Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Update function.ipynb #2264

Closed
wants to merge 1 commit into from
Closed

Update function.ipynb #2264

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 2 additions & 2 deletions site/en/guide/function.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -362,7 +362,7 @@
"\n",
"When called, a `Function` matches the call arguments to existing `ConcreteFunction`s using `tf.types.experimental.TraceType` of each argument. If a matching `ConcreteFunction` is found, the call is dispatched to it. If no match is found, a new `ConcreteFunction` is traced.\n",
"\n",
"If multiple matches are found, the most specific signature is chosen. Matching is done by [subtyping](https://en.wikipedia.org/wiki/Subtyping), much like normal function calls in C++ or Java, for instance. For example, `TensorShape([1, 2])` is a subtype of `TensorShape([None, None])` and so a call to the tf.function with `TensorShape([1, 2])` can be dispatched to the `ConcreteFunction` produced with `TensorShape([None, None])` but if a `ConcreteFunction` with `TensorShape([1, None])` also exists then it will prioritized since it is more specific.\n",
"If multiple matches are found, the most specific signature is chosen. Matching is done by [subtyping](https://en.wikipedia.org/wiki/Subtyping), much like normal function calls in C++ or Java, for instance. For example, `TensorShape([1, 2])` is a subtype of `TensorShape([None, None])` and so a call to the tf.function with `TensorShape([1, 2])` can be dispatched to the `ConcreteFunction` produced with `TensorShape([None, None])` but if a `ConcreteFunction` with `TensorShape([1, None])` also exists then it will be prioritized since it is more specific.\n",
"\n",
"The `TraceType` is determined from input arguments as follows:\n",
"* For `Tensor`, the type is parameterized by the `Tensor`'s `dtype` and `shape`; ranked shapes are a subtype of unranked shapes; fixed dimensions are a subtype of unknown dimensions\n",
Expand Down Expand Up @@ -395,7 +395,7 @@
"source": [
"### Controlling retracing\n",
"\n",
"Retracing, which is when your `Function` creates more than one trace, helps ensures that TensorFlow generates correct graphs for each set of inputs. However, tracing is an expensive operation! If your `Function` retraces a new graph for every call, you'll find that your code executes more slowly than if you didn't use `tf.function`.\n",
"Retracing, which is when your `Function` creates more than one trace, helps ensure that TensorFlow generates correct graphs for each set of inputs. However, tracing is an expensive operation! If your `Function` retraces a new graph for every call, you'll find that your code executes more slowly than if you didn't use `tf.function`.\n",
"\n",
"To control the tracing behavior, you can use the following techniques:"
]
Expand Down
Loading