z m!Z!ddl"m#Z#eddddddddddddd Z$edddZ%edddZ&e jNdfd e#e!e$fd!e#e!ejPfd"e#e!e%fd#e&d$e#e!e&ff d%Z)ed&ejTe)Z+d e#e!e$fd!e#e!ejPfd"e#e!e%fd#e&d$e#e!e&ff d'Z,ed(ddZ-ed)ddZ.ed*dddZ/dld+e#e!e-fd"e#e!e.fd,e#e!e/fd-e#e!e/fd.e#e!e/fd/e#e!e/fd$e#e!e/ffd0Z0ed1ejTe0Z1d+e#e!e-fd"e#e!e.fd,e#e!e/fd-e#e!e/fd.e#e!e/fd/e#e!e/fd$e#e!e/ffd2Z2ed3ddZ3ed4ddZ4ed5dddddZ5ed6dddddZ6e jNdfd+e#e!e3fd"e#e!e4fd7e#e!e5fd8e#e!e5fd9e6d$e#e!e6ff d:Z7ed;ejTe7Z8d+e#e!e3fd"e#e!e4fd7e#e!e5fd8e#e!e5fd9e6d$e#e!e6ff d<Z9ed=dddZ:ed>ddZ;ed?ddZd+e#e!e;fd"e#e!e  02F::L  fg? (' .7  & &- ##At,,  # #    1 +t,T  # #   s0DE%1E  E%$E%)E::FFzraw_ops.StatelessMultinomialc|tj}tj|d}tj|g|tj tj tjtjtjtjtjtjtjtjtjtjg \}\}tj|g|tjtjgtj\}\}t!j"|tj}|||g}d|d|d|f} tj$dd|| ||} tj&rtj(d|| | | \} | S)Nrrr sStatelessMultinomialr4attrsrrr)r,r-r.r/args_to_matching_eagerfloat32float64int32uint8int16int8bfloat16uint16halfuint32uint64r'convert_to_tensorrr2r5) rrrrrr_attr_T _attr_Tseedr>r=r8s r?r*r*Vs==L##L.A,66xwX_XgXgipivivxyFyFHOHUHUW^WcWcelerert{tDtDFMFTFTV]VbVbdkdrdrt{tBtBGEF'9F!88$w}}V]VcVcFfhohuhuv+w&&{GMMB++t,, '; M&   4a #)s ?' ""$  fg? (' .*TV_StatelessParameterizedTruncatedNormal_S.TV_StatelessParameterizedTruncatedNormal_Tseed.TV_StatelessParameterizedTruncatedNormal_dtypeshapemeansstddevsminvalsmaxvalsc tjxstj}|j}|jr t j |d||||||| } | Stjd|||||||\} } } } | dd} tj rYd| j#dd| j#dd| j#df}| j$}tj&d||| | \} | S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t||||||||S#t j$rYwxYw)arTODO: add doc. Args: shape: A `Tensor`. Must be one of the following types: `int32`, `int64`. The shape of the output tensor. seed: A `Tensor`. Must be one of the following types: `int32`, `int64`. 2 seeds (shape [2]). means: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`. The mean parameter of each batch. stddevs: A `Tensor`. Must have the same type as `means`. The standard deviation parameter of each batch. Must be greater than 0. minvals: A `Tensor`. Must have the same type as `means`. The minimum cutoff. May be -infinity. maxvals: A `Tensor`. Must have the same type as `means`. The maximum cutoff. May be +infinity, and must be more than the minval for each batch. name: A name for the operation (optional). Returns: A `Tensor`. Has the same type as `means`. %StatelessParameterizedTruncatedNormalNrr)rXrrYrZr[r\rSr dtype)r!rr"r#rr$r%r&r'r(r)7stateless_parameterized_truncated_normal_eager_fallbackr+r0r1r.r2r3r4r5)rXrrYrZr[r\rr6r7r8r9r:r;r<r=r>s r?(stateless_parameterized_truncated_normalrcls,    0h..0$ #\\ 11 5tUD w*gn(88/u47r=r8s r?rbrbsD55ugsW]]T[TaTaDde'8E!88$w}}V]VcVcFfhohuhuv+w'>>wPWY`?acfipiuiuw~xGxGIPIXIXi[ \+}'4$5'7Gugw@, '; E&   Eq$0C"& ('""$ /vwP (' .rTTV_StatelessRandomBinomial_S TV_StatelessRandomBinomial_TseedTV_StatelessRandomBinomial_T TV_StatelessRandomBinomial_dtypecountsprobsrac Ptjxstj}|j}|jr t j |d|||||d| }|S|tj}tj |d}t#j$d||||||\} } } } | dd}tj&rjd| j)dd| j)dd| j)dd| j)df} | j*}tj,d|| ||\}|S#t j$r } tj| |Yd} ~ nd} ~ wt j$rYnwxYw t|||||||S#t j$rYEwxYw) aOutputs deterministic pseudorandom random numbers from a binomial distribution. Outputs random values from a binomial distribution. The outputs are a deterministic function of `shape`, `seed`, `counts`, and `probs`. Args: shape: A `Tensor`. Must be one of the following types: `int32`, `int64`. The shape of the output tensor. seed: A `Tensor`. Must be one of the following types: `int32`, `int64`. 2 seeds (shape [2]). counts: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`, `int32`, `int64`. The counts of the binomial distribution. Must be broadcastable with `probs`, and broadcastable with the rightmost dimensions of `shape`. probs: A `Tensor`. Must have the same type as `counts`. The probability of success for the binomial distribution. Must be broadcastable with `counts` and broadcastable with the rightmost dimensions of `shape`. dtype: An optional `tf.DType` from: `tf.half, tf.float32, tf.float64, tf.int32, tf.int64`. Defaults to `tf.int64`. The type of the output. name: A name for the operation (optional). Returns: A `Tensor` of type `dtype`. StatelessRandomBinomialraNrarr)rXrrlrmrarr`r r)r!rr"r#rr$r%r&r'r(r)(stateless_random_binomial_eager_fallbackr+r,r-r.r/r0r1r2r3r4r5)rXrrlrmrarr6r7r8r9r:r;r<r=r>s r?stateless_random_binomialrrs2    0h..0$ #\\ 11 'udFEgn ] MME   UG ,%'88!T&).e$H!QX QK' ""$3%%c*G  )30B0B30Gs))'24F::L !<B (' .3  & &- ##At,,  # #    5 vuE$HH  # #   s0D11E8EE87E8<FF%$F%zraw_ops.StatelessRandomBinomialc  |tj}tj|d}tj|g|tj tjg\}\}tj|g|tj tjgtj\}\}tj||g|tj tjtjtj tjgtj\} } | \}}||||g} d|d|d| d|f} tjdd| | ||} tjrtjd| | | | \} | S) Nrar`r rsStatelessRandomBinomialrBrCro) r,r-r.r/rErHrNrFrGrr2r5)rXrrlrmrarrrerSrR _inputs_Tr>r=r8s r?rqrqs ] MME   UG ,%55ugsW]]T[TaTaDde'8E!88$w}}V]VcVcFfhohuhuv+w66gll\c\k\kmtm|m|FLLNUN[N[N^`g`o`op'9/65vu-, ';Wgu M&   7$0C"& ('""$ !<B (' .rTTV_StatelessRandomGammaV2_dtypeTV_StatelessRandomGammaV2_TTV_StatelessRandomGammaV2_Tseedalphactjxstj}|j}|jr t j |d||||}|Stjd||||\}}} } | dd}tj rYd| j#dd| j#dd| j#df} | j$} tj&d| | ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t|||||S#t j$rYwxYw)aOutputs deterministic pseudorandom random numbers from a gamma distribution. Outputs random values from a gamma distribution. The outputs are a deterministic function of `shape`, `seed`, and `alpha`. Args: shape: A `Tensor`. Must be one of the following types: `int32`, `int64`. The shape of the output tensor. seed: A `Tensor`. Must be one of the following types: `int32`, `int64`. 2 seeds (shape [2]). alpha: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`. The concentration of the gamma distribution. Shape must match the rightmost dimensions of `shape`. name: A name for the operation (optional). Returns: A `Tensor`. Has the same type as `alpha`. StatelessRandomGammaV2Nr_)rXrrxrrarr )r!rr"r#rr$r%r&r'r(r)(stateless_random_gamma_v2_eager_fallbackr+r0r1r.r2r3r4r5) rXrrxrr6r7r8r9r:r;r<r=r>s r?stateless_random_gamma_v2r|sk(    0h..0$ #\\ 11 &eT5Bg n(88 D'+-!QX QK' ""$s))'2C  %w0B0B70KMF::L  ,A (' .+  & &- ##At,,  # #    5 u4T33  # #   s0C33D:D!!D:9D:>EE%$E%zraw_ops.StatelessRandomGammaV2cTtj|g|tjtjtj g\}\}tj|g|tj tjg\}\}tj|g|tj tjgtj\}\}|||g}d|d|d|f} tjdd|| ||} tjrtjd|| | | \} | S)Nrarr sStatelessRandomGammaV2rBrCrz) r.rEr,rNrFrGrHr-rr2r5) rXrrxrrrfrRrSr>r=r8s r?r{r{Is "995'3W^WfWfhohwhwHz{+x55ugsW]]T[TaTaDde'8E!88$w}}V]VcVcFfhohuhuv+wu%, [#w E&   6$0C"& ('""$  ,A (' .rTTV_StatelessRandomNormal_dtypeTV_StatelessRandomNormal_TTV_StatelessRandomNormal_Tseedc "tjxstj}|j}|jr t j |d|||d|}|S|tj}tj |d}t#j$d||||\}}} } | dd}tj&rYd| j)dd| j)dd| j)df} | j*} tj,d| | ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t|||||S#t j$rY0wxYw)aOutputs deterministic pseudorandom values from a normal distribution. The generated values will have mean 0 and standard deviation 1. The outputs are a deterministic function of `shape` and `seed`. Args: shape: A `Tensor`. Must be one of the following types: `int32`, `int64`. The shape of the output tensor. seed: A `Tensor`. Must be one of the following types: `int32`, `int64`. 2 seeds (shape [2]). dtype: An optional `tf.DType` from: `tf.half, tf.bfloat16, tf.float32, tf.float64`. Defaults to `tf.float32`. The type of the output. name: A name for the operation (optional). Returns: A `Tensor` of type `dtype`. StatelessRandomNormalraNrprXrrarrr )r!rr"r#rr$r%r&r'r(r)&stateless_random_normal_eager_fallbackr+r,rFr.r/r0r1r2r3r4r5 rXrrarr6r7r8r9r:r;r<r=r>s r?stateless_random_normalr]s&    0h..0$ #\\ 11 %tUD'5Jg n ] OOE   UG ,%'88u4u&*,!QX QK' ""$s))'2C  %w0B0B70KMF::L vw@ (' .1  & &- ##At,,  # #    3 U499  # #   0DE#/E  E#"E#'E77F Fzraw_ops.StatelessRandomNormalc,|tj}tj|d}tj|g|tj tj gtj \}\}tj|g|tj tj gtj \}\}||g}d|d|d|f}tjdd||||} tjrtjd||| | \} | S)Nrarr sStatelessRandomNormalrBrCr r,rFr.r/rErHr-rr2r5 rXrrarrrRrSr>r=r8s r?rrs ] OOE   UG ,%55ugsW]]T[TaTaDdfmfsfst'8E!88$w}}V]VcVcFfhohuhuv+w, UC'; ?&   5q#)s ?' ""$ vw@ (' .rTTV_StatelessRandomPoisson_RtypeTV_StatelessRandomPoisson_dtypeTV_StatelessRandomPoisson_TTV_StatelessRandomPoisson_Tseedlamc &tjxstj}|j}|jr t j |d||||d|}|Stj|d}tj d|||||\} } } } | dd}tj"rjd| j%dd| j%dd| j%dd| j%df} | j&} tj(d| | ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t||||||S#t j$rY1wxYw) aTOutputs deterministic pseudorandom random numbers from a Poisson distribution. Outputs random values from a Poisson distribution. The outputs are a deterministic function of `shape`, `seed`, and `lam`. Args: shape: A `Tensor`. Must be one of the following types: `int32`, `int64`. The shape of the output tensor. seed: A `Tensor`. Must be one of the following types: `int32`, `int64`. 2 seeds (shape [2]). lam: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`, `int32`, `int64`. The rate of the Poisson distribution. Shape must match the rightmost dimensions of `shape`. dtype: A `tf.DType` from: `tf.half, tf.float32, tf.float64, tf.int32, tf.int64`. The type of the output. name: A name for the operation (optional). Returns: A `Tensor` of type `dtype`. StatelessRandomPoissonraNrp)rXrrrarRtyperr )r!rr"r#rr$r%r&r'r(r)'stateless_random_poisson_eager_fallbackr+r.r/r0r1r2r3r4r5)rXrrrarr6r7r8r9r:r;r<r=r>s r?stateless_random_poissonrs,    0h..0$ #\\ 11 &eT3 gn   UG ,%'88 Dc(-D:!QX QK' ""$s))'2G  )30B0B30Gs))'24F::L  ,A (' ./  & &- ##At,,  # #    4 s%d>>  # #   s0DE$0E  E$#E$(E99FFzraw_ops.StatelessRandomPoissonc tj|d}tj|g|tjtj tj tjtjg\}\}tj|g|tjtjg\}\}tj|g|tjtjgtj\}\}|||g} d|d|d|d|f} tjdd| | ||} tjrtjd| | | | \} | S) Nrarrr sStatelessRandomPoissonrBrCr) r.r/rEr,rNrFrGrHr-rr2r5) rXrrrarr _attr_RtyperRrSr>r=r8s r?rrsP   UG ,% 77sW\\SZSbSbdkdsdsu|vCvCELEREREUV+v55ugsW]]T[TaTaDde'8E!88$w}}V]VcVcFfhohuhuv+ws#, ['5#w  &   6$0C"& ('""$  ,A (' .rTTV_StatelessRandomUniform_dtypeTV_StatelessRandomUniform_TTV_StatelessRandomUniform_Tseedc "tjxstj}|j}|jr t j |d|||d|}|S|tj}tj |d}t#j$d||||\}}} } | dd}tj&rYd| j)dd| j)dd| j)df} | j*} tj,d| | ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t|||||S#t j$rY0wxYw)aOutputs deterministic pseudorandom random values from a uniform distribution. The generated values follow a uniform distribution in the range `[0, 1)`. The lower bound 0 is included in the range, while the upper bound 1 is excluded. The outputs are a deterministic function of `shape` and `seed`. Args: shape: A `Tensor`. Must be one of the following types: `int32`, `int64`. The shape of the output tensor. seed: A `Tensor`. Must be one of the following types: `int32`, `int64`. 2 seeds (shape [2]). dtype: An optional `tf.DType` from: `tf.half, tf.bfloat16, tf.float32, tf.float64`. Defaults to `tf.float32`. The type of the output. name: A name for the operation (optional). Returns: A `Tensor` of type `dtype`. StatelessRandomUniformraNrprrr )r!rr"r#rr$r%r&r'r(r)'stateless_random_uniform_eager_fallbackr+r,rFr.r/r0r1r2r3r4r5rs r?stateless_random_uniformrs(    0h..0$ #\\ 11 &eT7EKg n ] OOE   UG ,%'88 D'+-!QX QK' ""$s))'2C  %w0B0B70KMF::L  ,A (' .1  & &- ##At,,  # #    4 U499  # #   rzraw_ops.StatelessRandomUniformc,|tj}tj|d}tj|g|tj tj gtj \}\}tj|g|tj tj gtj \}\}||g}d|d|d|f}tjdd||||} tjrtjd||| | \} | S)Nrarr sStatelessRandomUniformrBrCrrrs r?rr2s ] OOE   UG ,%55ugsW]]T[TaTaDdfmfsfst'8E!88$w}}V]VcVcFfhohuhuv+w, UC'; ?&   6$0C"& ('""$  ,A (' .rT&TV_StatelessRandomUniformFullInt_dtype"TV_StatelessRandomUniformFullInt_T&TV_StatelessRandomUniformFullInt_Tseedc "tjxstj}|j}|jr t j |d|||d|}|S|tj}tj |d}t#j$d||||\}}} } | dd}tj&rYd| j)dd| j)dd| j)df} | j*} tj,d| | ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t|||||S#t j$rY0wxYw)aOutputs deterministic pseudorandom random integers from a uniform distribution. The generated values are uniform integers covering the whole range of `dtype`. The outputs are a deterministic function of `shape` and `seed`. Args: shape: A `Tensor`. Must be one of the following types: `int32`, `int64`. The shape of the output tensor. seed: A `Tensor`. Must be one of the following types: `int32`, `int64`, `uint32`, `uint64`. 2 seeds (shape [2]). dtype: An optional `tf.DType` from: `tf.int32, tf.int64, tf.uint32, tf.uint64`. Defaults to `tf.uint64`. The type of the output. name: A name for the operation (optional). Returns: A `Tensor` of type `dtype`. StatelessRandomUniformFullIntraNrprrr )r!rr"r#rr$r%r&r'r(r)0stateless_random_uniform_full_int_eager_fallbackr+r,rPr.r/r0r1r2r3r4r5rs r?!stateless_random_uniform_full_intrHs&    0h..0$ #\\ 11 -tUD' gn ] NNE   UG ,%'88'u4u.24!QX QK' ""$s))'2C  %w0B0B70KMF::L 'vwH (' .1  & &- ##At,,  # #    = U499  # #   rz%raw_ops.StatelessRandomUniformFullIntch|tj}tj|d}tj|g|tj tj gtj \}\}tj|g|tj tj tjtjgtj \}\}||g}d|d|d|f}tjdd||||} tjrtjd||| | \} | S)Nrarr sStatelessRandomUniformFullIntrBrCr) r,rPr.r/rErHr-rOrr2r5rs r?rrs' ] NNE   UG ,%55ugsW]]T[TaTaDdfmfsfst'8E!88$w}}V]VcVcelesesu|vDvDGGIPIVIVW+w, UC'; ?&   =q$0C"& ('""$ 'vwH (' .rT"TV_StatelessRandomUniformInt_dtypeTV_StatelessRandomUniformInt_T"TV_StatelessRandomUniformInt_Tseedminvalmaxvalc tjxstj}|j}|jr t j |d|||||}|Stjd|||||\} } } } | dd}tj rYd| j#dd| j#dd| j#df} | j$} tj&d| | ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t||||||S#t j$rY wxYw)a+Outputs deterministic pseudorandom random integers from a uniform distribution. The generated values follow a uniform distribution in the range `[minval, maxval)`. The outputs are a deterministic function of `shape`, `seed`, `minval`, and `maxval`. Args: shape: A `Tensor`. Must be one of the following types: `int32`, `int64`. The shape of the output tensor. seed: A `Tensor`. Must be one of the following types: `int32`, `int64`. 2 seeds (shape [2]). minval: A `Tensor`. Must be one of the following types: `int32`, `int64`. Minimum value (inclusive, scalar). maxval: A `Tensor`. Must have the same type as `minval`. Maximum value (exclusive, scalar). name: A name for the operation (optional). Returns: A `Tensor`. Has the same type as `minval`. StatelessRandomUniformIntNr_)rXrrrrrarr )r!rr"r#rr$r%r&r'r(r)+stateless_random_uniform_int_eager_fallbackr+r0r1r.r2r3r4r5)rXrrrrr6r7r8r9r:r;r<r=r>s r?stateless_random_uniform_intrsq*    0h..0$ #\\ 11 )4ffNg n(88#5tF,2?!QX QK' ""$s))'2C  %w0B0B70KMF::L #\67D (' .+  & &- ##At,,  # #    8 vvDd<<  # #   s0C55D<D##D<;D<EE('E(z!raw_ops.StatelessRandomUniformIntc@tj||g|tjtjg\}}|\}}tj|g|tjtjg\}\}tj|g|tjtjgtj\} \}||||g} d|d|d| f} tj dd| | ||} tj rtjd| | | | \} | S)Nrarr sStatelessRandomUniformIntrBrCr)r.rEr,rHr-rr2r5) rXrrrrrrfrgrRrSr>r=r8s r?rrs'>>?OQTW^WdWdfmfsfsVvw+}"6655ugsW]]T[TaTaDde'8E!88$w}}V]VcVcFfhohuhuv+wvv., [#w E&   91$0C"& ('""$ #\67D (' .rT!TV_StatelessTruncatedNormal_dtypeTV_StatelessTruncatedNormal_T!TV_StatelessTruncatedNormal_Tseedc "tjxstj}|j}|jr t j |d|||d|}|S|tj}tj |d}t#j$d||||\}}} } | dd}tj&rYd| j)dd| j)dd| j)df} | j*} tj,d| | ||\}|S#t j$r }tj||Yd}~nd}~wt j$rYnwxYw t|||||S#t j$rY0wxYw)a1Outputs deterministic pseudorandom values from a truncated normal distribution. The generated values follow a normal distribution with mean 0 and standard deviation 1, except that values whose magnitude is more than 2 standard deviations from the mean are dropped and re-picked. The outputs are a deterministic function of `shape` and `seed`. Args: shape: A `Tensor`. Must be one of the following types: `int32`, `int64`. The shape of the output tensor. seed: A `Tensor`. Must be one of the following types: `int32`, `int64`. 2 seeds (shape [2]). dtype: An optional `tf.DType` from: `tf.half, tf.bfloat16, tf.float32, tf.float64`. Defaults to `tf.float32`. The type of the output. name: A name for the operation (optional). Returns: A `Tensor` of type `dtype`. StatelessTruncatedNormalraNrprrr )r!rr"r#rr$r%r&r'r(r))stateless_truncated_normal_eager_fallbackr+r,rFr.r/r0r1r2r3r4r5rs r?stateless_truncated_normalrs*    0h..0$ #\\ 11 ($tWeMg n ] OOE   UG ,%'88"%d%)-/!QX QK' ""$s))'2C  %w0B0B70KMF::L "L&'C (' .1  & &- ##At,,  # #    6 U499  # #   rz raw_ops.StatelessTruncatedNormalc,|tj}tj|d}tj|g|tj tj gtj \}\}tj|g|tj tj gtj \}\}||g}d|d|d|f}tjdd||||} tjrtjd||| | \} | S)Nrarr sStatelessTruncatedNormalrBrCrrrs r?rrs ] OOE   UG ,%55ugsW]]T[TaTaDdfmfsfst'8E!88$w}}V]VcVcFfhohuhuv+w, UC'; ?&   8!$0C"& ('""$ "L&'C (' .rT)N)g__doc__ collectionstensorflow.pythonrtensorflow.python.eagerrr!rr%rr.tensorflow.python.frameworkrr,tensorflow.security.fuzzing.pyr_atypesr _op_def_registryr r'r r0"tensorflow.python.util.deprecationr tensorflow.python.utilr _dispatch tensorflow.python.util.tf_exportrtypingrrrtyping_extensionsrrrrr-Int32r@ to_raw_oprr*rUrVrWrcr^rbrhrirjrkrrrorqrurvrwr|rzr{r~rrrFrrrrrrrrrrrrrrrrrrrrPrrrrrrrrrrrrrrrrTr?rsY 67179FK3IC86%%'#$?ASUfhy|JL[]ln}MO_aqsCETU '(GZi j'./UWfhw'x$ahananuy4)C1J,J"K4ZcdgipivivdvZw4@IJMOlJl@m4|`4~GHKMqHq~r4lAy!?@PeAfg3@Y;Y1ZirsvxyFyFtFjGOXY\^{Y{O|Lp@IJMOsJs@t$.55acruD.E*189ikz}L2M.189ik|PR`2a.6IcCm>m4n6vADFtAtwu6~GHKM{H{~|6GPQTVDQDGE6PYZ]_MZMPN6YbcfhVcVYW6gpqtvdqdge6p)c 2a(bcqcgcqcqs[d\)]%9SR|M|C}FOPSUCPCFDMVWZ\JWJMKV_`ceS`SVT_hiln\i\_]hqruwerehfv@CEs@svt" ''EXgh#*+M`o#p &'EGXZkm{~MO^ _#*+MO`bsvDFUWf$g ^e^k^krv:Ys4P/P%Q:YbcfiIdIZJ:T]^ac^T@:IRSVXtStIu:}]:{DEHJjEj{k:xG)$EF~t~~VoGpqIcC_>_4`hqruxXsXiYclmprNmNcOXabegCbCXDMm}FGJLlGl}m(#**KM^`qtB#C%&C_Vef")*K_^m"n0Ys4O/O%P0XabehGcGYH0QZ[^`[Q@0PYZ]_~Z~P0dE#CD^T^^TmEno IcC^>^4_ gpqtwVrVhW `ijmoNjN`O _hilnMiM_N  "))IK]_psDFT"U$%A?Tcd!()I?\k!lkrkzkzAE29S2L-L#M2U^_beC`CVD2Lj2JSTWYwTwJx2hC "AB>4>>RiCjk)CA[<[2\dmnqtRoReS\zJSTWYwTwJx"#**KM^`qtBDSUd#e")*KM^`qtBDSUd#e%&C_Vef")*K_^m"n5Ic3N.N$O5W`adgFbFXG5NWX[]|X|N}5Fe5u~BDccud5nE#CD^T^^TlEmn9SB]=]3^fopsvUqUgV]fgjlKgK]LUtDMNQSrNrDs$#**KM_aruFHV#W%&C_Vef")*K_^m"novo~o~EI3Ic3N.N$O3W`adgFbFXG3On3NWX[]|X|N}3jE#CD^T^^TlEmn9SB]=]3^fopsvUqUgV_~NWX[]|X|N}$*11Y[jl{~NP`*a&%,-QSbds%t")01Y[jl{~NP`*a&MTM[M[bf3Ys<^7^-_3gpqtw]r]h^3fL3ktuxz`u`ka3j!S *Q RSaSWSaSacDTE!FIcKmFm4>>ZvKwxyFdAd7emvwz}_x_n`jstwy[t[j\fopsuWpWfXhqruwYrYhZ"%,,OQcevyJLZ%[! '(GZi j$+,OQ`bq$r!w~wFwFMQ4i5R0R&S4[dehkLfL\M4Uv4V_`ceF`FVG4lI9%GHXrIstYsDa?a5bjstwz[u[k\eFV_`ceF`FVGrT