o wic@szddlZddlZddlZddlZddlmZddlm Z ddl m Z ddl m Z ddlmZmZmZddlmZdd lmZdd lmZmZmZdd lmZeeZed Z d dZ!d?ddZ"d@ddZ#dAddZ$ddZ%dBddZ&dBddZ'dCdd Z(dDd!d"Z)dBd#d$Z*dEd%d&Z+dFd)d*Z,d+d,Z-dGd.d/Z.d0d1Z/d2d3Z0dHd5d6Z1dHd7d8Z2d@d9d:Z3d;d<Z4dBd=d>Z5dS)IN) layout_pb2)MeshPluginData)PrCurvePluginData)TextPluginData)HistogramProtoSummarySummaryMetadata) TensorProto)TensorShapeProto)_prepare_videoconvert_to_HWCconvert_to_NTCHW)make_npz [^-/\w\.]cCsF|dur!td|}|d}||kr!td|d|d|}|S)N_/z Summary name z is illegal; using z instead.)_INVALID_TAG_CHARACTERSsublstriploggerinfo)namenew_namerQ/home/ubuntu/sommelier/.venv/lib/python3.10/site-packages/tensorboardX/summary.py _clean_tags  rblackc Csddlm} m} | } | |} ||||f\} }}}| j| |f| |f||f||f| |fg||d|ru|}| |\}}}}||||}}td|}| j | ||d|f| ||fg|d| j | ||||f||| d|S)Nr) ImageDraw ImageFont)widthfillg?r)r!)r!font) PILrr load_defaultDrawlinegetbboxnpceil rectangletext)imagexminyminxmaxymax display_strcolor color_text thicknessrrr"drawleftrighttopbottom text_bottomltrb text_width text_heightmarginrrr_draw_single_box*s2   rBcsHddlm}m}m}mmm}ddlm}m }m }d} d} d} d} d} g}|}| D]\}}|dur6q-t |t rN||j|_||||dd q-t |trf||j|_||||d d q-t |ttfrt|d}||j|_||||d d q-t|rt|d t ||j|_||||dd q-||||d d q-||| d}ttj| |dd}ttj| |dgd}fdd|D}|||d}||| d}ttj| |dd}ttj| |dgd}||dd}||| d}ttj| |dd}ttj| |dgd}|||fS)Nr)DataType Experiment HParamInfo MetricInfo MetricNameStatus)HParamsPluginDataSessionEndInfoSessionStartInfohparamsz_hparams_/experimentz_hparams_/session_start_infoz_hparams_/session_end_infoDATA_TYPE_STRING)rtypeDATA_TYPE_BOOLDATA_TYPE_FLOAT64__name__DATA_TYPE_UNSET)session_start_infoversion plugin_namecontent plugin_data)tagmetadatavaluecsg|] }|ddqS)rZ)rr).0krFrGrr szhparams..) hparam_infos metric_infos) experimentrTSTATUS_SUCCESS)status)session_end_inforT)tensorboardX.proto.api_pb2rCrDrErFrGrH%tensorboardX.proto.plugin_hparams_pb2rIrJrKitems isinstancestrrL string_valueappendValuebool bool_valueintfloatr number_valuecallablegetattrr PluginDataSerializeToStringr) hparam_dict metric_dictrCrDrErHrIrJrK PLUGIN_NAMEPLUGIN_DATA_VERSIONEXPERIMENT_TAGSESSION_START_INFO_TAGSESSION_END_INFO_TAGhpsssir`vrWsmdmtsexpseirrarrLBsb               rLcCs|t|}t|}|jdksJdt|}|dkr,|dkr,ttj||dgdSt||d}ttj|||dgdS)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. display_name: The title of the plot. If empty string is passed, `name` will be used. summary_description: The comprehensive text that will showed by clicking the information icon on TensorBoard. Returns: A scalar `Tensor` of type `string`. Which contains a `Summary` protobuf. Raises: ValueError: If tensor has the wrong shape or type. rzscalar should be 0Dr)rZ simple_valuer\) display_namesummary_description)rZrr[)rrsqueezendimrtrrpr )rscalarrrr[rrrrs  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_limitbucketrZhistor\)rrrp) rrrrrr bucket_limits bucket_countshistrrr histogram_rawsrcCs8t|}t|}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\)rrmake_histogramastypertrrp)rvaluesbinsmax_binsrrrr histogramsrc 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_valuesaxisrr7)sidez1The histogram is empty, please file a bug report.r)size ValueErrorreshaper(rlenpadremptydtypecumsumgreater searchsortedrs concatenatedotrrrtolist) rrrcountslimitsnum_bins subsamplingsubsampling_remainder new_limits cum_countsstartendsum_sqrrrrsF     0 rCHWcCsXt|}t|}t||}|jtjkr|dtj}t||d}ttj ||dgdS)aOutputs 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. 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). Returns: A scalar `Tensor` of type `string`. The serialized `Summary` protocol buffer. o@)rescalerZr,r\) rrr rr(uint8r make_imagerrp)rZtensorr dataformatsr,rrrr, s   r,cCs\t|}t||}t|}|jtjkr|dtj}t||||d}ttj||dgdS)z0Outputs a `Summary` protocol buffer with images.r)rroislabelsrr\) rr rr(rrrrrp)rZ tensor_image tensor_boxesrrrr,rrr image_boxes+s  rc Csf|jd}t|}|D]%}t|||df||df||df||df|dur)dn||dd}q |S)NrrrRed)r1r2)shaperangerB) disp_imageboxesr num_boxeslist_gtirrr draw_boxes:s     rcCsddl}ddlm}ddlm}|j\}}} t||} t||} ||} |dur2t| ||d} ||j|dkrF| | | f|j j } n | | | f|j } ddl } | }| j|dd|}|tj||| |d S) z7Convert an numpy representation image to Image protobufrN)parse)Image)rz9.1.0PNG)formatheightr colorspaceencoded_image_string)r#packaging.versionrrrrs fromarrayr __version__resize ResamplingLANCZOSioBytesIOsavegetvaluecloser)rrrrr#rrrr channel scaled_height scaled_widthr,routput image_stringrrrrIs,      rNTCHWcCs`t|}t|}t||d}t|}|jtjkr |dtj}t||}t t j ||dgdS)N) input_formatrrr\) rrrr rr(rr make_videorrp)rZrfpsrvideorrrrds   rc Cs<ddl}ddlm}ddlm}ddlm}z||d}Wn|y-tdYdSwzddlm }Wn,t ybzddl m }Wnt y_}ztd|WYd}~YdSd}~wwYnw||d } ||d krz| |d krztd |j \} } } } | d kr||d ks| |dkrt j|ddd}|t||d}|jdddd}|j}||dkrtd|j|ddn||dkr|j|dddn|j|ddt|d }|}Wdn1swYzt|WntytdYnwWdn 1swYtj| | | |dS)Nr)PackageNotFoundErrorrT)Versionmoviepyzmoviepy is not installed.)ImageSequenceClipzgCan't create video. moviepy is installed, but can't import moviepy.video.io.ImageSequenceClip due to %rimageio2z2.29zYou are using moviepy >= 2.0.0 and imageio < 2.29.0. 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