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5b85f3dc
编写于
4月 06, 2022
作者:
A
Allen Guo
提交者:
GitHub
4月 06, 2022
浏览文件
操作
浏览文件
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电子邮件补丁
差异文件
[IPU] add more ipu UTs (#41176)
* add ipu uts * fix ut * split PR * fix ut * rm ut
上级
e9e68c36
变更
7
隐藏空白更改
内联
并排
Showing
7 changed file
with
799 addition
and
1 deletion
+799
-1
python/paddle/fluid/tests/unittests/ipu/test_cast_op_ipu.py
python/paddle/fluid/tests/unittests/ipu/test_cast_op_ipu.py
+99
-0
python/paddle/fluid/tests/unittests/ipu/test_eval_model_ipu.py
...n/paddle/fluid/tests/unittests/ipu/test_eval_model_ipu.py
+126
-0
python/paddle/fluid/tests/unittests/ipu/test_fp16_support_ipu.py
...paddle/fluid/tests/unittests/ipu/test_fp16_support_ipu.py
+211
-0
python/paddle/fluid/tests/unittests/ipu/test_gradient_clip_ipu.py
...addle/fluid/tests/unittests/ipu/test_gradient_clip_ipu.py
+140
-0
python/paddle/fluid/tests/unittests/ipu/test_ipu_shard_api.py
...on/paddle/fluid/tests/unittests/ipu/test_ipu_shard_api.py
+111
-0
python/paddle/fluid/tests/unittests/ipu/test_matmul_serilize_ipu.py
...dle/fluid/tests/unittests/ipu/test_matmul_serilize_ipu.py
+109
-0
python/paddle/fluid/tests/unittests/ipu/test_optimizer_ipu.py
...on/paddle/fluid/tests/unittests/ipu/test_optimizer_ipu.py
+3
-1
未找到文件。
python/paddle/fluid/tests/unittests/ipu/test_cast_op_ipu.py
浏览文件 @
5b85f3dc
...
...
@@ -94,6 +94,105 @@ class TestBase(IPUOpTest):
self
.
assertTrue
(
res0
.
shape
==
res1
.
shape
)
class
TestEnableFp16
(
TestBase
):
def
set_atol
(
self
):
self
.
atol
=
1e-10
def
set_data_feed
(
self
):
self
.
feed
=
{
"x"
:
np
.
array
([
1
,
200
,
3000
,
40000
]).
astype
(
'int32'
),
}
def
set_op_attrs
(
self
):
self
.
attrs
=
{}
self
.
attrs
[
'dtype'
]
=
'float32'
def
_test_base
(
self
,
run_ipu
=
True
):
scope
=
paddle
.
static
.
Scope
()
main_prog
=
paddle
.
static
.
Program
()
startup_prog
=
paddle
.
static
.
Program
()
main_prog
.
random_seed
=
self
.
SEED
startup_prog
.
random_seed
=
self
.
SEED
with
paddle
.
static
.
scope_guard
(
scope
):
with
paddle
.
static
.
program_guard
(
main_prog
,
startup_prog
):
x
=
paddle
.
static
.
data
(
name
=
self
.
feed_list
[
0
],
shape
=
self
.
feed_shape
[
0
],
dtype
=
self
.
feed_dtype
[
0
])
out
=
paddle
.
cast
(
x
,
**
self
.
attrs
)
fetch_list
=
[
out
.
name
]
if
run_ipu
:
place
=
paddle
.
IPUPlace
()
else
:
place
=
paddle
.
CPUPlace
()
exe
=
paddle
.
static
.
Executor
(
place
)
exe
.
run
(
startup_prog
)
if
run_ipu
:
feed_list
=
self
.
feed_list
ipu_strategy
=
paddle
.
static
.
IpuStrategy
()
ipu_strategy
.
set_graph_config
(
is_training
=
self
.
is_training
)
ipu_strategy
.
set_precision_config
(
enable_fp16
=
True
)
program
=
paddle
.
static
.
IpuCompiledProgram
(
main_prog
,
ipu_strategy
=
ipu_strategy
).
compile
(
feed_list
,
fetch_list
)
else
:
program
=
main_prog
result
=
exe
.
run
(
program
,
feed
=
self
.
feed
,
fetch_list
=
fetch_list
)
return
result
[
0
]
class
TestDisableTransferCast
(
TestEnableFp16
):
def
set_atol
(
self
):
self
.
atol
=
1e-10
def
set_data_feed
(
self
):
self
.
feed
=
{
"x"
:
np
.
array
([
1
,
200
,
3000
,
40000
]).
astype
(
'int32'
),
}
def
set_op_attrs
(
self
):
self
.
attrs
=
{}
self
.
attrs
[
'dtype'
]
=
'float32'
def
_test_base
(
self
,
run_ipu
=
True
):
scope
=
paddle
.
static
.
Scope
()
main_prog
=
paddle
.
static
.
Program
()
startup_prog
=
paddle
.
static
.
Program
()
main_prog
.
random_seed
=
self
.
SEED
startup_prog
.
random_seed
=
self
.
SEED
with
paddle
.
static
.
scope_guard
(
scope
):
with
paddle
.
static
.
program_guard
(
main_prog
,
startup_prog
):
x
=
paddle
.
static
.
data
(
name
=
self
.
feed_list
[
0
],
shape
=
self
.
feed_shape
[
0
],
dtype
=
self
.
feed_dtype
[
0
])
out
=
paddle
.
cast
(
x
,
**
self
.
attrs
)
fetch_list
=
[
out
.
name
]
if
run_ipu
:
place
=
paddle
.
IPUPlace
()
else
:
place
=
paddle
.
CPUPlace
()
exe
=
paddle
.
static
.
Executor
(
place
)
exe
.
run
(
startup_prog
)
if
run_ipu
:
feed_list
=
self
.
feed_list
ipu_strategy
=
paddle
.
static
.
IpuStrategy
()
ipu_strategy
.
set_graph_config
(
is_training
=
self
.
is_training
)
ipu_strategy
.
set_precision_config
(
enable_fp16
=
True
)
ipu_strategy
.
set_options
({
"transfer_cast_op"
:
False
})
program
=
paddle
.
static
.
IpuCompiledProgram
(
main_prog
,
ipu_strategy
=
ipu_strategy
).
compile
(
feed_list
,
fetch_list
)
else
:
program
=
main_prog
result
=
exe
.
run
(
program
,
feed
=
self
.
feed
,
fetch_list
=
fetch_list
)
return
result
[
0
]
class
TestCase2
(
TestBase
):
def
set_atol
(
self
):
self
.
atol
=
1e-10
...
...
python/paddle/fluid/tests/unittests/ipu/test_eval_model_ipu.py
0 → 100644
浏览文件 @
5b85f3dc
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import
unittest
import
numpy
as
np
import
paddle
import
paddle.static
from
paddle.fluid.tests.unittests.ipu.op_test_ipu
import
IPUOpTest
@
unittest
.
skipIf
(
not
paddle
.
is_compiled_with_ipu
(),
"core is not compiled with IPU"
)
class
TestBase
(
IPUOpTest
):
def
setUp
(
self
):
self
.
set_atol
()
self
.
set_data_feed
()
self
.
set_feed_attr
()
self
.
set_attrs
()
def
set_atol
(
self
):
self
.
atol
=
1e-4
def
set_data_feed
(
self
):
self
.
feed
=
{
"image"
:
np
.
random
.
uniform
(
size
=
[
1
,
3
,
10
,
10
]).
astype
(
'float32'
),
}
def
set_feed_attr
(
self
):
self
.
feed_shape
=
[
x
.
shape
for
x
in
self
.
feed
.
values
()]
self
.
feed_list
=
list
(
self
.
feed
.
keys
())
self
.
feed_dtype
=
[
x
.
dtype
for
x
in
self
.
feed
.
values
()]
def
set_attrs
(
self
):
self
.
attrs
=
{
"optimizer"
:
'lamb'
,
"weight_decay"
:
2.0
,
}
def
_test_optimizer
(
self
,
run_ipu
=
True
):
scope
=
paddle
.
static
.
Scope
()
main_prog
=
paddle
.
static
.
Program
()
startup_prog
=
paddle
.
static
.
Program
()
main_prog
.
random_seed
=
self
.
SEED
startup_prog
.
random_seed
=
self
.
SEED
np
.
random
.
seed
(
self
.
SEED
)
with
paddle
.
static
.
scope_guard
(
scope
):
with
paddle
.
static
.
program_guard
(
main_prog
,
startup_prog
):
image
=
paddle
.
static
.
data
(
name
=
'image'
,
shape
=
[
1
,
3
,
10
,
10
],
dtype
=
'float32'
)
conv1
=
paddle
.
static
.
nn
.
conv2d
(
image
,
num_filters
=
3
,
filter_size
=
3
,
bias_attr
=
False
)
loss
=
paddle
.
mean
(
conv1
)
weight_decay
=
self
.
attrs
[
'weight_decay'
]
opt
=
paddle
.
optimizer
.
SGD
(
learning_rate
=
1e-1
,
weight_decay
=
weight_decay
)
if
self
.
attrs
[
'optimizer'
]
==
'adam'
:
opt
=
paddle
.
optimizer
.
Adam
(
learning_rate
=
1e-1
,
weight_decay
=
weight_decay
)
elif
self
.
attrs
[
'optimizer'
]
==
'lamb'
:
opt
=
paddle
.
optimizer
.
Lamb
(
learning_rate
=
1e-1
,
lamb_weight_decay
=
weight_decay
)
opt
.
minimize
(
loss
)
if
run_ipu
:
place
=
paddle
.
IPUPlace
()
else
:
place
=
paddle
.
CPUPlace
()
exe
=
paddle
.
static
.
Executor
(
place
)
exe
.
run
(
startup_prog
)
if
run_ipu
:
feed_list
=
[
image
.
name
]
fetch_list
=
[
loss
.
name
]
ipu_strategy
=
paddle
.
static
.
IpuStrategy
()
ipu_strategy
.
set_graph_config
(
is_training
=
True
)
ipu_strategy
.
set_options
({
"runtime_options.enable_eval"
:
True
})
program
=
paddle
.
static
.
IpuCompiledProgram
(
main_prog
,
ipu_strategy
=
ipu_strategy
).
compile
(
feed_list
,
fetch_list
)
else
:
program
=
main_prog
result
=
[]
if
run_ipu
:
for
epoch
in
range
(
200
):
if
epoch
==
100
:
ipu_strategy
.
set_options
({
"runtime_options.enable_eval"
:
False
})
loss_res
=
exe
.
run
(
program
,
feed
=
self
.
feed
,
fetch_list
=
[
loss
])
result
.
append
(
loss_res
)
else
:
for
epoch
in
range
(
100
):
loss_res
=
exe
.
run
(
program
,
feed
=
self
.
feed
,
fetch_list
=
[
loss
])
result
.
append
(
loss_res
)
return
np
.
array
(
result
)
def
test
(
self
):
# cpu and ipu dimenstion mismatch, cpu:(100, 1, 1), ipu:(100, 1)
ipu_loss
=
self
.
_test_optimizer
(
True
).
flatten
()
cpu_loss
=
self
.
_test_optimizer
(
False
).
flatten
()
self
.
assertTrue
(
ipu_loss
[
0
]
==
ipu_loss
[
99
])
self
.
assertTrue
(
np
.
allclose
(
ipu_loss
[
100
:],
cpu_loss
,
atol
=
self
.
atol
))
if
__name__
==
"__main__"
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/ipu/test_fp16_support_ipu.py
0 → 100644
浏览文件 @
5b85f3dc
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import
unittest
import
numpy
as
np
import
paddle
import
paddle.fluid
as
fluid
import
paddle.static
from
paddle.fluid.tests.unittests.ipu.op_test_ipu
import
IPUOpTest
,
ExecutionMode
@
unittest
.
skipIf
(
not
paddle
.
is_compiled_with_ipu
(),
"core is not compiled with IPU"
)
class
TestBase
(
IPUOpTest
):
def
setUp
(
self
):
self
.
set_atol
()
self
.
set_training
()
self
.
set_data_feed
()
self
.
set_feed_attr
()
self
.
set_op_attrs
()
@
property
def
fp16_enabled
(
self
):
return
True
def
set_atol
(
self
):
self
.
atol
=
5e-6
self
.
rtol
=
1e-5
self
.
atol_fp16
=
1e-2
self
.
rtol_fp16
=
1e-3
def
set_data_feed
(
self
):
np_data
=
np
.
random
.
uniform
(
low
=-
1
,
high
=
1
,
size
=
[
1
,
3
,
100
,
100
])
self
.
feed_fp32
=
{
"x"
:
np_data
.
astype
(
'float32'
)}
self
.
feed_fp16
=
{
"x"
:
np_data
.
astype
(
'float16'
)}
def
set_feed_attr
(
self
):
self
.
feed_shape
=
[
x
.
shape
for
x
in
self
.
feed_fp32
.
values
()]
self
.
feed_list
=
list
(
self
.
feed_fp32
.
keys
())
self
.
feed_dtype
=
[
x
.
dtype
for
x
in
self
.
feed_fp32
.
values
()]
def
set_op_attrs
(
self
):
self
.
attrs
=
{}
def
_test_base
(
self
,
exec_mode
):
scope
=
fluid
.
core
.
Scope
()
main_prog
=
paddle
.
static
.
Program
()
startup_prog
=
paddle
.
static
.
Program
()
main_prog
.
random_seed
=
self
.
SEED
startup_prog
.
random_seed
=
self
.
SEED
with
fluid
.
scope_guard
(
scope
):
with
paddle
.
static
.
program_guard
(
main_prog
,
startup_prog
):
x
=
paddle
.
static
.
data
(
name
=
self
.
feed_list
[
0
],
shape
=
self
.
feed_shape
[
0
],
dtype
=
'float32'
)
conv1
=
paddle
.
static
.
nn
.
conv2d
(
x
,
num_filters
=
3
,
filter_size
=
3
,
bias_attr
=
False
)
conv2
=
paddle
.
static
.
nn
.
conv2d
(
x
,
num_filters
=
3
,
filter_size
=
3
,
bias_attr
=
False
)
add1
=
conv1
+
conv2
conv3
=
paddle
.
static
.
nn
.
conv2d
(
add1
,
num_filters
=
8
,
filter_size
=
8
,
bias_attr
=
False
)
out
=
paddle
.
fluid
.
layers
.
relu
(
conv3
,
**
self
.
attrs
)
fetch_list
=
[
out
.
name
]
if
exec_mode
==
ExecutionMode
.
CPU_FP32
:
place
=
paddle
.
CPUPlace
()
else
:
place
=
paddle
.
IPUPlace
()
exe
=
paddle
.
static
.
Executor
(
place
)
exe
.
run
(
startup_prog
)
if
exec_mode
!=
ExecutionMode
.
CPU_FP32
:
feed_list
=
self
.
feed_list
ipu_strategy
=
paddle
.
static
.
IpuStrategy
()
ipu_strategy
.
set_graph_config
(
is_training
=
self
.
is_training
)
if
exec_mode
==
ExecutionMode
.
IPU_POPART_FP16
:
ipu_strategy
.
set_precision_config
(
enable_fp16
=
True
)
program
=
paddle
.
static
.
IpuCompiledProgram
(
main_prog
,
ipu_strategy
=
ipu_strategy
).
compile
(
feed_list
,
fetch_list
)
else
:
program
=
main_prog
feed
=
self
.
feed_fp32
if
exec_mode
>
ExecutionMode
.
IPU_FP32
:
feed
=
self
.
feed_fp16
result
=
exe
.
run
(
program
,
feed
=
feed
,
fetch_list
=
fetch_list
)
return
result
[
0
]
def
test_base
(
self
):
output_dict
=
{}
for
mode
in
ExecutionMode
:
if
mode
>
ExecutionMode
.
IPU_FP32
and
not
self
.
fp16_enabled
:
break
output_dict
[
mode
]
=
self
.
_test_base
(
mode
).
flatten
()
self
.
check
(
output_dict
)
class
TestIntInput
(
IPUOpTest
):
def
setUp
(
self
):
self
.
set_atol
()
self
.
set_training
()
self
.
set_data_feed
()
self
.
set_feed_attr
()
self
.
set_op_attrs
()
@
property
def
fp16_enabled
(
self
):
return
True
def
set_data_feed
(
self
):
embedding
=
np
.
random
.
uniform
(
size
=
[
10
,
20
])
indice
=
np
.
array
([
1
,
3
,
5
]).
astype
(
np
.
int32
)
self
.
feed_fp32
=
{
"embedding"
:
embedding
.
astype
(
np
.
float32
),
"indice"
:
indice
,
}
self
.
feed_fp16
=
{
"embedding"
:
embedding
.
astype
(
np
.
float16
),
"indice"
:
indice
,
}
def
set_feed_attr
(
self
):
self
.
feed_shape
=
[
x
.
shape
for
x
in
self
.
feed_fp32
.
values
()]
self
.
feed_list
=
list
(
self
.
feed_fp32
.
keys
())
self
.
feed_dtype
=
[
x
.
dtype
for
x
in
self
.
feed_fp32
.
values
()]
def
set_op_attrs
(
self
):
self
.
attrs
=
{}
def
_test_base
(
self
,
exec_mode
):
scope
=
fluid
.
core
.
Scope
()
main_prog
=
paddle
.
static
.
Program
()
startup_prog
=
paddle
.
static
.
Program
()
main_prog
.
random_seed
=
self
.
SEED
startup_prog
.
random_seed
=
self
.
SEED
with
fluid
.
scope_guard
(
scope
):
with
paddle
.
static
.
program_guard
(
main_prog
,
startup_prog
):
x
=
paddle
.
static
.
data
(
name
=
self
.
feed_list
[
0
],
shape
=
self
.
feed_shape
[
0
],
dtype
=
'float32'
)
y
=
paddle
.
static
.
data
(
name
=
self
.
feed_list
[
1
],
shape
=
self
.
feed_shape
[
1
],
dtype
=
'int32'
)
out
=
paddle
.
fluid
.
layers
.
gather
(
x
,
index
=
y
)
fetch_list
=
[
out
.
name
]
if
exec_mode
==
ExecutionMode
.
CPU_FP32
:
place
=
paddle
.
CPUPlace
()
else
:
place
=
paddle
.
IPUPlace
()
exe
=
paddle
.
static
.
Executor
(
place
)
exe
.
run
(
startup_prog
)
if
exec_mode
!=
ExecutionMode
.
CPU_FP32
:
feed_list
=
self
.
feed_list
ipu_strategy
=
paddle
.
static
.
IpuStrategy
()
ipu_strategy
.
set_graph_config
(
is_training
=
self
.
is_training
)
if
exec_mode
==
ExecutionMode
.
IPU_POPART_FP16
:
ipu_strategy
.
set_precision_config
(
enable_fp16
=
True
)
program
=
paddle
.
static
.
IpuCompiledProgram
(
main_prog
,
ipu_strategy
=
ipu_strategy
).
compile
(
feed_list
,
fetch_list
)
else
:
program
=
main_prog
feed
=
self
.
feed_fp32
if
exec_mode
>
ExecutionMode
.
IPU_FP32
:
feed
=
self
.
feed_fp16
result
=
exe
.
run
(
program
,
feed
=
feed
,
fetch_list
=
fetch_list
)
return
np
.
array
(
result
)
def
test_base
(
self
):
output_dict
=
{}
for
mode
in
ExecutionMode
:
if
mode
>
ExecutionMode
.
IPU_FP32
and
not
self
.
fp16_enabled
:
break
output_dict
[
mode
]
=
self
.
_test_base
(
mode
).
flatten
()
self
.
check
(
output_dict
)
if
__name__
==
"__main__"
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/ipu/test_gradient_clip_ipu.py
0 → 100644
浏览文件 @
5b85f3dc
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import
unittest
import
numpy
as
np
import
paddle
import
paddle.static
from
paddle.fluid.tests.unittests.ipu.op_test_ipu
import
IPUOpTest
@
unittest
.
skipIf
(
not
paddle
.
is_compiled_with_ipu
(),
"core is not compiled with IPU"
)
class
TestBase
(
IPUOpTest
):
def
setUp
(
self
):
self
.
set_atol
()
self
.
set_data_feed
()
self
.
set_feed_attr
()
self
.
set_attrs
()
def
set_atol
(
self
):
self
.
atol
=
1e-6
def
set_data_feed
(
self
):
self
.
feed
=
{
"image"
:
np
.
random
.
uniform
(
size
=
[
1
,
3
,
10
,
10
]).
astype
(
'float32'
),
}
def
set_feed_attr
(
self
):
self
.
feed_shape
=
[
x
.
shape
for
x
in
self
.
feed
.
values
()]
self
.
feed_list
=
list
(
self
.
feed
.
keys
())
self
.
feed_dtype
=
[
x
.
dtype
for
x
in
self
.
feed
.
values
()]
def
set_attrs
(
self
):
self
.
attrs
=
{
"optimizer"
:
'sgd'
,
"weight_decay"
:
0.0
,
}
def
_test_optimizer
(
self
,
run_ipu
=
True
):
scope
=
paddle
.
static
.
Scope
()
main_prog
=
paddle
.
static
.
Program
()
startup_prog
=
paddle
.
static
.
Program
()
main_prog
.
random_seed
=
self
.
SEED
startup_prog
.
random_seed
=
self
.
SEED
np
.
random
.
seed
(
self
.
SEED
)
with
paddle
.
static
.
scope_guard
(
scope
):
with
paddle
.
static
.
program_guard
(
main_prog
,
startup_prog
):
image
=
paddle
.
static
.
data
(
name
=
'image'
,
shape
=
[
1
,
3
,
10
,
10
],
dtype
=
'float32'
)
conv1
=
paddle
.
static
.
nn
.
conv2d
(
image
,
num_filters
=
3
,
filter_size
=
3
,
bias_attr
=
False
)
loss
=
paddle
.
mean
(
conv1
)
weight_decay
=
self
.
attrs
[
'weight_decay'
]
# Only support ClipGradByGlobalNorm
clip
=
paddle
.
nn
.
ClipGradByGlobalNorm
(
clip_norm
=
1.0
)
if
self
.
attrs
[
'optimizer'
]
==
'sgd'
:
opt
=
paddle
.
optimizer
.
SGD
(
learning_rate
=
1e-1
,
weight_decay
=
weight_decay
,
grad_clip
=
clip
)
elif
self
.
attrs
[
'optimizer'
]
==
'adam'
:
opt
=
paddle
.
optimizer
.
Adam
(
learning_rate
=
1e-1
,
weight_decay
=
weight_decay
,
grad_clip
=
clip
)
elif
self
.
attrs
[
'optimizer'
]
==
'lamb'
:
opt
=
paddle
.
optimizer
.
Lamb
(
learning_rate
=
1e-1
,
lamb_weight_decay
=
weight_decay
,
grad_clip
=
clip
)
else
:
raise
ValueError
(
f
"Not supported optimizer
{
self
.
attrs
[
'optimizer'
]
}
for test"
)
opt
.
minimize
(
loss
)
if
run_ipu
:
place
=
paddle
.
IPUPlace
()
else
:
place
=
paddle
.
CPUPlace
()
exe
=
paddle
.
static
.
Executor
(
place
)
exe
.
run
(
startup_prog
)
if
run_ipu
:
feed_list
=
[
image
.
name
]
fetch_list
=
[
loss
.
name
]
ipu_strategy
=
paddle
.
static
.
IpuStrategy
()
ipu_strategy
.
set_graph_config
(
is_training
=
True
)
program
=
paddle
.
static
.
IpuCompiledProgram
(
main_prog
,
ipu_strategy
=
ipu_strategy
).
compile
(
feed_list
,
fetch_list
)
else
:
program
=
main_prog
result
=
[]
for
epoch
in
range
(
100
):
loss_res
=
exe
.
run
(
program
,
feed
=
self
.
feed
,
fetch_list
=
[
loss
])
result
.
append
(
loss_res
)
return
np
.
array
(
result
)
def
test
(
self
):
# cpu and ipu dimenstion mismatch, cpu:(100, 1, 1), ipu:(100, 1)
ipu_loss
=
self
.
_test_optimizer
(
True
).
flatten
()
cpu_loss
=
self
.
_test_optimizer
(
False
).
flatten
()
self
.
assertTrue
(
np
.
allclose
(
ipu_loss
,
cpu_loss
,
atol
=
self
.
atol
))
class
TestAdam
(
TestBase
):
def
set_attrs
(
self
):
self
.
attrs
=
{
"optimizer"
:
'adam'
,
"weight_decay"
:
0.0
,
}
class
TestLamb
(
TestBase
):
def
set_attrs
(
self
):
self
.
attrs
=
{
"optimizer"
:
'lamb'
,
"weight_decay"
:
0.1
,
}
if
__name__
==
"__main__"
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/ipu/test_ipu_shard_api.py
0 → 100644
浏览文件 @
5b85f3dc
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import
unittest
import
numpy
as
np
import
paddle
paddle
.
enable_static
()
@
unittest
.
skipIf
(
not
paddle
.
is_compiled_with_ipu
(),
"core is not compiled with IPU"
)
class
TestIpuShard
(
unittest
.
TestCase
):
def
_test
(
self
):
# build graph
a
=
paddle
.
static
.
data
(
name
=
'data'
,
shape
=
[
None
,
1
],
dtype
=
'int32'
)
b
=
a
+
2
# scale : scale * x + bias, ipu_index : no
with
paddle
.
static
.
ipu_shard_guard
(
index
=
1
):
c
=
b
+
1
# scale, ipu_index : 1
with
paddle
.
static
.
ipu_shard_guard
(
index
=
2
):
d
=
c
*
2
# scale, ipu_index : 2
with
paddle
.
static
.
ipu_shard_guard
(
index
=
3
):
e
=
d
+
3
# scale, ipu_index : 3
with
paddle
.
static
.
ipu_shard_guard
(
index
=
1
):
e
=
e
+
3
# scale, ipu_index : 1
with
paddle
.
static
.
ipu_shard_guard
(
index
=
2
):
e
=
e
+
3
# scale, ipu_index : 2
with
paddle
.
static
.
ipu_shard_guard
(
index
=
1
):
f
=
paddle
.
tensor
.
pow
(
e
,
2.0
)
# pow, ipu_index : 1
with
paddle
.
static
.
ipu_shard_guard
(
index
=
2
):
g
=
f
-
1
# scale, ipu_index : 2
h
=
g
+
1
# scale, ipu_index : no
ipu_index_list
=
[]
main_prog
=
paddle
.
static
.
default_main_program
()
for
op
in
main_prog
.
global_block
().
ops
:
if
op
.
desc
.
has_attr
(
"ipu_index"
):
ipu_index_list
.
append
(
op
.
desc
.
attr
(
"ipu_index"
))
return
ipu_index_list
def
test_ipu_shard
(
self
):
ipu_index_list
=
self
.
_test
()
expected_ipu_index_list
=
[
1
,
2
,
3
,
1
,
2
,
1
,
2
]
self
.
assertTrue
(
np
.
allclose
(
ipu_index_list
,
expected_ipu_index_list
,
atol
=
0
))
@
unittest
.
skipIf
(
not
paddle
.
is_compiled_with_ipu
(),
"core is not compiled with IPU"
)
class
TestIpuPipeline
(
unittest
.
TestCase
):
def
_test
(
self
):
# build graph
a
=
paddle
.
static
.
data
(
name
=
'data'
,
shape
=
[
None
,
1
],
dtype
=
'int32'
)
b
=
a
+
2
# scale : scale * x + bias, ipu_stage : no
with
paddle
.
static
.
ipu_shard_guard
(
stage
=
1
):
c
=
b
+
1
# scale, ipu_stage : 1
with
paddle
.
static
.
ipu_shard_guard
(
stage
=
2
):
d
=
c
*
2
# scale, ipu_stage : 2
with
paddle
.
static
.
ipu_shard_guard
(
stage
=
3
):
e
=
d
+
3
# scale, ipu_stage : 3
with
paddle
.
static
.
ipu_shard_guard
(
stage
=
1
):
e
=
e
+
3
# scale, ipu_stage : 1
with
paddle
.
static
.
ipu_shard_guard
(
stage
=
2
):
e
=
e
+
3
# scale, ipu_stage : 2
with
paddle
.
static
.
ipu_shard_guard
(
stage
=
1
):
f
=
paddle
.
tensor
.
pow
(
e
,
2.0
)
# pow, ipu_stage : 1
with
paddle
.
static
.
ipu_shard_guard
(
stage
=
2
):
g
=
f
-
1
# scale, ipu_stage : 2
h
=
g
+
1
# scale, ipu_stage : no
ipu_index_list
=
[]
main_prog
=
paddle
.
static
.
default_main_program
()
for
op
in
main_prog
.
global_block
().
ops
:
if
op
.
desc
.
has_attr
(
"ipu_stage"
):
ipu_index_list
.
append
(
op
.
desc
.
attr
(
"ipu_stage"
))
return
ipu_index_list
def
test_ipu_shard
(
self
):
ipu_index_list
=
self
.
_test
()
expected_ipu_index_list
=
[
1
,
2
,
3
,
1
,
2
,
1
,
2
]
self
.
assertTrue
(
np
.
allclose
(
ipu_index_list
,
expected_ipu_index_list
,
atol
=
0
))
if
__name__
==
"__main__"
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/ipu/test_matmul_serilize_ipu.py
0 → 100644
浏览文件 @
5b85f3dc
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import
unittest
import
numpy
as
np
import
paddle
import
paddle.static
from
paddle.fluid.tests.unittests.ipu.op_test_ipu
import
IPUOpTest
def
set_serialize_factor
(
serialize_factor
):
main_prog
=
paddle
.
static
.
default_main_program
()
op
=
main_prog
.
current_block
().
ops
[
-
1
]
op
.
_set_attr
(
'serialize_factor'
,
serialize_factor
)
@
unittest
.
skipIf
(
not
paddle
.
is_compiled_with_ipu
()
or
IPUOpTest
.
use_ipumodel
(),
"core is not compiled with IPU"
)
class
TestBase
(
IPUOpTest
):
def
setUp
(
self
):
self
.
set_atol
()
self
.
set_training
()
self
.
set_data_feed
()
self
.
set_feed_attr
()
self
.
set_op_attrs
()
def
set_data_feed
(
self
):
self
.
feed
=
{
"x"
:
np
.
random
.
uniform
(
size
=
[
2048
,
3072
]).
astype
(
'float32'
),
"y"
:
np
.
random
.
uniform
(
size
=
[
3072
,
2048
]).
astype
(
'float32'
),
}
def
set_feed_attr
(
self
):
self
.
feed_shape
=
[
x
.
shape
for
x
in
self
.
feed
.
values
()]
self
.
feed_list
=
list
(
self
.
feed
.
keys
())
self
.
feed_dtype
=
[
x
.
dtype
for
x
in
self
.
feed
.
values
()]
def
set_op_attrs
(
self
):
self
.
attrs
=
{
"transpose_x"
:
False
,
"transpose_y"
:
False
}
def
_test_base
(
self
,
run_ipu
=
True
):
scope
=
paddle
.
static
.
Scope
()
main_prog
=
paddle
.
static
.
Program
()
startup_prog
=
paddle
.
static
.
Program
()
main_prog
.
random_seed
=
self
.
SEED
startup_prog
.
random_seed
=
self
.
SEED
with
paddle
.
static
.
scope_guard
(
scope
):
with
paddle
.
static
.
program_guard
(
main_prog
,
startup_prog
):
x
=
paddle
.
static
.
data
(
name
=
self
.
feed_list
[
0
],
shape
=
self
.
feed_shape
[
0
],
dtype
=
self
.
feed_dtype
[
0
])
y
=
paddle
.
static
.
data
(
name
=
self
.
feed_list
[
1
],
shape
=
self
.
feed_shape
[
1
],
dtype
=
self
.
feed_dtype
[
1
])
# decrator maybe the best choice, but need to modify api
out
=
paddle
.
matmul
(
x
,
y
,
**
self
.
attrs
)
set_serialize_factor
(
4
)
fetch_list
=
[
out
.
name
]
if
run_ipu
:
place
=
paddle
.
IPUPlace
()
else
:
place
=
paddle
.
CPUPlace
()
exe
=
paddle
.
static
.
Executor
(
place
)
exe
.
run
(
startup_prog
)
if
run_ipu
:
feed_list
=
self
.
feed_list
ipu_strategy
=
paddle
.
static
.
IpuStrategy
()
ipu_strategy
.
set_graph_config
(
is_training
=
self
.
is_training
)
program
=
paddle
.
static
.
IpuCompiledProgram
(
main_prog
,
ipu_strategy
=
ipu_strategy
).
compile
(
feed_list
,
fetch_list
)
else
:
program
=
main_prog
result
=
exe
.
run
(
program
,
feed
=
self
.
feed
,
fetch_list
=
fetch_list
)
return
result
[
0
]
def
test_base
(
self
):
res0
=
self
.
_test_base
(
False
)
res1
=
self
.
_test_base
(
True
)
self
.
assertTrue
(
np
.
allclose
(
res0
.
flatten
(),
res1
.
flatten
(),
atol
=
self
.
atol
))
self
.
assertTrue
(
res0
.
shape
==
res1
.
shape
)
if
__name__
==
"__main__"
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/ipu/test_optimizer_ipu.py
浏览文件 @
5b85f3dc
...
...
@@ -90,7 +90,9 @@ class TestBase(IPUOpTest):
fetch_list
=
[
loss
.
name
]
ipu_strategy
=
paddle
.
static
.
IpuStrategy
()
ipu_strategy
.
set_graph_config
(
is_training
=
True
)
ipu_strategy
.
loss_scaling
=
self
.
attrs
[
"loss_scaling"
]
ipu_strategy
.
set_options
({
'loss_scaling'
:
self
.
attrs
[
"loss_scaling"
]
})
if
"use_no_bias_optimizer"
in
self
.
attrs
.
keys
():
ipu_strategy
.
set_options
({
"use_no_bias_optimizer"
:
...
...
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