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5c64d84f
编写于
12月 09, 2022
作者:
C
cyber-pioneer
提交者:
GitHub
12月 09, 2022
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差异文件
move fluid.layers.create_global_var to static.create_global_var (#48777)
上级
0f6c5459
变更
38
隐藏空白更改
内联
并排
Showing
38 changed file
with
179 addition
and
184 deletion
+179
-184
python/paddle/distributed/fleet/meta_optimizers/dgc_optimizer.py
...paddle/distributed/fleet/meta_optimizers/dgc_optimizer.py
+5
-5
python/paddle/distributed/fleet/metrics/metric.py
python/paddle/distributed/fleet/metrics/metric.py
+7
-7
python/paddle/distributed/passes/auto_parallel_gradient_merge.py
...paddle/distributed/passes/auto_parallel_gradient_merge.py
+3
-3
python/paddle/fluid/contrib/mixed_precision/bf16/decorator.py
...on/paddle/fluid/contrib/mixed_precision/bf16/decorator.py
+2
-1
python/paddle/fluid/contrib/mixed_precision/decorator.py
python/paddle/fluid/contrib/mixed_precision/decorator.py
+4
-4
python/paddle/fluid/contrib/optimizer.py
python/paddle/fluid/contrib/optimizer.py
+1
-1
python/paddle/fluid/dygraph/learning_rate_scheduler.py
python/paddle/fluid/dygraph/learning_rate_scheduler.py
+1
-1
python/paddle/fluid/layers/control_flow.py
python/paddle/fluid/layers/control_flow.py
+2
-1
python/paddle/fluid/layers/learning_rate_scheduler.py
python/paddle/fluid/layers/learning_rate_scheduler.py
+2
-2
python/paddle/fluid/layers/tensor.py
python/paddle/fluid/layers/tensor.py
+0
-87
python/paddle/fluid/optimizer.py
python/paddle/fluid/optimizer.py
+18
-17
python/paddle/fluid/tests/test_python_operator_overriding.py
python/paddle/fluid/tests/test_python_operator_overriding.py
+2
-3
python/paddle/fluid/tests/unittests/dist_transformer.py
python/paddle/fluid/tests/unittests/dist_transformer.py
+1
-1
python/paddle/fluid/tests/unittests/dygraph_to_static/test_bmn.py
...addle/fluid/tests/unittests/dygraph_to_static/test_bmn.py
+1
-1
python/paddle/fluid/tests/unittests/npu/test_adam_op_npu.py
python/paddle/fluid/tests/unittests/npu/test_adam_op_npu.py
+3
-3
python/paddle/fluid/tests/unittests/test_adam_op.py
python/paddle/fluid/tests/unittests/test_adam_op.py
+6
-6
python/paddle/fluid/tests/unittests/test_adamw_op.py
python/paddle/fluid/tests/unittests/test_adamw_op.py
+2
-2
python/paddle/fluid/tests/unittests/test_create_global_var.py
...on/paddle/fluid/tests/unittests/test_create_global_var.py
+4
-4
python/paddle/fluid/tests/unittests/test_eager_deletion_padding_rnn.py
.../fluid/tests/unittests/test_eager_deletion_padding_rnn.py
+1
-1
python/paddle/fluid/tests/unittests/test_fleet_metric.py
python/paddle/fluid/tests/unittests/test_fleet_metric.py
+2
-2
python/paddle/fluid/tests/unittests/test_imperative_optimizer.py
...paddle/fluid/tests/unittests/test_imperative_optimizer.py
+1
-1
python/paddle/fluid/tests/unittests/test_imperative_optimizer_v2.py
...dle/fluid/tests/unittests/test_imperative_optimizer_v2.py
+1
-1
python/paddle/fluid/tests/unittests/test_lr_scheduler.py
python/paddle/fluid/tests/unittests/test_lr_scheduler.py
+1
-1
python/paddle/fluid/tests/unittests/test_parallel_executor_feed_persistable_var.py
.../unittests/test_parallel_executor_feed_persistable_var.py
+1
-1
python/paddle/fluid/tests/unittests/test_queue.py
python/paddle/fluid/tests/unittests/test_queue.py
+3
-3
python/paddle/fluid/tests/unittests/test_switch.py
python/paddle/fluid/tests/unittests/test_switch.py
+2
-2
python/paddle/fluid/tests/unittests/test_var_info.py
python/paddle/fluid/tests/unittests/test_var_info.py
+2
-2
python/paddle/fluid/tests/unittests/xpu/test_adamw_op_xpu.py
python/paddle/fluid/tests/unittests/xpu/test_adamw_op_xpu.py
+2
-2
python/paddle/incubate/optimizer/distributed_fused_lamb.py
python/paddle/incubate/optimizer/distributed_fused_lamb.py
+2
-2
python/paddle/incubate/optimizer/lookahead.py
python/paddle/incubate/optimizer/lookahead.py
+3
-3
python/paddle/optimizer/adam.py
python/paddle/optimizer/adam.py
+2
-2
python/paddle/optimizer/adamw.py
python/paddle/optimizer/adamw.py
+2
-2
python/paddle/optimizer/lamb.py
python/paddle/optimizer/lamb.py
+3
-2
python/paddle/optimizer/momentum.py
python/paddle/optimizer/momentum.py
+2
-2
python/paddle/optimizer/optimizer.py
python/paddle/optimizer/optimizer.py
+2
-2
python/paddle/optimizer/sgd.py
python/paddle/optimizer/sgd.py
+3
-2
python/paddle/static/__init__.py
python/paddle/static/__init__.py
+1
-1
python/paddle/tensor/creation.py
python/paddle/tensor/creation.py
+79
-1
未找到文件。
python/paddle/distributed/fleet/meta_optimizers/dgc_optimizer.py
浏览文件 @
5c64d84f
...
...
@@ -23,9 +23,9 @@ from paddle import framework
from
paddle.common_ops_import
import
LayerHelper
from
paddle.fluid.clip
import
GradientClipByNorm
,
append_gradient_clip_ops
from
paddle.fluid.dygraph
import
base
as
imperative_base
from
paddle.fluid.layers
import
tensor
from
paddle.fluid.optimizer
import
Momentum
,
Optimizer
from
paddle.framework
import
core
from
paddle.static
import
create_global_var
class
DGCMomentumOptimizer
(
Optimizer
):
...
...
@@ -217,7 +217,7 @@ class DGCMomentumOptimizer(Optimizer):
)
# rampup begin step var for all_reduce_op_handle
self
.
_rampup_begin_step_var
=
tensor
.
create_global_var
(
self
.
_rampup_begin_step_var
=
create_global_var
(
shape
=
[
1
],
dtype
=
core
.
VarDesc
.
VarType
.
FP32
,
persistable
=
True
,
...
...
@@ -237,7 +237,7 @@ class DGCMomentumOptimizer(Optimizer):
v_var
=
self
.
_add_accumulator
(
self
.
_v_velocity_acc_str
,
param_var
)
k_var
=
tensor
.
create_global_var
(
k_var
=
create_global_var
(
shape
=
[
1
],
dtype
=
param_var
.
dtype
,
persistable
=
True
,
...
...
@@ -246,7 +246,7 @@ class DGCMomentumOptimizer(Optimizer):
force_cpu
=
True
,
)
encoded_var
=
tensor
.
create_global_var
(
encoded_var
=
create_global_var
(
shape
=
[
1
],
dtype
=
param_var
.
dtype
,
persistable
=
True
,
...
...
@@ -255,7 +255,7 @@ class DGCMomentumOptimizer(Optimizer):
force_cpu
=
False
,
)
gather_var
=
tensor
.
create_global_var
(
gather_var
=
create_global_var
(
shape
=
[
1
],
dtype
=
param_var
.
dtype
,
persistable
=
True
,
...
...
python/paddle/distributed/fleet/metrics/metric.py
浏览文件 @
5c64d84f
...
...
@@ -40,7 +40,7 @@ def sum(input, scope=None, util=None):
# in model.py
input = fluid.layers.cast(some_input, dtype='float32')
cnt = paddle.sum(input)
global_cnt =
fluid.layers
.create_global_var(persistable=True, dtype='float32', shape=[1], value=0)
global_cnt =
paddle.static
.create_global_var(persistable=True, dtype='float32', shape=[1], value=0)
tmp = fluid.layers.elementwise_add(cnt, global_cnt)
fluid.layers.assign(tmp, global_cnt)
...
...
@@ -80,7 +80,7 @@ def max(input, scope=None, util=None):
# in model.py
input = fluid.layers.cast(some_input, dtype='float32')
cnt = paddle.sum(input)
global_cnt =
fluid.layers
.create_global_var(persistable=True, dtype='float32', shape=[1], value=0)
global_cnt =
paddle.static
.create_global_var(persistable=True, dtype='float32', shape=[1], value=0)
tmp = paddle.maximum(cnt, global_cnt)
fluid.layers.assign(tmp, global_cnt)
...
...
@@ -120,7 +120,7 @@ def min(input, scope=None, util=None):
# in model.py
input = fluid.layers.cast(some_input, dtype='float32')
cnt = paddle.sum(input)
global_cnt =
fluid.layers
.create_global_var(persistable=True, dtype='float32', shape=[1], value=0)
global_cnt =
paddle.static
.create_global_var(persistable=True, dtype='float32', shape=[1], value=0)
tmp = fluid.layers.elementwise_min(cnt, global_cnt)
fluid.layers.assign(tmp, global_cnt)
...
...
@@ -391,15 +391,15 @@ def acc(correct, total, scope=None, util=None):
.. code-block:: python
# in model.py
correct =
fluid.layers
.create_global_var(dtype='float32', shape=[1], value=0)
total =
fluid.layers
.create_global_var(dtype='float32', shape=[1], value=0)
correct =
paddle.static
.create_global_var(dtype='float32', shape=[1], value=0)
total =
paddle.static
.create_global_var(dtype='float32', shape=[1], value=0)
acc = fluid.layers.acc(predict, label, k=1, correct=correct, total=total)
global_correct =
fluid.layers
.create_global_var(persistable=True, dtype='float32', shape=[1], value=0)
global_correct =
paddle.static
.create_global_var(persistable=True, dtype='float32', shape=[1], value=0)
tmp1 = fluid.layers.elementwise_min(correct, global_correct)
fluid.layers.assign(tmp1, global_correct)
global_total =
fluid.layers
.create_global_var(persistable=True, dtype='float32', shape=[1], value=0)
global_total =
paddle.static
.create_global_var(persistable=True, dtype='float32', shape=[1], value=0)
tmp2 = fluid.layers.elementwise_min(total, global_total)
fluid.layers.assign(tmp2, global_total)
...
...
python/paddle/distributed/passes/auto_parallel_gradient_merge.py
浏览文件 @
5c64d84f
...
...
@@ -64,7 +64,7 @@ def _remove_and_get_optimizer_op(main_program, dist_context):
def
_get_gm_cond_var
(
main_program
,
k_steps
,
dist_context
):
main_block
=
main_program
.
global_block
()
# Add const var
k_step_var
=
layers
.
create_global_var
(
k_step_var
=
paddle
.
static
.
create_global_var
(
name
=
"gradient_merge_k"
,
shape
=
[
1
],
value
=
int
(
k_steps
),
...
...
@@ -74,7 +74,7 @@ def _get_gm_cond_var(main_program, k_steps, dist_context):
)
set_var_dist_attr
(
dist_context
,
k_step_var
,
[
-
1
],
world_process_group
.
ranks
)
zero_var
=
layers
.
create_global_var
(
zero_var
=
paddle
.
static
.
create_global_var
(
name
=
"gradient_merge_zero"
,
shape
=
[
1
],
value
=
int
(
0
),
...
...
@@ -85,7 +85,7 @@ def _get_gm_cond_var(main_program, k_steps, dist_context):
set_var_dist_attr
(
dist_context
,
zero_var
,
[
-
1
],
world_process_group
.
ranks
)
# Add step var & cond var
step_var
=
layers
.
create_global_var
(
step_var
=
paddle
.
static
.
create_global_var
(
name
=
"gradient_merge_step"
,
shape
=
[
1
],
value
=
int
(
0
),
...
...
python/paddle/fluid/contrib/mixed_precision/bf16/decorator.py
浏览文件 @
5c64d84f
...
...
@@ -12,6 +12,7 @@
# See the License for the specific language governing permissions and
# limitations under the License.
import
paddle
from
paddle.fluid
import
(
core
,
default_main_program
,
...
...
@@ -68,7 +69,7 @@ class OptimizerWithMixedPrecision:
if
isinstance
(
self
.
_optimizer
.
_learning_rate
,
float
):
self
.
_optimizer
.
_learning_rate_map
[
default_main_program
()
]
=
layers
.
create_global_var
(
]
=
paddle
.
static
.
create_global_var
(
name
=
unique_name
.
generate
(
"learning_rate"
),
shape
=
[
1
],
value
=
float
(
self
.
_optimizer
.
_learning_rate
),
...
...
python/paddle/fluid/contrib/mixed_precision/decorator.py
浏览文件 @
5c64d84f
...
...
@@ -122,7 +122,7 @@ class OptimizerWithMixedPrecision:
return
getattr
(
self
.
_optimizer
,
"_supports_check_nan_inf"
,
False
)
def
_init_amp_var
(
self
):
self
.
_loss_scaling
=
layers
.
create_global_var
(
self
.
_loss_scaling
=
paddle
.
static
.
create_global_var
(
name
=
unique_name
.
generate
(
"loss_scaling"
),
shape
=
[
1
],
value
=
self
.
_init_loss_scaling
,
...
...
@@ -131,14 +131,14 @@ class OptimizerWithMixedPrecision:
)
if
self
.
_use_dynamic_loss_scaling
:
self
.
_num_good_steps
=
layers
.
create_global_var
(
self
.
_num_good_steps
=
paddle
.
static
.
create_global_var
(
name
=
unique_name
.
generate
(
"num_good_steps"
),
shape
=
[
1
],
value
=
0
,
dtype
=
'int32'
,
persistable
=
True
,
)
self
.
_num_bad_steps
=
layers
.
create_global_var
(
self
.
_num_bad_steps
=
paddle
.
static
.
create_global_var
(
name
=
unique_name
.
generate
(
"num_bad_steps"
),
shape
=
[
1
],
value
=
0
,
...
...
@@ -151,7 +151,7 @@ class OptimizerWithMixedPrecision:
if
isinstance
(
self
.
_optimizer
.
_learning_rate
,
float
):
self
.
_optimizer
.
_learning_rate_map
[
default_main_program
()
]
=
layers
.
create_global_var
(
]
=
paddle
.
static
.
create_global_var
(
name
=
unique_name
.
generate
(
"learning_rate"
),
shape
=
[
1
],
value
=
float
(
self
.
_optimizer
.
_learning_rate
),
...
...
python/paddle/fluid/contrib/optimizer.py
浏览文件 @
5c64d84f
...
...
@@ -143,7 +143,7 @@ class Momentum(Optimizer):
var_name
=
param
.
name
+
"_fp32_master"
var_name
=
unique_name
.
generate
(
var_name
)
var
=
layers
.
create_global_var
(
var
=
paddle
.
static
.
create_global_var
(
name
=
var_name
,
shape
=
param
.
shape
,
value
=
0
,
...
...
python/paddle/fluid/dygraph/learning_rate_scheduler.py
浏览文件 @
5c64d84f
...
...
@@ -68,7 +68,7 @@ class LearningRateDecay:
"""
from
..
import
layers
lr
=
layers
.
create_global_var
(
lr
=
paddle
.
static
.
create_global_var
(
name
=
unique_name
.
generate
(
"learning_rate"
),
shape
=
[
1
],
value
=
float
(
lr
),
...
...
python/paddle/fluid/layers/control_flow.py
浏览文件 @
5c64d84f
...
...
@@ -2368,9 +2368,10 @@ class Switch:
Examples:
.. code-block:: python
import paddle
import paddle.fluid as fluid
lr =
fluid.layers
.create_global_var(
lr =
paddle.static
.create_global_var(
shape=[1],
value=0.0,
dtype='float32',
...
...
python/paddle/fluid/layers/learning_rate_scheduler.py
浏览文件 @
5c64d84f
...
...
@@ -420,7 +420,7 @@ def piecewise_decay(boundaries, values):
else
:
global_step
=
_decay_step_counter
()
lr
=
tensor
.
create_global_var
(
lr
=
paddle
.
static
.
create_global_var
(
shape
=
[
1
],
value
=
0.0
,
dtype
=
'float32'
,
...
...
@@ -575,7 +575,7 @@ def linear_lr_warmup(learning_rate, warmup_steps, start_lr, end_lr):
)
return
lr
else
:
lr
=
tensor
.
create_global_var
(
lr
=
paddle
.
static
.
create_global_var
(
shape
=
[
1
],
value
=
0.0
,
dtype
=
dtype
,
...
...
python/paddle/fluid/layers/tensor.py
浏览文件 @
5c64d84f
...
...
@@ -12,25 +12,19 @@
# See the License for the specific language governing permissions and
# limitations under the License.
import
math
import
numpy
import
warnings
from
..layer_helper
import
LayerHelper
from
..param_attr
import
ParamAttr
from
..initializer
import
Initializer
from
..framework
import
(
_current_expected_place
,
convert_np_dtype_to_dtype_
,
_non_static_mode
,
_varbase_creator
,
device_guard
,
_in_legacy_dygraph
,
in_dygraph_mode
,
_get_paddle_place
,
)
from
..framework
import
Variable
from
..initializer
import
Constant
from
..core
import
VarDesc
from
..
import
core
from
.layer_function_generator
import
templatedoc
...
...
@@ -47,7 +41,6 @@ from .utils import check_shape
from
paddle
import
_C_ops
,
_legacy_C_ops
__all__
=
[
'create_global_var'
,
'cast'
,
'tensor_array_to_tensor'
,
'concat'
,
...
...
@@ -61,86 +54,6 @@ __all__ = [
]
def
create_global_var
(
shape
,
value
,
dtype
,
persistable
=
False
,
force_cpu
=
False
,
name
=
None
):
"""
This function creates a new tensor variable with value in the global block(block 0).
Parameters:
shape (list[int]|tuple[int]): Shape of the variable
value (float): The value of the variable. The new created
variable will be filled with it.
dtype (str): Data type of the variable
persistable (bool, optional): If this variable is persistable.
Default: False
force_cpu (bool, optional): Force this variable to be on CPU.
Default: False
name (str, optional): For detailed information, please refer to
:ref:`api_guide_Name` . Usually name is no need to set and None by default.
Returns:
Variable: The created Variable
Examples:
.. code-block:: python
import paddle
paddle.enable_static()
var = paddle.static.create_global_var(shape=[2,3], value=1.0, dtype='float32',
persistable=True, force_cpu=True, name='new_var')
"""
check_type
(
shape
,
'shape'
,
(
list
,
tuple
,
numpy
.
ndarray
),
'create_global_var'
)
for
item
in
shape
:
check_type
(
item
,
'item of shape'
,
(
int
,
numpy
.
uint8
,
numpy
.
int8
,
numpy
.
int16
,
numpy
.
int32
,
numpy
.
int64
,
),
'create_global_var'
,
)
check_dtype
(
dtype
,
'dtype'
,
[
'bool'
,
'float16'
,
'float32'
,
'float64'
,
'int8'
,
'int16'
,
'int32'
,
'int64'
,
'uint8'
,
'uint16'
,
],
'create_global_var'
,
)
helper
=
LayerHelper
(
"global_var"
,
**
locals
())
var
=
helper
.
create_global_variable
(
dtype
=
dtype
,
shape
=
shape
,
persistable
=
persistable
,
name
=
name
,
stop_gradient
=
True
,
)
helper
.
set_variable_initializer
(
var
,
initializer
=
Constant
(
value
=
float
(
value
),
force_cpu
=
force_cpu
)
)
return
var
def
cast
(
x
,
dtype
):
"""
...
...
python/paddle/fluid/optimizer.py
浏览文件 @
5c64d84f
...
...
@@ -418,7 +418,7 @@ class Optimizer:
else
:
self
.
_learning_rate_map
[
framework
.
default_main_program
()
]
=
layers
.
create_global_var
(
]
=
paddle
.
static
.
create_global_var
(
name
=
unique_name
.
generate
(
"learning_rate"
),
shape
=
[
1
],
value
=
float
(
self
.
_learning_rate
),
...
...
@@ -449,7 +449,7 @@ class Optimizer:
# create learning rate in the current main program
self
.
_learning_rate_map
[
framework
.
default_main_program
()
]
=
layers
.
create_global_var
(
]
=
paddle
.
static
.
create_global_var
(
name
=
unique_name
.
generate
(
"learning_rate"
),
shape
=
[
1
],
value
=
float
(
self
.
_learning_rate
),
...
...
@@ -474,6 +474,7 @@ class Optimizer:
Examples:
.. code-block:: python
import paddle
import paddle.fluid as fluid
import paddle
...
...
@@ -497,7 +498,7 @@ class Optimizer:
# set learning rate manually by framework Variable
lr_var =
fluid.layers
.create_global_var(
lr_var =
paddle.static
.create_global_var(
shape=[1], value=0.7, dtype='float32')
adam.set_lr(lr_var)
lr = adam.current_step_lr()
...
...
@@ -1498,7 +1499,7 @@ class SGDOptimizer(Optimizer):
var_name
=
param
.
name
+
"_fp32_master"
var_name
=
unique_name
.
generate
(
var_name
)
var
=
layers
.
create_global_var
(
var
=
paddle
.
static
.
create_global_var
(
name
=
var_name
,
shape
=
param
.
shape
,
value
=
0
,
...
...
@@ -1859,7 +1860,7 @@ class LarsMomentumOptimizer(Optimizer):
var_name
=
param
.
name
+
'_fp32_master'
var_name
=
unique_name
.
generate
(
var_name
)
var
=
layers
.
create_global_var
(
var
=
paddle
.
static
.
create_global_var
(
name
=
var_name
,
shape
=
param
.
shape
,
value
=
0
,
...
...
@@ -2267,21 +2268,21 @@ class AdamOptimizer(Optimizer):
def get_decayed_betas(beta1_init, beta2_init, decay_steps, decay_rate, epsilon_init):
global_step = lr_scheduler._decay_step_counter()
beta1 =
fluid.layers
.create_global_var(
beta1 =
paddle.static
.create_global_var(
shape=[1],
value=float(beta1_init),
dtype='float32',
# set persistable for save checkpoints and resume
persistable=True,
name="beta1")
beta2 =
fluid.layers
.create_global_var(
beta2 =
paddle.static
.create_global_var(
shape=[1],
value=float(beta2_init),
dtype='float32',
# set persistable for save checkpoints and resume
persistable=True,
name="beta2")
epsilon =
fluid.layers
.create_global_var(
epsilon =
paddle.static
.create_global_var(
shape=[1],
value=float(epsilon_init),
dtype='float32',
...
...
@@ -4326,7 +4327,7 @@ class ExponentialMovingAverage:
def
_get_ema_decay
(
self
):
with
default_main_program
().
_lr_schedule_guard
():
decay_var
=
layers
.
tensor
.
create_global_var
(
decay_var
=
paddle
.
static
.
create_global_var
(
shape
=
[
1
],
value
=
self
.
_decay
,
dtype
=
'float32'
,
...
...
@@ -4346,7 +4347,7 @@ class ExponentialMovingAverage:
return
decay_var
def
_get_decay_pow
(
self
,
block
):
global_step
=
layers
.
create_global_var
(
global_step
=
paddle
.
static
.
create_global_var
(
name
=
self
.
_step_counter_name
,
shape
=
[
1
],
value
=
0
,
...
...
@@ -4359,7 +4360,7 @@ class ExponentialMovingAverage:
return
decay_pow_acc
,
global_step
def
_create_ema_vars
(
self
,
param
):
param_ema
=
layers
.
create_global_var
(
param_ema
=
paddle
.
static
.
create_global_var
(
name
=
unique_name
.
generate
(
self
.
_name
+
param
.
name
+
'_ema'
),
shape
=
param
.
shape
,
value
=
0.0
,
...
...
@@ -7273,7 +7274,7 @@ class LookaheadOptimizer:
with
framework
.
program_guard
(
main_block
.
program
,
startup_program
):
# Add Var k to main prog and startup prog
k
=
layers
.
create_global_var
(
k
=
paddle
.
static
.
create_global_var
(
name
=
"lookahead_k"
,
shape
=
[
1
],
value
=
int
(
self
.
k
),
...
...
@@ -7282,7 +7283,7 @@ class LookaheadOptimizer:
)
# Add Var alpha to main prog and startup prog
alpha
=
layers
.
create_global_var
(
alpha
=
paddle
.
static
.
create_global_var
(
name
=
"lookahead_alpha"
,
shape
=
[
1
],
value
=
float
(
self
.
alpha
),
...
...
@@ -7291,7 +7292,7 @@ class LookaheadOptimizer:
)
# Add Var step
step
=
layers
.
create_global_var
(
step
=
paddle
.
static
.
create_global_var
(
name
=
"lookahead_step"
,
shape
=
[
1
],
value
=
int
(
0
),
...
...
@@ -7498,7 +7499,7 @@ class GradientMergeOptimizer:
def
_get_gm_cond_var
(
self
,
main_block
):
# Add const var
k_step_var
=
layers
.
create_global_var
(
k_step_var
=
paddle
.
static
.
create_global_var
(
name
=
"gradient_merge_k"
,
shape
=
[
1
],
value
=
int
(
self
.
k_steps
),
...
...
@@ -7507,7 +7508,7 @@ class GradientMergeOptimizer:
force_cpu
=
True
,
)
zero_var
=
layers
.
create_global_var
(
zero_var
=
paddle
.
static
.
create_global_var
(
name
=
"gradient_merge_zero"
,
shape
=
[
1
],
value
=
int
(
0
),
...
...
@@ -7517,7 +7518,7 @@ class GradientMergeOptimizer:
)
# Add step var & cond var
step_var
=
layers
.
create_global_var
(
step_var
=
paddle
.
static
.
create_global_var
(
name
=
"gradient_merge_step"
,
shape
=
[
1
],
value
=
int
(
0
),
...
...
python/paddle/fluid/tests/test_python_operator_overriding.py
浏览文件 @
5c64d84f
...
...
@@ -19,7 +19,6 @@ import numpy as np
import
paddle
import
paddle.fluid
as
fluid
import
paddle.fluid.framework
as
framework
import
paddle.fluid.layers
as
layers
paddle
.
enable_static
()
...
...
@@ -32,10 +31,10 @@ class TestPythonOperatorOverride(unittest.TestCase):
y_data
=
np
.
random
.
random
(
size
=
shape
).
astype
(
dtype
)
python_out
=
fn
(
x_data
,
y_data
)
x_var
=
layers
.
create_global_var
(
x_var
=
paddle
.
static
.
create_global_var
(
name
=
'x'
,
shape
=
shape
,
value
=
0.0
,
dtype
=
dtype
,
persistable
=
True
)
y_var
=
layers
.
create_global_var
(
y_var
=
paddle
.
static
.
create_global_var
(
name
=
'y'
,
shape
=
shape
,
value
=
0.0
,
dtype
=
dtype
,
persistable
=
True
)
out
=
fn
(
x_var
,
y_var
)
...
...
python/paddle/fluid/tests/unittests/dist_transformer.py
浏览文件 @
5c64d84f
...
...
@@ -289,7 +289,7 @@ class LearningRateScheduler:
self
.
warmup_steps
=
warmup_steps
self
.
d_model
=
d_model
self
.
static_lr
=
learning_rate
self
.
learning_rate
=
layers
.
create_global_var
(
self
.
learning_rate
=
paddle
.
static
.
create_global_var
(
name
=
name
,
shape
=
[
1
],
value
=
float
(
learning_rate
),
...
...
python/paddle/fluid/tests/unittests/dygraph_to_static/test_bmn.py
浏览文件 @
5c64d84f
...
...
@@ -308,7 +308,7 @@ def bmn_loss_func(
]
bm_mask
.
append
(
mask_vector
)
bm_mask
=
np
.
array
(
bm_mask
,
dtype
=
np
.
float32
)
self_bm_mask
=
fluid
.
layers
.
create_global_var
(
self_bm_mask
=
paddle
.
static
.
create_global_var
(
shape
=
[
dscale
,
tscale
],
value
=
0
,
dtype
=
DATATYPE
,
persistable
=
True
)
fluid
.
layers
.
assign
(
bm_mask
,
self_bm_mask
)
...
...
python/paddle/fluid/tests/unittests/npu/test_adam_op_npu.py
浏览文件 @
5c64d84f
...
...
@@ -354,21 +354,21 @@ class TestNetWithEpsilonTensor(unittest.TestCase):
beta2_init
=
0.999
epsilon_init
=
1e-8
if
use_tensor
:
beta1
=
fluid
.
layers
.
create_global_var
(
beta1
=
paddle
.
static
.
create_global_var
(
shape
=
[
1
],
value
=
float
(
beta1_init
),
dtype
=
'float32'
,
persistable
=
True
,
name
=
"beta1"
,
)
beta2
=
fluid
.
layers
.
create_global_var
(
beta2
=
paddle
.
static
.
create_global_var
(
shape
=
[
1
],
value
=
float
(
beta2_init
),
dtype
=
'float32'
,
persistable
=
True
,
name
=
"beta2"
,
)
epsilon
=
fluid
.
layers
.
create_global_var
(
epsilon
=
paddle
.
static
.
create_global_var
(
shape
=
[
1
],
value
=
float
(
epsilon_init
),
dtype
=
'float32'
,
...
...
python/paddle/fluid/tests/unittests/test_adam_op.py
浏览文件 @
5c64d84f
...
...
@@ -616,10 +616,10 @@ class TestAdamOpV2(unittest.TestCase):
conv
=
fluid
.
layers
.
conv2d
(
data
,
8
,
3
)
loss
=
paddle
.
mean
(
conv
)
beta1
=
fluid
.
layers
.
create_global_var
(
beta1
=
paddle
.
static
.
create_global_var
(
shape
=
[
1
],
value
=
0.85
,
dtype
=
'float32'
,
persistable
=
True
)
beta2
=
fluid
.
layers
.
create_global_var
(
beta2
=
paddle
.
static
.
create_global_var
(
shape
=
[
1
],
value
=
0.95
,
dtype
=
'float32'
,
persistable
=
True
)
betas
=
[
beta1
,
beta2
]
...
...
@@ -711,7 +711,7 @@ class TestAdamOpV2(unittest.TestCase):
cur_lr
=
adam
.
get_lr
()
assert
lr
==
cur_lr
with
self
.
assertRaises
(
TypeError
):
lr_var
=
paddle
.
fluid
.
layers
.
create_global_var
(
lr_var
=
paddle
.
static
.
create_global_var
(
shape
=
[
1
],
value
=
lr
,
dtype
=
'float32'
)
adam
.
set_lr
(
lr_var
)
...
...
@@ -817,21 +817,21 @@ class TestAdamOptimizer(unittest.TestCase):
beta2_init
=
0.999
epsilon_init
=
1e-8
if
use_tensor
:
beta1
=
fluid
.
layers
.
create_global_var
(
beta1
=
paddle
.
static
.
create_global_var
(
shape
=
[
1
],
value
=
float
(
beta1_init
),
dtype
=
'float32'
,
persistable
=
True
,
name
=
"beta1"
,
)
beta2
=
fluid
.
layers
.
create_global_var
(
beta2
=
paddle
.
static
.
create_global_var
(
shape
=
[
1
],
value
=
float
(
beta2_init
),
dtype
=
'float32'
,
persistable
=
True
,
name
=
"beta2"
,
)
epsilon
=
fluid
.
layers
.
create_global_var
(
epsilon
=
paddle
.
static
.
create_global_var
(
shape
=
[
1
],
value
=
float
(
epsilon_init
),
dtype
=
'float32'
,
...
...
python/paddle/fluid/tests/unittests/test_adamw_op.py
浏览文件 @
5c64d84f
...
...
@@ -212,10 +212,10 @@ class TestAdamWOp(unittest.TestCase):
conv
=
fluid
.
layers
.
conv2d
(
data
,
8
,
3
)
loss
=
paddle
.
mean
(
conv
)
beta1
=
fluid
.
layers
.
create_global_var
(
beta1
=
paddle
.
static
.
create_global_var
(
shape
=
[
1
],
value
=
0.85
,
dtype
=
'float32'
,
persistable
=
True
)
beta2
=
fluid
.
layers
.
create_global_var
(
beta2
=
paddle
.
static
.
create_global_var
(
shape
=
[
1
],
value
=
0.95
,
dtype
=
'float32'
,
persistable
=
True
)
betas
=
[
beta1
,
beta2
]
...
...
python/paddle/fluid/tests/unittests/test_create_global_var.py
浏览文件 @
5c64d84f
...
...
@@ -16,7 +16,7 @@ import unittest
import
numpy
as
np
import
paddle
.fluid
as
fluid
import
paddle
from
paddle.fluid
import
Program
,
program_guard
...
...
@@ -25,19 +25,19 @@ class TestCreateGlobalVarError(unittest.TestCase):
with
program_guard
(
Program
(),
Program
()):
def
test_shape
():
fluid
.
layers
.
create_global_var
(
1
,
2.0
,
np
.
float32
)
paddle
.
static
.
create_global_var
(
1
,
2.0
,
np
.
float32
)
self
.
assertRaises
(
TypeError
,
test_shape
)
def
test_shape_item
():
fluid
.
layers
.
create_global_var
([
1.0
,
2.0
,
3.0
],
2.0
,
'float32'
)
paddle
.
static
.
create_global_var
([
1.0
,
2.0
,
3.0
],
2.0
,
'float32'
)
self
.
assertRaises
(
TypeError
,
test_shape_item
)
# Since create_global_var support all dtype in convert_dtype().
# Hence, assertRaises ValueError not TypeError.
def
test_dtype
():
fluid
.
layers
.
create_global_var
([
1
,
2
,
3
],
2.0
,
np
.
complex128
)
paddle
.
static
.
create_global_var
([
1
,
2
,
3
],
2.0
,
np
.
complex128
)
self
.
assertRaises
(
TypeError
,
test_dtype
)
...
...
python/paddle/fluid/tests/unittests/test_eager_deletion_padding_rnn.py
浏览文件 @
5c64d84f
...
...
@@ -542,7 +542,7 @@ class PaddingRNNTestBase(unittest.TestCase):
)
)
self
.
learning_rate
=
fluid
.
layers
.
create_global_var
(
self
.
learning_rate
=
paddle
.
static
.
create_global_var
(
name
=
"learning_rate"
,
shape
=
[
1
],
value
=
1.0
,
...
...
python/paddle/fluid/tests/unittests/test_fleet_metric.py
浏览文件 @
5c64d84f
...
...
@@ -79,14 +79,14 @@ class TestFleetMetric(unittest.TestCase):
train
=
fluid
.
Program
()
startup
=
fluid
.
Program
()
with
fluid
.
program_guard
(
train
,
startup
):
t
=
fluid
.
layers
.
create_global_var
(
t
=
paddle
.
static
.
create_global_var
(
shape
=
[
1
,
1
],
value
=
1
,
dtype
=
'int64'
,
persistable
=
True
,
force_cpu
=
True
,
)
t1
=
fluid
.
layers
.
create_global_var
(
t1
=
paddle
.
static
.
create_global_var
(
shape
=
[
1
,
1
],
value
=
1
,
dtype
=
'int64'
,
...
...
python/paddle/fluid/tests/unittests/test_imperative_optimizer.py
浏览文件 @
5c64d84f
...
...
@@ -595,7 +595,7 @@ class TestOptimizerLearningRate(unittest.TestCase):
lr
=
adam
.
current_step_lr
()
np
.
testing
.
assert_allclose
(
lr
,
lr_list
[
i
],
rtol
=
1e-06
,
atol
=
0.0
)
lr_var
=
fluid
.
layers
.
create_global_var
(
lr_var
=
paddle
.
static
.
create_global_var
(
shape
=
[
1
],
value
=
0.7
,
dtype
=
'float32'
)
adam
.
set_lr
(
lr_var
)
...
...
python/paddle/fluid/tests/unittests/test_imperative_optimizer_v2.py
浏览文件 @
5c64d84f
...
...
@@ -721,7 +721,7 @@ class TestOptimizerLearningRate(unittest.TestCase):
np
.
testing
.
assert_allclose
(
lr
,
lr_list
[
i
],
rtol
=
1e-06
,
atol
=
0.0
)
with
self
.
assertRaises
(
TypeError
):
lr_var
=
fluid
.
layers
.
create_global_var
(
lr_var
=
paddle
.
static
.
create_global_var
(
shape
=
[
1
],
value
=
0.7
,
dtype
=
'float32'
)
adam
.
set_lr
(
lr_var
)
...
...
python/paddle/fluid/tests/unittests/test_lr_scheduler.py
浏览文件 @
5c64d84f
...
...
@@ -109,7 +109,7 @@ class TestReduceOnPlateauDecay:
main_prog
=
paddle
.
static
.
Program
()
start_prog
=
paddle
.
static
.
Program
()
with
paddle
.
static
.
program_guard
(
main_prog
,
start_prog
):
x
=
fluid
.
layers
.
create_global_var
(
x
=
paddle
.
static
.
create_global_var
(
[
1
],
1
,
'float32'
,
persistable
=
True
)
paddle
.
increment
(
x
)
...
...
python/paddle/fluid/tests/unittests/test_parallel_executor_feed_persistable_var.py
浏览文件 @
5c64d84f
...
...
@@ -39,7 +39,7 @@ class TestFeedPersistableVar(unittest.TestCase):
}
def
optimizer
(
self
):
learning_rate
=
fluid
.
layers
.
create_global_var
(
learning_rate
=
paddle
.
static
.
create_global_var
(
name
=
"learning_rate"
,
shape
=
[
1
],
value
=
1.0
,
...
...
python/paddle/fluid/tests/unittests/test_queue.py
浏览文件 @
5c64d84f
...
...
@@ -16,9 +16,9 @@ import unittest
import
numpy
as
np
import
paddle
import
paddle.fluid
as
fluid
import
paddle.fluid.core
as
core
import
paddle.fluid.layers
as
layers
class
TestQueue
(
unittest
.
TestCase
):
...
...
@@ -31,14 +31,14 @@ class TestQueue(unittest.TestCase):
startup_program
=
fluid
.
Program
()
value
=
np
.
random
.
rand
(
1
)
with
fluid
.
program_guard
(
main_program
,
startup_program
):
data_in
=
layers
.
create_global_var
(
data_in
=
paddle
.
static
.
create_global_var
(
shape
=
[
2
,
3
],
value
=
value
,
dtype
=
"float32"
,
persistable
=
True
,
name
=
'var_in'
,
)
data_out
=
layers
.
create_global_var
(
data_out
=
paddle
.
static
.
create_global_var
(
shape
=
[
2
,
3
],
value
=
value
-
1.0
,
dtype
=
"float32"
,
...
...
python/paddle/fluid/tests/unittests/test_switch.py
浏览文件 @
5c64d84f
...
...
@@ -30,7 +30,7 @@ class TestSwitch(unittest.TestCase):
two_var
=
layers
.
fill_constant
(
shape
=
[
1
],
dtype
=
'float32'
,
value
=
2.0
)
three_var
=
layers
.
fill_constant
(
shape
=
[
1
],
dtype
=
'float32'
,
value
=
3.0
)
result
=
layers
.
create_global_var
(
result
=
paddle
.
static
.
create_global_var
(
shape
=
[
1
],
value
=-
1.0
,
dtype
=
'float32'
,
persistable
=
True
)
...
...
@@ -71,7 +71,7 @@ class TestSwitchCaseError(unittest.TestCase):
shape
=
[
1
],
dtype
=
'float32'
,
value
=
0.0
)
result
=
layers
.
create_global_var
(
result
=
paddle
.
static
.
create_global_var
(
shape
=
[
1
],
value
=-
1.0
,
dtype
=
'float32'
,
persistable
=
True
)
...
...
python/paddle/fluid/tests/unittests/test_var_info.py
浏览文件 @
5c64d84f
...
...
@@ -20,7 +20,7 @@ import unittest
import
numpy
as
np
import
paddle
.fluid
as
fluid
import
paddle
class
TestVarInfo
(
unittest
.
TestCase
):
...
...
@@ -29,7 +29,7 @@ class TestVarInfo(unittest.TestCase):
def
test_var_info
(
self
):
"""Testcase for get and set info for variable."""
value
=
np
.
random
.
randn
(
1
)
var
=
fluid
.
layers
.
create_global_var
([
1
],
value
,
"float32"
)
var
=
paddle
.
static
.
create_global_var
([
1
],
value
,
"float32"
)
var
.
_set_info
(
"name"
,
"test"
)
ret
=
var
.
_get_info
(
"name"
)
assert
ret
==
"test"
...
...
python/paddle/fluid/tests/unittests/xpu/test_adamw_op_xpu.py
浏览文件 @
5c64d84f
...
...
@@ -199,13 +199,13 @@ class XPUTestAdamwOp2(XPUOpTestWrapper):
conv
=
fluid
.
layers
.
conv2d
(
data
,
8
,
3
)
loss
=
paddle
.
mean
(
conv
)
beta1
=
fluid
.
layers
.
create_global_var
(
beta1
=
paddle
.
static
.
create_global_var
(
shape
=
[
1
],
value
=
0.85
,
dtype
=
self
.
in_type_str
,
persistable
=
True
,
)
beta2
=
fluid
.
layers
.
create_global_var
(
beta2
=
paddle
.
static
.
create_global_var
(
shape
=
[
1
],
value
=
0.95
,
dtype
=
self
.
in_type_str
,
...
...
python/paddle/incubate/optimizer/distributed_fused_lamb.py
浏览文件 @
5c64d84f
...
...
@@ -15,7 +15,7 @@
import
os
import
paddle
from
paddle.fluid
import
core
,
framework
,
layers
,
unique_name
from
paddle.fluid
import
core
,
framework
,
unique_name
from
paddle.fluid.clip
import
ClipGradByGlobalNorm
from
paddle.fluid.executor
import
global_scope
from
paddle.fluid.framework
import
Variable
,
name_scope
...
...
@@ -172,7 +172,7 @@ class DistributedFusedLamb(Optimizer):
def
_create_scale_from_constant
(
self
,
value
):
name
=
unique_name
.
generate
(
'global_scale'
)
return
layers
.
create_global_var
(
return
paddle
.
static
.
create_global_var
(
name
=
name
,
shape
=
[
1
],
dtype
=
'float32'
,
...
...
python/paddle/incubate/optimizer/lookahead.py
浏览文件 @
5c64d84f
...
...
@@ -13,7 +13,7 @@
# limitations under the License.
import
paddle
from
paddle.fluid
import
framework
,
layers
,
unique_name
from
paddle.fluid
import
framework
,
unique_name
from
paddle.fluid.dygraph
import
base
as
imperative_base
from
paddle.fluid.framework
import
Variable
from
paddle.fluid.layer_helper
import
LayerHelper
...
...
@@ -192,7 +192,7 @@ class LookAhead(Optimizer):
def
_increment_global_var
(
self
):
if
self
.
_global_step_var
is
None
:
self
.
_global_step_var
=
layers
.
create_global_var
(
self
.
_global_step_var
=
paddle
.
static
.
create_global_var
(
name
=
unique_name
.
generate
(
"lookahead_step"
),
shape
=
[
1
],
value
=
0
,
...
...
@@ -212,7 +212,7 @@ class LookAhead(Optimizer):
zero_var
=
paddle
.
zeros
(
shape
=
[
1
],
dtype
=
'int32'
,
name
=
'lookahead_zeros'
)
k_var
=
layers
.
create_global_var
(
k_var
=
paddle
.
static
.
create_global_var
(
name
=
unique_name
.
generate
(
"lookahead_k"
),
shape
=
[
1
],
value
=
self
.
k
,
...
...
python/paddle/optimizer/adam.py
浏览文件 @
5c64d84f
...
...
@@ -18,7 +18,7 @@ from collections import defaultdict
import
paddle
from
paddle
import
_C_ops
,
_legacy_C_ops
from
..fluid
import
core
,
framework
,
layers
,
unique_name
from
..fluid
import
core
,
framework
,
unique_name
from
..fluid.dygraph
import
base
as
imperative_base
from
..fluid.framework
import
Variable
,
in_dygraph_mode
from
..fluid.layer_helper
import
LayerHelper
...
...
@@ -233,7 +233,7 @@ class Adam(Optimizer):
var_name
=
param
.
name
+
"_fp32_master"
var_name
=
unique_name
.
generate
(
var_name
)
var
=
layers
.
create_global_var
(
var
=
paddle
.
static
.
create_global_var
(
name
=
var_name
,
shape
=
param
.
shape
,
value
=
0
,
...
...
python/paddle/optimizer/adamw.py
浏览文件 @
5c64d84f
...
...
@@ -19,7 +19,7 @@ from collections.abc import Callable
import
paddle
from
..
import
_C_ops
,
_legacy_C_ops
from
..fluid
import
core
,
framework
,
layers
,
unique_name
from
..fluid
import
core
,
framework
,
unique_name
from
..fluid.clip
import
GradientClipBase
from
..fluid.dygraph
import
base
as
imperative_base
from
..fluid.framework
import
Parameter
,
Variable
...
...
@@ -338,7 +338,7 @@ class AdamW(Optimizer):
var_name
=
param
.
name
+
"_fp32_master"
var_name
=
unique_name
.
generate
(
var_name
)
var
=
layers
.
create_global_var
(
var
=
paddle
.
static
.
create_global_var
(
name
=
var_name
,
shape
=
param
.
shape
,
value
=
0
,
...
...
python/paddle/optimizer/lamb.py
浏览文件 @
5c64d84f
...
...
@@ -12,10 +12,11 @@
# See the License for the specific language governing permissions and
# limitations under the License.
import
paddle
from
paddle
import
_C_ops
,
_legacy_C_ops
from
paddle.fluid.executor
import
global_scope
from
..fluid
import
core
,
framework
,
layers
,
unique_name
from
..fluid
import
core
,
framework
,
unique_name
from
..fluid.framework
import
Variable
from
..fluid.layer_helper
import
LayerHelper
from
.optimizer
import
Optimizer
...
...
@@ -162,7 +163,7 @@ class Lamb(Optimizer):
var_name
=
param
.
name
+
"_fp32_master"
var_name
=
unique_name
.
generate
(
var_name
)
var
=
layers
.
create_global_var
(
var
=
paddle
.
static
.
create_global_var
(
name
=
var_name
,
shape
=
param
.
shape
,
value
=
0
,
...
...
python/paddle/optimizer/momentum.py
浏览文件 @
5c64d84f
...
...
@@ -19,7 +19,7 @@ from paddle import _C_ops, _legacy_C_ops
from
paddle.fluid.framework
import
_in_legacy_dygraph
,
in_dygraph_mode
from
paddle.fluid.regularizer
import
L2DecayRegularizer
from
..fluid
import
core
,
framework
,
layers
,
unique_name
from
..fluid
import
core
,
framework
,
unique_name
from
..fluid.layer_helper
import
LayerHelper
from
.optimizer
import
Optimizer
...
...
@@ -209,7 +209,7 @@ class Momentum(Optimizer):
var_name
=
param
.
name
+
"_fp32_master"
var_name
=
unique_name
.
generate
(
var_name
)
var
=
layers
.
create_global_var
(
var
=
paddle
.
static
.
create_global_var
(
name
=
var_name
,
shape
=
param
.
shape
,
value
=
0
,
...
...
python/paddle/optimizer/optimizer.py
浏览文件 @
5c64d84f
...
...
@@ -31,7 +31,7 @@ from paddle.fluid.framework import (
name_scope
,
)
from
..fluid
import
framework
,
layers
,
unique_name
from
..fluid
import
framework
,
unique_name
from
..fluid.backward
import
_get_no_grad_set_name
,
append_backward
from
..fluid.clip
import
(
GradientClipBase
,
...
...
@@ -469,7 +469,7 @@ class Optimizer:
else
:
self
.
_learning_rate_map
[
framework
.
default_main_program
()
]
=
layers
.
create_global_var
(
]
=
paddle
.
static
.
create_global_var
(
name
=
unique_name
.
generate
(
"learning_rate"
),
shape
=
[
1
],
value
=
float
(
self
.
_learning_rate
),
...
...
python/paddle/optimizer/sgd.py
浏览文件 @
5c64d84f
...
...
@@ -14,9 +14,10 @@
import
warnings
import
paddle
from
paddle
import
_C_ops
,
_legacy_C_ops
from
..fluid
import
core
,
framework
,
layers
,
unique_name
from
..fluid
import
core
,
framework
,
unique_name
from
..fluid.dygraph
import
no_grad
from
..fluid.framework
import
_in_legacy_dygraph
,
in_dygraph_mode
from
..fluid.layer_helper
import
LayerHelper
...
...
@@ -101,7 +102,7 @@ class SGD(Optimizer):
var_name
=
param
.
name
+
"_fp32_master"
var_name
=
unique_name
.
generate
(
var_name
)
var
=
layers
.
create_global_var
(
var
=
paddle
.
static
.
create_global_var
(
name
=
var_name
,
shape
=
param
.
shape
,
value
=
0
,
...
...
python/paddle/static/__init__.py
浏览文件 @
5c64d84f
...
...
@@ -33,6 +33,7 @@ from .input import data # noqa: F401
from
.input
import
InputSpec
# noqa: F401
from
..tensor.creation
import
create_parameter
# noqa: F401
from
..tensor.creation
import
create_global_var
# noqa: F401
from
..fluid.executor
import
Executor
# noqa: F401
from
..fluid.executor
import
global_scope
# noqa: F401
...
...
@@ -70,7 +71,6 @@ from ..fluid.io import load_vars # noqa: F401
from
..fluid.io
import
save_vars
# noqa: F401
from
..fluid.io
import
batch
# noqa: F401
from
..fluid.layers
import
create_global_var
# noqa: F401
from
..fluid.contrib.layers
import
ctr_metric_bundle
# noqa: F401
from
..fluid.layers
import
exponential_decay
# noqa: F401
...
...
python/paddle/tensor/creation.py
浏览文件 @
5c64d84f
...
...
@@ -36,7 +36,7 @@ from ..fluid.framework import (
_in_legacy_dygraph
,
device_guard
,
)
from
..fluid.initializer
import
Initializer
from
..fluid.initializer
import
Constant
,
Initializer
from
..fluid.layers
import
utils
from
..fluid.param_attr
import
ParamAttr
from
..framework
import
(
...
...
@@ -70,6 +70,84 @@ def _real_to_complex_dtype(dtype):
return
dtype
def
create_global_var
(
shape
,
value
,
dtype
,
persistable
=
False
,
force_cpu
=
False
,
name
=
None
):
"""
This function creates a new tensor variable with value in the global block(block 0).
Args:
shape (list[int]|tuple[int]): Shape of the variable
value (float): The value of the variable. The new created
variable will be filled with it.
dtype (str): Data type of the variable
persistable (bool, optional): If this variable is persistable.
Default: False
force_cpu (bool, optional): Force this variable to be on CPU.
Default: False
name (str, optional): For detailed information, please refer to
:ref:`api_guide_Name` . Usually name is no need to set and None by default.
Returns:
Variable: The created Variable
Examples:
.. code-block:: python
import paddle
paddle.enable_static()
var = paddle.static.create_global_var(shape=[2,3], value=1.0, dtype='float32',
persistable=True, force_cpu=True, name='new_var')
"""
check_type
(
shape
,
'shape'
,
(
list
,
tuple
,
np
.
ndarray
),
'create_global_var'
)
for
item
in
shape
:
check_type
(
item
,
'item of shape'
,
(
int
,
np
.
uint8
,
np
.
int8
,
np
.
int16
,
np
.
int32
,
np
.
int64
,
),
'create_global_var'
,
)
check_dtype
(
dtype
,
'dtype'
,
[
'bool'
,
'float16'
,
'float32'
,
'float64'
,
'int8'
,
'int16'
,
'int32'
,
'int64'
,
'uint8'
,
'uint16'
,
],
'create_global_var'
,
)
helper
=
LayerHelper
(
"global_var"
,
**
locals
())
var
=
helper
.
create_global_variable
(
dtype
=
dtype
,
shape
=
shape
,
persistable
=
persistable
,
name
=
name
,
stop_gradient
=
True
,
)
helper
.
set_variable_initializer
(
var
,
initializer
=
Constant
(
value
=
float
(
value
),
force_cpu
=
force_cpu
)
)
return
var
def
create_parameter
(
shape
,
dtype
,
name
=
None
,
attr
=
None
,
is_bias
=
False
,
default_initializer
=
None
):
...
...
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