a Sic8$@sRdZddlZddlmZddlmZejZejZd ddZd ddZ d d d Z dS)aHistogram summaries and TensorFlow operations to create them. A histogram summary stores a list of buckets. Each bucket is encoded as a triple `[left_edge, right_edge, count]`. Thus, a full histogram is encoded as a tensor of dimension `[k, 3]`. In general, the value of `k` (the number of buckets) will be a constant, like 30. There are two edge cases: if there is no data, then there are no buckets (the shape is `[0, 3]`); and if there is data but all points have the same value, then there is one bucket whose left and right endpoints are the same (the shape is `[1, 3]`). NOTE: This module is in beta, and its API is subject to change, but the data that it stores to disk will be supported forever. N)metadata) summary_v2c sddlmmdur tjjdgdj gzj dgd j  jdd}fdd }fd d }|||WdWdS1s0YWdn1s0YdS) aCreate a TensorFlow op to group data into histogram buckets. Arguments: data: A `Tensor` of any shape. Must be castable to `float64`. bucket_count: Optional positive `int` or scalar `int32` `Tensor`. Returns: A `Tensor` of shape `[k, 3]` and type `float64`. The `i`th row is a triple `[left_edge, right_edge, count]` for a single bucket. The value of `k` is either `bucket_count` or `1` or `0`. rNbuckets)values)shapeinputcsjgdjdS)Nr)rdtype)constantfloat64)tfra/var/www/html/django/DPS/env/lib/python3.9/site-packages/tensorboard/plugins/histogram/summary.py when_emptyDsz_buckets..when_emptycs`jdjdd}fdd}fdd}|||S)N) input_tensorrc sj}}j||jd}|d}j|jd}jj|ddjd}d}|dd}|dd}j |||gdS)Nr )depthr r)raxisra) castrfloorint32minimumone_hot reduce_sumlinspace transposestack) bucket_widthoffsetsbucket_indicesclamped_indicesone_hots bucket_countsedges left_edges right_edges) bucket_countdatamax_min_range_rrrwhen_nonsingularMs&   z9_buckets..when_nonempty..when_nonsingularcsZ}|dg}|dg}jdjg}j|||gdS)N?rr)r"rsizerr!)centerZ bucket_startsZ bucket_endsr()r-r/rrr when_singularesz6_buckets..when_nonempty..when_singular) reduce_min reduce_maxequalcond) is_singularr1r5r,r-r)r.r/r0r when_nonemptyGs    z_buckets..when_nonempty)tensorflow.compat.v1compatv1rDEFAULT_BUCKET_COUNT name_scopecontrol_dependencies assert_scalar assert_typerreshaperrr8r3r9)r-r,is_emptyrr<rr;r_buckets+s  +rGc Cszddlmm}|dur|}tj||d}||0t||d}|jjd|||dWdS1sl0YdS)aCreate a legacy histogram summary op. Arguments: name: A unique name for the generated summary node. data: A `Tensor` of any shape. Must be castable to `float64`. bucket_count: Optional positive `int`. The output will have this many buckets, except in two edge cases. If there is no data, then there are no buckets. If there is data but all points have the same value, then there is one bucket whose left and right endpoints are the same. display_name: Optional name for this summary in TensorBoard, as a constant `str`. Defaults to `name`. description: Optional long-form description for this summary, as a constant `str`. Markdown is supported. Defaults to empty. collections: Optional list of graph collections keys. The new summary op is added to these collections. Defaults to `[Graph Keys.SUMMARIES]`. Returns: A TensorFlow summary op. rN display_name description)r,histogram_summary)nametensor collectionssummary_metadata) r=r>r?rcreate_summary_metadatarArGsummarytensor_summary) rLr-r,rIrJrNrrOrMrrropus  rScCsddlmm}|dur tj}t|t }|j dkrRtg d}n t |}t |}||} | dkr|} t| d| dt |j gg}n| |} ||} t| | t} t| |d}t|gtd|k}|j|j |fksJ|j|j |fftj|dd}t|||d}|dd}|dd}t|||g}|j||jd}|dur||}tj||d }|j|}|}|jjd |||d |S) aaCreate a legacy histogram summary protobuf. Arguments: name: A unique name for the generated summary, including any desired name scopes. data: A `np.array` or array-like form of any shape. Must have type castable to `float`. bucket_count: Optional positive `int`. The output will have this many buckets, except in two edge cases. If there is no data, then there are no buckets. If there is data but all points have the same value, then there is one bucket whose left and right endpoints are the same. display_name: Optional name for this summary in TensorBoard, as a `str`. Defaults to `name`. description: Optional long-form description for this summary, as a `str`. Markdown is supported. Defaults to empty. Returns: A `tf.Summary` protobuf object. rNr r2r)rrrrHz%s/histogram_summary)tagrrM) r=r>r?rr@nparrayflattenastypefloatr3rEminmaxrintrr!arangersumr make_tensor_protorrrPSummaryMetadata FromStringSerializeToStringSummaryvalueadd)rLr-r,rIrJrrr/r.r0r4r#r$r%r&r'r(r)r*r+rMrOtf_summary_metadatarQrrrpbs\   "   rg)N)NNNN)NNN) __doc__numpyrUtensorboard.plugins.histogramrr histogram histogram_pbrGrSrgrrrrs   M /