o hZ@sjddlZddlZddlZddlmZddlZddlZddlm Z ddl m Z m Z m Z ddlmZddlmZddlmZddlmZdd lmZd d lmZd d lmZmZgd ZeeZ iej!dej"dej#dej$dej%dej&dej'dej(dej)dej*dej+dej,dej-dej.dej/dej0dej1dej2dej3dej4dej5dej6dej7dej)dej8dej9di Z:ddZ;   dRd d!Zd'd(Z?d)d*Z@dUd+d,ZAdUd-d.ZBdVd0d1ZC dWd3d4ZDdUd5d6ZEdXd7d8ZFdYd:d;ZGdparameter: hparam_dict should be a dictionary, nothing logged.z>parameter: metric_dict should be a dictionary, nothing logged.zIparameter: hparam_domain_discrete should be a dictionary, nothing logged.c3s"|] }t|tVqdSN)r:type.0d) hparam_dictkrBrC s zhparams..z"parameter: hparam_domain_discrete[z/] should be a list of same type as hparam_dict[z].cSg|]}tj|dqS)) number_valuerValuerurBrBrC  zhparams..)valuesDATA_TYPE_FLOAT64)namertdomain_discretecSr{)) string_valuer}rurBrBrCrrDATA_TYPE_STRINGcSr{)) bool_valuer}rurBrBrCrrDATA_TYPE_BOOL)rrtz=value should be one of int, float, str, bool, or torch.Tensor)session_start_infoversion plugin_namecontent plugin_data)tagmetadatavaluecsg|] }|ddqS)r)rrB)rvry)rhrirBrCr%) hparam_infos metric_infos) experimentrSTATUS_SUCCESS)status)session_end_infor).torch#tensorboard.plugins.hparams.api_pb2rerfrgrhrirj$tensorboard.plugins.hparams.metadatarkrlrmrnro+tensorboard.plugins.hparams.plugin_data_pb2rprqrrr:dictloggerwarning TypeErroritemslistallintfloatrr|r ListValueappendr~strrboolrTensorr ValueErrorr PluginDataSerializeToStringrkeys)rx metric_dicthparam_domain_discreterrerfrgrjrkrlrmrnrorprqrrvhpsssirrsmdmtsexpseirB)rhrirxryrCrs                   rFc Cst|}|jdksJd|jd|jdt|}|rEt|gdd}|r.t|gdd}tjd d }t|d }ttj |||d gd Sttj ||dgd S)aOutputs a `Summary` protocol buffer containing a single scalar value. The generated Summary has a Tensor.proto containing the input Tensor. Args: name: A name for the generated node. Will also serve as the series name in TensorBoard. tensor: A real numeric Tensor containing a single value. collections: Optional list of graph collections keys. The new summary op is added to these collections. Defaults to `[GraphKeys.SUMMARIES]`. new_style: Whether to use new style (tensor field) or old style (simple_value field). New style could lead to faster data loading. Returns: A scalar `Tensor` of type `string`. Which contains a `Summary` protobuf. Raises: ValueError: If tensor has the wrong shape or type. rzBTensor should contain one element (0 dimensions). Was given size: z and z dimensions.r')r&r>r()r)r>scalarsrrrr@rr)r simple_value) r squeezendimsizerrrrrr~) rr@ collections new_styledouble_precisionrrrrrBrBrCr=s(     rcsjdkr tdjtvritjd}|dks!|dkr+t}ndkr7 g}ndkr@g}n}dtjddt fd d t Dd ||i}t di|}n t|d jtjd d}t|d}ttj|||dgdS)aOutputs a `Summary` protocol buffer containing the full tensor. The generated Summary has a Tensor.proto containing the input Tensor. Args: name: A name for the generated node. Will also serve as the series name in TensorBoard. tensor: Tensor to be converted to protobuf Returns: A tensor protobuf in a `Summary` protobuf. Raises: ValueError: If tensor is too big to be converted to protobuf, or tensor data type is not supported lzAtensor is bigger than protocol buffer's hard limit of 2GB in sizer r2r7rr> tensor_shapecsg|] }tjj|dqS)r)rDimshape)rvir@rBrCrsz tensor_proto..dimz has unsupported tensor dtype r@rrrrr@rNrB)numelitemsizerr>_TENSOR_TYPE_MAPr view_as_realflattentolistitemrrangerrrrrr~)rr@proto_val_fieldproto_val_contentstensor_proto_argsrrrrBrrCrgs4           rc Cs,t|||||||d}ttj||dgdS)aOutputs a `Summary` protocol buffer with a histogram. The generated [`Summary`](https://www.tensorflow.org/code/tensorflow/core/framework/summary.proto) has one summary value containing a histogram for `values`. Args: name: A name for the generated node. Will also serve as a series name in TensorBoard. min: A float or int min value max: A float or int max value num: Int number of values sum: Float or int sum of all values sum_squares: Float or int sum of squares for all values bucket_limits: A numeric `Tensor` with upper value per bucket bucket_counts: A numeric `Tensor` with number of values per bucket Returns: A scalar `Tensor` of type `string`. The serialized `Summary` protocol buffer. minmaxnumsum sum_squares bucket_limitbucketrhistor)rrr~) rrrrrr bucket_limits bucket_countshistrBrBrCrs rcCs0t|}t|t||}ttj||dgdS)adOutputs a `Summary` protocol buffer with a histogram. The generated [`Summary`](https://www.tensorflow.org/code/tensorflow/core/framework/summary.proto) has one summary value containing a histogram for `values`. This op reports an `InvalidArgument` error if any value is not finite. Args: name: A name for the generated node. Will also serve as a series name in TensorBoard. values: A real numeric `Tensor`. Any shape. Values to use to build the histogram. Returns: A scalar `Tensor` of type `string`. The serialized `Summary` protocol buffer. rr)r rastyperrr~)rrbinsmax_binsrrBrBrCrsrc Cs|jdkr td|d}tj||d\}}t|}|dure||kre||}||}|dkr=tj|d||ggddd}|d|jdd}t|jd f|j }|dd||dd<|d|d<|}t t |d} tj | d| dd gd d \} } t | } t | d } ~ | dkr|| d | n tdg|d| g}|| | d }|jdks|jdkrtd ||} t||t||| ||d S)zDConvert values into a histogram proto using logic from histogram.cc.rzThe input has no element.)rNconstant) pad_widthmodeconstant_values)axisr r])sidez1The histogram is empty, please file a bug report.r)rrreshaper;rlenpadremptyr>cumsumgreater searchsortedr concatenatedotrrrr) rrrcountslimitsnum_bins subsamplingsubsampling_remainder new_limits cum_countsstartendsum_sqrBrBrCrsP      . rNCHWcCs`t|}t||}t|}|tj}||ddtj}t||d}t t j ||dgdS)aJOutputs a `Summary` protocol buffer with images. The summary has up to `max_images` summary values containing images. The images are built from `tensor` which must be 3-D with shape `[height, width, channels]` and where `channels` can be: * 1: `tensor` is interpreted as Grayscale. * 3: `tensor` is interpreted as RGB. * 4: `tensor` is interpreted as RGBA. The `name` in the outputted Summary.Value protobufs is generated based on the name, with a suffix depending on the max_outputs setting: * If `max_outputs` is 1, the summary value tag is '*name*/image'. * If `max_outputs` is greater than 1, the summary value tags are generated sequentially as '*name*/image/0', '*name*/image/1', etc. Args: tag: A name for the generated node. Will also serve as a series name in TensorBoard. tensor: A 3-D `uint8` or `float32` `Tensor` of shape `[height, width, channels]` where `channels` is 1, 3, or 4. 'tensor' can either have values in [0, 1] (float32) or [0, 255] (uint8). The image() function will scale the image values to [0, 255] by applying a scale factor of either 1 (uint8) or 255 (float32). Out-of-range values will be clipped. Returns: A scalar `Tensor` of type `string`. The serialized `Summary` protocol buffer. rr9)rescalerrr) r rrDrr;float32clipr?rrr~)rr@r dataformats scale_factorrrBrBrCrs   rCHWcCsdt|}t||}t|}|tjt|}t|ddtj|||d}t t j ||dgdS)z0Outputs a `Summary` protocol buffer with images.rr9)rroislabelsrr) r rrr;rrDrrr?rr~)r tensor_image tensor_boxesrrr rrBrBrCr*s rc Csf|jd}t|}|D]%}t|||df||df||df||df|dur)dn||dd}q |S)Nrr rFRed)rWrX)rrrd) disp_imageboxesr  num_boxeslist_gtrrBrBrCr;s      rcCsddlm}|j\}}}t||}t||} ||} |dur(t| ||d} z|jj} Wn ty:|j } Ynw| | |f| } ddl } | } | j | dd| }| tj||||dS)z string_valrcustom_scalars__config__rr)rrr MarginChartContentSeriesChartMultilineChartContentrCategoryLayoutrrrrrrr~)layout categoriesryrcharts chart_namechart_meatadatatagsmgccrcmlccrrr@rBrBrCrs<      rcCsftjdtddd}t|d}td|jddgttjd d gd d }ttj |d ||dgdS)Nrr)rrrreutf_8)encodingr rrrfz /text_summaryrr) rrr rrencoderrrr~)rrrrr@rBrBrCrs  rc Cs|dkrd}t||||||f} td|d} tjd| d} t| d} td| dt t j | j dd t j | j d d gd d } t t j || | d gdS)Nrzrrnum_thresholds pr_curvesrrr'rrr rr>r&rrr)r;stackr rrrrrrrrrrr~)rtpfptnfn precisionrecallr|weightsrWpr_curve_plugin_datarrr@rBrBrCrs,   rc Cst|d}t||||d}td|d}tjd|d}t|d}td|d t t j |j dd t j |j d d gd d } t t j ||| dgdS)Nrz)r|rrr{r}rrr'rrr rr~rr)rr!r rrrrrrrrrrr~) rr  predictionsr|rrWrrrr@rBrBrCr s.    r cCs d}|durd}tt||d}|tj}d|df}tj|||||d\}} tj|||d||d\} } t|dddddd} t| dddddd} | d| } | d| }| t|| | }| t|| |}t| | | |||fS)NgHz>g?r r)rrrr) r;int32floorrfloat64rrmaximumr)r rr|r_MINIMUM_COUNTbucket_indices float_labelshistogram_range tp_buckets_ fp_bucketsrrrrrrrBrBrCr!&s2       r!c Csddl}ddlm}||}|j|||||j||d} td|dt t j |jddt j |jddt j |jd dgd d }t j | |||| d } | S) aCreates a tensor summary with summary metadata. Args: name: Uniquely identifiable name of the summary op. Could be replaced by combination of name and type to make it unique even outside of this summary. display_name: Will be used as the display name in TensorBoard. Defaults to `name`. description: A longform readable description of the summary data. Markdown is supported. tensor: Tensor to display in summary. content_type: Type of content inside the Tensor. components: Bitmask representing present parts (vertices, colors, etc.) that belong to the summary. json_config: A string, JSON-serialized dictionary of ThreeJS classes configuration. Returns: Tensor summary with metadata. rNr) json_configr'rrr rFrr~r)rtensorboard.plugins.meshr as_tensorcreate_summary_metadatarrrrrrrr~get_instance_name) r display_name descriptionr@rN componentsrrrtensor_metadatatensor_summaryrBrBrC_get_tensor_summaryGs8     rcCsd}|dur tj|dd}|S)z6Parses and returns JSON string from python dictionary.z{}NT) sort_keys)jsondumps) config_dictrrBrBrC_get_json_configsrc Csddlm}ddlm}t|} g} ||jf||jf||jfg} dd| D} |dd| D} | D]\} }| t |||| || | q3t | dS)a(Outputs a merged `Summary` protocol buffer with a mesh/point cloud. Args: tag: A name for this summary operation. vertices: Tensor of shape `[dim_1, ..., dim_n, 3]` representing the 3D coordinates of vertices. faces: Tensor of shape `[dim_1, ..., dim_n, 3]` containing indices of vertices within each triangle. colors: Tensor of shape `[dim_1, ..., dim_n, 3]` containing colors for each vertex. display_name: If set, will be used as the display name in TensorBoard. Defaults to `name`. description: A longform readable description of the summary data. Markdown is supported. config_dict: Dictionary with ThreeJS classes names and configuration. Returns: Merged summary for mesh/point cloud representation. rr)MeshPluginDatacSsg|] }|ddur|qS)rNrB)rvr@rBrBrCrrzmesh..cSsg|]\}}|qSrBrB)rvr@rNrBrBrCrsr) rr(tensorboard.plugins.mesh.plugin_data_pb2rrVERTEXFACECOLORget_components_bitmaskrrr)rverticescolorsfacesrrrrrr summariestensorsrr@rNrBrBrCr"s2     r")rErErF)NNN)NFFrs)r r)r r N)r NN)r,)rH)rzN)NN)Rrloggingr=typingrrr=r;google.protobufr$tensorboard.compat.proto.summary_pb2rrr#tensorboard.compat.proto.tensor_pb2r)tensorboard.compat.proto.tensor_shape_pb2r!tensorboard.plugins.custom_scalarr ,tensorboard.plugins.pr_curve.plugin_data_pb2r (tensorboard.plugins.text.plugin_data_pb2r _convert_npr _utilsrr__all__ getLogger__name__rhalffloat16bfloat16rrrdoubleint8r?qint8rQshortrrqint32int64 complex32chalf complex64cfloatr complex128cdoublequint8quint4x2rrDrdrrrrrrrrrrrrrrrrr r!rrr"rBrBrBrCs                * =*3  7%    +%  !;