Lines Matching +refs:icu +refs:dependencies +refs:mode
267 * Eager mode can now execute each op as a `tf.function`, allowing for more
785 * Updates `icu` to `69.1` to handle
934 * Updates `icu` to `69.1` to handle
1055 * Updates `icu` to `69.1` to handle
1168 * Updates `icu` to `69.1` to handle
1286 be one of `OFF` (equivalent to today's `"parallel_epochs"` mode),
1287 `DYNAMIC` (equivalent to today's `"distributed_epoch"` mode), or one of
1397 mode. In this mode, the table resource can only be accessed via resource
1698 the API only works in graph mode and is not customizable. The function is
1767 * Renamed `"binary"` output mode to `"multi_hot"` for
1772 * Added a new output mode `"one_hot"` for `CategoryEncoding`,
1775 dimension if necessary. Use this mode on rank 1 inputs for the old
2737 * Fixes vulnerabilities where session operations in eager mode lead to null
2973 * Fixes vulnerabilities where session operations in eager mode lead to null
3209 * Fixes vulnerabilities where session operations in eager mode lead to null
3445 * Fixes vulnerabilities where session operations in eager mode lead to null
3683 * tf.data input pipelines can now be executed in debug mode, which
3687 debug mode can be enabled through
3907 `tf.config.experimental.mlir_bridge_rollout` to enable a \"safe\" mode.
3912 the MLIR bridge in a \"safe\" mode. This runs the MLIR bridge in a
3913 FallbackEnabled mode when an analysis of the graph determines that the
3962 * Fixes vulnerabilities where session operations in eager mode lead to
4415 on Ampere based GPUs. TensorFloat-32, or TF32 for short, is a math mode for
4430 [sampling mode API](https://www.tensorflow.org/guide/profiler#profiling_apis).
4651 on Ampere based GPUs.TensorFloat-32, or TF32 for short, is a math mode
4702 * Adds support for a new "distributed_epoch" processing mode. This processing
4703 mode distributes a dataset across all tf.data workers, instead of having
4872 * Fixes segfault raised by calling session-only ops in eager mode,
4984 * Fixes segfault raised by calling session-only ops in eager mode
5025 * Fixes segfault raised by calling session-only ops in eager mode
5075 * Fixes segfault raised by calling session-only ops in eager mode
5121 * Fixes segfault raised by calling session-only ops in eager mode
5166 * Fixes segfault raised by calling session-only ops in eager mode
5375 * Deprecate `tf.group`. It is not useful in eager mode.
5504 * Enabled experimental support for a new quantization mode with 16-bit
5771 Eager mode.
5830 * Speed up `GradientTape` in eager mode by auto-generating list of op
5954 error and the output mode is `in-place`.
6228 * Added `tf.autodiff.ForwardAccumulator` for forward-mode autodiff
6384 * Add an `implementation=3` mode for `tf.keras.layers.LocallyConnected2D`
6397 * tflite object detection script has a debug mode.
6440 * Fix accidental quadratic graph construction cost in graph-mode
6668 between CPU and GPU mode, since the CuDNN kernel is using sigmoid, we change
6669 the default for CPU mode to sigmoid as well. With that, the default GRU will
6734 in eager mode.
6822 * Add an `implementation=3` mode for `tf.keras.layers.LocallyConnected2D`
6836 * Add support for temporal sample weight mode in subclassed models.
6924 * Fix accidental quadratic graph construction cost in graph-mode
7043 * Transitive dependencies on :`pooling_ops` were removed. Some users may
7044 need to add explicit dependencies on :`pooling_ops` if they reference
7064 * Fix callbacks do not log values in eager mode when a deferred build
7069 * Add support for `add_metric` in the graph function mode.
7196 * Callbacks now log values in eager mode when a deferred build model is used.
7197 * Transitive dependencies on :pooling_ops were removed. Some users may need to
7198 add explicit dependencies on :pooling_ops if they reference the operators
7237 tf.keras.experimental.export. (SignatureDef key for evaluation mode is
7265 * Add support for `add_metric` in the graph function mode.
7317 unified backend between CPU and GPU mode, since the CuDNN kernel is
7318 using sigmoid, we change the default for CPU mode to sigmoid as well.
7337 eager mode.
7465 * Update the doc with the details about the rounding mode used in
7537 between CPU and GPU mode, since the CuDNN kernel is using sigmoid, we
7538 change the default for CPU mode to sigmoid as well. With that, the
7605 `tf.data.Dataset.map` work in Eager mode.
7798 and `tf.keras.layers.LocallyConnected1D`. The new mode
7852 * boosted trees: adding pruning mode.
8321 * Eager mode is moving out of contrib, try `tf.enable_eager_execution()`.
9179 dependencies.
9203 * Remove estimator_spec(mode) argument.
9341 * C API: Graph imports now support input remapping, control dependencies, and
9532 * Android: TF stats now exposed directly in demo and log when debug mode is