a du@sddlZddlZddlZddlmZddlZddlmZddl m Z ddl m Z ddl m Z ddl mZddlmZdd lmZdd lmZdd lmZd d lmZd dlmZmZgdZeeZddZ dDddZ!dEddZ"dFddZ#ddZ$dGddZ%dHdd Z&dId"d#Z'dJd%d&Z(dKd'd(Z)dLd)d*Z*dMd,d-Z+d.d/Z,dNd1d2Z-d3d4Z.d5d6Z/dOd8d9Z0dPd:d;Z1dQdd?Z3d@dAZ4dRdBdCZ5dS)SN)Optional) struct_pb2)HistogramProto)Summary)SummaryMetadata) TensorProto)TensorShapeProto) layout_pb2)PrCurvePluginData)TextPluginData)make_np)_prepare_videoconvert_to_HWC)hparamsscalar histogram_raw histogrammake_histogramimage image_boxes draw_boxes make_imagevideo make_videoaudiocustom_scalarstext pr_curve_rawpr_curve compute_curvemeshcCs,t|tjs|n|}|jtjkr(dSdS)Nr ) isinstancenpZndarraynumpydtypeuint8)tensorZ convertedr)h/var/www/html/stable-diffusion-webui/venv/lib/python3.9/site-packages/torch/utils/tensorboard/summary.py_calc_scale_factorsr+blackc Csddlm} m} | } | |} ||||f\} }}}| j| |f| |f||f||f| |fg||d|r|}| |\}}td|}| j | ||d|f| ||fg|d| j | ||||f||| d|S)Nr) ImageDraw ImageFont)widthfillg?r-)r1)r1font) PILr.r/Z load_defaultZDrawlinegetsizer$ceilZ rectangler)rZxminZyminZxmaxZymax display_strcolorZ color_textZ thicknessr.r/r2ZdrawleftrighttopZbottomZ text_bottom text_widthZ text_heightmarginr)r)r*_draw_single_box!s4    r>cs~ddl}ddlm}m}mmm}m}ddlm }m } m } m } m } ddlm} m}m}ttsttdtdt|tstdtd|pi}t|tstd|D]B\}vst|trtfd d |Dstd qg}|}D]\}|dur qt|ttfr||j_|vrbtj d d |Dd}nd}|!||"d|dqt|t#r||j_$|vrtj dd |Dd}nd}|!||"d|dqt|t%rD||j_&|vr"tj dd |Dd}nd}|!||"d|dqt||j'rt(|d}||j_|!||"ddqt)dq| || d}t*t*j+||,dd}t-t-j"| |dgd}fdd |.D}|||d}| || d}t*t*j+||,dd}t-t-j"| |dgd}||"dd }| || d!}t*t*j+||,dd}t-t-j"| |dgd}|||fS)"a2Outputs three `Summary` protocol buffers needed by hparams plugin. `Experiment` keeps the metadata of an experiment, such as the name of the hyperparameters and the name of the metrics. `SessionStartInfo` keeps key-value pairs of the hyperparameters `SessionEndInfo` describes status of the experiment e.g. STATUS_SUCCESS Args: hparam_dict: A dictionary that contains names of the hyperparameters and their values. metric_dict: A dictionary that contains names of the metrics and their values. hparam_domain_discrete: (Optional[Dict[str, List[Any]]]) A dictionary that contains names of the hyperparameters and all discrete values they can hold Returns: The `Summary` protobufs for Experiment, SessionStartInfo and SessionEndInfo rN) Experiment HParamInfo MetricInfo MetricNameStatusDataType) PLUGIN_NAMEPLUGIN_DATA_VERSIONEXPERIMENT_TAGSESSION_START_INFO_TAGSESSION_END_INFO_TAG)HParamsPluginDataSessionEndInfoSessionStartInfoz>parameter: 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|tVqdS)N)r#type.0d) hparam_dictkr)r* zhparams..zWparameter: hparam_domain_discrete[{}] should be a list of same type as hparam_dict[{}].cSsg|]}tj|dqS)) number_valuerValuerNr)r)r* szhparams..)valuesZDATA_TYPE_FLOAT64)namerMdomain_discretecSsg|]}tj|dqS)) string_valuerVrNr)r)r*rXsZDATA_TYPE_STRINGcSsg|]}tj|dqS)) bool_valuerVrNr)r)r*rXsZDATA_TYPE_BOOL)rZrMz=value should be one of int, float, str, bool, or torch.Tensor)Zsession_start_infoversion plugin_namecontent plugin_data)tagmetadatavaluecsg|]}|ddqS)rd)rZr))rOrR)rArBr)r*rXrT)Z hparam_infosZ metric_infos)Z experimentr^ZSTATUS_SUCCESS)status)Zsession_end_infor^)/torchZ#tensorboard.plugins.hparams.api_pb2r?r@rArBrCrDZ$tensorboard.plugins.hparams.metadatarErFrGrHrIZ+tensorboard.plugins.hparams.plugin_data_pb2rJrKrLr#dictloggerwarning TypeErroritemslistallformatintfloatrrUrZ ListValueappendrWstrr\boolr]ZTensorr ValueErrorr PluginDataSerializeToStringrkeys)rQZ metric_dictZhparam_domain_discreterjr?r@rCrDrErFrGrHrIrJrKrLvZhpsZssir[rasmdZmtsexpZseir))rArBrQrRr*rKs                     rFc Cst|}|jdks0Jd|jd|jdt|}|rt|gdd}|r\t|gdd}tjd d }t|d }ttj |||d gd Sttj ||dgd SdS)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.DT_FLOAT) float_valr&Z DT_DOUBLE)Z double_valr&Zscalarsr`rbrdr(rerf)rdZ simple_valueN) r squeezendimsizertrrryrrW) rZr( collectionsZ new_styleZdouble_precisionrZ tensor_protorcr}r)r)r*rs*    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_squaresZ bucket_limitZbucketrdZhistorf)rrrW) rZrrrrrZ bucket_limitsZ bucket_countshistr)r)r*r2s 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. rrf)r rastypertrrW)rZrYbinsmax_binsrr)r)r*rRsrc Cs|jdkrtd|d}tj||d\}}t|}|dur||kr||}||}|dkrztj|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 | ntdg|d| g}|| | d }|jdksl|jdkrttd ||} t||t||| ||d S)zDConvert values into a histogram proto using logic from histogram.cc.rzThe input has no element.)rNZconstant)Z pad_widthmodeZconstant_values)Zaxisr r:)Zsidez1The histogram is empty, please file a bug report.r)rrxreshaper$rlenpadremptyr&cumsumZgreaterZ searchsortedrsZ concatenatedotrrrtolist) rYrrcountsZlimitsZnum_binsZ subsamplingZsubsampling_remainderZ new_limits cum_countsstartendZsum_sqr)r)r*rgsP      0 rNCHWcCs`t|}t||}t|}|tj}||ddtj}t||d}t t j ||dgdS)aJOutputs a `Summary` protocol buffer with images. The summary has up to `max_images` summary values containing images. The images are built from `tensor` which must be 3-D with shape `[height, width, channels]` and where `channels` can be: * 1: `tensor` is interpreted as Grayscale. * 3: `tensor` is interpreted as RGB. * 4: `tensor` is interpreted as RGBA. The `name` in the outputted Summary.Value protobufs is generated based on the name, with a suffix depending on the max_outputs setting: * If `max_outputs` is 1, the summary value tag is '*name*/image'. * If `max_outputs` is greater than 1, the summary value tags are generated sequentially as '*name*/image/0', '*name*/image/1', etc. Args: tag: A name for the generated node. Will also serve as a series name in TensorBoard. tensor: A 3-D `uint8` or `float32` `Tensor` of shape `[height, width, channels]` where `channels` is 1, 3, or 4. 'tensor' can either have values in [0, 1] (float32) or [0, 255] (uint8). The image() function will scale the image values to [0, 255] by applying a scale factor of either 1 (uint8) or 255 (float32). Out-of-range values will be clipped. Returns: A scalar `Tensor` of type `string`. The serialized `Summary` protocol buffer. rr")rescalerdrrf) r rr+rr$float32clipr'rrrW)rdr(r dataformats scale_factorrr)r)r*rs   rCHWcCsdt|}t||}t|}|tjt|}t|ddtj|||d}t t j ||dgdS)z0Outputs a `Summary` protocol buffer with images.rr")rroislabelsrrf) r rrr$rr+rrr'rrW)rdZ tensor_imageZ tensor_boxesrrrrr)r)r*rs rc Csf|jd}t|}|D]J}t|||df||df||df||df|durRdn||dd}q|S)Nrr r-ZRed)r7r8)shaperanger>)Z disp_imageZboxesrZ num_boxesZlist_gtir)r)r*rs      rcCsddlm}|j\}}}t||}t||} ||} |durPt| ||d} z |jj} Wntyt|j } Yn0| | |f| } ddl } | } | j | dd| }| tj||||dS)zg?r r)rrrr) r$int32floorrfloat64rrmaximumr)rrrrZ_MINIMUM_COUNTZbucket_indicesZ float_labelsZhistogram_rangeZ tp_buckets_Z fp_bucketsrrrrrrr)r)r*r 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. 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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. r)MeshPluginDatarcSsg|]}|ddur|qS)rNr))rOr(r)r)r*rX?rTzmesh..cSsg|] \}}|qSr)r))rOr(rr)r)r*rXArTrf) Z(tensorboard.plugins.mesh.plugin_data_pb2r rrer ZVERTEXZFACEZCOLORZget_components_bitmaskrurr)rdZverticescolorsZfacesr rrr rerZ summariesZtensorsrr(rr)r)r*r!s2     r!)r,r,r-)NNN)NFF)N)N)r r)r rN)N)r NN)r)r)rN)rN)NN)NN)6rloggingrtypingrr%r$Zgoogle.protobufrZ$tensorboard.compat.proto.summary_pb2rrrZ#tensorboard.compat.proto.tensor_pb2rZ)tensorboard.compat.proto.tensor_shape_pb2rZ!tensorboard.plugins.custom_scalarr Z,tensorboard.plugins.pr_curve.plugin_data_pb2r Z(tensorboard.plugins.text.plugin_data_pb2r Z _convert_npr _utilsrr__all__ getLogger__name__rlr+r>rrrrrrrrrrrrrrrrr rr r!r)r)r)r*s\              * > *  6 %    + %   !;