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| # Copyright 2021 The TensorFlow Authors. All Rights Reserved. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| # ============================================================================== | |
| """Implementation for tensorboard.summary.Writer and related symbols. | |
| This provides a TensorBoard-native summary writing API that only depends | |
| on numpy and not any particular ML framework. | |
| """ | |
| import time | |
| import numpy as np | |
| from tensorboard.plugins.scalar import metadata as scalars_metadata | |
| from tensorboard.summary import _output | |
| class Writer: | |
| """Writes summary data for visualization in TensorBoard. | |
| This class is not thread-safe. | |
| TODO(#4581): This API should be considered EXPERIMENTAL and subject to | |
| backwards-incompatible changes without notice. | |
| """ | |
| def __init__(self, output): | |
| """Constructs a Writer. | |
| Args: | |
| output: `tensorboard.summary.Output` object, or a string which will be | |
| interpreted as shorthand for an `Output` of the appropriate type. The | |
| only currently supported type is `DirectoryOutput`, where the string | |
| value given here will be used as the directory path. | |
| """ | |
| if isinstance(output, _output.Output): | |
| self._output = output | |
| elif isinstance(output, str): | |
| self._output = _output.DirectoryOutput(output) | |
| else: | |
| raise TypeError("Unsupported output object %r" % output) | |
| self._closed = False | |
| def _check_not_closed(self): | |
| if self._closed: | |
| raise RuntimeError("Writer is already closed") | |
| def flush(self): | |
| """Flushes any buffered data.""" | |
| self._check_not_closed() | |
| self._output.flush() | |
| def close(self): | |
| """Closes the writer and prevents further use.""" | |
| self._check_not_closed() | |
| self._output.close() | |
| self._closed = True | |
| def add_scalar(self, tag, data, step, *, wall_time=None, description=None): | |
| """Adds a scalar summary. | |
| Args: | |
| tag: string tag used to uniquely identify this time series. | |
| data: numeric scalar value for this data point. Accepts any value that | |
| can be converted to a `np.float32` scalar. | |
| step: integer step value for this data point. Accepts any value that | |
| can be converted to a `np.int64` scalar. | |
| wall_time: optional `float` seconds since the Unix epoch, representing | |
| the real-world timestamp for this data point. Defaults to None in | |
| which case the current time will be used. | |
| description: optional string description for this entire time series. | |
| This should be constant for a given tag; only the first value | |
| encountered will be used. | |
| """ | |
| self._check_not_closed() | |
| validated_data = _validate_scalar_shape(np.float32(data), "data") | |
| validated_step = _validate_scalar_shape(np.int64(step), "step") | |
| wall_time = wall_time if wall_time is not None else time.time() | |
| self._output.emit_scalar( | |
| plugin_name=scalars_metadata.PLUGIN_NAME, | |
| tag=tag, | |
| data=validated_data, | |
| step=validated_step, | |
| wall_time=wall_time, | |
| description=description, | |
| ) | |
| def _validate_scalar_shape(ndarray, name): | |
| if ndarray.ndim != 0: | |
| raise ValueError( | |
| "Expected scalar value for %r but got %r" % (name, ndarray) | |
| ) | |
| return ndarray | |