experiments/STT-tensorflow
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Fixing the markdown and disabling internal auto-formatting.

Browse Source
This commit is contained in:
Advait Jain 2020-10-19 14:21:00 -07:00
parent db14325178
commit c702a443f5
2 changed files with 57 additions and 46 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

64
tensorflow/lite/micro/cortex_m_generic/README.md
View File

@ -1,3 +1,5 @@
<!-- mdformat off(b/169948621#comment2) -->
# Generic Cortex-Mx customizations
The customization requires a definition where the debug log goes to. The purpose
@ -13,42 +15,50 @@ See debug_log_callback.h
# How to build
Required parameters: - TARGET: cortex_m_generic - TARGET_ARCH: cortex-mXX (For
all options see:
tensorflow/lite/micro/tools/make/targets/cortex_m_generic_makefile.inc)
Required parameters:
Optional parameters: - TOOLCHAIN: armgcc (default) or armmclang - For
Cortex-M55, ARM Compiler 6.14 or later is required.
- TARGET: cortex_m_generic
- TARGET_ARCH: cortex-mXX (For all options see: tensorflow/lite/micro/tools/make/targets/cortex_m_generic_makefile.inc)
Optional parameters:
- TOOLCHAIN: armgcc (default) or armmclang
- For Cortex-M55, ARM Compiler 6.14 or later is required.
Some examples:
Building with arm-gcc ``` make -f tensorflow/lite/micro/tools/make/Makefile
TARGET=cortex_m_generic TARGET_ARCH=cortex-m7 microlite make -f
tensorflow/lite/micro/tools/make/Makefile TARGET=cortex_m_generic
TARGET_ARCH=cortex-m7 TAGS=cmsis-nn microlite
Building with arm-gcc
```
make -f tensorflow/lite/micro/tools/make/Makefile TARGET=cortex_m_generic TARGET_ARCH=cortex-m7 microlite
make -f tensorflow/lite/micro/tools/make/Makefile TARGET=cortex_m_generic TARGET_ARCH=cortex-m7 TAGS=cmsis-nn microlite
make -f tensorflow/lite/micro/tools/make/Makefile TARGET=cortex_m_generic
TARGET_ARCH=cortex-m4 TAGS=cmsis-nn microlite make -f
tensorflow/lite/micro/tools/make/Makefile TARGET=cortex_m_generic
TARGET_ARCH=cortex-m4+fp TAGS=cmsis-nn microlite ```
make -f tensorflow/lite/micro/tools/make/Makefile TARGET=cortex_m_generic TARGET_ARCH=cortex-m4 TAGS=cmsis-nn microlite
make -f tensorflow/lite/micro/tools/make/Makefile TARGET=cortex_m_generic TARGET_ARCH=cortex-m4+fp TAGS=cmsis-nn microlite
```
Building with armclang `make -f tensorflow/lite/micro/tools/make/Makefile
TOOLCHAIN=armclang TARGET=cortex_m_generic TARGET_ARCH=cortex-m55 microlite make
-f tensorflow/lite/micro/tools/make/Makefile TOOLCHAIN=armclang
TARGET=cortex_m_generic TARGET_ARCH=cortex-m55 TAGS=cmsis-nn microlite make -f
tensorflow/lite/micro/tools/make/Makefile TOOLCHAIN=armclang
TARGET=cortex_m_generic TARGET_ARCH=cortex-m55+nofp TAGS=cmsis-nn microlite`
Building with armclang
```
make -f tensorflow/lite/micro/tools/make/Makefile TOOLCHAIN=armclang TARGET=cortex_m_generic TARGET_ARCH=cortex-m55 microlite
make -f tensorflow/lite/micro/tools/make/Makefile TOOLCHAIN=armclang TARGET=cortex_m_generic TARGET_ARCH=cortex-m55 TAGS=cmsis-nn microlite
make -f tensorflow/lite/micro/tools/make/Makefile TOOLCHAIN=armclang TARGET=cortex_m_generic TARGET_ARCH=cortex-m55+nofp TAGS=cmsis-nn microlite
```
The Tensorflow Lite Micro makefiles download a specific version of the arm-gcc
compiler to tensorflow/lite/micro/tools/make/downloads/gcc_embedded. If desired,
a different version can be used by providing `TARGET_TOOLCHAIN_ROOT` option to
the Makefile. `make -f tensorflow/lite/micro/tools/make/Makefile
TARGET=cortex_m_generic TARGET_ARCH=cortex-m4
TARGET_TOOLCHAIN_ROOT=/path/to/arm-gcc/ microlite`
compiler to tensorflow/lite/micro/tools/make/downloads/gcc_embedded.
If desired, a different version can be used by providing `TARGET_TOOLCHAIN_ROOT`
option to the Makefile:
```
make -f tensorflow/lite/micro/tools/make/Makefile TARGET=cortex_m_generic TARGET_ARCH=cortex-m4+fp TARGET_TOOLCHAIN_ROOT=/path/to/arm-gcc/ microlite
```
Similarly, `TAGS=cmsis-nn` downloads a specific version of CMSIS to
tensorflow/lite/micro/tools/make/downloads/cmsis. While this is the only version
that is regularly tested, you can use your own version of CMSIS as well by
providing `CMSIS_PATH` to the Makefile: `make -f
tensorflow/lite/micro/tools/make/Makefile TARGET=cortex_m_generic
TARGET_ARCH=cortex-m4 TAGS=cmsis-nn CMSIS_PATH=/path/to/own/cmsis microlite`
providing `CMSIS_PATH` to the Makefile:
```
make -f tensorflow/lite/micro/tools/make/Makefile TARGET=cortex_m_generic TARGET_ARCH=cortex-m4+fp TAGS=cmsis-nn CMSIS_PATH=/path/to/own/cmsis microlite
```

39
tensorflow/lite/micro/docs/memory_management.md
View File

@ -1,3 +1,5 @@
<!-- mdformat off(b/169948621#comment2) -->
<!--
Semi-automated TOC generation with instructions from
https://github.com/ekalinin/github-markdown-toc#auto-insert-and-update-toc
@ -38,13 +40,14 @@ sections:
The illustration below represents typical allocations in TFLM:
## ```
| | | | | HEAD |<-- TEMPORARY -->| TAIL |
## | | | |
* Lowest Address Highest Address * ```
```
--------------------------------------------------------------------------------
| | | |
| HEAD |<-- TEMPORARY -->| TAIL |
| | | |
--------------------------------------------------------------------------------
* Lowest Address Highest Address *
```
### Head Section
@ -129,20 +132,18 @@ interpreter.PrintAllocations();
The output of this call will look something similar to this (output from the
[memory_arena_threshold_test](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/micro/memory_arena_threshold_test.cc#L205)):
`sh [RecordingMicroAllocator] Arena allocation total 9568 bytes
```bash
[RecordingMicroAllocator] Arena allocation total 9568 bytes
[RecordingMicroAllocator] Arena allocation head 7744 bytes
[RecordingMicroAllocator] Arena allocation tail 1824 bytes
[RecordingMicroAllocator] 'TfLiteEvalTensor data' used 360 bytes with alignment
overhead (requested 360 bytes for 15 allocations) [RecordingMicroAllocator]
'Persistent TfLiteTensor data' used 0 bytes with alignment overhead (requested 0
bytes for 0 tensors) [RecordingMicroAllocator] 'Persistent TfLiteTensor
quantization data' used 0 bytes with alignment overhead (requested 0 bytes for 0
allocations) [RecordingMicroAllocator] 'TfLiteTensor variable buffer data' used
0 bytes with alignment overhead (requested 0 bytes for 0 allocations)
[RecordingMicroAllocator] 'NodeAndRegistration struct' used 392 bytes with
alignment overhead (requested 392 bytes for 7 NodeAndRegistration structs)
[RecordingMicroAllocator] 'Operator runtime data' used 136 bytes with alignment
overhead (requested 136 bytes for 5 OpData structs)`
[RecordingMicroAllocator] 'TfLiteEvalTensor data' used 360 bytes with alignment overhead (requested 360 bytes for 15 allocations)
[RecordingMicroAllocator] 'Persistent TfLiteTensor data' used 0 bytes with alignment overhead (requested 0 bytes for 0 tensors)
[RecordingMicroAllocator] 'Persistent TfLiteTensor quantization data' used 0 bytes with alignment overhead (requested 0 bytes for 0 allocations)
[RecordingMicroAllocator] 'TfLiteTensor variable buffer data' used 0 bytes with alignment overhead (requested 0 bytes for 0 allocations)
[RecordingMicroAllocator] 'NodeAndRegistration struct' used 392 bytes with alignment overhead (requested 392 bytes for 7 NodeAndRegistration structs)
[RecordingMicroAllocator] 'Operator runtime data' used 136 bytes with alignment overhead (requested 136 bytes for 5 OpData structs)
```
### Allocation Section Details