`port c++ energy op to open source in tflm_signal`
-port energy op and corresponding to new open source location for C++
BUG=[b/289422411](https://b.corp.google.com/issues/289422411)
`port c++ stacker op to open source in tflm_signal`
-port stacker op and corresponding to new open source location for C++
BUG=[b/289298641](https://b.corp.google.com/issues/289298641)
`port c++ delay op to open source in tflm_signal`
-port delay op and corresponding to new open source location for C++
BUG=[b/289296081](https://b.corp.google.com/issues/289296081)
`port c++ Overlapp_Add op to open source in tflm_signal`
-port Overlapp_Add op and corresponding to new open source location for C++
BUG=[b/289291202](https://b.corp.google.com/issues/289291202)
`port c++ framer op to open source in tflm_signal`
-port framer op and corresponding to new open source location for C++
BUG=[b/288965505](https://b.corp.google.com/288965505)
This is needed to properly build all the ops together. Since we are calling into a singular utils function to load the ops, if it checks for any other ops, it would break before this.
Now we make it build all ops everytime utils.py is built.
BUG=[288938993](http://b/288938993)
Second OP for the TFLM Signal library, Real-Valued Fast Fourier Transform.
The RFFT OP provides three resolutions: `FLOAT, INT16, INT32`
Similar usage as to previous Window OP:
* `op_resolver.AddRfft()` (which will add all resolutions, and determine the type at runtime)
* `op_resolver.AddRfftFloat()`, `op_resolver.AddRfftInt16()`, `op_resolver.AddRfftInt32()` for a specific resolution type.
* or via python as can be seen in `fft_ops_test.py`
3 testing options are provided:
* Micro(C++): bazel run signal/micro/kernels:fft_test
* Tensorflow/Micro(Python): bazel run python/tflite_micro/signal:fft_ops_test
* Makefile(C++): make -f tensorflow/lite/micro/tools/make/Makefile test_kernel_fft_test
BUG=[287346710](http://b/287346710)
To package the module `runtime` as `tflite_micro.runtime`, put `runtime` under
a directory representing the Python namespace package `tflite_micro`. For
organization's sake, move it all to the top-level directory `python/`. Adjust
tests and docs to match.
Some code outside of the Python extension module has come to depend on
`python/tflite_micro:python_ops_resolver` as a replacement for
`all_ops_resolver` (e.g.:`t/l/m/integration_tests/seanet/add/integration_tests.cc`).
`python_ops_resolver` is intended to be a private implementation detail of the
Python extension module. For now, grandfather in the dependent code by updating
its references to the resolver's location; however, soon the dependent code
should be migrated away to a different resolver. (#2033,
https://issuetracker.google.com/286508251)
BUG=part of #1484
We have some name clash issues with the current Window OP name.
We will be changing it from "Window"->"SignalWindow" until the names clashes are resolved and revert back afterwards.
This is an internal implementation detail, so user level API has no change from current usage, i.e. still use (op_resolver.AddWindow() and window_op.window)
BUG=[286250473](http://b/286250473)
First Op for the TFLM Signal Processing Ops library.
Doc linked in bug.
The Window OP is a custom signal processing OP similar to what is found in tf.signal library, but specific for integer (int16) purposes.
You can directly use this as a builtin op via the op resolver as:
* `op_resolver.AddWindow()`
* or via python as shown in `window_op_test.py`
3 testing options are provided:
* Micro(C++): `bazel run signal/micro/kernels:window_test`
* Tensorflow/Micro(Python): `bazel run python/tflite_micro/signal:window_op_test`
* Makefile(C++): `make -f tensorflow/lite/micro/tools/make/Makefile test_kernel_window_test`
BUG=[259145369](http://b/259145369)
In preparation for upgrading the Tensorflow Python package dependency, upgrade
the C++ standard used when compiling //python/tests:cc_deps_link_test from
C++14 to C++17. cc_deps_link_test tests linking against the Tensorflow Python
package's extension module.
Bug=#1966.
Extend the Python repository_rule used to create external repositories, adding targets for C-language binary libraries shipped inside Python packages; e.g., that shipped in package tensorflow-gpu.
These targets are to be used as dependencies by C-language targets.
Note: when debugging the build, it can be helpful to examine the repository directory and BUILD file this repository_rule generates in the bazel cache.
Begin using a python/ directory at the root of the project for code that is specific to Python.
Upgrade to the latest version of rules_python first. Note that the unit test to keep requirements.in and requirements.txt is disabled (specifically with
ec6bdc5d4443285d28a44076f06c203d9582e4a1)
Add a unit test for this feature.
BUG=see description
