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体验新版 GitCode,发现更多精彩内容 >>
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b8057515
编写于
9月 06, 2018
作者:
Q
Qiyang Min
提交者:
GitHub
9月 06, 2018
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差异文件
Merge pull request #13223 from velconia/open_python35_CI
Open python35 ci
上级
34e467dc
8059445f
变更
6
隐藏空白更改
内联
并排
Showing
6 changed file
with
43 addition
and
30 deletion
+43
-30
paddle/fluid/operators/fake_quantize_op.cu
paddle/fluid/operators/fake_quantize_op.cu
+2
-1
paddle/scripts/paddle_build.sh
paddle/scripts/paddle_build.sh
+2
-0
python/paddle/fluid/tests/unittests/dist_transformer.py
python/paddle/fluid/tests/unittests/dist_transformer.py
+20
-14
python/paddle/fluid/tests/unittests/test_prelu_op.py
python/paddle/fluid/tests/unittests/test_prelu_op.py
+13
-9
python/paddle/fluid/transpiler/details/program_utils.py
python/paddle/fluid/transpiler/details/program_utils.py
+1
-1
python/paddle/fluid/transpiler/distribute_transpiler.py
python/paddle/fluid/transpiler/distribute_transpiler.py
+5
-5
未找到文件。
paddle/fluid/operators/fake_quantize_op.cu
浏览文件 @
b8057515
...
...
@@ -119,7 +119,8 @@ struct FindRangeAbsMaxFunctor<platform::CUDADeviceContext, T> {
const
framework
::
Tensor
&
last_scale
,
const
framework
::
Tensor
&
iter
,
const
int
window_size
,
framework
::
Tensor
*
scales_arr
,
framework
::
Tensor
*
out_scale
)
{
auto
&
gpu_place
=
boost
::
get
<
platform
::
CUDAPlace
>
(
ctx
.
GetPlace
());
const
auto
gpu_place
=
boost
::
get
<
platform
::
CUDAPlace
>
(
ctx
.
GetPlace
());
T
*
scale_arr
=
scales_arr
->
mutable_data
<
T
>
(
gpu_place
);
T
*
out_scale_data
=
out_scale
->
mutable_data
<
T
>
(
gpu_place
);
...
...
paddle/scripts/paddle_build.sh
浏览文件 @
b8057515
...
...
@@ -115,6 +115,7 @@ function cmake_gen() {
-DWITH_FLUID_ONLY=
${
WITH_FLUID_ONLY
:-
OFF
}
-DCMAKE_EXPORT_COMPILE_COMMANDS=ON
-DWITH_CONTRIB=
${
WITH_CONTRIB
:-
ON
}
-DWITH_INFERENCE=
${
WITH_INFERENCE
:-
ON
}
-DWITH_ANAKIN=
${
WITH_ANAKIN
:-
OFF
}
-DPY_VERSION=
${
PY_VERSION
:-
2
.7
}
========================================
...
...
@@ -144,6 +145,7 @@ EOF
-DWITH_FLUID_ONLY
=
${
WITH_FLUID_ONLY
:-
OFF
}
\
-DCMAKE_EXPORT_COMPILE_COMMANDS
=
ON
\
-DWITH_CONTRIB
=
${
WITH_CONTRIB
:-
ON
}
\
-DWITH_INFERENCE
=
${
WITH_INFERENCE
:-
ON
}
\
-DWITH_ANAKIN
=
${
WITH_ANAKIN
:-
OFF
}
\
-DPY_VERSION
=
${
PY_VERSION
:-
2
.7
}
}
...
...
python/paddle/fluid/tests/unittests/dist_transformer.py
浏览文件 @
b8057515
...
...
@@ -36,6 +36,7 @@ import paddle.fluid as fluid
import
paddle.fluid.layers
as
layers
from
paddle.fluid
import
core
from
test_dist_base
import
TestDistRunnerBase
,
runtime_main
import
paddle.compat
as
cpt
from
paddle.compat
import
long_type
import
hashlib
...
...
@@ -315,8 +316,9 @@ def pad_batch_data(insts,
"""
return_list
=
[]
max_len
=
max
(
len
(
inst
)
for
inst
in
insts
)
num_token
=
reduce
(
lambda
x
,
y
:
x
+
y
,
[
len
(
inst
)
for
inst
in
insts
])
if
return_num_token
else
0
num_token
=
six
.
moves
.
reduce
(
lambda
x
,
y
:
x
+
y
,
[
len
(
inst
)
for
inst
in
insts
])
if
return_num_token
else
0
# Any token included in dict can be used to pad, since the paddings' loss
# will be masked out by weights and make no effect on parameter gradients.
inst_data
=
np
.
array
(
...
...
@@ -328,7 +330,7 @@ def pad_batch_data(insts,
return_list
+=
[
inst_weight
.
astype
(
"float32"
).
reshape
([
-
1
,
1
])]
else
:
# position data
inst_pos
=
np
.
array
([
range
(
1
,
len
(
inst
)
+
1
)
+
[
0
]
*
(
max_len
-
len
(
inst
))
list
(
range
(
1
,
len
(
inst
)
+
1
)
)
+
[
0
]
*
(
max_len
-
len
(
inst
))
for
inst
in
insts
])
return_list
+=
[
inst_pos
.
astype
(
"int64"
).
reshape
([
-
1
,
1
])]
...
...
@@ -385,10 +387,11 @@ def prepare_batch_input(insts, data_input_names, src_pad_idx, trg_pad_idx,
return_num_token
=
True
)
data_input_dict
=
dict
(
zip
(
data_input_names
,
[
src_word
,
src_pos
,
src_slf_attn_bias
,
trg_word
,
trg_pos
,
trg_slf_attn_bias
,
trg_src_attn_bias
,
lbl_word
,
lbl_weight
]))
list
(
zip
(
data_input_names
,
[
src_word
,
src_pos
,
src_slf_attn_bias
,
trg_word
,
trg_pos
,
trg_slf_attn_bias
,
trg_src_attn_bias
,
lbl_word
,
lbl_weight
])))
return
data_input_dict
,
np
.
asarray
([
num_token
],
dtype
=
"float32"
)
...
...
@@ -561,7 +564,7 @@ def train_loop(exe, train_progm, dev_count, sum_cost, avg_cost, lr_scheduler,
np
.
log
(
TrainTaskConfig
.
label_smooth_eps
/
(
ModelHyperParams
.
trg_vocab_size
-
1
)
+
1e-20
))
init
=
False
for
pass_id
in
xrange
(
TrainTaskConfig
.
pass_num
):
for
pass_id
in
six
.
moves
.
xrange
(
TrainTaskConfig
.
pass_num
):
pass_start_time
=
time
.
time
()
for
batch_id
,
data
in
enumerate
(
train_data
()):
if
batch_id
>=
5
:
...
...
@@ -587,11 +590,11 @@ def train_loop(exe, train_progm, dev_count, sum_cost, avg_cost, lr_scheduler,
ModelHyperParams
.
eos_idx
,
ModelHyperParams
.
n_head
,
ModelHyperParams
.
d_model
)
total_num_token
+=
num_token
feed_kv_pairs
=
data_input_dict
.
items
(
)
feed_kv_pairs
=
list
(
data_input_dict
.
items
()
)
if
TrainTaskConfig
.
local
:
feed_kv_pairs
+=
{
feed_kv_pairs
+=
list
(
{
lr_scheduler
.
learning_rate
.
name
:
lr_rate
}.
items
()
}.
items
()
)
feed_list
.
append
(
dict
(
feed_kv_pairs
))
if
not
init
:
...
...
@@ -873,6 +876,7 @@ class DataReader(object):
f
=
tarfile
.
open
(
fpaths
[
0
],
"r"
)
for
line
in
f
.
extractfile
(
tar_fname
):
line
=
cpt
.
to_text
(
line
)
fields
=
line
.
strip
(
"
\n
"
).
split
(
self
.
_field_delimiter
)
if
(
not
self
.
_only_src
and
len
(
fields
)
==
2
)
or
(
self
.
_only_src
and
len
(
fields
)
==
1
):
...
...
@@ -882,8 +886,9 @@ class DataReader(object):
if
not
os
.
path
.
isfile
(
fpath
):
raise
IOError
(
"Invalid file: %s"
%
fpath
)
with
open
(
fpath
,
"r"
)
as
f
:
with
open
(
fpath
,
"r
b
"
)
as
f
:
for
line
in
f
:
line
=
cpt
.
to_text
(
line
)
fields
=
line
.
strip
(
"
\n
"
).
split
(
self
.
_field_delimiter
)
if
(
not
self
.
_only_src
and
len
(
fields
)
==
2
)
or
(
self
.
_only_src
and
len
(
fields
)
==
1
):
...
...
@@ -892,8 +897,9 @@ class DataReader(object):
@
staticmethod
def
load_dict
(
dict_path
,
reverse
=
False
):
word_dict
=
{}
with
open
(
dict_path
,
"r"
)
as
fdict
:
with
open
(
dict_path
,
"r
b
"
)
as
fdict
:
for
idx
,
line
in
enumerate
(
fdict
):
line
=
cpt
.
to_text
(
line
)
if
reverse
:
word_dict
[
idx
]
=
line
.
strip
(
"
\n
"
)
else
:
...
...
@@ -1034,7 +1040,7 @@ def multi_head_attention(queries,
# size of the input as the output dimension size.
return
layers
.
reshape
(
x
=
trans_x
,
shape
=
map
(
int
,
[
0
,
0
,
trans_x
.
shape
[
2
]
*
trans_x
.
shape
[
3
]]
))
shape
=
list
(
map
(
int
,
[
0
,
0
,
trans_x
.
shape
[
2
]
*
trans_x
.
shape
[
3
]])
))
def
scaled_dot_product_attention
(
q
,
k
,
v
,
attn_bias
,
d_model
,
dropout_rate
):
"""
...
...
python/paddle/fluid/tests/unittests/test_prelu_op.py
浏览文件 @
b8057515
...
...
@@ -16,6 +16,7 @@ from __future__ import print_function
import
unittest
import
numpy
as
np
import
six
from
op_test
import
OpTest
...
...
@@ -62,17 +63,20 @@ class PReluTest(OpTest):
# TODO(minqiyang): Resume these test cases after fixing Python3 CI job issues
# class TestCase1(PReluTest):
# def initTestCase(self):
# self.attrs = {'mode': "all"}
if
six
.
PY2
:
# class TestCase2(PReluTest):
# def initTestCase(self):
# self.attrs = {'mode': "channel"}
class
TestCase1
(
PReluTest
):
def
initTestCase
(
self
):
self
.
attrs
=
{
'mode'
:
"all"
}
class
TestCase2
(
PReluTest
):
def
initTestCase
(
self
):
self
.
attrs
=
{
'mode'
:
"channel"
}
class
TestCase3
(
PReluTest
):
def
initTestCase
(
self
):
self
.
attrs
=
{
'mode'
:
"element"
}
# class TestCase3(PReluTest):
# def initTestCase(self):
# self.attrs = {'mode': "element"}
if
__name__
==
"__main__"
:
unittest
.
main
()
python/paddle/fluid/transpiler/details/program_utils.py
浏览文件 @
b8057515
...
...
@@ -153,7 +153,7 @@ def block_to_code(block, block_idx):
indent
+=
1
# sort all vars
all_vars
=
sorted
(
block
.
vars
.
iteritems
(
),
key
=
lambda
x
:
x
[
0
])
all_vars
=
sorted
(
six
.
iteritems
(
block
.
vars
),
key
=
lambda
x
:
x
[
0
])
for
var
in
all_vars
:
print
(
"{}{}"
.
format
(
get_indent_space
(
indent
),
variable_to_code
(
var
[
1
])))
...
...
python/paddle/fluid/transpiler/distribute_transpiler.py
浏览文件 @
b8057515
...
...
@@ -300,7 +300,7 @@ class DistributeTranspiler(object):
input_deps
=
grad_name_to_send_dummy_out
.
values
()
program
.
global_block
().
append_op
(
type
=
"send_barrier"
,
inputs
=
{
"X"
:
input_deps
},
inputs
=
{
"X"
:
list
(
input_deps
)
},
outputs
=
{
"Out"
:
send_barrier_out
},
attrs
=
{
"endpoints"
:
pserver_endpoints
,
...
...
@@ -401,7 +401,7 @@ class DistributeTranspiler(object):
Args:
recv_vars (list): Variable list to recv for current trainer_id
eplist (list): A list of strings indicating
eplist (list): A list of strings indicating
Returns:
Program: trainer side startup program.
...
...
@@ -455,7 +455,7 @@ class DistributeTranspiler(object):
if
len
(
splited_var
)
<=
1
:
continue
# NOTE: if enable memory optimization, origin vars maybe removed.
if
startup_program
.
global_block
().
vars
.
has_key
(
varname
)
:
if
varname
in
startup_program
.
global_block
().
vars
:
orig_param
=
startup_program
.
global_block
().
vars
[
varname
]
else
:
origin_param_var
=
self
.
origin_program
.
global_block
().
vars
[
...
...
@@ -690,7 +690,7 @@ class DistributeTranspiler(object):
Args:
endpoint (str): current pserver endpoint.
Returns:
tuple: (main_program, startup_program), of type "Program"
"""
...
...
@@ -713,7 +713,7 @@ class DistributeTranspiler(object):
endpoint (str): current pserver endpoint.
pserver_program (Program): deprecated, call get_pserver_program first.
startup_program (Program): deprecated, should pass startup_program
when initalizing
when initalizing
Returns:
Program: parameter server side startup program.
...
...
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