U Vcl@s$dZddlZddlZddlZddlmZddlmZddlm Z ddlm Z ddlm Z ddlm Z Gd d d e Zd d Zd dZddZddZddZddZddZddZddZddZdd Zd!d"Zed#d$ZGd%d&d&e Zd'd(Zed)d*d+gZd,d-Z d.d/Z!d0d1Z"dS)2zBClasses and functions for handling the ListSessionGroups API call.N) struct_pb2)provider)api_pb2)error)metadata)metricsc@sheZdZdZddZddZddZdd Zd d Zd d Z ddZ ddZ ddZ ddZ ddZdS)Handlerz$Handles a ListSessionGroups request.cCsX||_||_||_||_t|j|_t|j|j|_| |||_ | |||j |_ dS)a$Constructor. Args: request_context: A tensorboard.context.RequestContext. backend_context: A backend_context.Context instance. experiment_id: A string, as from `plugin_util.experiment_id`. request: A ListSessionGroupsRequest protobuf. 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Representing the session groups and sessions found so far. )r&r2 monitor_urlN) group_namer&r2extendrZ SessionGrouprBhparamsr)ZCopyFrom)rr?r=r7rCrAr(valuerrrr0s  zHandler._add_sessioncCsJ|dk s ttj||j|j||||jd}|dk rF|j|_|j|_|S)zBuilds a session object.N)r&start_time_secs model_uri metric_valuesrB) AssertionErrorrSessionrGrH_build_session_metric_valuesrBr/Z end_time_secs)rr&r=r>r<resultrrrr.s  zHandler._build_sessionc Csfg}|jj}|D]P}|j}t||\}}||i|} | sBq|tj|| j | j | j dq|S)z!Builds the session metric values.)r&wall_time_secs training_steprF) rr+r&rr,getappendrZ MetricValueZ wall_timesteprF) rr8r<rMr+Z metric_infor:r r;ZdatumrrrrLs(z$Handler._build_session_metric_valuescCs|jjtjks|jjtjkr&t|np|jjtjkrDt||jjnR|jjtj krdt ||jjt n2|jjtj krt ||jjt ntd|jjdS)z8Sets the metrics of the group based on aggregation_type.z'Unknown aggregation_type in request: %sN)r Zaggregation_typerZAGGREGATION_AVGZAGGREGATION_UNSET_set_avg_session_metricsZAGGREGATION_MEDIAN_set_median_session_metricsaggregation_metricZAGGREGATION_MIN_set_extremum_session_metricsminZAGGREGATION_MAXmaxr HParamsErrorr session_grouprrrr6s6   zHandler._aggregate_metricscsfdd|DS)Ncsg|]}|r|qSr)_passes_all_filters)r"Zsgrrrr$s z#Handler._filter..rrrr]rrszHandler._filtercstfdd|jDS)Nc3s|]}|VqdSNr)r" filter_fnr[rr sz.Handler._passes_all_filters..)allrrZrr`rr\szHandler._passes_all_filterscCs|jtddttt|jj|jD]p\}}|j t j kr@q*|j t j krf|jt ||j ddq*|j t jkr|jt ||jdddq*td|q*dS)zASorts 'session_groups' in place according to _request.col_params.r&r')none_is_largestT)r(reversez!Unknown col_param.order given: %sN)r3r4r5reversedlistzipr rrorderrZORDER_UNSPECIFIEDZ ORDER_ASC_create_key_funcZmissing_values_firstZ ORDER_DESCrrY)rr col_param extractorrrrrs0    z Handler._sortcCs*tj||jj|jj|jjt|dS)N)rZ total_size)rZListSessionGroupsResponser start_indexZ slice_sizelenrrrrrszHandler._create_responseN)__name__ __module__ __qualname____doc__rr rr0r.rLr6rr\rrrrrrrs @##rcs$|rfdd}|Sfdd}|S)aReturns a key_func to be used in list.sort(). Returns a key_func to be used in list.sort() that sorts session groups by the value extracted by extractor. 'None' extracted values will either be considered largest or smallest as specified by the "none_is_largest" boolean parameter. Args: extractor: An extractor function that extract the key from the session group. none_is_largest: bool. If true treats 'None's as largest; otherwise smallest. cs|}|dk|fSr^rr[rFrkrrkey_func_none_is_largest5sz2_create_key_func..key_func_none_is_largestcs|}|dk |fSr^rrrrsrrkey_func_none_is_smallest;sz3_create_key_func..key_func_none_is_smallestr)rkrcrtrurrsrri%s   ricCs g}|D]}|t|q|S)aMCreates extractors to extract properties corresponding to 'col_params'. Args: col_params: List of ListSessionGroupsRequest.ColParam protobufs. Returns: A list of extractor functions. The ith element in the returned list extracts the column corresponding to the ith element of _request.col_params )rQ_create_extractor)rrMrjrrrr Ds r cCs:|drt|jS|dr(t|jStd|dS)Nr9hparamz=Got ColParam with both "metric" and "hparam" fields unset: %s)HasField_create_metric_extractorr9_create_hparam_extractorrwrrY)rjrrrrvTs    rvcsfdd}|S)aReturns function that extracts a metric from a session group or a session. Args: metric_name: tensorboard.hparams.MetricName protobuffer. Identifies the metric to extract from the session group. Returns: A function that takes a tensorboard.hparams.SessionGroup or tensorborad.hparams.Session protobuffer and returns the value of the metric identified by 'metric_name' or None if the value doesn't exist. cst|}|r|jSdSr^)_find_metric_valuerF)session_or_group metric_valuer:rr extractor_fnms z._create_metric_extractor..extractor_fnr)r:rrr~rry`s rycCs4|jD](}|jj|jkr|jj|jkr|SqdS)aReturns the metric_value for a given metric in a session or session group. Args: session_or_group: A Session protobuffer or SessionGroup protobuffer. metric_name: A MetricName protobuffer. The metric to search for. Returns: A MetricValue protobuffer representing the value of the given metric or None if no such metric was found in session_or_group. N)rIr&r;rA)r|r:r}rrrr{ts    r{csfdd}|S)aoReturns an extractor function that extracts an hparam from a session group. Args: hparam_name: str. Identies the hparam to extract from the session group. Returns: A function that takes a tensorboard.hparams.SessionGroup protobuffer and returns the value, as a native Python object, of the hparam identified by 'hparam_name'. cs|jkrt|jSdSr^)rE_value_to_pythonr` hparam_namerrrs z._create_hparam_extractor..extractor_fnr)rrrrrrzs rzcCs4g}t||D] \}}t||}|r||q|S)aCreates filters for the given col_params. Args: col_params: List of ListSessionGroupsRequest.ColParam protobufs. extractors: list of extractor functions of the same length as col_params. Each element should extract the column described by the corresponding element of col_params. Returns: A list of filter functions. Each corresponding to a single col_params.filter oneof field of _request )rg_create_filterrQ)rZ extractorsrMrjrkZa_filterrrrrs   rcsn|j |drt|jn<|dr4t|jn&|drJt|jnrRdSddfdd}|S) afCreates a filter for the given col_param and extractor. Args: col_param: A tensorboard.hparams.ColParams object identifying the column and describing the filter to apply. extractor: A function that extract the column value identified by 'col_param' from a tensorboard.hparams.SessionGroup protobuffer. Returns: A boolean function taking a tensorboard.hparams.SessionGroup protobuffer returning True if the session group passes the filter described by 'col_param'. If col_param does not specify a filter (i.e. any session group passes) returns None. filter_regexpfilter_intervalfilter_discreteNcSsdS)NTr)_rrrz _create_filter..cs|}|dkrS|Sr^rrrrkZinclude_missing_valuesZvalue_filter_fnrrr_sz!_create_filter..filter_fn)Zexclude_missing_valuesrx_create_regexp_filterr_create_interval_filterr_create_discrete_set_filterr)rjrkr_rrrrs      rcst|fdd}|S)zReturns a boolean function that filters strings based on a regular exp. Args: regex: A string describing the regexp to use. Returns: A function taking a string and returns True if any of its substrings matches regex. cs0t|ts tdt||ft|dk S)Nz.filter_fn)rcompile)regexr_rrrrs  rcsfdd}|S)a0Returns a function that checkes whether a number belongs to an interval. Args: interval: A tensorboard.hparams.Interval protobuf describing the interval. Returns: A function taking a number (float or int) that returns True if the number belongs to (the closed) 'interval'. cs8t|ttfs$tdt||fj|ko6|jkS)Nz@Cannot use an interval filter for a value of type: %s, Value: %s)rintfloatrrYrZ min_valueZ max_valuerintervalrrr_s z*_create_interval_filter..filter_fnr)rr_rrrrs rcsfdd}|S)aiReturns a function that checks whether a value belongs to a set. Args: discrete_set: A list of objects representing the set. Returns: A function taking an object and returns True if its in the set. Membership is tested using the Python 'in' operator (thus, equality of distinct objects is computed using the '==' operator). cs|kSr^rr discrete_setrrr_sz._create_discrete_set_filter..filter_fnr)rr_rrrr s rcCsTt|tjst|d}|dkr(|jS|dkr6|jS|dkrD|jStd|dS)z;Converts a google.protobuf.Value to a native Python object.kind number_value string_value bool_valuez,Unknown struct_pb2.Value oneof field set: %sN) rrValuerJZ WhichOneofrrr ValueError)rFfieldrrrrs r_MetricIdentifierz group tagc@s$eZdZdZddddgZddZdS) _MetricStatsa A simple class to hold metric stats used in calculating metric averages. Used in _set_avg_session_metrics(). See the comments in that function for more details. Attributes: total: int. The sum of the metric measurements seen so far. count: int. The number of largest-step measuremens seen so far. total_step: int. The sum of the steps at which the measurements were taken total_wall_time_secs: float. The sum of the wall_time_secs at which the measurements were taken. totalcount total_steptotal_wall_time_secscCsd|_d|_d|_d|_dS)Nrg)rrrrr]rrrrLsz_MetricStats.__init__N)rnrorprq __slots__rrrrrr5srcCs|jstdtt}|jD]j}|jD]^}t|jj|jj d}||}|j |j 7_ |j d7_ |j |j7_ |j|j7_q(q|jdd=|D]J\}}|jjtj|j|j dt|j t|j |j |j |j|j dqdS)aSets the metrics for the group to be the average of its sessions. The resulting session group metrics consist of the union of metrics across the group's sessions. The value of each session group metric is the average of that metric values across the sessions in the group. The 'step' and 'wall_time_secs' fields of the resulting MetricValue field in the session group are populated with the corresponding averages (truncated for 'step') as well. Args: session_group: A SessionGroup protobuffer. zSessionGroup cannot be empty.)rAr;N)r&rFrOrN)r2rJ collections defaultdictrrIrr&rAr;rrFrrrOrrNr)r-rZ MetricNamer)r[Z metric_statsr?r}r:statsrrrrSSs0       rS _Measurementr} session_indexcCsRtt||tdd}|t|ddj}|jdd=|j|j|jdS)aSets the metrics for session_group to those of its "median session". The median session is the session in session_group with the median value of the metric given by 'aggregation_metric'. The median is taken over the subset of sessions in the group whose 'aggregation_metric' was measured at the largest training step among the sessions in the group. Args: session_group: A SessionGroup protobuffer. aggregation_metric: A MetricName protobuffer. metric_value.valuer'rN) sorted _measurementsr4r5rmrrI MergeFromr2)r[rU measurementsZmedian_sessionrrrrTs   rTcCsBt||}||tddj}|jdd=|j|j|jdS)a[Sets the metrics for session_group to those of its "extremum session". The extremum session is the session in session_group with the extremum value of the metric given by 'aggregation_metric'. The extremum is taken over the subset of sessions in the group whose 'aggregation_metric' was measured at the largest training step among the sessions in the group. Args: session_group: A SessionGroup protobuffer. aggregation_metric: A MetricName protobuffer. extremum_fn: callable. Must be either 'min' or 'max'. Determines the type of extremum to compute. rr'N)rr4r5rrIrr2)r[rUZ extremum_fnrZ ext_sessionrrrrVs   rVccs4t|jD]$\}}t||}|s"q t||Vq dS)aA generator for the values of the metric across the sessions in the group. Args: session_group: A SessionGroup protobuffer. metric_name: A MetricName protobuffer. Yields: The next metric value wrapped in a _Measurement instance. N) enumerater2r{r)r[r:rr?r}rrrrs  r)#rqrr4rZgoogle.protobufrZtensorboard.datarZtensorboard.plugins.hparamsrrrrobjectrrir rvryr{rzrrrrrr namedtuplerrrSrrTrVrrrrrsD       & +