tf.summary - LostTech.TensorFlow Documentation

object all_v2_summary_ops()

Returns all V2-style summary ops defined in the current default graph.

This includes ops from TF 2.0 tf.summary and TF 1.x tf.contrib.summary (except for tf.contrib.summary.graph and tf.contrib.summary.import_event), but does *not* include TF 1.x tf.summary ops.

Returns

object: List of summary ops, or None if called under eager execution.

object all_v2_summary_ops_dyn()

Returns all V2-style summary ops defined in the current default graph.

This includes ops from TF 2.0 tf.summary and TF 1.x tf.contrib.summary (except for tf.contrib.summary.graph and tf.contrib.summary.import_event), but does *not* include TF 1.x tf.summary ops.

Returns

object: List of summary ops, or None if called under eager execution.

Tensor audio(string name, IGraphNodeBase tensor, int sample_rate, int max_outputs, object collections, string family)

Outputs a `Summary` protocol buffer with audio.

The summary has up to `max_outputs` summary values containing audio. The audio is built from `tensor` which must be 3-D with shape `[batch_size, frames, channels]` or 2-D with shape `[batch_size, frames]`. The values are assumed to be in the range of `[-1.0, 1.0]` with a sample rate of `sample_rate`.

The `tag` in the outputted Summary.Value protobufs is generated based on the name, with a suffix depending on the max_outputs setting:

* If `max_outputs` is 1, the summary value tag is '*name*/audio'. * If `max_outputs` is greater than 1, the summary value tags are generated sequentially as '*name*/audio/0', '*name*/audio/1', etc

Parameters

string name: A name for the generated node. Will also serve as a series name in TensorBoard.
IGraphNodeBase tensor: A 3-D `float32` `Tensor` of shape `[batch_size, frames, channels]` or a 2-D `float32` `Tensor` of shape `[batch_size, frames]`.
int sample_rate: A Scalar `float32` `Tensor` indicating the sample rate of the signal in hertz.
int max_outputs: Max number of batch elements to generate audio for.
object collections: Optional list of ops.GraphKeys. The collections to add the summary to. Defaults to [_ops.GraphKeys.SUMMARIES]
string family: Optional; if provided, used as the prefix of the summary tag name, which controls the tab name used for display on Tensorboard.

Returns

Tensor: A scalar `Tensor` of type `string`. The serialized `Summary` protocol buffer.

Tensor audio(string name, IGraphNodeBase tensor, double sample_rate, int max_outputs, object collections, string family)

Outputs a `Summary` protocol buffer with audio.

The summary has up to `max_outputs` summary values containing audio. The audio is built from `tensor` which must be 3-D with shape `[batch_size, frames, channels]` or 2-D with shape `[batch_size, frames]`. The values are assumed to be in the range of `[-1.0, 1.0]` with a sample rate of `sample_rate`.

The `tag` in the outputted Summary.Value protobufs is generated based on the name, with a suffix depending on the max_outputs setting:

* If `max_outputs` is 1, the summary value tag is '*name*/audio'. * If `max_outputs` is greater than 1, the summary value tags are generated sequentially as '*name*/audio/0', '*name*/audio/1', etc

Parameters

string name: A name for the generated node. Will also serve as a series name in TensorBoard.
IGraphNodeBase tensor: A 3-D `float32` `Tensor` of shape `[batch_size, frames, channels]` or a 2-D `float32` `Tensor` of shape `[batch_size, frames]`.
double sample_rate: A Scalar `float32` `Tensor` indicating the sample rate of the signal in hertz.
int max_outputs: Max number of batch elements to generate audio for.
object collections: Optional list of ops.GraphKeys. The collections to add the summary to. Defaults to [_ops.GraphKeys.SUMMARIES]
string family: Optional; if provided, used as the prefix of the summary tag name, which controls the tab name used for display on Tensorboard.

Returns

Tensor: A scalar `Tensor` of type `string`. The serialized `Summary` protocol buffer.

object audio_dyn(object name, object tensor, object sample_rate, ImplicitContainer<T> max_outputs, object collections, object family)

Outputs a `Summary` protocol buffer with audio.

The summary has up to `max_outputs` summary values containing audio. The audio is built from `tensor` which must be 3-D with shape `[batch_size, frames, channels]` or 2-D with shape `[batch_size, frames]`. The values are assumed to be in the range of `[-1.0, 1.0]` with a sample rate of `sample_rate`.

The `tag` in the outputted Summary.Value protobufs is generated based on the name, with a suffix depending on the max_outputs setting:

* If `max_outputs` is 1, the summary value tag is '*name*/audio'. * If `max_outputs` is greater than 1, the summary value tags are generated sequentially as '*name*/audio/0', '*name*/audio/1', etc

Parameters

object name: A name for the generated node. Will also serve as a series name in TensorBoard.
object tensor: A 3-D `float32` `Tensor` of shape `[batch_size, frames, channels]` or a 2-D `float32` `Tensor` of shape `[batch_size, frames]`.
object sample_rate: A Scalar `float32` `Tensor` indicating the sample rate of the signal in hertz.
ImplicitContainer<T> max_outputs: Max number of batch elements to generate audio for.
object collections: Optional list of ops.GraphKeys. The collections to add the summary to. Defaults to [_ops.GraphKeys.SUMMARIES]
object family: Optional; if provided, used as the prefix of the summary tag name, which controls the tab name used for display on Tensorboard.

Returns

object: A scalar `Tensor` of type `string`. The serialized `Summary` protocol buffer.

ResourceSummaryWriter create_file_writer(IGraphNodeBase logdir, Nullable<int> max_queue, Nullable<int> flush_millis, string filename_suffix, string name)

NoopSummaryWriter create_noop_writer()

object create_noop_writer_dyn()

object flush(SummaryWriter writer, string name)

object flush(IGraphNodeBase writer, string name)

object get_summary_description(object node_def)

Given a TensorSummary node_def, retrieve its SummaryDescription.

When a Summary op is instantiated, a SummaryDescription of associated metadata is stored in its NodeDef. This method retrieves the description.

Parameters

object node_def: the node_def_pb2.NodeDef of a TensorSummary op

Returns

object: a summary_pb2.SummaryDescription

object get_summary_description_dyn(object node_def)

Given a TensorSummary node_def, retrieve its SummaryDescription.

When a Summary op is instantiated, a SummaryDescription of associated metadata is stored in its NodeDef. This method retrieves the description.

Parameters

object node_def: the node_def_pb2.NodeDef of a TensorSummary op

Returns

object: a summary_pb2.SummaryDescription

Tensor histogram(string name, IEnumerable<IGraphNodeBase> values, object collections, string family)

Outputs a `Summary` protocol buffer with a histogram.

Adding a histogram summary makes it possible to visualize your data's distribution in TensorBoard. You can see a detailed explanation of the TensorBoard histogram dashboard [here](https://www.tensorflow.org/get_started/tensorboard_histograms).

The generated [`Summary`](https://www.tensorflow.org/code/tensorflow/core/framework/summary.proto) has one summary value containing a histogram for `values`.

This op reports an `InvalidArgument` error if any value is not finite.

Parameters

string name: A name for the generated node. Will also serve as a series name in TensorBoard.
IEnumerable<IGraphNodeBase> values: A real numeric `Tensor`. Any shape. Values to use to build the histogram.
object collections: Optional list of graph collections keys. The new summary op is added to these collections. Defaults to `[GraphKeys.SUMMARIES]`.
string family: Optional; if provided, used as the prefix of the summary tag name, which controls the tab name used for display on Tensorboard.

Returns

Tensor: A scalar `Tensor` of type `string`. The serialized `Summary` protocol buffer.

Tensor histogram(string name, object values, object collections, string family)

Outputs a `Summary` protocol buffer with a histogram.

Adding a histogram summary makes it possible to visualize your data's distribution in TensorBoard. You can see a detailed explanation of the TensorBoard histogram dashboard [here](https://www.tensorflow.org/get_started/tensorboard_histograms).

The generated [`Summary`](https://www.tensorflow.org/code/tensorflow/core/framework/summary.proto) has one summary value containing a histogram for `values`.

This op reports an `InvalidArgument` error if any value is not finite.

Parameters

string name: A name for the generated node. Will also serve as a series name in TensorBoard.
object values: A real numeric `Tensor`. Any shape. Values to use to build the histogram.
object collections: Optional list of graph collections keys. The new summary op is added to these collections. Defaults to `[GraphKeys.SUMMARIES]`.
string family: Optional; if provided, used as the prefix of the summary tag name, which controls the tab name used for display on Tensorboard.

Returns

Tensor: A scalar `Tensor` of type `string`. The serialized `Summary` protocol buffer.

Tensor image(int name, IDictionary<object, object> tensor, int max_outputs, IEnumerable<object> collections, string family)

Outputs a `Summary` protocol buffer with images.

The summary has up to `max_outputs` summary values containing images. The images are built from `tensor` which must be 4-D with shape `[batch_size, height, width, channels]` and where `channels` can be:

* 1: `tensor` is interpreted as Grayscale. * 3: `tensor` is interpreted as RGB. * 4: `tensor` is interpreted as RGBA.

The images have the same number of channels as the input tensor. For float input, the values are normalized one image at a time to fit in the range `[0, 255]`. `uint8` values are unchanged. The op uses two different normalization algorithms:

* If the input values are all positive, they are rescaled so the largest one is 255.

* If any input value is negative, the values are shifted so input value 0.0 is at 127. They are then rescaled so that either the smallest value is 0, or the largest one is 255.

The `tag` in the outputted Summary.Value protobufs is generated based on the name, with a suffix depending on the max_outputs setting:

* If `max_outputs` is 1, the summary value tag is '*name*/image'. * If `max_outputs` is greater than 1, the summary value tags are generated sequentially as '*name*/image/0', '*name*/image/1', etc.

Parameters

int name: A name for the generated node. Will also serve as a series name in TensorBoard.
IDictionary<object, object> tensor: A 4-D `uint8` or `float32` `Tensor` of shape `[batch_size, height, width, channels]` where `channels` is 1, 3, or 4.
int max_outputs: Max number of batch elements to generate images for.
IEnumerable<object> collections: Optional list of ops.GraphKeys. The collections to add the summary to. Defaults to [_ops.GraphKeys.SUMMARIES]
string family: Optional; if provided, used as the prefix of the summary tag name, which controls the tab name used for display on Tensorboard.

Returns

Tensor: A scalar `Tensor` of type `string`. The serialized `Summary` protocol buffer.

Tensor image(string name, IEnumerable<SparseTensor> tensor, int max_outputs, IEnumerable<object> collections, string family)

Outputs a `Summary` protocol buffer with images.

The summary has up to `max_outputs` summary values containing images. The images are built from `tensor` which must be 4-D with shape `[batch_size, height, width, channels]` and where `channels` can be:

* 1: `tensor` is interpreted as Grayscale. * 3: `tensor` is interpreted as RGB. * 4: `tensor` is interpreted as RGBA.

The images have the same number of channels as the input tensor. For float input, the values are normalized one image at a time to fit in the range `[0, 255]`. `uint8` values are unchanged. The op uses two different normalization algorithms:

* If the input values are all positive, they are rescaled so the largest one is 255.

* If any input value is negative, the values are shifted so input value 0.0 is at 127. They are then rescaled so that either the smallest value is 0, or the largest one is 255.

The `tag` in the outputted Summary.Value protobufs is generated based on the name, with a suffix depending on the max_outputs setting:

* If `max_outputs` is 1, the summary value tag is '*name*/image'. * If `max_outputs` is greater than 1, the summary value tags are generated sequentially as '*name*/image/0', '*name*/image/1', etc.

Parameters

string name: A name for the generated node. Will also serve as a series name in TensorBoard.
IEnumerable<SparseTensor> tensor: A 4-D `uint8` or `float32` `Tensor` of shape `[batch_size, height, width, channels]` where `channels` is 1, 3, or 4.
int max_outputs: Max number of batch elements to generate images for.
IEnumerable<object> collections: Optional list of ops.GraphKeys. The collections to add the summary to. Defaults to [_ops.GraphKeys.SUMMARIES]
string family: Optional; if provided, used as the prefix of the summary tag name, which controls the tab name used for display on Tensorboard.

Returns

Tensor: A scalar `Tensor` of type `string`. The serialized `Summary` protocol buffer.

Tensor image(string name, IDictionary<object, object> tensor, int max_outputs, IEnumerable<object> collections, string family)

Outputs a `Summary` protocol buffer with images.

The summary has up to `max_outputs` summary values containing images. The images are built from `tensor` which must be 4-D with shape `[batch_size, height, width, channels]` and where `channels` can be:

* 1: `tensor` is interpreted as Grayscale. * 3: `tensor` is interpreted as RGB. * 4: `tensor` is interpreted as RGBA.

The images have the same number of channels as the input tensor. For float input, the values are normalized one image at a time to fit in the range `[0, 255]`. `uint8` values are unchanged. The op uses two different normalization algorithms:

* If the input values are all positive, they are rescaled so the largest one is 255.

* If any input value is negative, the values are shifted so input value 0.0 is at 127. They are then rescaled so that either the smallest value is 0, or the largest one is 255.

The `tag` in the outputted Summary.Value protobufs is generated based on the name, with a suffix depending on the max_outputs setting:

* If `max_outputs` is 1, the summary value tag is '*name*/image'. * If `max_outputs` is greater than 1, the summary value tags are generated sequentially as '*name*/image/0', '*name*/image/1', etc.

Parameters

string name: A name for the generated node. Will also serve as a series name in TensorBoard.
IDictionary<object, object> tensor: A 4-D `uint8` or `float32` `Tensor` of shape `[batch_size, height, width, channels]` where `channels` is 1, 3, or 4.
int max_outputs: Max number of batch elements to generate images for.
IEnumerable<object> collections: Optional list of ops.GraphKeys. The collections to add the summary to. Defaults to [_ops.GraphKeys.SUMMARIES]
string family: Optional; if provided, used as the prefix of the summary tag name, which controls the tab name used for display on Tensorboard.

Returns

Tensor: A scalar `Tensor` of type `string`. The serialized `Summary` protocol buffer.

Tensor image(int name, IGraphNodeBase tensor, int max_outputs, IEnumerable<object> collections, string family)

Outputs a `Summary` protocol buffer with images.

The summary has up to `max_outputs` summary values containing images. The images are built from `tensor` which must be 4-D with shape `[batch_size, height, width, channels]` and where `channels` can be:

* 1: `tensor` is interpreted as Grayscale. * 3: `tensor` is interpreted as RGB. * 4: `tensor` is interpreted as RGBA.

The images have the same number of channels as the input tensor. For float input, the values are normalized one image at a time to fit in the range `[0, 255]`. `uint8` values are unchanged. The op uses two different normalization algorithms:

* If the input values are all positive, they are rescaled so the largest one is 255.

* If any input value is negative, the values are shifted so input value 0.0 is at 127. They are then rescaled so that either the smallest value is 0, or the largest one is 255.

The `tag` in the outputted Summary.Value protobufs is generated based on the name, with a suffix depending on the max_outputs setting:

* If `max_outputs` is 1, the summary value tag is '*name*/image'. * If `max_outputs` is greater than 1, the summary value tags are generated sequentially as '*name*/image/0', '*name*/image/1', etc.

Parameters

int name: A name for the generated node. Will also serve as a series name in TensorBoard.
IGraphNodeBase tensor: A 4-D `uint8` or `float32` `Tensor` of shape `[batch_size, height, width, channels]` where `channels` is 1, 3, or 4.
int max_outputs: Max number of batch elements to generate images for.
IEnumerable<object> collections: Optional list of ops.GraphKeys. The collections to add the summary to. Defaults to [_ops.GraphKeys.SUMMARIES]
string family: Optional; if provided, used as the prefix of the summary tag name, which controls the tab name used for display on Tensorboard.

Returns

Tensor: A scalar `Tensor` of type `string`. The serialized `Summary` protocol buffer.

Tensor image(int name, IEnumerable<SparseTensor> tensor, int max_outputs, IEnumerable<object> collections, string family)

Outputs a `Summary` protocol buffer with images.

The summary has up to `max_outputs` summary values containing images. The images are built from `tensor` which must be 4-D with shape `[batch_size, height, width, channels]` and where `channels` can be:

* 1: `tensor` is interpreted as Grayscale. * 3: `tensor` is interpreted as RGB. * 4: `tensor` is interpreted as RGBA.

The images have the same number of channels as the input tensor. For float input, the values are normalized one image at a time to fit in the range `[0, 255]`. `uint8` values are unchanged. The op uses two different normalization algorithms:

* If the input values are all positive, they are rescaled so the largest one is 255.

* If any input value is negative, the values are shifted so input value 0.0 is at 127. They are then rescaled so that either the smallest value is 0, or the largest one is 255.

The `tag` in the outputted Summary.Value protobufs is generated based on the name, with a suffix depending on the max_outputs setting:

* If `max_outputs` is 1, the summary value tag is '*name*/image'. * If `max_outputs` is greater than 1, the summary value tags are generated sequentially as '*name*/image/0', '*name*/image/1', etc.

Parameters

int name: A name for the generated node. Will also serve as a series name in TensorBoard.
IEnumerable<SparseTensor> tensor: A 4-D `uint8` or `float32` `Tensor` of shape `[batch_size, height, width, channels]` where `channels` is 1, 3, or 4.
int max_outputs: Max number of batch elements to generate images for.
IEnumerable<object> collections: Optional list of ops.GraphKeys. The collections to add the summary to. Defaults to [_ops.GraphKeys.SUMMARIES]
string family: Optional; if provided, used as the prefix of the summary tag name, which controls the tab name used for display on Tensorboard.

Returns

Tensor: A scalar `Tensor` of type `string`. The serialized `Summary` protocol buffer.

Tensor image(string name, IGraphNodeBase tensor, int max_outputs, IEnumerable<object> collections, string family)

Outputs a `Summary` protocol buffer with images.

The summary has up to `max_outputs` summary values containing images. The images are built from `tensor` which must be 4-D with shape `[batch_size, height, width, channels]` and where `channels` can be:

* 1: `tensor` is interpreted as Grayscale. * 3: `tensor` is interpreted as RGB. * 4: `tensor` is interpreted as RGBA.

The images have the same number of channels as the input tensor. For float input, the values are normalized one image at a time to fit in the range `[0, 255]`. `uint8` values are unchanged. The op uses two different normalization algorithms:

* If the input values are all positive, they are rescaled so the largest one is 255.

* If any input value is negative, the values are shifted so input value 0.0 is at 127. They are then rescaled so that either the smallest value is 0, or the largest one is 255.

The `tag` in the outputted Summary.Value protobufs is generated based on the name, with a suffix depending on the max_outputs setting:

* If `max_outputs` is 1, the summary value tag is '*name*/image'. * If `max_outputs` is greater than 1, the summary value tags are generated sequentially as '*name*/image/0', '*name*/image/1', etc.

Parameters

string name: A name for the generated node. Will also serve as a series name in TensorBoard.
IGraphNodeBase tensor: A 4-D `uint8` or `float32` `Tensor` of shape `[batch_size, height, width, channels]` where `channels` is 1, 3, or 4.
int max_outputs: Max number of batch elements to generate images for.
IEnumerable<object> collections: Optional list of ops.GraphKeys. The collections to add the summary to. Defaults to [_ops.GraphKeys.SUMMARIES]
string family: Optional; if provided, used as the prefix of the summary tag name, which controls the tab name used for display on Tensorboard.

Returns

Tensor: A scalar `Tensor` of type `string`. The serialized `Summary` protocol buffer.

object image_dyn(object name, object tensor, ImplicitContainer<T> max_outputs, object collections, object family)

Outputs a `Summary` protocol buffer with images.

The summary has up to `max_outputs` summary values containing images. The images are built from `tensor` which must be 4-D with shape `[batch_size, height, width, channels]` and where `channels` can be:

* 1: `tensor` is interpreted as Grayscale. * 3: `tensor` is interpreted as RGB. * 4: `tensor` is interpreted as RGBA.

The images have the same number of channels as the input tensor. For float input, the values are normalized one image at a time to fit in the range `[0, 255]`. `uint8` values are unchanged. The op uses two different normalization algorithms:

* If the input values are all positive, they are rescaled so the largest one is 255.

* If any input value is negative, the values are shifted so input value 0.0 is at 127. They are then rescaled so that either the smallest value is 0, or the largest one is 255.

The `tag` in the outputted Summary.Value protobufs is generated based on the name, with a suffix depending on the max_outputs setting:

* If `max_outputs` is 1, the summary value tag is '*name*/image'. * If `max_outputs` is greater than 1, the summary value tags are generated sequentially as '*name*/image/0', '*name*/image/1', etc.

Parameters

object name: A name for the generated node. Will also serve as a series name in TensorBoard.
object tensor: A 4-D `uint8` or `float32` `Tensor` of shape `[batch_size, height, width, channels]` where `channels` is 1, 3, or 4.
ImplicitContainer<T> max_outputs: Max number of batch elements to generate images for.
object collections: Optional list of ops.GraphKeys. The collections to add the summary to. Defaults to [_ops.GraphKeys.SUMMARIES]
object family: Optional; if provided, used as the prefix of the summary tag name, which controls the tab name used for display on Tensorboard.

Returns

object: A scalar `Tensor` of type `string`. The serialized `Summary` protocol buffer.

void initialize(Graph graph, object session)

Initializes summary writing for graph execution mode.

This operation is a no-op when executing eagerly.

This helper method provides a higher-level alternative to using tf.contrib.summary.summary_writer_initializer_op and tf.contrib.summary.graph.

Most users will also want to call `tf.compat.v1.train.create_global_step` which can happen before or after this function is called.

Parameters

Graph graph: A tf.Graph or `tf.compat.v1.GraphDef` to output to the writer. This function will not write the default graph by default. When writing to an event log file, the associated step will be zero.
object session: So this method can call tf.Session.run. This defaults to `tf.compat.v1.get_default_session`.

Tensor merge(IEnumerable<IGraphNodeBase> inputs, object collections, string name)

Merges summaries.

This op creates a [`Summary`](https://www.tensorflow.org/code/tensorflow/core/framework/summary.proto) protocol buffer that contains the union of all the values in the input summaries.

When the Op is run, it reports an `InvalidArgument` error if multiple values in the summaries to merge use the same tag.

Parameters

IEnumerable<IGraphNodeBase> inputs: A list of `string` `Tensor` objects containing serialized `Summary` protocol buffers.
object collections: Optional list of graph collections keys. The new summary op is added to these collections. Defaults to `[]`.
string name: A name for the operation (optional).

Returns

Tensor: A scalar `Tensor` of type `string`. The serialized `Summary` protocol buffer resulting from the merging.

Tensor merge_all(ImplicitContainer<T> key, string scope, string name)

Merges all summaries collected in the default graph.

Parameters

ImplicitContainer<T> key: `GraphKey` used to collect the summaries. Defaults to `GraphKeys.SUMMARIES`.
string scope: Optional scope used to filter the summary ops, using `re.match`
string name

Returns

Tensor: If no summaries were collected, returns None. Otherwise returns a scalar `Tensor` of type `string` containing the serialized `Summary` protocol buffer resulting from the merging.

object merge_all_dyn(ImplicitContainer<T> key, object scope, object name)

Merges all summaries collected in the default graph.

Parameters

ImplicitContainer<T> key: `GraphKey` used to collect the summaries. Defaults to `GraphKeys.SUMMARIES`.
object scope: Optional scope used to filter the summary ops, using `re.match`
object name

Returns

object: If no summaries were collected, returns None. Otherwise returns a scalar `Tensor` of type `string` containing the serialized `Summary` protocol buffer resulting from the merging.

object merge_dyn(object inputs, object collections, object name)

Merges summaries.

This op creates a [`Summary`](https://www.tensorflow.org/code/tensorflow/core/framework/summary.proto) protocol buffer that contains the union of all the values in the input summaries.

When the Op is run, it reports an `InvalidArgument` error if multiple values in the summaries to merge use the same tag.

Parameters

object inputs: A list of `string` `Tensor` objects containing serialized `Summary` protocol buffers.
object collections: Optional list of graph collections keys. The new summary op is added to these collections. Defaults to `[]`.
object name: A name for the operation (optional).

Returns

object: A scalar `Tensor` of type `string`. The serialized `Summary` protocol buffer resulting from the merging.

IContextManager<T> record_if(bool condition)

IContextManager<T> record_if(IGraphNodeBase condition)

IContextManager<T> record_if(object condition)

object record_if_dyn(object condition)

Tensor scalar(string name, object tensor, IEnumerable<string> collections, string family)

Outputs a `Summary` protocol buffer containing a single scalar value.

The generated Summary has a Tensor.proto containing the input Tensor.

Parameters

string name: A name for the generated node. Will also serve as the series name in TensorBoard.
object tensor: A real numeric Tensor containing a single value.
IEnumerable<string> collections: Optional list of graph collections keys. The new summary op is added to these collections. Defaults to `[GraphKeys.SUMMARIES]`.
string family: Optional; if provided, used as the prefix of the summary tag name, which controls the tab name used for display on Tensorboard.

Returns

Tensor: A scalar `Tensor` of type `string`. Which contains a `Summary` protobuf.

Tensor scalar(string name, PythonFunctionContainer tensor, IEnumerable<string> collections, string family)

Outputs a `Summary` protocol buffer containing a single scalar value.

The generated Summary has a Tensor.proto containing the input Tensor.

Parameters

string name: A name for the generated node. Will also serve as the series name in TensorBoard.
PythonFunctionContainer tensor: A real numeric Tensor containing a single value.
IEnumerable<string> collections: Optional list of graph collections keys. The new summary op is added to these collections. Defaults to `[GraphKeys.SUMMARIES]`.
string family: Optional; if provided, used as the prefix of the summary tag name, which controls the tab name used for display on Tensorboard.

Returns

Tensor: A scalar `Tensor` of type `string`. Which contains a `Summary` protobuf.

Tensor tensor_summary(string name, IGraphNodeBase tensor, string summary_description, object collections, object summary_metadata, object family, string display_name)

Outputs a `Summary` protocol buffer with a serialized tensor.proto.

Parameters

string name: A name for the generated node. If display_name is not set, it will also serve as the tag name in TensorBoard. (In that case, the tag name will inherit tf name scopes.)
IGraphNodeBase tensor: A tensor of any type and shape to serialize.
string summary_description: A long description of the summary sequence. Markdown is supported.
object collections: Optional list of graph collections keys. The new summary op is added to these collections. Defaults to `[GraphKeys.SUMMARIES]`.
object summary_metadata: Optional SummaryMetadata proto (which describes which plugins may use the summary value).
object family: Optional; if provided, used as the prefix of the summary tag, which controls the name used for display on TensorBoard when display_name is not set.
string display_name: A string used to name this data in TensorBoard. If this is not set, then the node name will be used instead.

Returns

Tensor: A scalar `Tensor` of type `string`. The serialized `Summary` protocol buffer.

object tensor_summary_dyn(object name, object tensor, object summary_description, object collections, object summary_metadata, object family, object display_name)

Outputs a `Summary` protocol buffer with a serialized tensor.proto.

Parameters

object name: A name for the generated node. If display_name is not set, it will also serve as the tag name in TensorBoard. (In that case, the tag name will inherit tf name scopes.)
object tensor: A tensor of any type and shape to serialize.
object summary_description: A long description of the summary sequence. Markdown is supported.
object collections: Optional list of graph collections keys. The new summary op is added to these collections. Defaults to `[GraphKeys.SUMMARIES]`.
object summary_metadata: Optional SummaryMetadata proto (which describes which plugins may use the summary value).
object family: Optional; if provided, used as the prefix of the summary tag, which controls the name used for display on TensorBoard when display_name is not set.
object display_name: A string used to name this data in TensorBoard. If this is not set, then the node name will be used instead.

Returns

object: A scalar `Tensor` of type `string`. The serialized `Summary` protocol buffer.

Tensor text(string name, IGraphNodeBase tensor, object collections)

Summarizes textual data.

Text data summarized via this plugin will be visible in the Text Dashboard in TensorBoard. The standard TensorBoard Text Dashboard will render markdown in the strings, and will automatically organize 1d and 2d tensors into tables. If a tensor with more than 2 dimensions is provided, a 2d subarray will be displayed along with a warning message. (Note that this behavior is not intrinsic to the text summary api, but rather to the default TensorBoard text plugin.)

Parameters

string name: A name for the generated node. Will also serve as a series name in TensorBoard.
IGraphNodeBase tensor: a string-type Tensor to summarize.
object collections: Optional list of ops.GraphKeys. The collections to add the summary to. Defaults to [_ops.GraphKeys.SUMMARIES]

Returns

Tensor: A TensorSummary op that is configured so that TensorBoard will recognize that it contains textual data. The TensorSummary is a scalar `Tensor` of type `string` which contains `Summary` protobufs.

object text_dyn(object name, object tensor, object collections)

Summarizes textual data.

Text data summarized via this plugin will be visible in the Text Dashboard in TensorBoard. The standard TensorBoard Text Dashboard will render markdown in the strings, and will automatically organize 1d and 2d tensors into tables. If a tensor with more than 2 dimensions is provided, a 2d subarray will be displayed along with a warning message. (Note that this behavior is not intrinsic to the text summary api, but rather to the default TensorBoard text plugin.)

Parameters

object name: A name for the generated node. Will also serve as a series name in TensorBoard.
object tensor: a string-type Tensor to summarize.
object collections: Optional list of ops.GraphKeys. The collections to add the summary to. Defaults to [_ops.GraphKeys.SUMMARIES]

Returns

object: A TensorSummary op that is configured so that TensorBoard will recognize that it contains textual data. The TensorSummary is a scalar `Tensor` of type `string` which contains `Summary` protobufs.

void trace_export(string name, IEnumerable<object> step, object profiler_outdir)

void trace_export(string name, int step, object profiler_outdir)

object trace_export_dyn(object name, object step, object profiler_outdir)

void trace_off()

object trace_off_dyn()

void trace_on(bool graph, bool profiler)

object trace_on_dyn(ImplicitContainer<T> graph, ImplicitContainer<T> profiler)

object write(string tag, double tensor, IEnumerable<object> step, IGraphNodeBase metadata, string name)

object write(string tag, IEnumerable<object> tensor, object step, IGraphNodeBase metadata, string name)

object write(string tag, ValueTuple<PythonClassContainer, PythonClassContainer> tensor, IEnumerable<object> step, IGraphNodeBase metadata, string name)

Methods

Properties

Public static methods

object all_v2_summary_ops()

Returns

object all_v2_summary_ops_dyn()

Returns

Tensor audio(string name, IGraphNodeBase tensor, int sample_rate, int max_outputs, object collections, string family)

Parameters

Returns

Tensor audio(string name, IGraphNodeBase tensor, double sample_rate, int max_outputs, object collections, string family)

Parameters

Returns

object audio_dyn(object name, object tensor, object sample_rate, ImplicitContainer<T> max_outputs, object collections, object family)

Parameters

Returns

ResourceSummaryWriter create_file_writer(IGraphNodeBase logdir, Nullable<int> max_queue, Nullable<int> flush_millis, string filename_suffix, string name)

NoopSummaryWriter create_noop_writer()

object create_noop_writer_dyn()

object flush(SummaryWriter writer, string name)

object flush(IGraphNodeBase writer, string name)

object get_summary_description(object node_def)

Parameters

Returns

object get_summary_description_dyn(object node_def)

Parameters

Returns

Tensor histogram(string name, IEnumerable<IGraphNodeBase> values, object collections, string family)

Parameters

Returns

Tensor histogram(string name, object values, object collections, string family)

Parameters

Returns

Tensor image(int name, IDictionary<object, object> tensor, int max_outputs, IEnumerable<object> collections, string family)

Parameters

Returns

Tensor image(string name, IEnumerable<SparseTensor> tensor, int max_outputs, IEnumerable<object> collections, string family)

Parameters

Returns

Tensor image(string name, IDictionary<object, object> tensor, int max_outputs, IEnumerable<object> collections, string family)

Parameters

Returns

Tensor image(int name, IGraphNodeBase tensor, int max_outputs, IEnumerable<object> collections, string family)

Parameters

Returns

Tensor image(int name, IEnumerable<SparseTensor> tensor, int max_outputs, IEnumerable<object> collections, string family)

Parameters

Returns

Tensor image(string name, IGraphNodeBase tensor, int max_outputs, IEnumerable<object> collections, string family)

Parameters

Returns

object image_dyn(object name, object tensor, ImplicitContainer<T> max_outputs, object collections, object family)

Parameters

Returns

void initialize(Graph graph, object session)

Parameters

Tensor merge(IEnumerable<IGraphNodeBase> inputs, object collections, string name)

Parameters

Returns

Tensor merge_all(ImplicitContainer<T> key, string scope, string name)

Parameters

Returns

object merge_all_dyn(ImplicitContainer<T> key, object scope, object name)

Parameters

Returns

object merge_dyn(object inputs, object collections, object name)

Parameters

Returns

IContextManager<T> record_if(bool condition)

IContextManager<T> record_if(IGraphNodeBase condition)

IContextManager<T> record_if(object condition)

object record_if_dyn(object condition)

Tensor scalar(string name, object tensor, IEnumerable<string> collections, string family)

Parameters

Returns

Tensor scalar(string name, PythonFunctionContainer tensor, IEnumerable<string> collections, string family)

Parameters

Returns

Tensor tensor_summary(string name, IGraphNodeBase tensor, string summary_description, object collections, object summary_metadata, object family, string display_name)

Parameters