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1ca791c7
编写于
12月 14, 2021
作者:
J
jianghaicheng
提交者:
GitHub
12月 14, 2021
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差异文件
ipu_commit_tests p5 (#38091)
上级
b5b9b0b9
变更
8
隐藏空白更改
内联
并排
Showing
8 changed file
with
947 addition
and
0 deletion
+947
-0
python/paddle/fluid/tests/unittests/ipu/test_gelu_op_ipu.py
python/paddle/fluid/tests/unittests/ipu/test_gelu_op_ipu.py
+113
-0
python/paddle/fluid/tests/unittests/ipu/test_groupnorm_op_ipu.py
...paddle/fluid/tests/unittests/ipu/test_groupnorm_op_ipu.py
+169
-0
python/paddle/fluid/tests/unittests/ipu/test_instancenorm_op_ipu.py
...dle/fluid/tests/unittests/ipu/test_instancenorm_op_ipu.py
+140
-0
python/paddle/fluid/tests/unittests/ipu/test_ipu_batchs_per_step_simple.py
...id/tests/unittests/ipu/test_ipu_batchs_per_step_simple.py
+90
-0
python/paddle/fluid/tests/unittests/ipu/test_ipu_fp16_support.py
...paddle/fluid/tests/unittests/ipu/test_ipu_fp16_support.py
+109
-0
python/paddle/fluid/tests/unittests/ipu/test_ipu_inference_model_io.py
.../fluid/tests/unittests/ipu/test_ipu_inference_model_io.py
+169
-0
python/paddle/fluid/tests/unittests/ipu/test_ipu_model_pipeline.py
...ddle/fluid/tests/unittests/ipu/test_ipu_model_pipeline.py
+86
-0
python/paddle/fluid/tests/unittests/ipu/test_ipu_pipeline.py
python/paddle/fluid/tests/unittests/ipu/test_ipu_pipeline.py
+71
-0
未找到文件。
python/paddle/fluid/tests/unittests/ipu/test_gelu_op_ipu.py
0 → 100644
浏览文件 @
1ca791c7
# Copyright (c) 2021 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.fluid.compiler
as
compiler
import
paddle.optimizer
import
paddle.static
from
paddle.fluid.tests.unittests.ipu.op_test_ipu
import
(
IPUOpTest
,
np_dtype_to_fluid_str
)
paddle
.
enable_static
()
@
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_feed
()
self
.
set_feed_attr
()
self
.
set_attrs
()
def
set_atol
(
self
):
self
.
atol
=
1e-3
def
set_feed
(
self
):
self
.
feed
=
{
"x"
:
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
=
[
np_dtype_to_fluid_str
(
x
.
dtype
)
for
x
in
self
.
feed
.
values
()
]
def
set_attrs
(
self
):
self
.
attrs
=
{
"approximate"
:
False
}
def
_test_base
(
self
,
run_ipu
=
True
):
scope
=
fluid
.
core
.
Scope
()
main_prog
=
paddle
.
static
.
Program
()
startup_prog
=
paddle
.
static
.
Program
()
SEED
=
self
.
SEED
main_prog
.
random_seed
=
SEED
startup_prog
.
random_seed
=
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
=
self
.
feed_dtype
[
0
])
out
=
paddle
.
fluid
.
layers
.
gelu
(
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
=
compiler
.
get_ipu_strategy
()
ipu_strategy
.
is_training
=
self
.
is_training
program
=
compiler
.
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
)
@
unittest
.
skip
(
'approximate=True is not supported'
)
class
TestCase1
(
TestBase
):
def
set_attrs
(
self
):
self
.
attrs
=
{
"approximate"
:
True
}
if
__name__
==
"__main__"
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/ipu/test_groupnorm_op_ipu.py
0 → 100644
浏览文件 @
1ca791c7
# Copyright (c) 2021 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.fluid.compiler
as
compiler
import
paddle.optimizer
import
paddle.static
from
paddle.fluid.tests.unittests.ipu.op_test_ipu
import
(
IPUOpTest
,
np_dtype_to_fluid_str
)
paddle
.
enable_static
()
@
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_feed
()
self
.
set_feed_attr
()
self
.
set_attrs
()
def
set_feed
(
self
):
self
.
feed
=
{
"x"
:
np
.
random
.
uniform
(
size
=
[
1
,
8
,
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
=
[
np_dtype_to_fluid_str
(
x
.
dtype
)
for
x
in
self
.
feed
.
values
()
]
def
set_attrs
(
self
):
self
.
attrs
=
{
"groups"
:
8
,
"epsilon"
:
1e-05
,
"data_layout"
:
'NCHW'
,
}
def
_test_base
(
self
,
run_ipu
=
True
):
scope
=
fluid
.
core
.
Scope
()
main_prog
=
paddle
.
static
.
Program
()
startup_prog
=
paddle
.
static
.
Program
()
SEED
=
self
.
SEED
main_prog
.
random_seed
=
SEED
startup_prog
.
random_seed
=
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
=
self
.
feed_dtype
[
0
])
if
self
.
is_training
:
ch
=
self
.
feed_shape
[
0
][
1
]
conv1
=
paddle
.
static
.
nn
.
conv2d
(
x
,
num_filters
=
ch
,
filter_size
=
3
,
bias_attr
=
False
)
scale
=
paddle
.
ParamAttr
(
trainable
=
True
)
bias
=
paddle
.
ParamAttr
(
trainable
=
True
)
out
=
paddle
.
fluid
.
layers
.
nn
.
group_norm
(
conv1
,
param_attr
=
scale
,
bias_attr
=
bias
,
**
self
.
attrs
)
else
:
scale
=
True
bias
=
True
out
=
paddle
.
fluid
.
layers
.
nn
.
group_norm
(
x
,
param_attr
=
scale
,
bias_attr
=
bias
,
**
self
.
attrs
)
if
self
.
is_training
:
loss
=
paddle
.
mean
(
out
)
adam
=
paddle
.
optimizer
.
Adam
(
learning_rate
=
1e-2
)
adam
.
minimize
(
loss
)
fetch_list
=
[
loss
.
name
]
else
:
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
=
compiler
.
get_ipu_strategy
()
ipu_strategy
.
is_training
=
self
.
is_training
program
=
compiler
.
IPUCompiledProgram
(
main_prog
,
ipu_strategy
=
ipu_strategy
).
compile
(
feed_list
,
fetch_list
)
else
:
program
=
main_prog
if
self
.
is_training
:
result
=
[]
for
_
in
range
(
self
.
epoch
):
loss_res
=
exe
.
run
(
program
,
feed
=
self
.
feed
,
fetch_list
=
fetch_list
)
result
.
append
(
loss_res
[
0
])
return
np
.
array
(
result
)
else
:
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
)
class
TestCase1
(
TestBase
):
def
set_attrs
(
self
):
self
.
attrs
=
{
"groups"
:
4
,
"epsilon"
:
1e-05
,
"data_layout"
:
'NCHW'
,
}
class
TestTrainCase1
(
TestBase
):
def
set_training
(
self
):
self
.
is_training
=
True
self
.
epoch
=
10
class
TestTrainCase2
(
TestBase
):
def
set_atol
(
self
):
self
.
atol
=
1e-3
def
set_attrs
(
self
):
self
.
attrs
=
{
"groups"
:
4
,
"epsilon"
:
1e-05
,
"data_layout"
:
'NCHW'
,
}
def
set_training
(
self
):
self
.
is_training
=
True
self
.
epoch
=
10
# not support `group_norm(x, param_attr=False, bias_attr=False, **self.attrs)`
if
__name__
==
"__main__"
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/ipu/test_instancenorm_op_ipu.py
0 → 100644
浏览文件 @
1ca791c7
# Copyright (c) 2021 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.fluid.compiler
as
compiler
import
paddle.optimizer
import
paddle.static
from
paddle.fluid.tests.unittests.ipu.op_test_ipu
import
(
IPUOpTest
,
np_dtype_to_fluid_str
)
paddle
.
enable_static
()
@
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_feed
()
self
.
set_feed_attr
()
self
.
set_attrs
()
def
set_feed
(
self
):
self
.
feed
=
{
"x"
:
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
=
[
np_dtype_to_fluid_str
(
x
.
dtype
)
for
x
in
self
.
feed
.
values
()
]
def
set_attrs
(
self
):
self
.
attrs
=
{
"epsilon"
:
1e-05
}
def
_test_base
(
self
,
run_ipu
=
True
):
scope
=
fluid
.
core
.
Scope
()
main_prog
=
paddle
.
static
.
Program
()
startup_prog
=
paddle
.
static
.
Program
()
SEED
=
self
.
SEED
main_prog
.
random_seed
=
SEED
startup_prog
.
random_seed
=
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
=
self
.
feed_dtype
[
0
])
if
self
.
is_training
:
ch
=
self
.
feed_shape
[
0
][
1
]
conv1
=
paddle
.
static
.
nn
.
conv2d
(
x
,
num_filters
=
ch
,
filter_size
=
3
,
bias_attr
=
False
)
scale
=
paddle
.
ParamAttr
(
trainable
=
True
)
bias
=
paddle
.
ParamAttr
(
trainable
=
True
)
out
=
paddle
.
fluid
.
layers
.
nn
.
instance_norm
(
conv1
,
param_attr
=
scale
,
bias_attr
=
bias
,
**
self
.
attrs
)
else
:
scale
=
True
bias
=
True
out
=
paddle
.
fluid
.
layers
.
nn
.
instance_norm
(
x
,
param_attr
=
scale
,
bias_attr
=
bias
,
**
self
.
attrs
)
if
self
.
is_training
:
loss
=
paddle
.
mean
(
out
)
adam
=
paddle
.
optimizer
.
Adam
(
learning_rate
=
1e-2
)
adam
.
minimize
(
loss
)
fetch_list
=
[
loss
.
name
]
else
:
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
=
compiler
.
get_ipu_strategy
()
ipu_strategy
.
is_training
=
self
.
is_training
program
=
compiler
.
IPUCompiledProgram
(
main_prog
,
ipu_strategy
=
ipu_strategy
).
compile
(
feed_list
,
fetch_list
)
else
:
program
=
main_prog
if
self
.
is_training
:
result
=
[]
for
_
in
range
(
self
.
epoch
):
loss_res
=
exe
.
run
(
program
,
feed
=
self
.
feed
,
fetch_list
=
fetch_list
)
result
.
append
(
loss_res
)
return
np
.
array
(
result
)
else
:
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
)
class
TestTrainCase1
(
TestBase
):
def
set_training
(
self
):
self
.
is_training
=
True
self
.
epoch
=
10
# not support `instance_norm(x, param_attr=False, bias_attr=False, **self.attrs)`
if
__name__
==
"__main__"
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/ipu/test_ipu_batchs_per_step_simple.py
0 → 100644
浏览文件 @
1ca791c7
# Copyright (c) 2021 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.
from
__future__
import
print_function
import
numpy
as
np
import
unittest
import
paddle
import
paddle.fluid
as
fluid
import
paddle.fluid.compiler
as
compiler
paddle
.
enable_static
()
SEED
=
2021
@
unittest
.
skipIf
(
not
paddle
.
is_compiled_with_ipu
(),
"core is not compiled with IPU"
)
class
TestFunc
(
unittest
.
TestCase
):
def
_test_func
(
self
,
run_ipu
=
True
):
scope
=
fluid
.
core
.
Scope
()
main_prog
=
paddle
.
static
.
Program
()
startup_prog
=
paddle
.
static
.
Program
()
main_prog
.
random_seed
=
SEED
startup_prog
.
random_seed
=
SEED
np
.
random
.
seed
(
SEED
)
bps
=
5
n
=
1
if
run_ipu
else
-
1
c
,
h
,
w
=
3
,
10
,
10
np_image
=
np
.
random
.
uniform
(
size
=
[
1
*
bps
,
c
,
h
,
w
]).
astype
(
np
.
float32
)
with
fluid
.
scope_guard
(
scope
):
with
paddle
.
static
.
program_guard
(
main_prog
,
startup_prog
):
image
=
paddle
.
static
.
data
(
name
=
'image'
,
shape
=
[
n
,
c
,
h
,
w
],
dtype
=
'float32'
)
conv2d
=
paddle
.
static
.
nn
.
conv2d
(
image
,
num_filters
=
3
,
filter_size
=
3
,
bias_attr
=
False
)
# paddle.mean oshape on ipu is [bps], need another mean()
# paddle.mean oshape on cpu is [1]
# out = paddle.mean(conv2d)
out
=
conv2d
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
=
[
out
.
name
]
ipu_strategy
=
compiler
.
get_ipu_strategy
()
ipu_strategy
.
is_training
=
False
ipu_strategy
.
batches_per_step
=
bps
program
=
compiler
.
IPUCompiledProgram
(
main_prog
,
ipu_strategy
=
ipu_strategy
).
compile
(
feed_list
,
fetch_list
)
else
:
program
=
main_prog
result
=
exe
.
run
(
program
,
feed
=
{
image
.
name
:
np_image
},
fetch_list
=
[
out
])
return
result
[
0
]
def
test_func
(
self
):
ipu_res
=
self
.
_test_func
(
True
)
cpu_res
=
self
.
_test_func
(
False
)
if
np
.
prod
(
ipu_res
.
shape
)
==
np
.
prod
(
cpu_res
.
shape
):
ipu_res
=
ipu_res
.
reshape
(
cpu_res
.
shape
)
self
.
assertTrue
(
np
.
allclose
(
ipu_res
,
cpu_res
,
atol
=
1e-4
))
if
__name__
==
"__main__"
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/ipu/test_ipu_fp16_support.py
0 → 100644
浏览文件 @
1ca791c7
# Copyright (c) 2021 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.fluid.compiler
as
compiler
import
paddle.optimizer
import
paddle.static
from
paddle.fluid.tests.unittests.ipu.op_test_ipu
import
(
IPUOpTest
,
np_dtype_to_fluid_str
)
paddle
.
enable_static
()
@
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_feed
()
self
.
set_feed_attr
()
self
.
set_attrs
()
def
set_feed
(
self
):
np_data
=
np
.
random
.
uniform
(
low
=-
1
,
high
=
1
,
size
=
[
1
,
3
,
100
,
100
])
self
.
feed_ipu
=
{
"x"
:
np_data
.
astype
(
'float16'
)}
self
.
feed_cpu
=
{
"x"
:
np_data
.
astype
(
'float32'
)}
def
set_feed_attr
(
self
):
self
.
feed_shape
=
[
x
.
shape
for
x
in
self
.
feed_cpu
.
values
()]
self
.
feed_list
=
list
(
self
.
feed_cpu
.
keys
())
self
.
feed_dtype
=
[
np_dtype_to_fluid_str
(
x
.
dtype
)
for
x
in
self
.
feed_cpu
.
values
()
]
def
set_attrs
(
self
):
self
.
attrs
=
{}
def
_test_base
(
self
,
run_ipu
=
True
):
scope
=
fluid
.
core
.
Scope
()
main_prog
=
paddle
.
static
.
Program
()
startup_prog
=
paddle
.
static
.
Program
()
SEED
=
self
.
SEED
main_prog
.
random_seed
=
SEED
startup_prog
.
random_seed
=
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
=
self
.
feed_dtype
[
0
])
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
run_ipu
:
place
=
paddle
.
IPUPlace
()
else
:
place
=
paddle
.
CPUPlace
()
exe
=
paddle
.
static
.
Executor
(
place
)
exe
.
run
(
startup_prog
)
feed
=
self
.
feed_ipu
if
run_ipu
else
self
.
feed_cpu
if
run_ipu
:
feed_list
=
self
.
feed_list
ipu_strategy
=
compiler
.
get_ipu_strategy
()
ipu_strategy
.
is_training
=
False
ipu_strategy
.
enable_fp16
=
True
program
=
compiler
.
IPUCompiledProgram
(
main_prog
,
ipu_strategy
=
ipu_strategy
).
compile
(
feed_list
,
fetch_list
)
else
:
feed_list
=
self
.
feed_list
program
=
main_prog
result
=
exe
.
run
(
program
,
feed
=
feed
,
fetch_list
=
fetch_list
)
return
result
[
0
]
def
test_base
(
self
):
res0
=
self
.
_test_base
(
False
)
res1
=
self
.
_test_base
(
True
)
self
.
assertTrue
(
res0
.
shape
==
res1
.
shape
)
mae
=
np
.
mean
(
np
.
abs
(
res0
.
flatten
()
-
res1
.
flatten
()))
print
(
"mae is "
,
mae
)
self
.
assertTrue
(
mae
<
0.001
)
if
__name__
==
"__main__"
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/ipu/test_ipu_inference_model_io.py
0 → 100644
浏览文件 @
1ca791c7
# Copyright (c) 2021 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
shutil
import
numpy
as
np
import
paddle
import
paddle.fluid
as
fluid
import
paddle.fluid.compiler
as
compiler
import
paddle.optimizer
import
paddle.static
from
paddle.fluid.tests.unittests.ipu.op_test_ipu
import
IPUOpTest
paddle
.
enable_static
()
@
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_feed
()
self
.
set_attrs
()
def
set_feed
(
self
):
self
.
feed_shape
=
[]
self
.
feed_shape
.
append
([
1
,
3
,
10
,
10
])
self
.
feed
=
{}
self
.
feed
[
"in_0"
]
=
np
.
random
.
uniform
(
size
=
self
.
feed_shape
[
0
]).
astype
(
np
.
float32
)
self
.
feed_list
=
list
(
self
.
feed
.
keys
())
def
set_attrs
(
self
):
self
.
attrs
=
{}
self
.
attrs
[
'steps'
]
=
100
self
.
attrs
[
'save_at_step'
]
=
20
self
.
attrs
[
'is_training'
]
=
True
self
.
attrs
[
'opt_type'
]
=
'sgd'
self
.
attrs
[
'path'
]
=
'model'
self
.
attrs
[
'model_name'
]
=
'test'
def
_test_save
(
self
):
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
generator
=
fluid
.
unique_name
.
UniqueNameGenerator
()
self
.
full_name
=
'/'
.
join
(
[
self
.
attrs
[
'path'
],
self
.
attrs
[
'model_name'
]])
with
fluid
.
unique_name
.
guard
(
generator
):
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
,
name
=
'conv2d'
)
loss
=
paddle
.
mean
(
conv1
)
if
self
.
attrs
[
'is_training'
]:
if
self
.
attrs
[
'opt_type'
]
==
'sgd'
:
sgd
=
paddle
.
optimizer
.
SGD
(
learning_rate
=
1e-2
)
sgd
.
minimize
(
loss
)
elif
self
.
attrs
[
'opt_type'
]
==
'adam'
:
adam
=
paddle
.
optimizer
.
Adam
(
learning_rate
=
1e-2
)
adam
.
minimize
(
loss
)
elif
self
.
attrs
[
'opt_type'
]
==
'lamb'
:
lamb
=
paddle
.
optimizer
.
Lamb
(
learning_rate
=
1e-2
)
lamb
.
minimize
(
loss
)
fetch_list
=
[
loss
.
name
]
place
=
paddle
.
IPUPlace
()
exe
=
paddle
.
static
.
Executor
(
place
)
exe
.
run
(
startup_prog
)
ipu_strategy
=
compiler
.
get_ipu_strategy
()
ipu_strategy
.
is_training
=
self
.
attrs
[
'is_training'
]
program
=
compiler
.
IPUCompiledProgram
(
main_prog
,
ipu_strategy
=
ipu_strategy
).
compile
(
self
.
feed_list
,
fetch_list
)
result
=
[]
for
i
in
range
(
self
.
attrs
[
'steps'
]):
tmp
=
exe
.
run
(
program
,
feed
=
self
.
feed
,
fetch_list
=
fetch_list
)
result
.
append
(
tmp
)
paddle
.
static
.
save_inference_model
(
self
.
full_name
,
x
,
loss
,
exe
,
program
=
program
.
org_program
)
def
_test_load
(
self
,
run_ipu
):
if
run_ipu
:
place
=
paddle
.
IPUPlace
()
else
:
place
=
paddle
.
CPUPlace
()
exe
=
paddle
.
static
.
Executor
(
place
)
[
inference_program
,
feed_target_names
,
fetch_targets
]
=
(
paddle
.
static
.
load_inference_model
(
self
.
full_name
,
exe
))
if
run_ipu
:
feed_list
=
feed_target_names
fetch_list
=
[
fetch_targets
[
0
].
name
]
ipu_strategy
=
compiler
.
get_ipu_strategy
()
ipu_strategy
.
is_training
=
False
program
=
compiler
.
IPUCompiledProgram
(
inference_program
,
ipu_strategy
=
ipu_strategy
).
compile
(
feed_list
,
fetch_list
)
else
:
program
=
inference_program
tmp
=
exe
.
run
(
program
,
feed
=
self
.
feed
,
fetch_list
=
[
fetch_targets
])
return
tmp
def
test_base
(
self
):
self
.
_test_save
()
cpu_res
=
self
.
_test_load
(
False
)
ipu_res
=
self
.
_test_load
(
True
)
self
.
assertTrue
(
np
.
allclose
(
cpu_res
,
ipu_res
,
atol
=
self
.
atol
))
shutil
.
rmtree
(
self
.
attrs
[
'path'
],
True
)
class
TestAdam
(
TestBase
):
def
set_attrs
(
self
):
self
.
attrs
=
{}
self
.
attrs
[
'steps'
]
=
100
self
.
attrs
[
'is_training'
]
=
True
self
.
attrs
[
'opt_type'
]
=
'adam'
self
.
attrs
[
'path'
]
=
'model'
self
.
attrs
[
'model_name'
]
=
'test'
class
TestLamb
(
TestBase
):
def
set_attrs
(
self
):
self
.
attrs
=
{}
self
.
attrs
[
'steps'
]
=
100
self
.
attrs
[
'is_training'
]
=
True
self
.
attrs
[
'opt_type'
]
=
'lamb'
self
.
attrs
[
'path'
]
=
'model'
self
.
attrs
[
'model_name'
]
=
'test'
if
__name__
==
"__main__"
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/ipu/test_ipu_model_pipeline.py
0 → 100644
浏览文件 @
1ca791c7
# Copyright (c) 2021 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.
from
__future__
import
print_function
import
numpy
as
np
import
unittest
import
paddle
import
paddle.fluid
as
fluid
import
paddle.fluid.compiler
as
compiler
paddle
.
enable_static
()
SEED
=
2021
@
unittest
.
skipIf
(
not
paddle
.
is_compiled_with_ipu
(),
"core is not compiled with IPU"
)
class
TestCastNet
(
unittest
.
TestCase
):
def
_test
(
self
,
run_ipu
=
True
):
scope
=
fluid
.
core
.
Scope
()
main_prog
=
paddle
.
static
.
Program
()
startup_prog
=
paddle
.
static
.
Program
()
main_prog
.
random_seed
=
SEED
startup_prog
.
random_seed
=
SEED
np
.
random
.
seed
(
SEED
)
np_image
=
np
.
random
.
rand
(
1
,
3
,
10
,
10
).
astype
(
np
.
float32
)
with
fluid
.
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'
)
with
fluid
.
ipu_shard
(
ipu_index
=
0
):
conv1
=
paddle
.
static
.
nn
.
conv2d
(
image
,
num_filters
=
3
,
filter_size
=
3
,
bias_attr
=
False
)
with
fluid
.
ipu_shard
(
ipu_index
=
1
):
conv2
=
paddle
.
static
.
nn
.
conv2d
(
conv1
,
num_filters
=
3
,
filter_size
=
3
,
bias_attr
=
False
)
loss
=
paddle
.
mean
(
conv2
)
if
run_ipu
:
place
=
paddle
.
IPUPlace
()
else
:
place
=
paddle
.
CPUPlace
()
executor
=
paddle
.
static
.
Executor
(
place
)
executor
.
run
(
startup_prog
)
if
run_ipu
:
feed_list
=
[
image
.
name
]
fetch_list
=
[
loss
.
name
]
ipu_strategy
=
compiler
.
get_ipu_strategy
()
ipu_strategy
.
num_ipus
=
2
ipu_strategy
.
is_training
=
False
ipu_strategy
.
enable_manual_shard
=
True
ipu_strategy
.
enable_pipelining
=
False
program
=
compiler
.
IPUCompiledProgram
(
main_prog
,
ipu_strategy
=
ipu_strategy
).
compile
(
feed_list
,
fetch_list
)
else
:
program
=
main_prog
loss_res
=
executor
.
run
(
program
,
feed
=
{
"image"
:
np_image
},
fetch_list
=
[
loss
])
return
loss_res
def
test_cast
(
self
):
cpu_outputs
=
self
.
_test
(
False
)
ipu_outputs
=
self
.
_test
(
True
)
self
.
assertTrue
(
np
.
allclose
(
cpu_outputs
,
ipu_outputs
,
atol
=
1e-4
))
if
__name__
==
"__main__"
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/ipu/test_ipu_pipeline.py
0 → 100644
浏览文件 @
1ca791c7
# Copyright (c) 2021 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.
from
__future__
import
print_function
import
numpy
as
np
import
unittest
import
sys
import
paddle
import
paddle.fluid
as
fluid
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_stage : no
with
paddle
.
fluid
.
ipu_shard
(
ipu_stage
=
1
):
c
=
b
+
1
# scale, ipu_stage : 1
with
paddle
.
fluid
.
ipu_shard
(
ipu_stage
=
2
):
d
=
c
*
2
# scale, ipu_stage : 2
with
paddle
.
fluid
.
ipu_shard
(
ipu_stage
=
3
):
e
=
d
+
3
# scale, ipu_stage : 3
with
paddle
.
fluid
.
ipu_shard
(
ipu_stage
=
1
):
e
=
e
+
3
# scale, ipu_stage : 1
with
paddle
.
fluid
.
ipu_shard
(
ipu_stage
=
2
):
e
=
e
+
3
# scale, ipu_stage : 2
with
paddle
.
fluid
.
ipu_shard
(
ipu_stage
=
1
):
f
=
paddle
.
tensor
.
pow
(
e
,
2.0
)
# pow, ipu_stage : 1
with
paddle
.
fluid
.
ipu_shard
(
ipu_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
()
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