[tflite] add xnnpack delegate to label_image

rebase and resubmit #36749 to see if it works.
This commit is contained in:
Koan-Sin Tan 2020-03-25 13:21:04 +08:00
parent 69396208c8
commit 70cb1703c4
5 changed files with 121 additions and 29 deletions

View File

@ -33,6 +33,7 @@ cc_binary(
"//tensorflow/lite:framework",
"//tensorflow/lite:string_util",
"//tensorflow/lite/delegates/nnapi:nnapi_delegate",
"//tensorflow/lite/delegates/xnnpack:xnnpack_delegate",
"//tensorflow/lite/kernels:builtin_ops",
"//tensorflow/lite/profiling:profiler",
"//tensorflow/lite/tools/evaluation:utils",

View File

@ -90,39 +90,96 @@ adb push tensorflow/lite/examples/label_image/testdata/grace_hopper.bmp /data/l
adb push /tmp/labels.txt /data/local/tmp
```
Run it, `adb shell "/data/local/tmp/label_image \ -m
/data/local/tmp/mobilenet_v1_1.0_224.tflite \ -i
/data/local/tmp/grace_hopper.bmp \ -l /data/local/tmp/labels.txt"` then you
should see something like the followings: `Loaded model
/data/local/tmp/mobilenet_v1_1.0_224.tflite resolved reporter INFO: Initialized
TensorFlow Lite runtime. invoked average time: 25.03 ms 0.907071: 653 military
uniform 0.0372416: 907 Windsor tie 0.00733753: 466 bulletproof vest 0.00592852:
458 bow tie 0.00414091: 514 cornet`
Run it,
```
adb shell "/data/local/tmp/label_image \
-m /data/local/tmp/mobilenet_v1_1.0_224.tflite \
-i /data/local/tmp/grace_hopper.bmp \
-l /data/local/tmp/labels.txt"
```
then you should see something like the followings:
```
Loaded model
/data/local/tmp/mobilenet_v1_1.0_224.tflite
resolved reporter
INFO: Initialized TensorFlow Lite runtime.
invoked
average time: 25.03 ms
0.907071: 653 military uniform
0.0372416: 907 Windsor tie
0.00733753: 466 bulletproof vest
0.00592852: 458 bow tie
0.00414091: 514 cornet
```
Run the model with NNAPI delegate (`-a 1`), `adb shell
"/data/local/tmp/label_image \ -m /data/local/tmp/mobilenet_v1_1.0_224.tflite \
-i /data/local/tmp/grace_hopper.bmp \ -l /data/local/tmp/labels.txt -a 1 -f 1"`
then you should see something like the followings: `Loaded model
/data/local/tmp/mobilenet_v1_1.0_224.tflite resolved reporter INFO: Initialized
TensorFlow Lite runtime. INFO: Created TensorFlow Lite delegate for NNAPI.
Applied NNAPI delegate.invoked average time: 10.348 ms 0.905401: 653 military
uniform 0.0379589: 907 Windsor tie 0.00735866: 466 bulletproof vest 0.00605307:
458 bow tie 0.00422573: 514 cornet`
Run the model with NNAPI delegate (`-a 1`),
```
adb shell "/data/local/tmp/label_image \
-m /data/local/tmp/mobilenet_v1_1.0_224.tflite \
-i /data/local/tmp/grace_hopper.bmp \
-l /data/local/tmp/labels.txt -a 1 -f 1"
```
then you should see something like the followings:
```
Loaded model /data/local/tmp/mobilenet_v1_1.0_224.tflite
resolved reporter
INFO: Initialized TensorFlow Lite runtime.
INFO: Created TensorFlow Lite delegate for NNAPI.
Applied NNAPI delegate.
invoked average time:10.348 ms
0.905401: 653 military uniform
0.0379589: 907 Windsor tie
0.00735866: 466 bulletproof vest
0.00605307: 458 bow tie
0.00422573: 514 cornet
```
To run a model with the Hexagon Delegate, assuming we have followed the
[Hexagon Delegate Guide](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/g3doc/performance/hexagon_delegate.md)
and installed Hexagon libraries in `/data/local/tmp`. Run it `adb shell
"/data/local/tmp/label_image \ -m
/data/local/tmp/mobilenet_v1_1.0_224_quant.tflite \ -i
/data/local/tmp/grace_hopper.bmp \ -l /data/local/tmp/labels.txt -j 1"` then you
should see something like the followings: ``` Loaded model
/data/local/tmp/mobilenet_v1_1.0_224_quant.tflite resolved reporter INFO:
Initialized TensorFlow Lite runtime. INFO: Created TensorFlow Lite delegate for
Hexagon. INFO: Hexagon delegate: 31 nodes delegated out of 31 nodes.
and installed Hexagon libraries in `/data/local/tmp`. Run it
```
adb shell "/data/local/tmp/label_image \
-m /data/local/tmp/mobilenet_v1_1.0_224_quant.tflite \
-i /data/local/tmp/grace_hopper.bmp \
-l /data/local/tmp/labels.txt -j 1"
```
then you should see something like the followings:
```
Loaded model /data/local/tmp/mobilenet_v1_1.0_224_quant.tflite
resolved reporter
INFO: Initialized TensorFlow Lite runtime.
INFO: Created TensorFlow Lite delegate for Hexagon.
INFO: Hexagon delegate: 31 nodes delegated out of 31 nodes.
remote_handle_control available and used Applied Hexagon delegate.invoked
average time: 8.307 ms 0.729412: 653 military uniform 0.0980392: 907 Windsor tie
0.0313726: 466 bulletproof vest 0.0313726: 458 bow tie 0.0117647: 700 panpipe
remote_handle_control available and used
Applied Hexagon delegate.invoked
average time: 8.307 ms
0.729412: 653 military uniform
0.0980392: 907 Windsor tie
0.0313726: 466 bulletproof vest
0.0313726: 458 bow tie
0.0117647: 700 panpipe
```
Run the model with the XNNPACK delegate (`-x 1`),
```
adb shell "/data/local/tmp/label_image \
-m /data/local/tmp/mobilenet_v1_1.0_224.tflite \
-i /data/local/tmp/grace_hopper.bmp \
-l /data/local/tmp/labels.txt -x 1"
```
then you should see something like the followings:
```
Loaded model /data/local/tmp/mobilenet_v1_1.0_224.tflite
resolved reporter
INFO: Initialized TensorFlow Lite runtime.
Applied XNNPACK delegate.invoked
average time: 11.0237 ms
0.90707: 653 military uniform
0.0372418: 907 Windsor tie
0.0073376: 466 bulletproof vest
0.00592856: 458 bow tie
0.00414093: 514 cornet
```
See the `label_image.cc` source code for other command line options.

View File

@ -37,6 +37,7 @@ limitations under the License.
#include "absl/memory/memory.h"
#include "tensorflow/lite/delegates/nnapi/nnapi_delegate.h"
#include "tensorflow/lite/delegates/xnnpack/xnnpack_delegate.h"
#include "tensorflow/lite/examples/label_image/bitmap_helpers.h"
#include "tensorflow/lite/examples/label_image/get_top_n.h"
#include "tensorflow/lite/kernels/register.h"
@ -101,6 +102,19 @@ TfLiteDelegatePtrMap GetDelegates(Settings* s) {
}
}
if (s->xnnpack_delegate) {
TfLiteXNNPackDelegateOptions xnnpack_options =
TfLiteXNNPackDelegateOptionsDefault();
xnnpack_options.num_threads = s->number_of_threads;
auto delegate = evaluation::CreateXNNPACKDelegate(&xnnpack_options);
if (!delegate) {
LOG(INFO) << "XNNPACK acceleration is unsupported on this platform.";
} else {
delegates.emplace("XNNPACK", std::move(delegate));
}
}
return delegates;
}
@ -360,6 +374,7 @@ void display_usage() {
<< "--threads, -t: number of threads\n"
<< "--verbose, -v: [0|1] print more information\n"
<< "--warmup_runs, -w: number of warmup runs\n"
<< "--xnnpack_delegate, -x: xnnpack delegate\n"
<< "\n";
}
@ -386,13 +401,14 @@ int Main(int argc, char** argv) {
{"warmup_runs", required_argument, nullptr, 'w'},
{"gl_backend", required_argument, nullptr, 'g'},
{"hexagon_delegate", required_argument, nullptr, 'j'},
{"xnnpack_delegate", required_argument, nullptr, 'x'},
{nullptr, 0, nullptr, 0}};
/* getopt_long stores the option index here. */
int option_index = 0;
c = getopt_long(argc, argv,
"a:b:c:d:e:f:g:i:j:l:m:p:r:s:t:v:w:", long_options,
"a:b:c:d:e:f:g:i:j:l:m:p:r:s:t:v:w:x:", long_options,
&option_index);
/* Detect the end of the options. */
@ -460,6 +476,9 @@ int Main(int argc, char** argv) {
s.number_of_warmup_runs =
strtol(optarg, nullptr, 10); // NOLINT(runtime/deprecated_fn)
break;
case 'x':
s.xnnpack_delegate = optarg;
break;
case 'h':
case '?':
/* getopt_long already printed an error message. */

View File

@ -31,6 +31,7 @@ struct Settings {
bool allow_fp16 = false;
bool gl_backend = false;
bool hexagon_delegate = false;
bool xnnpack_delegate = false;
int loop_count = 1;
float input_mean = 127.5f;
float input_std = 127.5f;

View File

@ -100,6 +100,8 @@ MACH_ARM_SRCS = [
cc_library(
name = "cpuinfo_impl",
srcs = select({
":linux_aarch64": COMMON_SRCS + ARM_SRCS + LINUX_SRCS + LINUX_ARM64_SRCS,
":linux_arm": COMMON_SRCS + ARM_SRCS + LINUX_SRCS + LINUX_ARM32_SRCS,
":linux_x86_64": COMMON_SRCS + X86_SRCS + LINUX_SRCS + LINUX_X86_SRCS,
":macos_x86_64": COMMON_SRCS + X86_SRCS + MACH_SRCS + MACH_X86_SRCS,
":android_armv7": COMMON_SRCS + ARM_SRCS + LINUX_SRCS + LINUX_ARM32_SRCS + ANDROID_ARM_SRCS,
@ -158,6 +160,18 @@ cc_library(
############################# Build configurations #############################
config_setting(
name = "linux_aarch64",
values = {"cpu": "aarch64"},
visibility = ["//visibility:public"],
)
config_setting(
name = "linux_arm",
values = {"cpu": "arm"},
visibility = ["//visibility:public"],
)
config_setting(
name = "linux_x86_64",
values = {"cpu": "k8"},