o 2hZ@sTdZddlZddlmZddlmZddlm Z ddl m Z d ddZ d d d Z dS) zScalar summaries and TensorFlow operations to create them, V2 versions. A scalar summary stores a single floating-point value, as a rank-0 tensor. N)tf2) summary_pb2)metadata) tensor_utilcCstjd|d}ttjjddptjj}||d||gd\}}tj|tjj |t |tj ||dWdS1s>wYdS)aWrite a scalar summary. See also `tf.summary.image`, `tf.summary.histogram`, `tf.summary.SummaryWriter`. Writes simple numeric values for later analysis in TensorBoard. Writes go to the current default summary writer. Each summary point is associated with an integral `step` value. This enables the incremental logging of time series data. A common usage of this API is to log loss during training to produce a loss curve. For example: ```python test_summary_writer = tf.summary.create_file_writer('test/logdir') with test_summary_writer.as_default(): tf.summary.scalar('loss', 0.345, step=1) tf.summary.scalar('loss', 0.234, step=2) tf.summary.scalar('loss', 0.123, step=3) ``` Multiple independent time series may be logged by giving each series a unique `name` value. See [Get started with TensorBoard](https://www.tensorflow.org/tensorboard/get_started) for more examples of effective usage of `tf.summary.scalar`. In general, this API expects that data points are logged with a monotonically increasing step value. Duplicate points for a single step or points logged out of order by step are not guaranteed to display as desired in TensorBoard. Arguments: name: A name for this summary. The summary tag used for TensorBoard will be this name prefixed by any active name scopes. data: A real numeric scalar value, convertible to a `float32` Tensor. step: Explicit `int64`-castable monotonic step value for this summary. If omitted, this defaults to `tf.summary.experimental.get_step()`, which must not be None. description: Optional long-form description for this summary, as a constant `str`. Markdown is supported. Defaults to empty. Returns: True on success, or false if no summary was written because no default summary writer was available. Raises: ValueError: if a default writer exists, but no step was provided and `tf.summary.experimental.get_step()` is None. N display_name description summary_scopescalar_summary)values)tagtensorstepr) rcreate_summary_metadatagetattrtfsummary experimentalr debugging assert_scalarwritecastfloat32)namedatarrsummary_metadatar r _r`/var/www/html/chatgem/venv/lib/python3.10/site-packages/tensorboard/plugins/scalar/summary_v2.pyscalars1  $rcCs|t|}|jdkrtd|j|jjdvrtd|jjt| tj }t j d|d}t }|jj|||d|S)aCreate a scalar summary_pb2.Summary protobuf. Arguments: tag: String tag for the summary. data: A 0-dimensional `np.array` or a compatible python number type. description: Optional long-form description for this summary, as a `str`. Markdown is supported. Defaults to empty. Raises: ValueError: If the type or shape of the data is unsupported. Returns: A `summary_pb2.Summary` protobuf object. rz0Expected scalar shape for tensor, got shape: %s.)biufz!Cast %s to float is not supportedNr)r rr )nparrayshape ValueErrordtypekindrrmake_tensor_protoastyperrrrSummaryvalueadd)r rrarr tensor_protorrrrr scalar_pbas   r1)NN)N)__doc__numpyr$tensorboard.compatrrtensorboard.compat.protortensorboard.plugins.scalarrtensorboard.utilrrr1rrrrs     C