1VhddZddlZddlmZddlmZddlmZejZ ddZ d dZ y) aHImage summaries and TensorFlow operations to create them. An image summary stores the width, height, and PNG-encoded data for zero or more images in a rank-1 string array: `[w, h, png0, png1, ...]`. 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_v2)encoderc ddlmcm}||}tj||}|j |5|j |j|d|j||j|j|g5|d|}|j|jj||jd} |j|} |j!|j#| dd |j#| d d gd } |j%| | gd} |j&j)d| ||cdddcdddS#1swYnxYwdddy#1swYyxYw)aCreate a legacy image summary op for use in a TensorFlow graph. Arguments: name: A unique name for the generated summary node. images: A `Tensor` representing pixel data with shape `[k, h, w, c]`, where `k` is the number of images, `h` and `w` are the height and width of the images, and `c` is the number of channels, which should be 1, 3, or 4. Any of the dimensions may be statically unknown (i.e., `None`). max_outputs: Optional `int` or rank-0 integer `Tensor`. At most this many images will be emitted at each step. When more than `max_outputs` many images are provided, the first `max_outputs` many images will be used and the rest silently discarded. 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 descriptionencode_each_image)dtypename)inputwidth)r height dimensions)axis image_summary)r tensor collectionssummary_metadata)tensorflow.compat.v1compatv1rcreate_summary_metadata name_scopecontrol_dependencies assert_rank assert_typeuint8assert_non_negativemap_fnimage encode_pngstringshapestack as_stringconcatsummarytensor_summary) r images max_outputsrr rtfrlimited_imagesencoded_images image_shaperrs Q/home/dcms/DCMS/lib/python3.12/site-packages/tensorboard/plugins/image/summary.pyopr4$swB&% 77!{ t  b55 NN61 % NN6288 ,  " "; /   - HH   ))$ #  hhVh, XX [^' : [^( ;   J7a@zz(( #- ) /       s%AE'B;E? E'E E''E0cddlmcm}tj|j tj }|jdk7rtd|jd|d|}|Dcgc]}tj|}}|jd|jd} } t| t| g|z} |j| |j} ||}tj || } |j"j%| j'}|j)}|j*j-d |z|| |Scc}w) a\Create a legacy image summary protobuf. This behaves as if you were to create an `op` with the same arguments (wrapped with constant tensors where appropriate) and then execute that summary op in a TensorFlow session. Arguments: name: A unique name for the generated summary, including any desired name scopes. images: An `np.array` representing pixel data with shape `[k, h, w, c]`, where `k` is the number of images, `w` and `h` are the width and height of the images, and `c` is the number of channels, which should be 1, 3, or 4. max_outputs: Optional `int`. At most this many images will be emitted. If more than this many images are provided, the first `max_outputs` many images will be used and the rest silently discarded. 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 zShape z must have rank 4rr)r rz%s/image_summary)tagrr)rrrnparrayastyper!ndim ValueErrorr'rr%strmake_tensor_protor&rrSummaryMetadata FromStringSerializeToStringSummaryvalueadd)r r-r.rr r/r0r$r1rrcontentrrtf_summary_metadatar+s r3pbrFks=6&% XXf  $ $RXX .F {{a FGGL[)N=KLEg((/LNL||A QFU5z3v;'.8G  ! !' ! ;F 77!{,,77**,jjlG MM  %$ N)Ms-E)NNN)rGNN) __doc__numpyr7tensorboard.plugins.imagerrtensorboard.utilrr$r4rFr3rNs?.0$   D N6rM