tf.contrib.graph_editor.compute_boundary_ts
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Compute the tensors at the boundary of a set of ops.
tf.contrib.graph_editor.compute_boundary_ts(
ops
)
This function looks at all the tensors connected to the given ops (in/out)
and classify them into three categories:
1) input tensors: tensors whose generating operation is not in ops.
2) output tensors: tensors whose consumer operations are not in ops
3) inside tensors: tensors which are neither input nor output tensors.
Note that a tensor can be both an inside tensor and an output tensor if it is
consumed by operations both outside and inside of ops.
Args |
|---|
ops
|
an object convertible to a list of tf.Operation.
|
Returns |
|---|
A tuple (outside_input_ts, outside_output_ts, inside_ts) where:
outside_input_ts is a Python list of input tensors;
outside_output_ts is a python list of output tensors;
inside_ts is a python list of inside tensors.
Since a tensor can be both an inside tensor and an output tensor,
outside_output_ts and inside_ts might intersect.
|
Raises |
|---|
TypeError
|
if ops cannot be converted to a list of tf.Operation.
|
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Last updated 2020-10-01 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2020-10-01 UTC."],[],[],null,["# tf.contrib.graph_editor.compute_boundary_ts\n\n\u003cbr /\u003e\n\n|------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/contrib/graph_editor/select.py#L280-L329) |\n\nCompute the tensors at the boundary of a set of ops. \n\n tf.contrib.graph_editor.compute_boundary_ts(\n ops\n )\n\nThis function looks at all the tensors connected to the given ops (in/out)\nand classify them into three categories:\n\n1) input tensors: tensors whose generating operation is not in ops.\n2) output tensors: tensors whose consumer operations are not in ops\n3) inside tensors: tensors which are neither input nor output tensors.\n\nNote that a tensor can be both an inside tensor and an output tensor if it is\nconsumed by operations both outside and inside of `ops`.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|-------|--------------------------------------------------|\n| `ops` | an object convertible to a list of tf.Operation. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A tuple `(outside_input_ts, outside_output_ts, inside_ts)` where: `outside_input_ts` is a Python list of input tensors; `outside_output_ts` is a python list of output tensors; `inside_ts` is a python list of inside tensors. Since a tensor can be both an inside tensor and an output tensor, `outside_output_ts` and `inside_ts` might intersect. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ------ ||\n|-------------|-------------------------------------------------------|\n| `TypeError` | if ops cannot be converted to a list of tf.Operation. |\n\n\u003cbr /\u003e"]]
View source on GitHub