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体验新版 GitCode,发现更多精彩内容 >>
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9ebc2ecb
编写于
11月 14, 2017
作者:
L
liuqi
浏览文件
操作
浏览文件
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电子邮件补丁
差异文件
Add icnet validation script for auto test.
上级
61715ab7
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
200 addition
and
7 deletion
+200
-7
mace/kernels/opencl/cl/conv_2d_1x1.cl
mace/kernels/opencl/cl/conv_2d_1x1.cl
+5
-7
tools/validate_icnet.py
tools/validate_icnet.py
+124
-0
tools/validate_icnet.sh
tools/validate_icnet.sh
+71
-0
未找到文件。
mace/kernels/opencl/cl/conv_2d_1x1.cl
浏览文件 @
9ebc2ecb
...
...
@@ -49,13 +49,11 @@ __kernel void conv_2d_1x1_v2(__global const float *input, /* n, c, h, w */
int
out_chan_len
=
out_chan_end
-
out_chan_begin
;
int
pixel_len
=
out_pixel_end
-
out_pixel_begin
;
if
(
bias
!=
NULL
)
{
for
(
int
out_chan
=
out_chan_begin
; out_chan < out_chan_end; ++out_chan) {
float
*output_ptr
=
output_base
+
out_chan
*
pixel_num
;
float
bias_value
=
bias[out_chan]
;
for
(
int
p
=
0
; p < pixel_len; ++p) {
output_ptr[p]
=
bias_value
;
}
for
(
int
out_chan
=
out_chan_begin
; out_chan < out_chan_end; ++out_chan) {
float
*output_ptr
=
output_base
+
out_chan
*
pixel_num
;
float
bias_value
=
bias
==
NULL
?
0
:
bias[out_chan]
;
for
(
int
p
=
0
; p < pixel_len; ++p) {
output_ptr[p]
=
bias_value
;
}
}
...
...
tools/validate_icnet.py
0 → 100644
浏览文件 @
9ebc2ecb
import
argparse
import
sys
import
tensorflow
as
tf
import
numpy
as
np
from
tensorflow
import
gfile
# Validation Flow:
# 1. Generate input data
# python validate_icnet.py --generate_data 1 \
# --random_seed 1
# 2. Use mace_run to run icnet on phone.
# 3. adb pull the result.
# 4. Compare output data of mace and tf
# python validate_icnet.py --model_file opt_icnet.pb \
# --tf_input_file input_file \
# --mace_out_file icnet.out
def
generate_data
(
shape
):
np
.
random
.
seed
(
FLAGS
.
random_seed
)
data
=
np
.
random
.
random
(
shape
)
print
FLAGS
.
tf_input_file
data
.
astype
(
np
.
float32
).
tofile
(
FLAGS
.
tf_input_file
)
mace_data
=
np
.
transpose
(
data
,
axes
=
(
2
,
0
,
1
))
mace_data
.
astype
(
np
.
float32
).
tofile
(
FLAGS
.
mace_input_file
)
print
"Generate input file done."
def
load_data
(
file
):
return
np
.
fromfile
(
file
=
file
,
dtype
=
np
.
float32
)
def
valid_output
(
out_shape
,
mace_out_file
,
tf_out_value
):
mace_out_value
=
load_data
(
mace_out_file
)
mace_out_value
=
mace_out_value
.
reshape
(
out_shape
)
tf_out_data_t
=
np
.
transpose
(
tf_out_value
,
axes
=
(
0
,
3
,
1
,
2
))
res
=
np
.
allclose
(
mace_out_value
,
tf_out_data_t
,
rtol
=
0
,
atol
=
1e-5
)
print
'Passed! Haha'
if
res
else
'Failed! Oops'
def
run_model
(
input_shape
):
if
not
gfile
.
Exists
(
FLAGS
.
model_file
):
print
(
"Input graph file '"
+
FLAGS
.
model_file
+
"' does not exist!"
)
return
-
1
input_graph_def
=
tf
.
GraphDef
()
with
gfile
.
Open
(
FLAGS
.
model_file
,
"rb"
)
as
f
:
data
=
f
.
read
()
input_graph_def
.
ParseFromString
(
data
)
tf
.
import_graph_def
(
input_graph_def
,
name
=
""
)
with
tf
.
Session
()
as
session
:
with
session
.
graph
.
as_default
()
as
graph
:
tf
.
import_graph_def
(
input_graph_def
,
name
=
""
)
input_node
=
graph
.
get_tensor_by_name
(
'input_node:0'
)
output_node
=
graph
.
get_tensor_by_name
(
'output_node:0'
)
input_value
=
load_data
(
FLAGS
.
tf_input_file
)
input_value
=
input_value
.
reshape
(
input_shape
)
output_value
=
session
.
run
(
output_node
,
feed_dict
=
{
input_node
:
[
input_value
]})
return
output_value
def
main
(
unused_args
):
input_shape
=
[
int
(
x
)
for
x
in
FLAGS
.
input_shape
.
split
(
','
)]
output_shape
=
[
int
(
x
)
for
x
in
FLAGS
.
output_shape
.
split
(
','
)]
if
FLAGS
.
generate_data
:
generate_data
(
input_shape
)
else
:
output_value
=
run_model
(
input_shape
)
valid_output
(
output_shape
,
FLAGS
.
mace_out_file
,
output_value
)
def
parse_args
():
"""Parses command line arguments."""
parser
=
argparse
.
ArgumentParser
()
parser
.
register
(
"type"
,
"bool"
,
lambda
v
:
v
.
lower
()
==
"true"
)
parser
.
add_argument
(
"--model_file"
,
type
=
str
,
default
=
""
,
help
=
"TensorFlow
\'
GraphDef
\'
file to load."
)
parser
.
add_argument
(
"--tf_input_file"
,
type
=
str
,
default
=
""
,
help
=
"tensorflow input data to load."
)
parser
.
add_argument
(
"--mace_input_file"
,
type
=
str
,
default
=
""
,
help
=
"mace input data to load."
)
parser
.
add_argument
(
"--mace_out_file"
,
type
=
str
,
default
=
""
,
help
=
"mace output file to load."
)
parser
.
add_argument
(
"--input_shape"
,
type
=
str
,
default
=
"480,480,3"
,
help
=
"input shape."
)
parser
.
add_argument
(
"--output_shape"
,
type
=
str
,
default
=
"1,2,480,480"
,
help
=
"output shape."
)
parser
.
add_argument
(
"--generate_data"
,
type
=
'bool'
,
default
=
"false"
,
help
=
"Random seed for generate test case."
)
parser
.
add_argument
(
"--random_seed"
,
type
=
int
,
default
=
"0"
,
help
=
"Random seed for generate test case."
)
return
parser
.
parse_known_args
()
if
__name__
==
'__main__'
:
FLAGS
,
unparsed
=
parse_args
()
main
(
unused_args
=
[
sys
.
argv
[
0
]]
+
unparsed
)
tools/validate_icnet.sh
0 → 100644
浏览文件 @
9ebc2ecb
#!/bin/bash
# Must run at root dir of mace project.
set
-e
Usage
()
{
echo
'Usage: bash tools/validate_icnet.sh tf_model_file'
}
if
[
$#
!=
1
]
;
then
Usage
exit
-1
fi
TF_MODEL_FILE_PATH
=
$1
MODEL_DIR
=
$(
dirname
${
TF_MODEL_FILE_PATH
}
)
MACE_MODEL_NAME
=
'mace_model.pb'
TF_INPUT_FILE_NAME
=
'tf_model_input'
MACE_INPUT_FILE_NAME
=
'mace_model_input'
OUTPUT_FILE_NAME
=
'icnet.out'
PHONE_DATA_DIR
=
"/data/local/tmp/
${
MACE_MODEL_NAME
}
"
KERNEL_DIR
=
"
${
PHONE_DATA_DIR
}
/cl/"
# Step 1: convert tf model to mace model
echo
"Step 1: convert tf model to mace model"
bazel build //mace/python/tools:tf_converter
bazel-bin/mace/python/tools/tf_converter
--input
=
${
TF_MODEL_FILE_PATH
}
--output
=
${
MODEL_DIR
}
/
${
MACE_MODEL_NAME
}
# Step 2: Generate input data
echo
"Step 2: Generate input data"
python tools/validate_icnet.py
--generate_data
true
--random_seed
1
\
--mace_input_file
${
MODEL_DIR
}
/
${
MACE_INPUT_FILE_NAME
}
--tf_input_file
${
MODEL_DIR
}
/
${
TF_INPUT_FILE_NAME
}
# Step 3: Run model on the phone
echo
"Step 3: Run model on the phone"
bazel build
-c
opt
--strip
always mace/examples:mace_run
\
--crosstool_top
=
//external:android/crosstool
\
--host_crosstool_top
=
@bazel_tools//tools/cpp:toolchain
\
--cpu
=
arm64-v8a
adb shell
"mkdir -p
${
PHONE_DATA_DIR
}
"
adb shell
"mkdir -p
${
KERNEL_DIR
}
"
adb push mace/kernels/opencl/cl/
*
${
KERNEL_DIR
}
adb push
${
MODEL_DIR
}
/
${
MACE_MODEL_NAME
}
${
PHONE_DATA_DIR
}
adb push
${
MODEL_DIR
}
/
${
MACE_INPUT_FILE_NAME
}
${
PHONE_DATA_DIR
}
adb push bazel-bin/mace/examples/mace_run
${
PHONE_DATA_DIR
}
num_threads
=
${
1
:-
1
}
adb shell
MACE_RUN_PARAMETER_PATH
=
${
PHONE_DATA_DIR
}
/mace_run.config
\
MACE_KERNEL_PATH
=
$KERNEL_DIR
\
OMP_NUM_THREADS
=
$num_threads
\
${
PHONE_DATA_DIR
}
/mace_run
\
--model
=
${
PHONE_DATA_DIR
}
/
${
MACE_MODEL_NAME
}
\
--input
=
input_node
\
--output
=
icnet/Conv_11/BatchNorm/batchnorm/add_1
\
--input_shape
=
1,3,480,480
\
--input_file
=
${
PHONE_DATA_DIR
}
/
${
MACE_INPUT_FILE_NAME
}
\
--output_file
=
${
PHONE_DATA_DIR
}
/
${
OUTPUT_FILE_NAME
}
\
--device
=
OPENCL
# Step 4: pull the mace run result.
echo
"Step 4: pull the mace run result."
adb pull
${
PHONE_DATA_DIR
}
/
${
OUTPUT_FILE_NAME
}
${
MODEL_DIR
}
# Step 5: validate the result
echo
"Step 5: validate the result"
python tools/validate_icnet.py
--model_file
${
TF_MODEL_FILE_PATH
}
\
--tf_input_file
${
MODEL_DIR
}
/
${
TF_INPUT_FILE_NAME
}
\
--mace_out_file
${
MODEL_DIR
}
/
${
OUTPUT_FILE_NAME
}
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