* Groundwork to enable python format checks (via yapf) as part of the CI.

With this change:
 * we are set up to use yapf as part of the docker container
 * pigweed patch is updated to use the google Python style (pep8 with indent of 2 spaces)
 * some documentation updates.

The code still needs to be formatted, and then the Python formatting check will be turned on as part of ci.

BUG=http://b/194404216

* Format all the code.

Once this change is merged, we will turn on Python formatting check as
part of the CI.

* minor formatting update.

* Turn on Python formatting checks as part of CI.

Also, add an option to fix the formatting via the test_code_style.sh
script.

BUG=http://b/194404984 and http://b/194404216

* Groundwork to enable python format checks (via yapf) as part of the CI.

With this change:
 * we are set up to use yapf as part of the docker container
 * pigweed patch is updated to use the google Python style (pep8 with indent of 2 spaces)
 * some documentation updates.

The code still needs to be formatted, and then the Python formatting check will be turned on as part of ci.

BUG=http://b/194404216

* Format all the code.

Once this change is merged, we will turn on Python formatting check as
part of the CI.

* minor formatting update.

With this change:
 * we are set up to use yapf as part of the docker container
 * pigweed patch is updated to use the google Python style (pep8 with indent of 2 spaces)
 * some documentation updates.

The code still needs to be formatted, and then the Python formatting check will be turned on as part of ci.

BUG=http://b/194404216

* Remove distinction between fusion_f1 and hifi4.

Hifi4, Fusion F1 and Hifi3Z all use the same underlying xannlib hifi4
optimizations and with this change we can specify TARGET_ARCH=hifi4 for
each of these cores.

BUG=http://b/194225949

* Fix the build

Use base class version of AllocateFromTail() instead of derived class
version in FlatBufferVectorToTfLiteTypeArray() to solve the issue
Signed-off-by: NKun-Lu <kun.lu@ibm.com>

I copied the sparkfun-edge action and then adjusted to call the esp32 ci test script.

Changed the job name from cortex_m to esp32.

Inserted the Readme entry at the alphabetically appropriate index.
Signed-off-by: NMichael O'Cleirigh <michael.ocleirigh@gmail.com>
Co-authored-by: NMichael O'Cleirigh <michael.ocleirigh@gmail.com>

* Cadence HiFi 5 Neural Network Library v1.6.0
updated the download script to use hifi5 v1.6.0 archive.
depthwise_conv kernel is updated and patch is not required now.
quantize optimized kernel is renamed in the v1.6.0, updated with new
kernel name.

* Fix formatting.
Co-authored-by: Nbhanu prakash bandaru venkata <bhanup@cadence.com>
Co-authored-by: NAdvait Jain <advaitjain@users.noreply.github.com>
Co-authored-by: NAdvait Jain <advaitjain@google.com>

* Updated utility functions to work with embARC MLI Library 2.0

* Updated copyrights in several files.

* Minor fix for mli_tf_utils.h

* Update mli_tf_utils.h

* Updated pooling kernel to work with embARC MLI Library 2.0

* Update pooling.cc copyright.

* Updated fully_connected kernel to work with embARC MLI Library 2.0

* Update fully_connected.cc

* Minor fix for fully_connected activation functions.

* Updated depthwise_conv kernel to work with embARC MLI Library 2.0

* Update depthwise_conv.cc

* Minor fix for depthwise conv activation functions.

* Updated convolution kernel to work with embARC MLI Library 2.0

* Update conv.cc

* Minor fix for conv2d activation functions.

BUG=http://b/193437031

* Have a TFLM-specific version of lite/kernels/op_macros.h

 * After this change, we can remove the TFLM-specific code from upstream
   Tensorflow.
 * Both the TfLite and TFLM implementations of op_macros.h will be
   simplified.

BUG=http://b/187728891
NO_CHECK_TFLITE_FILE=lite/kernels/kernel_util.cc will be modified in upstream as well

* Fix target-specific makefile build.

The corresponding internal change is http://cl/384575105

BUG=http://b/188064725

* XTENSA_CODE_REFACTOR: depthwise_conv
Refactored the xtensa hifi optimized code for depthwise_conv operator.

* Small fixes for the CI.
Co-authored-by: Nbhanu prakash bandaru venkata <bhanup@cadence.com>
Co-authored-by: NAdvait Jain <advaitjain@google.com>

* modify a tflite file in the tflite-micro repository.

* fix the path

* Update workflow logic to complete workflow without error with NO_CHECK_TFLITE_FILES

* revert change to the tflite files.

* fail PRs that overwrite a set of files from upstream

* Change some names, modify Python script logic etc.

* small fixes.

* Use more restrictive TFLM-bot token.
Co-authored-by: NAdvait Jain <advaitjain@users.noreply.github.com>
Co-authored-by: NAdvait Jain <advaitjain@google.com>

* Force FLATBUFFERS_LOCALE_INDEPENDENT=0

With this change, we no longer need a #define in the sources that
directly or indrectly include flatbuffers/base.h

BUG=http://b/193264978

* Fix xtensa script.

* micro_profiler.cc: add CSV output

Adds a method to log output in CSV form, suitable for input to a
spreadsheet.

* micro_profiler.cc: remove ms from CSV output

Removes milliseconds from CSV output.
Co-authored-by: NAdvait Jain <advaitjain@users.noreply.github.com>

* Check for the case where the Operators vector in a tflite model is missing

Some of our tools remove the vector if it's empty (i.e. the subgraph doesn't contain ops). The check is added until the tools are fixed.

BUG=http://b/192589496

* Move NumSubgraphOperators to flatbuffer_utils.h/cc

* Fix the CI errors.

* Remove `#define FLATBUFFERS_LOCALE_INDEPENDENT 0`

We will handle that via the Makefile instead.

* Add  -DFLATBUFFERS_LOCALE_INDEPENDENT=0 to makefile.

* remove references to flatbuffer from kernel_utils.cc/h

* Fix the build.

* run buildifier
Co-authored-by: NAdvait Jain <advaitjain@google.com>
Co-authored-by: NAdvait Jain <advaitjain@users.noreply.github.com>

Co-authored-by: NAdvait Jain <advaitjain@users.noreply.github.com>

* fixed scratch buffer extern decleration in ceva_common.h

* Add optimized depthwise conv BX1 and SP500

* fixed year in copyright notice
Co-authored-by: NAdvait Jain <advaitjain@users.noreply.github.com>

- Save ~4KB of RAM by implementing a lightweight version of the vector, which only accesses integer values, without implicit conversion.
- Change Micro kernels to access flexbuffers as vectors instead of maps, which is recommended by the flexbuffers doc for efficiency. Since the values in the vector are ordered alphabetically by their keys, the kernels can access them by index instead.
- Revert detection_postprocess to the native flexbuffers API. The
LiteVector API doesn't support IsNull() and I prefer not to support two
custom flexbuffer APIs.
Co-authored-by: NNat Jeffries <natmjeffries@gmail.com>

BUG=http://b/192614484

* Remove MICROLITE_CC_KERNELS_SRCS from the MICROLITE_CC_SRCS list.

Stop the kernel sources from being compiled into both the core
objects and kernel objects.

* Add kernel sources to list_library_sources

* Fix project generation presubmit
Co-authored-by: NNat Jeffries <natmjeffries@gmail.com>

Change-Id: I23e7425445fd8fdb37be0ebb43cb9c8529ceb368
Co-authored-by: NAdvait Jain <advaitjain@users.noreply.github.com>

Co-authored-by: NAdvait Jain <advaitjain@users.noreply.github.com>

Previously, some sources were built before THIRD_PARTY_TARGETS was downloaded, meaning dependencies in those sources on flatbuffers, gemmlowp, etc could be missed. An alternative to this "dependency for every source" approach could be to add $(THIRD_PARTY_TARGETS) as the first dependency in $(MICROLITE_LIB_PATH), but this relies on Make dependency ordering which is ill-advised

Background: https://stackoverflow.com/questions/9159960/order-of-processing-components-in-makefile

Lots of large models have >50 ops, so upping the max number to 1024 seems reasonable. Most TFLM models should not exceed 1024 ops.