tf.compat.v1.summary.FileWriter

Writes Summary protocol buffers to event files.

tf.compat.v1.summary.FileWriter(
    logdir, graph=None, max_queue=10, flush_secs=120, graph_def=None,
    filename_suffix=None, session=None
)

The FileWriter class provides a mechanism to create an event file in a given directory and add summaries and events to it. The class updates the file contents asynchronously. This allows a training program to call methods to add data to the file directly from the training loop, without slowing down training.

When constructed with a tf.compat.v1.Session parameter, a FileWriter instead forms a compatibility layer over new graph-based summaries (tf.contrib.summary) to facilitate the use of new summary writing with pre-existing code that expects a FileWriter instance.

Args:

logdir: A string. Directory where event file will be written.
graph: A Graph object, such as sess.graph.
max_queue: Integer. Size of the queue for pending events and summaries.
flush_secs: Number. How often, in seconds, to flush the pending events and summaries to disk.
graph_def: DEPRECATED: Use the graph argument instead.
filename_suffix: A string. Every event file's name is suffixed with suffix.
session: A tf.compat.v1.Session object. See details above.

Raises:

RuntimeError: If called with eager execution enabled.

Methods

`enter`

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__enter__()

Make usable with "with" statement.

`exit`

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__exit__(
    unused_type, unused_value, unused_traceback
)

Make usable with "with" statement.

`add_event`

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add_event(
    event
)

Adds an event to the event file.

Args:

event: An Event protocol buffer.

`add_graph`

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add_graph(
    graph, global_step=None, graph_def=None
)

Adds a Graph to the event file.

The graph described by the protocol buffer will be displayed by TensorBoard. Most users pass a graph in the constructor instead.

Args:

graph: A Graph object, such as sess.graph.
global_step: Number. Optional global step counter to record with the graph.
graph_def: DEPRECATED. Use the graph parameter instead.

Raises:

ValueError: If both graph and graph_def are passed to the method.

`add_meta_graph`

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add_meta_graph(
    meta_graph_def, global_step=None
)

Adds a MetaGraphDef to the event file.

The MetaGraphDef allows running the given graph via saver.import_meta_graph().

Args:

meta_graph_def: A MetaGraphDef object, often as returned by saver.export_meta_graph().
global_step: Number. Optional global step counter to record with the graph.

Raises:

TypeError: If both meta_graph_def is not an instance of MetaGraphDef.

`add_run_metadata`

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add_run_metadata(
    run_metadata, tag, global_step=None
)

Adds a metadata information for a single session.run() call.

Args:

run_metadata: A RunMetadata protobuf object.
tag: The tag name for this metadata.
global_step: Number. Optional global step counter to record with the StepStats.

Raises:

ValueError: If the provided tag was already used for this type of event.

`add_session_log`

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add_session_log(
    session_log, global_step=None
)

Adds a SessionLog protocol buffer to the event file.

This method wraps the provided session in an Event protocol buffer and adds it to the event file.

Args:

session_log: A SessionLog protocol buffer.
global_step: Number. Optional global step value to record with the summary.

`add_summary`

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add_summary(
    summary, global_step=None
)

Adds a Summary protocol buffer to the event file.

This method wraps the provided summary in an Event protocol buffer and adds it to the event file.

You can pass the result of evaluating any summary op, using tf.Session.run or tf.Tensor.eval, to this function. Alternatively, you can pass a tf.compat.v1.Summary protocol buffer that you populate with your own data. The latter is commonly done to report evaluation results in event files.

Args:

summary: A Summary protocol buffer, optionally serialized as a string.
global_step: Number. Optional global step value to record with the summary.