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Paddle
未验证 提交 c985b1ac 编写于 作者: G GGBond8488 提交者： GitHub
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Fluid clean move out fill constant (#49511) 

* migrate fill_constant to paddle.tensor

* move fill_constant to paddle.tensor and repalce the reference

* add missing fill_constant replacement

* fix typro

* remove unused import fill_constant

* fix zeros import error

* fix circle import

* fix layers.zeros

* fix unitest

* fix unitests

* fix unitest

* use paddle.full replace fill_constant in samplecode

* fix sample code

* recovery xpu test

* recovery xpu test

* fix circle import

* fix utils import error

* fix utils error

* fix circle import

* redo

* fix circle import

* fix prim fill constant import

* fix type error

* fix increase error

* fix test error

* fix fill_constant
上级 4851c642
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Showing with 899 addition and 717 deletion
python/paddle/common_ops_import.py
浏览文件 @ c985b1ac
......@@ -33,7 +33,6 @@ from paddle.fluid.framework import ( # noqa: F401
in_dygraph_mode,
)
from paddle.fluid.layer_helper import LayerHelper # noqa: F401
from paddle.fluid.layers import fill_constant # noqa: F401
from paddle.fluid.layers.layer_function_generator import ( # noqa: F401
templatedoc,
)
......
python/paddle/distributed/auto_parallel/process_group.py
浏览文件 @ c985b1ac
......@@ -17,8 +17,8 @@ from collections import OrderedDict
import paddle
from paddle import _legacy_C_ops
from paddle.framework import core, in_dygraph_mode
from paddle.tensor import fill_constant
from ...fluid.layers.tensor import fill_constant
from ..collective import _get_global_env, _new_ring_id
......
python/paddle/distributed/fleet/utils/hybrid_parallel_inference.py
浏览文件 @ c985b1ac
......@@ -50,9 +50,9 @@ class HybridParallelInferenceHelper:
# while op pattern
with paddle.fluid.device_guard(f'{device}:all'):
# init global cond
max_len = layers.fill_constant(shape=[1], dtype="int64", value=10, force_cpu=False)
step_idx = layers.fill_constant(shape=[1], dtype="int64", value=0, force_cpu=False)
cond_int = layers.fill_constant(shape=[1], dtype="int64", value=0, force_cpu=False, name="cond_int")
max_len = paddle.full(shape=[1], dtype="int64", fill_value=10)
step_idx = paddle.full(shape=[1], dtype="int64", fill_value=0)
cond_int = paddle.full(shape=[1], dtype="int64", fill_value=0, name="cond_int")
cond = layers.cast(step_idx < max_len, dtype="bool")
while_op = layers.While(cond, is_test=True)
......@@ -124,14 +124,14 @@ class HybridParallelInferenceHelper:
X = paddle.static.data(name='X', shape=[None, 2], dtype='float32')
with paddle.fluid.device_guard(f'{device}:all'):
max_len = layers.fill_constant(
shape=[1], dtype="int64", value=5, force_cpu=False, name="n")
step_idx = layers.fill_constant(
shape=[1], dtype="int64", value=0, force_cpu=False, name="i")
max_len = paddle.full(
shape=[1], dtype="int64", fill_value=5, name="n")
step_idx = paddle.full(
shape=[1], dtype="int64", fill_value=0, name="i")
data = paddle.tensor.array_write(X, step_idx)
cond_int = layers.fill_constant(shape=[1], dtype="int64", value=0, force_cpu=False, name="cond_int")
cond_int = paddle.full(shape=[1], dtype="int64", fill_value=0, name="cond_int")
cond = paddle.less_than(x=step_idx, y=max_len)
while_op = layers.While(cond, is_test=True)
......
python/paddle/distributed/passes/auto_parallel_gradient_merge.py
浏览文件 @ c985b1ac
......@@ -25,7 +25,6 @@ from paddle.distributed.auto_parallel.utils import (
set_var_dist_attr,
)
from paddle.distributed.fleet.meta_optimizers.common import OP_ROLE_KEY, OpRole
from paddle.fluid import layers
from paddle.framework import core
from paddle.static import device_guard
......@@ -284,7 +283,7 @@ def _create_cond_block_and_update_optimizer(
# clear gradient_merge_vars
for param, new_grad in new_params_to_grads:
layers.fill_constant(
paddle.tensor.fill_constant(
shape=new_grad.shape,
dtype=new_grad.dtype,
value=0.0,
......
python/paddle/fluid/contrib/layers/metric_op.py
浏览文件 @ c985b1ac
......@@ -14,7 +14,7 @@
"""
Contrib layers just related to metric.
"""
import paddle
import warnings
import paddle
from paddle.fluid.layer_helper import LayerHelper
......@@ -79,7 +79,7 @@ def ctr_metric_bundle(input, label, ins_tag_weight=None):
"""
if ins_tag_weight is None:
ins_tag_weight = tensor.fill_constant(
ins_tag_weight = paddle.tensor.fill_constant(
shape=[1, 1], dtype="float32", value=1.0
)
......
python/paddle/fluid/contrib/tests/test_multi_precision_fp16_train.py
浏览文件 @ c985b1ac
......@@ -287,10 +287,10 @@ class TestAmpWithNonIterableDataLoader(unittest.TestCase):
iterable=False,
use_double_buffer=False,
)
zero_var = fluid.layers.fill_constant(
zero_var = paddle.tensor.fill_constant(
shape=[1], dtype='int64', value=0
)
one_var = fluid.layers.fill_constant(
one_var = paddle.tensor.fill_constant(
shape=[1], dtype='int64', value=1
)
with fluid.layers.control_flow.Switch() as switch:
......
python/paddle/fluid/layers/control_flow.py
浏览文件 @ c985b1ac
......@@ -15,7 +15,6 @@
from ..wrapped_decorator import signature_safe_contextmanager
from .layer_function_generator import templatedoc
from .tensor import fill_constant
from .. import core
from ..framework import (
Program,
......@@ -925,11 +924,12 @@ class While:
.. code-block:: python
import paddle.fluid as fluid
import paddle
import numpy as np
i = fluid.layers.fill_constant(shape=[1], dtype='int64', value=0) # loop counter
i = paddle.full(shape=[1], dtype='int64', fill_value=0) # loop counter
loop_len = fluid.layers.fill_constant(shape=[1],dtype='int64', value=10) # loop length
loop_len = paddle.full(shape=[1],dtype='int64', fill_value=10) # loop length
cond = paddle.less_than(x=i, y=loop_len)
while_op = fluid.layers.While(cond=cond)
......@@ -952,11 +952,11 @@ class While:
import numpy as np
paddle.enable_static()
i = fluid.layers.fill_constant(shape=[1], dtype='int64', value=0)
loop_len = fluid.layers.fill_constant(shape=[1], dtype='int64', value=10)
one = fluid.layers.fill_constant(shape=[1], dtype='float32', value=1)
i = paddle.full(shape=[1], dtype='int64', fill_value=0)
loop_len = paddle.full(shape=[1], dtype='int64', fill_value=10)
one = paddle.full(shape=[1], dtype='float32', fill_value=1)
data = fluid.data(name='data', shape=[1], dtype='float32')
sums = fluid.layers.fill_constant(shape=[1], dtype='float32', value=0) # Define the variable to be obtained ouside of While, which name should be different from the variable inside the While to be obtained
sums = paddle.full(shape=[1], dtype='float32', fill_value=0) # Define the variable to be obtained ouside of While, which name should be different from the variable inside the While to be obtained
cond = paddle.less_than(x=i, y=loop_len)
while_op = fluid.layers.While(cond=cond)
......@@ -1537,13 +1537,15 @@ class Switch:
.. code-block:: python
'''
import paddle
import paddle.fluid as fluid
with fluid.layers.Switch() as switch:
with switch.case(cond1):
i = fluid.layers.fill_constant(shape=[1], dtype='int64', value=1)
i = paddle.full(shape=[1], dtype='int64', fill_value=1)
with switch.case(cond2):
i = fluid.layers.fill_constant(shape=[1], dtype='int64', value=2)
i = paddle.full(shape=[1], dtype='int64', fill_value=2)
with switch.default():
i = fluid.layers.fill_constant(shape=[1], dtype='int64', value=0)
i = paddle.full(shape=[1], dtype='int64', fill_value=0)
'''
Args:
......@@ -1561,20 +1563,20 @@ class Switch:
dtype='float32',
persistable=True,
name="learning_rate")
zero_var = fluid.layers.fill_constant(
shape=[1], dtype='float32', value=0.0)
one_var = fluid.layers.fill_constant(
shape=[1], dtype='float32', value=1.0)
two_var = fluid.layers.fill_constant(
shape=[1], dtype='float32', value=2.0)
zero_var = paddle.full(
shape=[1], dtype='float32', fill_value=0.0)
one_var = paddle.full(
shape=[1], dtype='float32', fill_value=1.0)
two_var = paddle.full(
shape=[1], dtype='float32', fill_value=2.0)
global_step = fluid.layers.autoincreased_step_counter(counter_name='@LR_DECAY_COUNTER@', begin=0, step=1)
with fluid.layers.control_flow.Switch() as switch:
with switch.case(global_step == zero_var):
fluid.layers.assign(input=one_var, output=lr)
paddle.assign(input=one_var, output=lr)
with switch.default():
fluid.layers.assign(input=two_var, output=lr)
paddle.assign(input=two_var, output=lr)
exe = fluid.Executor(fluid.CPUPlace())
exe.run(fluid.default_startup_program())
......
python/paddle/fluid/layers/learning_rate_scheduler.py
浏览文件 @ c985b1ac
......@@ -352,10 +352,10 @@ def polynomial_decay(
if cycle:
div_res = paddle.ceil(global_step / decay_steps)
zero_var = tensor.fill_constant(
zero_var = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.0
)
one_var = tensor.fill_constant(
one_var = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=1.0
)
......@@ -364,7 +364,7 @@ def polynomial_decay(
paddle.assign(one_var, output=div_res)
decay_steps = decay_steps * div_res
else:
decay_steps_var = tensor.fill_constant(
decay_steps_var = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=float(decay_steps)
)
global_step = paddle.minimum(x=global_step, y=decay_steps_var)
......@@ -435,21 +435,21 @@ def piecewise_decay(boundaries, values):
with control_flow.Switch() as switch:
for i in range(len(boundaries)):
boundary_val = tensor.fill_constant(
boundary_val = paddle.tensor.fill_constant(
shape=[1],
dtype='float32',
value=float(boundaries[i]),
force_cpu=True,
)
with switch.case(global_step < boundary_val):
tensor.fill_constant(
paddle.tensor.fill_constant(
shape=[1],
dtype="float32",
value=float(values[i]),
out=lr,
)
with switch.default():
tensor.fill_constant(
paddle.tensor.fill_constant(
shape=[1],
dtype="float32",
value=float(values[len(values) - 1]),
......@@ -598,7 +598,7 @@ def linear_lr_warmup(learning_rate, warmup_steps, start_lr, end_lr):
paddle.assign(decayed_lr, lr)
with switch.default():
if not isinstance(learning_rate, Variable):
learning_rate = tensor.fill_constant(
learning_rate = paddle.tensor.fill_constant(
shape=[1], dtype=dtype, value=float(learning_rate)
)
paddle.assign(learning_rate, lr)
......
python/paddle/fluid/layers/nn.py
浏览文件 @ c985b1ac
......@@ -41,7 +41,7 @@ from .layer_function_generator import (
templatedoc,
_generate_doc_string_,
)
from .tensor import fill_constant, zeros
from .tensor import zeros
from .. import unique_name
from .. import core
from ...utils import deprecated
......
python/paddle/fluid/layers/tensor.py
浏览文件 @ c985b1ac
......@@ -39,142 +39,10 @@ from paddle import _C_ops, _legacy_C_ops
__all__ = [
'fill_constant_batch_size_like',
'fill_constant',
'zeros',
]
def fill_constant(shape, dtype, value, force_cpu=False, out=None, name=None):
"""
This OP creates a Tensor with specified `shape` and `dtype`, and
initializes it with a constant specified by `value`.
The attribute `stop_gradient` of the created Tensor is set to True.
Args:
shape(list|tuple|Tensor): Shape of the output Tensor, the data type of ``shape`` is int32 or int64.
If ``shape`` is a list or tuple, the elements of it should be integers or Tensors with shape [1].
If ``shape`` is an Tensor, it should be an 1-D Tensor with date type int32 or int64.
dtype(np.dtype|str): Data type of the output Tensor which can
be float16, float32, float64, uint8, int16, int32, int64.
value(bool|float|int|Tensor): The constant value used to initialize
the Tensor to be created. If ``value`` is an Tensor, it should be an 1-D Tensor.
force_cpu(bool, optional): data should be on CPU if it's true, default value is False.
out(Tensor, optional): Optional output which can be any created
Tensor that meets the requirements to store the result of operation.
if ``out`` is None, a new Tensor will be create to store the result.
name(str, optional): The default value is None. Normally there is no need for user to set this
property. For more information, please refer to :ref:`api_guide_Name`.
Returns:
Tensor: Tensor which is created according to shape and dtype.
Examples:
.. code-block:: python
import paddle.fluid as fluid
# attr shape is a list which doesn't contain Tensor.
data1 = fluid.layers.fill_constant(shape=[2,1], value=0, dtype='int64') # data1=[[0],[0]]
data2 = fluid.layers.fill_constant(shape=[2,1], value=5, dtype='int64', out=data1)
# data1=[[5], [5]] data2=[[5], [5]]
# attr shape is a list which contains Tensor.
positive_2 = fluid.layers.fill_constant([1], "int32", 2)
data3 = fluid.layers.fill_constant(shape=[1, positive_2], dtype='float32', value=1.5) # data3=[[1.5, 1.5]]
# attr shape is a Tensor.
shape = fluid.layers.fill_constant([2], "int32", 2) # shape=[2,2]
data4 = fluid.layers.fill_constant(shape=shape, dtype='bool', value=True) # data4=[[True,True],[True,True]]
# attr value is a Tensor.
val = fluid.layers.fill_constant([1], "float32", 2.0) # val=[2.0]
data5 = fluid.layers.fill_constant(shape=[2,1], value=val, dtype='float32') #data5=[[2.0],[2.0]]
"""
if in_dygraph_mode():
place = _current_expected_place()
if force_cpu:
place = core.CPUPlace()
if isinstance(shape, (list, tuple)):
shape = paddle.utils.convert_shape_to_list(shape)
if not isinstance(dtype, core.VarDesc.VarType):
dtype = convert_np_dtype_to_dtype_(dtype)
if out is None:
out = _C_ops.full(shape, float(value), dtype, place)
out.stop_gradient = True
return out
if out is not None:
# final state mode is support out is not None.
_C_ops.full_(out, shape, float(value), dtype, place)
out.stop_gradient = True
return out
else:
attrs = {'force_cpu': force_cpu}
dtype = convert_dtype(dtype)
if not isinstance(value, Variable):
if dtype in ['uint8', 'int16', 'int32', 'int64']:
attrs['str_value'] = str(int(value))
attrs['value'] = int(value)
else:
attrs['str_value'] = str(float(value))
attrs['value'] = float(value)
helper = LayerHelper("fill_constant", **locals())
inputs = {}
if isinstance(value, Variable):
if convert_dtype(value.dtype) != dtype:
value = paddle.cast(value, dtype)
inputs['ValueTensor'] = value
paddle.utils.check_shape(shape)
check_dtype(
dtype,
'dtype',
[
'bool',
'float16',
'float32',
'float64',
'uint8',
'int16',
'int32',
'int64',
'complex64',
'complex128',
'uint16',
],
'fill_constant',
)
check_type(shape, 'shape', (Variable, list, tuple), 'fill_constant')
if out is not None:
check_variable_and_dtype(
out, 'out', [convert_dtype(dtype)], 'fill_constant'
)
helper = LayerHelper("fill_constant", **locals())
paddle.utils.get_shape_tensor_inputs(
inputs=inputs, attrs=attrs, shape=shape, op_type='fill_constant'
)
if out is None:
out = helper.create_variable_for_type_inference(dtype=dtype)
attrs['dtype'] = out.dtype
helper.append_op(
type='fill_constant',
inputs=inputs,
outputs={'Out': [out]},
attrs=attrs,
stop_gradient=True,
)
out.stop_gradient = True
return out
@deprecated(since='1.8.0', update_to="paddle.fluid.layers.fill_constant")
@templatedoc()
def fill_constant_batch_size_like(
......@@ -214,8 +82,9 @@ def fill_constant_batch_size_like(
.. code-block:: python
import paddle
import paddle.fluid as fluid
like = fluid.layers.fill_constant(shape=[1,2], value=10, dtype='int64') #like=[[10, 10]]
like = paddle.full(shape=[1,2], fill_value=10, dtype='int64') #like=[[10, 10]]
data = fluid.layers.fill_constant_batch_size_like(
input=like, shape=[1], value=0, dtype='int64') #like=[[10, 10]] data=[0]
......@@ -279,10 +148,16 @@ def zeros(shape, dtype, force_cpu=False, name=None):
.. code-block:: python
import paddle.fluid as fluid
import paddle
data = fluid.layers.zeros(shape=[3, 2], dtype='float32') # [[0., 0.], [0., 0.], [0., 0.]]
# shape is a Tensor
shape = fluid.layers.fill_constant(shape=[2], dtype='int32', value=2)
shape = paddle.full(shape=[2], dtype='int32', fill_value=2)
data1 = fluid.layers.zeros(shape=shape, dtype='int32') #[[0, 0], [0, 0]]
"""
return fill_constant(value=0.0, **locals())
# TODO: remove zeros
from paddle.tensor import fill_constant
return fill_constant(
value=0.0, shape=shape, dtype=dtype, force_cpu=force_cpu, name=name
)
python/paddle/fluid/optimizer.py
浏览文件 @ c985b1ac
......@@ -236,7 +236,7 @@ class Optimizer:
None, name='global_step', dtype='int32'
)
tensor.fill_constant(
paddle.tensor.fill_constant(
[1], "int32", self._learning_rate.step_num, out=var_temp
)
......@@ -7393,11 +7393,11 @@ class LookaheadOptimizer:
paddle.increment(x=step, value=1.0)
# lookahead
zero_var = layers.fill_constant(
zero_var = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.0
)
one_var = layers.fill_constant(
one_var = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=1.0
)
......@@ -7747,7 +7747,7 @@ class GradientMergeOptimizer:
# clear gradient_merge_vars
for param, new_grad in new_params_grads:
layers.fill_constant(
paddle.tensor.fill_constant(
shape=new_grad.shape,
dtype=new_grad.dtype,
value=0.0,
......
python/paddle/fluid/tests/unittests/ascend_group.py
浏览文件 @ c985b1ac
......@@ -96,7 +96,9 @@ def init_communicator(
with fluid.program_guard(main_program):
op_type = "c_allreduce_sum"
data = fluid.layers.fill_constant(shape=[1], dtype='float32', value=2.5)
data = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=2.5
)
helper = LayerHelper(op_type, **locals())
helper.append_op(
type=op_type,
......
python/paddle/fluid/tests/unittests/auto_parallel/test_while_op_partition.py
浏览文件 @ c985b1ac
......@@ -117,11 +117,11 @@ def get_program():
with fluid.program_guard(train_program, start_program):
# 循环计数器
i = fluid.layers.fill_constant(shape=[1], dtype='int64', value=0)
i = paddle.tensor.fill_constant(shape=[1], dtype='int64', value=0)
auto.shard_tensor(i, _g_process_mesh, [None])
# 循环次数
loop_len = fluid.layers.fill_constant(
loop_len = paddle.tensor.fill_constant(
shape=[1], dtype='int64', value=epoch_num
)
auto.shard_tensor(loop_len, _g_process_mesh, [None])
......
python/paddle/fluid/tests/unittests/check_nan_inf_base.py
浏览文件 @ c985b1ac
......@@ -50,7 +50,7 @@ def net():
y = paddle.static.data(name="y", shape=[-1, 1], dtype='int64')
# test int64 value
zero = fluid.layers.fill_constant(shape=[1], dtype='int64', value=0)
zero = paddle.tensor.fill_constant(shape=[1], dtype='int64', value=0)
# test float16 value
fp16_zero = paddle.cast(zero, dtype='float16')
......
python/paddle/fluid/tests/unittests/collective/collective_scatter_api.py
浏览文件 @ c985b1ac
......@@ -16,7 +16,6 @@ from test_collective_api_base import TestCollectiveAPIRunnerBase, runtime_main
import paddle
import paddle.fluid as fluid
import paddle.fluid.layers as layers
paddle.enable_static()
......@@ -32,7 +31,7 @@ class TestCollectiveScatterAPI(TestCollectiveAPIRunnerBase):
shape=[10, 1000],
dtype='float32',
)
toutdata = layers.fill_constant(
toutdata = paddle.tensor.fill_constant(
shape=[5, 1000], dtype='float32', value=1.0
)
tensor_list = None
......
python/paddle/fluid/tests/unittests/collective/collective_sendrecv_op_array.py
浏览文件 @ c985b1ac
......@@ -41,7 +41,7 @@ class TestCollectiveSendRecv(TestCollectiveRunnerBase):
data1 = paddle.assign(np.array([[3, 4, 5]], dtype='float32'))
data2 = paddle.assign(np.array([[0, 1, 2]], dtype='float32'))
tensor_array = paddle.tensor.create_array(dtype='float32')
i = fluid.layers.fill_constant(shape=[1], dtype='int64', value=0)
i = paddle.tensor.fill_constant(shape=[1], dtype='int64', value=0)
paddle.tensor.array_write(data1, i, tensor_array)
paddle.tensor.array_write(data2, i + 1, tensor_array)
if self.rank == 0:
......
python/paddle/fluid/tests/unittests/collective/fleet/hybrid_parallel_inference_helper.py
浏览文件 @ c985b1ac
......@@ -19,7 +19,6 @@ import numpy as np
import paddle
import paddle.distributed.fleet as fleet
import paddle.fluid.layers as layers
from paddle.distributed.fleet.utils.hybrid_parallel_inference import (
HybridParallelInferenceHelper,
)
......@@ -66,16 +65,16 @@ class TestHybridParallelInferenceHelperClass(unittest.TestCase):
)
with paddle.fluid.device_guard(f'{device}:all'):
max_len = layers.fill_constant(
max_len = paddle.tensor.fill_constant(
shape=[1], dtype="int64", value=2, force_cpu=False, name="n"
)
step_idx = layers.fill_constant(
step_idx = paddle.tensor.fill_constant(
shape=[1], dtype="int64", value=0, force_cpu=False, name="i"
)
data = paddle.tensor.array_write(X, step_idx)
cond_int = layers.fill_constant(
cond_int = paddle.tensor.fill_constant(
shape=[1],
dtype="int64",
value=0,
......
python/paddle/fluid/tests/unittests/dist_fleet_simnet_bow.py
浏览文件 @ c985b1ac
......@@ -59,7 +59,7 @@ def get_acc(cos_q_nt, cos_q_pt, batch_size):
cond_3 = paddle.sum(cond)
acc = paddle.divide(
cond_3,
fluid.layers.fill_constant(
paddle.tensor.fill_constant(
shape=[1], value=batch_size * 1.0, dtype='float64'
),
name="simnet_acc",
......
python/paddle/fluid/tests/unittests/dygraph_to_static/ifelse_simple_func.py
浏览文件 @ c985b1ac
......@@ -60,7 +60,7 @@ def dyfunc_with_if_else2(x, col=100):
# TODO: Don't support return non-Tensor in Tensor-dependent `if` stament currently.
# `x` is Tensor, `col` is not Tensor, and `col` is the return value of `true_fn` after transformed.
# col = -1
col = fluid.layers.fill_constant(shape=[1], value=-1, dtype="int64")
col = paddle.tensor.fill_constant(shape=[1], value=-1, dtype="int64")
if paddle.mean(x).numpy() > x.numpy()[row][col]:
y = paddle.nn.functional.relu(x)
else:
......@@ -149,7 +149,7 @@ def dyfunc_with_if_else_with_list_geneator(x):
def nested_if_else(x_v):
batch_size = 16
feat_size = x_v.shape[-1]
bias = fluid.layers.fill_constant([feat_size], dtype='float32', value=1)
bias = paddle.tensor.fill_constant([feat_size], dtype='float32', value=1)
if x_v.shape[0] != batch_size:
# TODO: Don't support return non-Tensor in Tensor-dependent `if` stament currently.
# `x_v.shape[0]` is not Tensor, and `batch_size` is the return value of `true_fn` after transformed.
......@@ -160,14 +160,14 @@ def nested_if_else(x_v):
# if tensor.shape is [1], now support to compare with numpy.
if paddle.mean(x_v).numpy() < 0:
y = x_v + bias
w = fluid.layers.fill_constant([feat_size], dtype='float32', value=10)
w = paddle.tensor.fill_constant([feat_size], dtype='float32', value=10)
if y.numpy()[0] < 10:
tmp = y * w
y = paddle.nn.functional.relu(tmp)
if paddle.mean(y).numpy() < batch_size:
y = paddle.abs(y)
else:
tmp = fluid.layers.fill_constant(
tmp = paddle.tensor.fill_constant(
y.shape, dtype='float32', value=-1
)
y = y - tmp
......@@ -185,13 +185,13 @@ def nested_if_else_2(x):
x_shape_0 = x.shape[0]
if x_shape_0 < 1:
if paddle.shape(y).numpy()[0] < 1:
res = fluid.layers.fill_constant(
res = paddle.tensor.fill_constant(
value=2, shape=x.shape, dtype="int32"
)
# `z` is a new var here.
z = y + 1
else:
res = fluid.layers.fill_constant(
res = paddle.tensor.fill_constant(
value=3, shape=x.shape, dtype="int32"
)
else:
......@@ -218,13 +218,13 @@ def nested_if_else_3(x):
else:
y_shape = paddle.shape(y)
if y_shape.numpy()[0] < 1:
res = fluid.layers.fill_constant(
res = paddle.tensor.fill_constant(
value=2, shape=x.shape, dtype="int32"
)
# `z` is created in above code block.
z = y + 1
else:
res = fluid.layers.fill_constant(
res = paddle.tensor.fill_constant(
value=3, shape=x.shape, dtype="int32"
)
# `out` is a new var.
......@@ -259,14 +259,14 @@ class NetWithControlFlowIf(fluid.dygraph.Layer):
)
)
self.constant_vars['bias'] = fluid.layers.fill_constant(
self.constant_vars['bias'] = paddle.tensor.fill_constant(
[5], dtype='float32', value=1
)
# Control flow `if` statement
fc_out = self.fc(input)
if paddle.mean(fc_out).numpy() < 0:
y = fc_out + self.constant_vars['bias']
self.constant_vars['w'] = fluid.layers.fill_constant(
self.constant_vars['w'] = paddle.tensor.fill_constant(
[5], dtype='float32', value=10
)
if y.numpy()[0] < self.alpha:
......@@ -277,12 +277,12 @@ class NetWithControlFlowIf(fluid.dygraph.Layer):
# Nested `if/else`
if y.numpy()[-1] < self.alpha:
# Modify variable of class
self.constant_vars['w'] = fluid.layers.fill_constant(
self.constant_vars['w'] = paddle.tensor.fill_constant(
[hidden_dim], dtype='float32', value=9
)
y = paddle.abs(y)
else:
tmp = fluid.layers.fill_constant(
tmp = paddle.tensor.fill_constant(
y.shape, dtype='float32', value=-1
)
y = y - tmp
......
python/paddle/fluid/tests/unittests/dygraph_to_static/simnet_dygraph_model.py
浏览文件 @ c985b1ac
......@@ -15,7 +15,6 @@
from functools import reduce
import paddle
import paddle.fluid as fluid
import paddle.fluid.param_attr as attr
from paddle.common_ops_import import Variable
from paddle.fluid.dygraph import Layer
......@@ -214,7 +213,7 @@ class ConstantLayer:
shape = list(shape)
input_shape = paddle.shape(input)
shape[0] = input_shape[0]
constant = fluid.layers.fill_constant(shape, dtype, value)
constant = paddle.tensor.fill_constant(shape, dtype, value)
return constant
......
python/paddle/fluid/tests/unittests/dygraph_to_static/simnet_dygraph_model_v2.py
浏览文件 @ c985b1ac
......@@ -210,7 +210,7 @@ class ConstantLayer:
shape = list(shape)
input_shape = paddle.shape(input)
shape[0] = input_shape[0]
constant = paddle.fluid.layers.fill_constant(shape, dtype, value)
constant = paddle.tensor.fill_constant(shape, dtype, value)
return constant
......
python/paddle/fluid/tests/unittests/dygraph_to_static/test_break_continue.py
浏览文件 @ c985b1ac
......@@ -62,7 +62,7 @@ def test_continue_in_for_at_end(x):
def test_continue_in_while(x):
x = fluid.dygraph.to_variable(x)
i = fluid.layers.fill_constant(shape=[1], dtype='int32', value=0)
i = paddle.tensor.fill_constant(shape=[1], dtype='int32', value=0)
while i < 10:
i += 1
if i > 5:
......@@ -94,7 +94,7 @@ def test_break_in_for_at_end(x):
def test_break_in_while(x):
x = fluid.dygraph.to_variable(x)
i = fluid.layers.fill_constant(shape=[1], dtype='int32', value=0)
i = paddle.tensor.fill_constant(shape=[1], dtype='int32', value=0)
while i < 10:
i += 1
if i > 5:
......@@ -116,8 +116,8 @@ def test_break_continue_in_for(x):
break
x += 10086
a = fluid.layers.fill_constant(shape=[1], dtype='int32', value=0)
b = fluid.layers.fill_constant(shape=[1], dtype='int32', value=3)
a = paddle.tensor.fill_constant(shape=[1], dtype='int32', value=0)
b = paddle.tensor.fill_constant(shape=[1], dtype='int32', value=3)
# b = 10
# TODO: add Raise Error and suggestion for usage:
# Py for contains break/continue depends on control-flow.
......@@ -192,7 +192,7 @@ def test_optim_break_in_for(x):
def test_optim_break_in_while(x):
x = paddle.to_tensor(x)
i = fluid.layers.fill_constant(shape=[1], dtype='int32', value=0)
i = paddle.tensor.fill_constant(shape=[1], dtype='int32', value=0)
while i < 10:
if i > 5:
break
......
python/paddle/fluid/tests/unittests/dygraph_to_static/test_dict.py
浏览文件 @ c985b1ac
......@@ -84,12 +84,12 @@ class MainNetWithDict(fluid.dygraph.Layer):
def forward(self, input, max_len=4):
input = fluid.dygraph.to_variable(input)
cache = {
"k": fluid.layers.fill_constant(
"k": paddle.tensor.fill_constant(
shape=[self.batch_size, self.output_size],
dtype='float32',
value=0,
),
"v": fluid.layers.fill_constant(
"v": paddle.tensor.fill_constant(
shape=[self.batch_size, self.output_size],
dtype='float32',
value=0,
......
python/paddle/fluid/tests/unittests/dygraph_to_static/test_error.py
浏览文件 @ c985b1ac
......@@ -25,7 +25,7 @@ from paddle.jit.dy2static.origin_info import unwrap
def inner_func():
fluid.layers.fill_constant(shape=[1, 2], value=9, dtype="int")
paddle.tensor.fill_constant(shape=[1, 2], value=9, dtype="int")
return
......@@ -50,7 +50,7 @@ def func_error_in_compile_time_2(x):
@paddle.jit.to_static
def func_error_in_runtime(x):
x = fluid.dygraph.to_variable(x)
two = fluid.layers.fill_constant(shape=[1], value=2, dtype="int32")
two = paddle.tensor.fill_constant(shape=[1], value=2, dtype="int32")
x = paddle.reshape(x, shape=[1, two])
return x
......@@ -77,7 +77,7 @@ class LayerErrorInCompiletime(fluid.dygraph.Layer):
)
def forward(self, x):
y = self._linear(x)
z = fluid.layers.fill_constant(shape=[1, 2], value=9, dtype="int")
z = paddle.tensor.fill_constant(shape=[1, 2], value=9, dtype="int")
out = paddle.mean(y[z])
return out
......@@ -101,7 +101,7 @@ class LayerErrorInCompiletime2(fluid.dygraph.Layer):
@paddle.jit.to_static
def func_error_in_runtime_with_empty_line(x):
x = fluid.dygraph.to_variable(x)
two = fluid.layers.fill_constant(shape=[1], value=2, dtype="int32")
two = paddle.tensor.fill_constant(shape=[1], value=2, dtype="int32")
x = paddle.reshape(x, shape=[1, two])
......@@ -261,7 +261,7 @@ class TestErrorStaticLayerCallInCompiletime(TestErrorBase):
'inner_func()',
'File "{}", line 28, in inner_func'.format(self.filepath),
'def inner_func():',
'fluid.layers.fill_constant(shape=[1, 2], value=9, dtype="int")',
'paddle.tensor.fill_constant(shape=[1, 2], value=9, dtype="int")',
'<--- HERE',
'return',
]
......@@ -340,7 +340,7 @@ class TestErrorStaticLayerCallInRuntime(TestErrorStaticLayerCallInCompiletime):
self.filepath
),
'x = fluid.dygraph.to_variable(x)',
'two = fluid.layers.fill_constant(shape=[1], value=2, dtype="int32")',
'two = paddle.tensor.fill_constant(shape=[1], value=2, dtype="int32")',
'x = paddle.reshape(x, shape=[1, two])',
'<--- HERE',
'return x',
......@@ -356,7 +356,7 @@ class TestErrorStaticLayerCallInRuntime2(TestErrorStaticLayerCallInRuntime):
'File "{}", line 106, in func_error_in_runtime_with_empty_line'.format(
self.filepath
),
'two = fluid.layers.fill_constant(shape=[1], value=2, dtype="int32")',
'two = paddle.tensor.fill_constant(shape=[1], value=2, dtype="int32")',
'x = paddle.reshape(x, shape=[1, two])',
'<--- HERE',
'return x',
......@@ -379,7 +379,7 @@ class TestJitSaveInCompiletime(TestErrorBase):
'File "{}", line 80, in forward'.format(self.filepath),
'def forward(self, x):',
'y = self._linear(x)',
'z = fluid.layers.fill_constant(shape=[1, 2], value=9, dtype="int")',
'z = paddle.tensor.fill_constant(shape=[1, 2], value=9, dtype="int")',
'<--- HERE',
'out = paddle.mean(y[z])',
'return out',
......
python/paddle/fluid/tests/unittests/dygraph_to_static/test_for_enumerate.py
浏览文件 @ c985b1ac
......@@ -26,7 +26,7 @@ from paddle.static import InputSpec
# 0. for in range var.numpy()[0]
@paddle.jit.to_static
def for_in_range(x):
z = fluid.layers.fill_constant([1], 'int32', 0)
z = paddle.tensor.fill_constant([1], 'int32', 0)
x = fluid.dygraph.to_variable(x)
for i in range(x.numpy()[0]):
z = z + i
......@@ -36,7 +36,7 @@ def for_in_range(x):
# 1. for iter list
@paddle.jit.to_static
def for_iter_list(x_array):
z = fluid.layers.fill_constant([1], 'int32', 0)
z = paddle.tensor.fill_constant([1], 'int32', 0)
for x in x_array:
z = z + x
return z
......@@ -45,7 +45,7 @@ def for_iter_list(x_array):
# 2. for enumerate list
@paddle.jit.to_static
def for_enumerate_list(x_array):
z = fluid.layers.fill_constant([1], 'int32', 0)
z = paddle.tensor.fill_constant([1], 'int32', 0)
for i, x in enumerate(x_array):
z = z + x + i
return z
......@@ -54,7 +54,7 @@ def for_enumerate_list(x_array):
# 3. for iter var.numpy()
@paddle.jit.to_static
def for_iter_var_numpy(x_array):
z = fluid.layers.fill_constant([1], 'int32', 0)
z = paddle.tensor.fill_constant([1], 'int32', 0)
x_array = fluid.dygraph.to_variable(x_array)
for x in x_array.numpy():
z = z + x
......@@ -64,8 +64,8 @@ def for_iter_var_numpy(x_array):
# 4. for enumerate var.numpy()
@paddle.jit.to_static
def for_enumerate_var_numpy(x_array):
y = fluid.layers.fill_constant([1], 'int32', 0)
z = fluid.layers.fill_constant([1], 'int32', 0)
y = paddle.tensor.fill_constant([1], 'int32', 0)
z = paddle.tensor.fill_constant([1], 'int32', 0)
x_array = fluid.dygraph.to_variable(x_array)
for i, x in enumerate(x_array.numpy()):
y = y + i
......@@ -76,8 +76,8 @@ def for_enumerate_var_numpy(x_array):
# 5. for enumerate var.numpy() with start
@paddle.jit.to_static
def for_enumerate_var_numpy_with_start(x_array):
y = fluid.layers.fill_constant([1], 'int32', 0)
z = fluid.layers.fill_constant([1], 'int32', 0)
y = paddle.tensor.fill_constant([1], 'int32', 0)
z = paddle.tensor.fill_constant([1], 'int32', 0)
x_array = fluid.dygraph.to_variable(x_array)
for i, x in enumerate(x_array.numpy(), 1):
y = y + i
......@@ -88,7 +88,7 @@ def for_enumerate_var_numpy_with_start(x_array):
# 6. for in range with break
@paddle.jit.to_static
def for_in_range_with_break(x):
z = fluid.layers.fill_constant([1], 'int32', 0)
z = paddle.tensor.fill_constant([1], 'int32', 0)
x = fluid.dygraph.to_variable(x)
for i in range(x.numpy()[0]):
z = z + i
......@@ -100,8 +100,8 @@ def for_in_range_with_break(x):
# 7. for enumerate var.numpy() with break
@paddle.jit.to_static
def for_enumerate_var_numpy_with_break(x_array):
y = fluid.layers.fill_constant([1], 'int32', 0)
z = fluid.layers.fill_constant([1], 'int32', 0)
y = paddle.tensor.fill_constant([1], 'int32', 0)
z = paddle.tensor.fill_constant([1], 'int32', 0)
x_array = fluid.dygraph.to_variable(x_array)
for i, x in enumerate(x_array.numpy()):
y = y + i
......@@ -114,8 +114,8 @@ def for_enumerate_var_numpy_with_break(x_array):
# 8. for enumerate var.numpy() with continue
@paddle.jit.to_static
def for_enumerate_var_numpy_with_continue(x_array):
y = fluid.layers.fill_constant([1], 'int32', 0)
z = fluid.layers.fill_constant([1], 'int32', 0)
y = paddle.tensor.fill_constant([1], 'int32', 0)
z = paddle.tensor.fill_constant([1], 'int32', 0)
x_array = fluid.dygraph.to_variable(x_array)
for i, x in enumerate(x_array.numpy()):
y = y + i
......@@ -128,8 +128,8 @@ def for_enumerate_var_numpy_with_continue(x_array):
# 9. for enumerate var.numpy() with start & break
@paddle.jit.to_static
def for_enumerate_var_numpy_with_start_break(x_array):
y = fluid.layers.fill_constant([1], 'int32', 0)
z = fluid.layers.fill_constant([1], 'int32', 0)
y = paddle.tensor.fill_constant([1], 'int32', 0)
z = paddle.tensor.fill_constant([1], 'int32', 0)
x_array = fluid.dygraph.to_variable(x_array)
for i, x in enumerate(x_array.numpy(), 1):
y = y + i
......@@ -142,8 +142,8 @@ def for_enumerate_var_numpy_with_start_break(x_array):
# 10. for enumerate var.numpy() with start & continue
@paddle.jit.to_static
def for_enumerate_var_numpy_with_start_continue(x_array):
y = fluid.layers.fill_constant([1], 'int32', 0)
z = fluid.layers.fill_constant([1], 'int32', 0)
y = paddle.tensor.fill_constant([1], 'int32', 0)
z = paddle.tensor.fill_constant([1], 'int32', 0)
x_array = fluid.dygraph.to_variable(x_array)
for i, x in enumerate(x_array.numpy(), 1):
y = y + i
......@@ -156,7 +156,7 @@ def for_enumerate_var_numpy_with_start_continue(x_array):
# 11. for iter var
@paddle.jit.to_static
def for_iter_var(x_array):
z = fluid.layers.fill_constant([1], 'int32', 0)
z = paddle.tensor.fill_constant([1], 'int32', 0)
x_array = fluid.dygraph.to_variable(x_array)
for x in x_array:
......@@ -167,8 +167,8 @@ def for_iter_var(x_array):
# 12. for enumerate var
@paddle.jit.to_static
def for_enumerate_var(x_array):
y = fluid.layers.fill_constant([1], 'int32', 0)
z = fluid.layers.fill_constant([1], 'int32', 0)
y = paddle.tensor.fill_constant([1], 'int32', 0)
z = paddle.tensor.fill_constant([1], 'int32', 0)
x_array = fluid.dygraph.to_variable(x_array)
for i, x in enumerate(x_array):
y = y + i
......@@ -181,12 +181,12 @@ def for_enumerate_var(x_array):
def for_iter_var_list(x):
# 1. prepare data, ref test_list.py
x = fluid.dygraph.to_variable(x)
iter_num = fluid.layers.fill_constant(shape=[1], value=5, dtype="int32")
iter_num = paddle.tensor.fill_constant(shape=[1], value=5, dtype="int32")
a = []
for i in range(iter_num):
a.append(x + i)
# 2. iter list[var]
y = fluid.layers.fill_constant([1], 'int32', 0)
y = paddle.tensor.fill_constant([1], 'int32', 0)
for x in a:
y = y + x
return y
......@@ -197,13 +197,13 @@ def for_iter_var_list(x):
def for_enumerate_var_list(x):
# 1. prepare data, ref test_list.py
x = fluid.dygraph.to_variable(x)
iter_num = fluid.layers.fill_constant(shape=[1], value=5, dtype="int32")
iter_num = paddle.tensor.fill_constant(shape=[1], value=5, dtype="int32")
a = []
for i in range(iter_num):
a.append(x + i)
# 2. iter list[var]
y = fluid.layers.fill_constant([1], 'int32', 0)
z = fluid.layers.fill_constant([1], 'int32', 0)
y = paddle.tensor.fill_constant([1], 'int32', 0)
z = paddle.tensor.fill_constant([1], 'int32', 0)
for i, x in enumerate(a):
y = y + i
z = z + x
......@@ -213,7 +213,7 @@ def for_enumerate_var_list(x):
# 15. for enumerate list[var] with a nested for range
@paddle.jit.to_static
def for_enumerate_var_with_nested_range(x_array):
x = fluid.layers.fill_constant([1], 'int32', 0)
x = paddle.tensor.fill_constant([1], 'int32', 0)
x_array = fluid.dygraph.to_variable(x_array)
for i, num in enumerate(x_array):
for idx in range(num):
......@@ -224,7 +224,7 @@ def for_enumerate_var_with_nested_range(x_array):
# 16. for iter var[idx]
@paddle.jit.to_static
def for_iter_var_idx(x_array):
z = fluid.layers.fill_constant([1], 'int32', 0)
z = paddle.tensor.fill_constant([1], 'int32', 0)
x_array = fluid.dygraph.to_variable(x_array)
for x in x_array[0:]:
......@@ -306,7 +306,7 @@ class ForwardContainsForLayer(paddle.nn.Layer):
# 21. for original list
@paddle.jit.to_static
def for_original_list():
z = fluid.layers.fill_constant([1], 'int32', 0)
z = paddle.tensor.fill_constant([1], 'int32', 0)
for x in [1, 2, 3]:
z = z + x
return z
......@@ -315,7 +315,7 @@ def for_original_list():
# 22. for original tuple
@paddle.jit.to_static
def for_original_tuple():
z = fluid.layers.fill_constant([1], 'int32', 0)
z = paddle.tensor.fill_constant([1], 'int32', 0)
for x in (1, 2, 3):
z = z + x
return z
......
python/paddle/fluid/tests/unittests/dygraph_to_static/test_ifelse.py
浏览文件 @ c985b1ac
......@@ -158,8 +158,8 @@ def dyfunc_ifExp_with_while(x):
i += 1
return [i, ten, y]
i = fluid.layers.fill_constant(shape=[1], dtype='int64', value=0)
ten = fluid.layers.fill_constant(shape=[1], dtype='int64', value=10)
i = paddle.tensor.fill_constant(shape=[1], dtype='int64', value=0)
ten = paddle.tensor.fill_constant(shape=[1], dtype='int64', value=10)
i, ten, y = paddle.static.nn.while_loop(cond, body, [i, ten, y])
return y[0]
......@@ -180,7 +180,7 @@ def dyfunc_ifExp(x):
def map_func(func, tensor_list):
return [func(x) for x in tensor_list]
i = fluid.layers.fill_constant(shape=[1], dtype='int64', value=0)
i = paddle.tensor.fill_constant(shape=[1], dtype='int64', value=0)
# It will be converted into `layers.cond` as followed.
# map_func(lambda x: paddle.static.nn.cond(i==1, lambda: x, lambda: add_fn(x), y)
# `if (Tensor) == 1` is supported in dygraph.
......
python/paddle/fluid/tests/unittests/dygraph_to_static/test_len.py
浏览文件 @ c985b1ac
......@@ -35,7 +35,7 @@ def len_with_tensor(x):
def len_with_lod_tensor_array(x):
x = fluid.dygraph.to_variable(x)
i = fluid.layers.fill_constant(shape=[1], dtype='int64', value=0)
i = paddle.tensor.fill_constant(shape=[1], dtype='int64', value=0)
arr = paddle.tensor.array_write(x, i=i)
arr_len = len(arr)
......
python/paddle/fluid/tests/unittests/dygraph_to_static/test_list.py
浏览文件 @ c985b1ac
......@@ -42,7 +42,7 @@ def test_list_append_in_if(x):
a.append(x)
else:
a.append(
fluid.layers.fill_constant(shape=[1, 2], value=9, dtype="int64")
paddle.tensor.fill_constant(shape=[1, 2], value=9, dtype="int64")
)
# TODO(Aurelius84): Currently, run_program_op doesn't support output LoDTensorArray.
return a[0]
......@@ -51,7 +51,7 @@ def test_list_append_in_if(x):
def test_list_append_in_for_loop(x, iter_num):
x = fluid.dygraph.to_variable(x)
# Use `fill_constant` so that static analysis can analyze the type of iter_num is Tensor
iter_num = fluid.layers.fill_constant(
iter_num = paddle.tensor.fill_constant(
shape=[1], value=iter_num, dtype="int32"
) # TODO(liym27): Delete it if the type of parameter iter_num can be resolved
a = []
......@@ -88,7 +88,7 @@ def test_list_append_in_for_loop_with_concat(x, iter_num):
x = fluid.dygraph.to_variable(x)
a = []
# Use `fill_constant` so that static analysis can analyze the type of iter_num is Tensor
iter_num = fluid.layers.fill_constant(
iter_num = paddle.tensor.fill_constant(
shape=[1], value=iter_num, dtype="int32"
) # TODO(liym27): Delete it if the type of parameter iter_num can be resolved
for i in range(iter_num):
......@@ -99,7 +99,7 @@ def test_list_append_in_for_loop_with_concat(x, iter_num):
def test_list_append_in_while_loop(x, iter_num):
x = fluid.dygraph.to_variable(x)
iter_num = fluid.layers.fill_constant(
iter_num = paddle.tensor.fill_constant(
shape=[1], value=iter_num, dtype="int32"
)
a = []
......@@ -112,7 +112,7 @@ def test_list_append_in_while_loop(x, iter_num):
def test_list_append_in_while_loop_with_stack(x, iter_num):
x = fluid.dygraph.to_variable(x)
iter_num = fluid.layers.fill_constant(
iter_num = paddle.tensor.fill_constant(
shape=[1], value=iter_num, dtype="int32"
)
a = []
......@@ -159,11 +159,11 @@ def test_list_pop_in_if(x):
if x.numpy()[0] > 0:
a.append(x)
b.append(x + 1)
a.append(fluid.layers.fill_constant(shape=[1], value=1, dtype="int64"))
a.append(paddle.tensor.fill_constant(shape=[1], value=1, dtype="int64"))
else:
a.append(x + 1)
b.append(x - 1)
a.append(fluid.layers.fill_constant(shape=[2], value=2, dtype="int64"))
a.append(paddle.tensor.fill_constant(shape=[2], value=2, dtype="int64"))
item1 = a.pop(1)
return item1, b[-1]
......@@ -171,7 +171,7 @@ def test_list_pop_in_if(x):
def test_list_pop_in_for_loop(x, iter_num):
x = fluid.dygraph.to_variable(x)
# Use `fill_constant` so that static analysis can analyze the type of iter_num is Tensor
iter_num = fluid.layers.fill_constant(
iter_num = paddle.tensor.fill_constant(
shape=[1], value=iter_num, dtype="int32"
) # TODO(liym27): Delete it if the type of parameter iter_num can be resolved
......@@ -189,7 +189,7 @@ def test_list_pop_in_for_loop(x, iter_num):
def test_list_pop_in_while_loop(x, iter_num):
x = fluid.dygraph.to_variable(x)
iter_num = fluid.layers.fill_constant(
iter_num = paddle.tensor.fill_constant(
shape=[1], value=iter_num, dtype="int32"
)
a = []
......
python/paddle/fluid/tests/unittests/dygraph_to_static/test_loop.py
浏览文件 @ c985b1ac
......@@ -89,7 +89,7 @@ def for_loop_dyfunc(max_len):
def for_loop_dyfunc2(max_len):
# Test case: a variable is used and created in loop, but used before created
x = fluid.layers.fill_constant(shape=[1, 2], dtype="int32", value=1)
x = paddle.tensor.fill_constant(shape=[1, 2], dtype="int32", value=1)
for i in range(max_len):
if i > 1:
......@@ -97,7 +97,7 @@ def for_loop_dyfunc2(max_len):
a = 1
q, _ = x.shape # test var x.shape only used but not created in loop
ret = fluid.layers.fill_constant(shape=[1], dtype="int32", value=s + q)
ret = paddle.tensor.fill_constant(shape=[1], dtype="int32", value=s + q)
return ret
......@@ -189,7 +189,7 @@ def for_loop_class_var(max_len):
foo = Foo()
# Use `to_variable` so that static analysis can analyze the type of X is Tensor
max_len = fluid.layers.fill_constant(
max_len = paddle.tensor.fill_constant(
shape=[1], value=max_len, dtype="int32"
)
......@@ -206,8 +206,8 @@ def var_create_in_for_loop(max_len):
def nested_for_loop_dyfunc():
two = fluid.layers.fill_constant(shape=[1], value=2, dtype="int32")
three = fluid.layers.fill_constant(shape=[1], value=3, dtype="int32")
two = paddle.tensor.fill_constant(shape=[1], value=2, dtype="int32")
three = paddle.tensor.fill_constant(shape=[1], value=3, dtype="int32")
for j in range(two):
for i in range(10):
a = 2 + j
......
python/paddle/fluid/tests/unittests/dygraph_to_static/test_return.py
浏览文件 @ c985b1ac
......@@ -69,7 +69,7 @@ def test_return_if_else(x):
@to_static
def test_return_in_while(x):
x = fluid.dygraph.to_variable(x)
i = fluid.layers.fill_constant(shape=[1], dtype='int32', value=0)
i = paddle.tensor.fill_constant(shape=[1], dtype='int32', value=0)
while i < 10:
i += 1
if i > 5:
......
python/paddle/fluid/tests/unittests/dygraph_to_static/test_tensor_shape.py
浏览文件 @ c985b1ac
......@@ -109,11 +109,11 @@ def dyfunc_with_if_1(x):
# `res.shape[0]` is transformed into
# `paddle.jit.dy2static.convert_var_shape(res)[0]`
if res.shape[0] > 1:
res = fluid.layers.fill_constant(
res = paddle.tensor.fill_constant(
value=2, shape=x.shape, dtype="int32"
)
else:
res = fluid.layers.fill_constant(
res = paddle.tensor.fill_constant(
value=3, shape=x.shape, dtype="int32"
)
return res
......@@ -125,14 +125,14 @@ def dyfunc_with_if_2(x):
if len(x.shape) < 1:
res = x
else:
res = fluid.layers.fill_constant(value=8, shape=x.shape, dtype="int32")
res = paddle.tensor.fill_constant(value=8, shape=x.shape, dtype="int32")
return res
def dyfunc_with_for_1(x):
x = fluid.dygraph.to_variable(x)
res = fluid.layers.fill_constant(value=0, shape=[1], dtype="int32")
res = paddle.tensor.fill_constant(value=0, shape=[1], dtype="int32")
# `x.shape[0]` is transformed into `paddle.jit.dy2static.convert_var_shape(x)[0]`
for i in range(x.shape[0]):
res += 1
......@@ -142,7 +142,7 @@ def dyfunc_with_for_1(x):
def dyfunc_with_for_2(x):
x = fluid.dygraph.to_variable(x)
x_shape_0 = x.shape[0]
res = fluid.layers.fill_constant(value=0, shape=[1], dtype="int32")
res = paddle.tensor.fill_constant(value=0, shape=[1], dtype="int32")
# `x_shape_0` is transformed into `paddle.jit.dy2static.convert_var_shape(x)[0]`
for i in range(x_shape_0):
......@@ -152,7 +152,7 @@ def dyfunc_with_for_2(x):
def dyfunc_with_for_3(x):
x = fluid.dygraph.to_variable(x)
res = fluid.layers.fill_constant(value=0, shape=[1], dtype="int32")
res = paddle.tensor.fill_constant(value=0, shape=[1], dtype="int32")
# `len(x.shape)` is not transformed.
for i in range(len(x.shape)):
res += 1
......@@ -162,7 +162,7 @@ def dyfunc_with_for_3(x):
def dyfunc_with_while_1(x):
x = fluid.dygraph.to_variable(x)
res = fluid.layers.fill_constant(value=0, shape=[1], dtype="int32")
res = paddle.tensor.fill_constant(value=0, shape=[1], dtype="int32")
# `x.shape[0]` is transformed into `paddle.jit.dy2static.convert_var_shape(x)[0]`
i = 1
while i < x.shape[0]:
......@@ -174,7 +174,7 @@ def dyfunc_with_while_1(x):
def dyfunc_with_while_2(x):
x = fluid.dygraph.to_variable(x)
x_shape_0 = x.shape[0]
res = fluid.layers.fill_constant(value=0, shape=[1], dtype="int32")
res = paddle.tensor.fill_constant(value=0, shape=[1], dtype="int32")
i = 1
# `x_shape_0` is transformed into `paddle.jit.dy2static.convert_var_shape(x)[0]`
while i < x_shape_0:
......@@ -186,7 +186,7 @@ def dyfunc_with_while_2(x):
def dyfunc_with_while_3(x):
x = fluid.dygraph.to_variable(x)
x_shape = x.shape
res = fluid.layers.fill_constant(value=0, shape=[1], dtype="int32")
res = paddle.tensor.fill_constant(value=0, shape=[1], dtype="int32")
i = 1
# `len(x.shape)` is not transformed.
......@@ -601,7 +601,7 @@ def dyfunc_with_static_convert_var_shape(x):
else:
# Test for correctly to find `batch_size__static_convert_var_shape_suffix_0` in
# deeply nested scope.
res = fluid.layers.fill_constant(
res = paddle.tensor.fill_constant(
value=8, shape=[batch_size], dtype="int32"
)
......
python/paddle/fluid/tests/unittests/dygraph_to_static/transformer_dygraph_model.py
浏览文件 @ c985b1ac
......@@ -16,7 +16,6 @@ import numpy as np
import paddle
import paddle.fluid as fluid
import paddle.fluid.layers as layers
import paddle.nn.functional as F
from paddle.fluid.dygraph import Layer, to_variable
from paddle.jit.api import dygraph_to_static_func
......@@ -796,7 +795,7 @@ class Transformer(Layer):
# constant number
inf = float(1.0 * 1e7)
max_len = (enc_output.shape[1] + 20) if max_len is None else max_len
vocab_size_tensor = layers.fill_constant(
vocab_size_tensor = paddle.tensor.fill_constant(
shape=[1], dtype="int64", value=self.trg_vocab_size
)
end_token_tensor = to_variable(
......@@ -824,7 +823,7 @@ class Transformer(Layer):
np.full([batch_size, beam_size], 0, dtype="bool")
)
trg_word = layers.fill_constant(
trg_word = paddle.tensor.fill_constant(
shape=[batch_size * beam_size, 1], dtype="int64", value=bos_id
)
......@@ -838,12 +837,12 @@ class Transformer(Layer):
# init states (caches) for transformer, need to be updated according to selected beam
caches = [
{
"k": layers.fill_constant(
"k": paddle.tensor.fill_constant(
shape=[batch_size, beam_size, self.n_head, 0, self.d_key],
dtype=enc_output.dtype,
value=0,
),
"v": layers.fill_constant(
"v": paddle.tensor.fill_constant(
shape=[batch_size, beam_size, self.n_head, 0, self.d_value],
dtype=enc_output.dtype,
value=0,
......@@ -853,7 +852,7 @@ class Transformer(Layer):
]
for i in range(paddle.to_tensor(max_len)):
trg_pos = layers.fill_constant(
trg_pos = paddle.tensor.fill_constant(
shape=trg_word.shape, dtype="int64", value=i
)
caches = paddle.utils.map_structure(
......
python/paddle/fluid/tests/unittests/ipu/test_clip_op_ipu.py
浏览文件 @ c985b1ac
......@@ -89,10 +89,10 @@ class TestMinMaxTensor(TestBase):
name=self.feed_list[0], shape=self.feed_shape[0], dtype='float32'
)
min = paddle.fluid.layers.fill_constant(
min = paddle.tensor.fill_constant(
name="min", shape=[1], dtype='float32', value=0.1
)
max = paddle.fluid.layers.fill_constant(
max = paddle.tensor.fill_constant(
name="max", shape=[1], dtype='float32', value=3.4
)
x = paddle.clip(x, min=min, max=max)
......@@ -106,7 +106,7 @@ class TestMinTensor(TestBase):
name=self.feed_list[0], shape=self.feed_shape[0], dtype='float32'
)
min = paddle.fluid.layers.fill_constant(
min = paddle.tensor.fill_constant(
name="min", shape=[1], dtype='float32', value=0.1
)
x = paddle.clip(x, min=min)
......@@ -120,7 +120,7 @@ class TestMaxTensor(TestBase):
name=self.feed_list[0], shape=self.feed_shape[0], dtype='float32'
)
max = paddle.fluid.layers.fill_constant(
max = paddle.tensor.fill_constant(
name="max", shape=[1], dtype='float32', value=3.4
)
x = paddle.clip(x, max=max)
......@@ -134,7 +134,7 @@ class TestCombine1(TestBase):
name=self.feed_list[0], shape=self.feed_shape[0], dtype='float32'
)
min = paddle.fluid.layers.fill_constant(
min = paddle.tensor.fill_constant(
name="min", shape=[1], dtype='float32', value=0.1
)
x = paddle.clip(x, min=min, max=3.4)
......@@ -148,7 +148,7 @@ class TestCombine2(TestBase):
name=self.feed_list[0], shape=self.feed_shape[0], dtype='float32'
)
max = paddle.fluid.layers.fill_constant(
max = paddle.tensor.fill_constant(
name="max", shape=[1], dtype='float32', value=3.4
)
x = paddle.clip(x, min=0.1, max=max)
......@@ -186,10 +186,10 @@ class TestIntMinMax(TestBase):
x = paddle.static.data(
name=self.feed_list[0], shape=self.feed_shape[0], dtype='int32'
)
min = paddle.fluid.layers.fill_constant(
min = paddle.tensor.fill_constant(
name="min", shape=[1], dtype='int32', value=1
)
max = paddle.fluid.layers.fill_constant(
max = paddle.tensor.fill_constant(
name="max", shape=[1], dtype='int32', value=3
)
x = paddle.clip(x, min=min, max=max)
......
python/paddle/fluid/tests/unittests/ipu/test_expand_op_ipu.py
浏览文件 @ c985b1ac
......@@ -80,7 +80,7 @@ class TestCase1(TestBase):
x = paddle.static.data(
name=self.feed_list[0], shape=self.feed_shape[0], dtype="float32"
)
expand_times = paddle.fluid.layers.fill_constant(
expand_times = paddle.tensor.fill_constant(
shape=[len(self.feed_shape[0])], dtype="int32", value=2
)
out = paddle.expand(x, expand_times, **self.attrs)
......
python/paddle/fluid/tests/unittests/ipu/test_expand_v2_op_ipu.py
浏览文件 @ c985b1ac
......@@ -100,7 +100,7 @@ class TestCase4(TestBase):
'dtype': 'int32',
'value': 3,
}
y = paddle.fluid.layers.fill_constant(**self.attrs)
y = paddle.tensor.fill_constant(**self.attrs)
out = paddle.expand(x, shape=y)
self.fetch_list = [out.name]
......
python/paddle/fluid/tests/unittests/ipu/test_fill_constant_op_ipu.py
浏览文件 @ c985b1ac
......@@ -46,7 +46,7 @@ class TestBase(IPUOpTest):
@IPUOpTest.static_graph
def build_model(self):
x = paddle.fluid.layers.fill_constant(**self.attrs)
x = paddle.tensor.fill_constant(**self.attrs)
out = paddle.add(x, x)
self.fetch_list = [out.name]
......
python/paddle/fluid/tests/unittests/ipu/test_pad_op_ipu.py
浏览文件 @ c985b1ac
......@@ -73,7 +73,7 @@ class TestCase1(TestBase):
'dtype': 'int32',
'value': 2,
}
y = paddle.fluid.layers.fill_constant(**const_attrs)
y = paddle.tensor.fill_constant(**const_attrs)
pad = paddle.nn.functional.pad(x, pad=y)
self.fetch_list = [pad.name]
......
python/paddle/fluid/tests/unittests/ipu/test_topk_op_ipu.py
浏览文件 @ c985b1ac
......@@ -57,7 +57,7 @@ class TestTopKOp(IPUOpTest):
topk_values, topk_indices = self.op(x, **self.attrs)
else:
# !important, popart cannot accept non const tensor
K_t = paddle.fluid.layers.fill_constant(
K_t = paddle.tensor.fill_constant(
shape=[1], dtype='int32', value=self.k, name="in_2"
)
topk_values, topk_indices = self.op(x, K_t, **self.attrs)
......
python/paddle/fluid/tests/unittests/ipu/test_yolo_box_op_ipu.py
浏览文件 @ c985b1ac
......@@ -64,7 +64,7 @@ class TestBase(IPUOpTest):
'dtype': 'int32',
'value': 6,
}
img_size = paddle.fluid.layers.fill_constant(**attrs)
img_size = paddle.tensor.fill_constant(**attrs)
out = paddle.vision.ops.yolo_box(x=x, img_size=img_size, **self.attrs)
self.fetch_list = [x.name for x in out]
......
python/paddle/fluid/tests/unittests/ir/test_ir_fusion_group_pass.py
浏览文件 @ c985b1ac
......@@ -20,7 +20,6 @@ from pass_test import PassTest
import paddle
import paddle.fluid as fluid
import paddle.fluid.core as core
import paddle.fluid.layers as layers
class FusionGroupPassTest(PassTest):
......@@ -86,7 +85,7 @@ class FusionGroupPassComplicatedTest(FusionGroupPassTest):
with fluid.program_guard(self.main_program, self.startup_program):
self.feed_vars = self._prepare_feed_vars([32, 64], dtype, 5, False)
one = layers.fill_constant(shape=[1], dtype=dtype, value=1.0)
one = paddle.tensor.fill_constant(shape=[1], dtype=dtype, value=1.0)
tmp_0 = one * self.feed_vars[0]
# subgraph with 9 op nodes
tmp_1 = tmp_0 * paddle.nn.functional.sigmoid(
......@@ -142,7 +141,9 @@ class FusionGroupPassTestCastAndFP16(FusionGroupPassTest):
tmp_0 = self.feed_vars[0] * self.feed_vars[1]
tmp_0.stop_gradient = False
tmp_1 = paddle.cast(tmp_0, dtype="float16")
zero = layers.fill_constant(shape=[128], dtype="float16", value=0)
zero = paddle.tensor.fill_constant(
shape=[128], dtype="float16", value=0
)
# TODO(xreki): fix precision problem when using softmax of float16.
# tmp_2 = layers.softmax(tmp_1)
tmp_2 = paddle.add(tmp_1, zero)
......@@ -212,7 +213,9 @@ class FusionGroupPassFillConstantTest(FusionGroupPassTest):
tmp_0 = paddle.add(self.feed_vars[0], self.feed_vars[1])
tmp_0.stop_gradient = False
tmp_1 = layers.fill_constant(shape=[2, 2], dtype=dtype, value=2.0)
tmp_1 = paddle.tensor.fill_constant(
shape=[2, 2], dtype=dtype, value=2.0
)
tmp_2 = paddle.scale(
tmp_1, scale=3.0, bias=1.0, bias_after_scale=True
)
......
python/paddle/fluid/tests/unittests/ir/test_ir_subgraph_python_interface.py
浏览文件 @ c985b1ac
......@@ -16,7 +16,6 @@ import unittest
import paddle
import paddle.fluid as fluid
import paddle.fluid.layers as layers
from paddle.fluid import core
from paddle.fluid.framework import IrGraph, Program, program_guard
from paddle.fluid.tests.unittests.op_test import OpTestTool
......@@ -55,8 +54,12 @@ class TestQuantizationSubGraph(unittest.TestCase):
return linear_fc(5)
with program_guard(main_program, startup_program):
x = layers.fill_constant(shape=[1], dtype='float32', value=0.1)
y = layers.fill_constant(shape=[1], dtype='float32', value=0.23)
x = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.1
)
y = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.23
)
pred = paddle.less_than(y, x)
out = paddle.static.nn.cond(pred, true_func, false_func)
......
python/paddle/fluid/tests/unittests/mlu/test_expand_v2_op_mlu.py
浏览文件 @ c985b1ac
......@@ -235,7 +235,7 @@ class TestExpandV2API(unittest.TestCase):
name='x', shape=[12, 14], dtype="float32"
)
positive_2 = fluid.layers.fill_constant([1], "int32", 12)
positive_2 = paddle.tensor.fill_constant([1], "int32", 12)
expand_shape = paddle.static.data(
name="expand_shape",
shape=[2],
......
python/paddle/fluid/tests/unittests/mlu/test_fill_constant_op_mlu.py
浏览文件 @ c985b1ac
......@@ -268,8 +268,8 @@ class TestFillConstantOp2_ValueTensor(OpTest):
class TestFillConstantAPI(unittest.TestCase):
def test_api(self):
positive_2_int32 = fluid.layers.fill_constant([1], "int32", 2)
positive_2_int64 = fluid.layers.fill_constant([1], "int64", 2)
positive_2_int32 = paddle.tensor.fill_constant([1], "int32", 2)
positive_2_int64 = paddle.tensor.fill_constant([1], "int64", 2)
shape_tensor_int32 = fluid.data(
name="shape_tensor_int32", shape=[2], dtype="int32"
......@@ -278,41 +278,41 @@ class TestFillConstantAPI(unittest.TestCase):
name="shape_tensor_int64", shape=[2], dtype="int64"
)
out_1 = fluid.layers.fill_constant(
out_1 = paddle.tensor.fill_constant(
shape=[1, 2], dtype="float32", value=1.1
)
out_2 = fluid.layers.fill_constant(
out_2 = paddle.tensor.fill_constant(
shape=[1, positive_2_int32], dtype="float32", value=1.1
)
out_3 = fluid.layers.fill_constant(
out_3 = paddle.tensor.fill_constant(
shape=[1, positive_2_int64], dtype="float32", value=1.1
)
out_4 = fluid.layers.fill_constant(
out_4 = paddle.tensor.fill_constant(
shape=shape_tensor_int32, dtype="float32", value=1.1
)
out_5 = fluid.layers.fill_constant(
out_5 = paddle.tensor.fill_constant(
shape=shape_tensor_int64, dtype="float32", value=1.1
)
out_6 = fluid.layers.fill_constant(
out_6 = paddle.tensor.fill_constant(
shape=shape_tensor_int64, dtype=np.float32, value=1.1
)
val1 = fluid.layers.fill_constant(
val1 = paddle.tensor.fill_constant(
shape=[1], dtype=np.float32, value=1.1
)
val2 = fluid.layers.fill_constant(
val2 = paddle.tensor.fill_constant(
shape=[1], dtype=np.float64, value=1.1
)
out_7 = fluid.layers.fill_constant(
out_7 = paddle.tensor.fill_constant(
shape=shape_tensor_int64, dtype=np.float32, value=val1
)
out_8 = fluid.layers.fill_constant(
out_8 = paddle.tensor.fill_constant(
shape=shape_tensor_int64, dtype=np.float32, value=val2
)
......@@ -345,16 +345,16 @@ class TestFillConstantImperative(unittest.TestCase):
shape = fluid.dygraph.to_variable(data1)
val = fluid.dygraph.to_variable(data2)
value = fluid.dygraph.to_variable(data3)
res1 = fluid.layers.fill_constant(
res1 = paddle.tensor.fill_constant(
shape=[1, 2], dtype='float32', value=1.1
)
res2 = fluid.layers.fill_constant(
res2 = paddle.tensor.fill_constant(
shape=shape, dtype='float32', value=1.1
)
res3 = fluid.layers.fill_constant(
res3 = paddle.tensor.fill_constant(
shape=shape, dtype='float32', value=val
)
res4 = fluid.layers.fill_constant(
res4 = paddle.tensor.fill_constant(
shape=shape, dtype='int32', value=value
)
assert np.array_equal(
......@@ -372,17 +372,17 @@ class TestFillConstantImperative(unittest.TestCase):
def test_nan(self):
with fluid.dygraph.guard():
res = fluid.layers.fill_constant([1], 'float32', np.nan)
res = paddle.tensor.fill_constant([1], 'float32', np.nan)
self.assertTrue(np.isnan(res.numpy().item(0)))
def test_inf(self):
with fluid.dygraph.guard():
res = fluid.layers.fill_constant([1], 'float32', np.inf)
res = paddle.tensor.fill_constant([1], 'float32', np.inf)
self.assertTrue(np.isinf(res.numpy().item(0)))
def test_ninf(self):
with fluid.dygraph.guard():
res = fluid.layers.fill_constant([1], 'float32', np.NINF)
res = paddle.tensor.fill_constant([1], 'float32', np.NINF)
self.assertTrue(np.isinf(res.numpy().item(0)))
self.assertEqual(np.NINF, res.numpy().item(0))
......@@ -434,13 +434,13 @@ class TestFillConstantOpError(unittest.TestCase):
# The argument shape's type of fill_constant_op must be list, tuple or Variable.
def test_shape_type():
fluid.layers.fill_constant(shape=1, dtype="float32", value=1)
paddle.tensor.fill_constant(shape=1, dtype="float32", value=1)
self.assertRaises(TypeError, test_shape_type)
# The argument shape's size of fill_constant_op must not be 0.
def test_shape_size():
fluid.layers.fill_constant(shape=[], dtype="float32", value=1)
paddle.tensor.fill_constant(shape=[], dtype="float32", value=1)
self.assertRaises(AssertionError, test_shape_size)
......@@ -449,7 +449,7 @@ class TestFillConstantOpError(unittest.TestCase):
shape = fluid.data(
name="shape_tensor", shape=[2], dtype="float32"
)
fluid.layers.fill_constant(
paddle.tensor.fill_constant(
shape=shape, dtype="float32", value=1
)
......@@ -459,7 +459,7 @@ class TestFillConstantOpError(unittest.TestCase):
shape = fluid.data(
name="shape_tensor_list", shape=[1], dtype="bool"
)
fluid.layers.fill_constant(
paddle.tensor.fill_constant(
shape=[shape, 2], dtype="float32", value=1
)
......
python/paddle/fluid/tests/unittests/mlu/test_strided_slice_op_mlu.py
浏览文件 @ c985b1ac
......@@ -525,8 +525,8 @@ class TestStridedSliceOp_strides_Tensor(OpTest):
class TestStridedSliceAPI(unittest.TestCase):
def test_1(self):
input = np.random.random([3, 4, 5, 6]).astype("float32")
minus_1 = fluid.layers.fill_constant([1], "int32", -1)
minus_3 = fluid.layers.fill_constant([1], "int32", -3)
minus_1 = paddle.tensor.fill_constant([1], "int32", -1)
minus_3 = paddle.tensor.fill_constant([1], "int32", -3)
starts = paddle.static.data(
name='starts', shape=[3], dtype='int32'
)
......
python/paddle/fluid/tests/unittests/mlu/test_tile_op_mlu.py
浏览文件 @ c985b1ac
......@@ -234,7 +234,7 @@ class TestTileAPIStatic(unittest.TestCase):
repeat_times = [2, 2]
x1 = paddle.static.data(name='x1', shape=[-1, 4], dtype="int32")
out = paddle.tile(x1, repeat_times)
positive_2 = fluid.layers.fill_constant([1], dtype="int32", value=2)
positive_2 = paddle.tensor.fill_constant([1], dtype="int32", value=2)
out2 = paddle.tile(x1, repeat_times=[positive_2, 2])
......
python/paddle/fluid/tests/unittests/npu/test_concat_op_npu.py
浏览文件 @ c985b1ac
......@@ -171,7 +171,7 @@ class TestConcatAPIWithLoDTensorArray(unittest.TestCase):
with fluid.program_guard(self.program):
input = paddle.assign(self.x)
tensor_array = paddle.tensor.create_array(dtype='float32')
zero = fluid.layers.fill_constant(
zero = paddle.tensor.fill_constant(
shape=[1], value=0, dtype="int64"
)
......
python/paddle/fluid/tests/unittests/npu/test_expand_v2_op_npu.py
浏览文件 @ c985b1ac
......@@ -270,7 +270,7 @@ class TestExpandV2API(unittest.TestCase):
dtype="float32",
)
positive_2 = fluid.layers.fill_constant([1], "int32", 12)
positive_2 = paddle.tensor.fill_constant([1], "int32", 12)
expand_shape = paddle.static.data(
name="expand_shape",
shape=[2],
......
python/paddle/fluid/tests/unittests/npu/test_stack_op_npu.py
浏览文件 @ c985b1ac
......@@ -139,7 +139,7 @@ class TestStackAPIWithLoDTensorArray(unittest.TestCase):
with fluid.program_guard(self.program):
input = paddle.assign(self.x)
tensor_array = paddle.tensor.create_array(dtype='float32')
zero = fluid.layers.fill_constant(shape=[1], value=0, dtype="int64")
zero = paddle.tensor.fill_constant(shape=[1], value=0, dtype="int64")
for i in range(self.iter_num):
paddle.tensor.array_write(input, zero + i, tensor_array)
......@@ -177,7 +177,7 @@ class TestTensorStackAPIWithLoDTensorArray(unittest.TestCase):
with fluid.program_guard(self.program):
input = paddle.assign(self.x)
tensor_array = paddle.tensor.create_array(dtype='float32')
zero = fluid.layers.fill_constant(shape=[1], value=0, dtype="int64")
zero = paddle.tensor.fill_constant(shape=[1], value=0, dtype="int64")
for i in range(self.iter_num):
paddle.tensor.array_write(input, zero + i, tensor_array)
......
python/paddle/fluid/tests/unittests/npu/test_strided_slice_op_npu.py
浏览文件 @ c985b1ac
......@@ -578,8 +578,8 @@ class TestStridedSliceOp_strides_Tensor(OpTest):
class TestStridedSliceAPI(unittest.TestCase):
def test_1(self):
input = np.random.random([3, 4, 5, 6]).astype("float64")
minus_1 = fluid.layers.fill_constant([1], "int32", -1)
minus_3 = fluid.layers.fill_constant([1], "int32", -3)
minus_1 = paddle.tensor.fill_constant([1], "int32", -1)
minus_3 = paddle.tensor.fill_constant([1], "int32", -3)
starts = paddle.static.data(
name='starts', shape=[3], dtype='int32'
)
......
python/paddle/fluid/tests/unittests/npu/test_while_op_npu.py
浏览文件 @ c985b1ac
......@@ -50,15 +50,15 @@ class TestWhileOp(unittest.TestCase):
i = layers.zeros(shape=[1], dtype='int32')
i = paddle.cast(i, 'int64')
i.stop_gradient = True
array_len = layers.fill_constant(shape=[1], dtype='int32', value=5)
array_len = paddle.tensor.fill_constant(shape=[1], dtype='int32', value=5)
array_len = paddle.cast(array_len, 'int64')
array_len.stop_gradient = True
cond = paddle.ones(shape=[1], dtype='int32')
cond = paddle.cast(cond, 'bool')
j = layers.fill_constant(shape=[1], dtype='int32', value=1)
j = paddle.tensor.fill_constant(shape=[1], dtype='int32', value=1)
j = paddle.cast(j, 'int64')
j.stop_gradient = True
array_len2 = layers.fill_constant(shape=[1], dtype='int32', value=3)
array_len2 = paddle.tensor.fill_constant(shape=[1], dtype='int32', value=3)
array_len2 = paddle.cast(array_len2, 'int64')
array_len2.stop_gradient = True
cond2 = paddle.logical_or(x=j, y=array_len2)
......
python/paddle/fluid/tests/unittests/standalone_executor/test_standalone_controlflow.py
浏览文件 @ c985b1ac
......@@ -17,7 +17,6 @@ import unittest
import numpy as np
import paddle
import paddle.fluid.layers as layers
from paddle.fluid import core, framework
from paddle.fluid.framework import Program, program_guard
......@@ -42,20 +41,26 @@ class TestCompatibility(unittest.TestCase):
def build_program(self):
def true_func():
return layers.fill_constant(
return paddle.tensor.fill_constant(
shape=[1, 2], dtype='int32', value=1
), layers.fill_constant(shape=[2, 3], dtype='bool', value=True)
), paddle.tensor.fill_constant(
shape=[2, 3], dtype='bool', value=True
)
def false_func():
return layers.fill_constant(
return paddle.tensor.fill_constant(
shape=[3, 4], dtype='float32', value=3
), layers.fill_constant(shape=[4, 5], dtype='int64', value=2)
), paddle.tensor.fill_constant(shape=[4, 5], dtype='int64', value=2)
main_program = Program()
startup_program = Program()
with program_guard(main_program, startup_program):
x = layers.fill_constant(shape=[1], dtype='float32', value=0.1)
y = layers.fill_constant(shape=[1], dtype='float32', value=0.23)
x = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.1
)
y = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.23
)
pred = paddle.less_than(x, y)
out = paddle.static.nn.cond(pred, true_func, false_func)
# out is a tuple containing 2 tensors
......
python/paddle/fluid/tests/unittests/standalone_executor/test_standalone_executor.py
浏览文件 @ c985b1ac
......@@ -395,7 +395,7 @@ class TestInplaceApiWithDataTransform(unittest.TestCase):
def test_increment(self):
if paddle.fluid.core.is_compiled_with_cuda():
with paddle.fluid.device_guard("gpu:0"):
x = paddle.fluid.layers.fill_constant([1], "float32", 0)
x = paddle.tensor.fill_constant([1], "float32", 0)
with paddle.fluid.device_guard("cpu"):
x = paddle.increment(x)
exe = paddle.static.Executor(paddle.CUDAPlace(0))
......
python/paddle/fluid/tests/unittests/test_activation_op.py
浏览文件 @ c985b1ac
......@@ -3045,7 +3045,7 @@ class TestPow_factor_tensor(TestActivation):
)
factor_1 = 2.0
factor_2 = fluid.layers.fill_constant([1], "float32", 3.0)
factor_2 = paddle.tensor.fill_constant([1], "float32", 3.0)
out_1 = paddle.pow(x, factor_1)
out_2 = paddle.pow(x, factor_2)
out_4 = paddle.pow(x, factor_1, name='pow_res')
......
python/paddle/fluid/tests/unittests/test_assert_op.py
浏览文件 @ c985b1ac
......@@ -16,7 +16,6 @@ import unittest
import paddle
import paddle.fluid as fluid
import paddle.fluid.layers as layers
from paddle.static.nn.control_flow import Assert
......@@ -31,7 +30,7 @@ class TestAssertOp(unittest.TestCase):
def test_assert_true(self):
def net_func():
condition = layers.fill_constant(
condition = paddle.tensor.fill_constant(
shape=[1], dtype='bool', value=True
)
Assert(condition, [])
......@@ -40,7 +39,7 @@ class TestAssertOp(unittest.TestCase):
def test_assert_false(self):
def net_func():
condition = layers.fill_constant(
condition = paddle.tensor.fill_constant(
shape=[1], dtype='bool', value=False
)
Assert(condition)
......@@ -50,7 +49,7 @@ class TestAssertOp(unittest.TestCase):
def test_assert_cond_numel_error(self):
def net_func():
condition = layers.fill_constant(
condition = paddle.tensor.fill_constant(
shape=[1, 2], dtype='bool', value=True
)
Assert(condition, [])
......@@ -60,8 +59,10 @@ class TestAssertOp(unittest.TestCase):
def test_assert_print_data(self):
def net_func():
zero = layers.fill_constant(shape=[1], dtype='int64', value=0)
one = layers.fill_constant(shape=[1], dtype='int64', value=1)
zero = paddle.tensor.fill_constant(
shape=[1], dtype='int64', value=0
)
one = paddle.tensor.fill_constant(shape=[1], dtype='int64', value=1)
condition = paddle.less_than(one, zero) # False
Assert(condition, [zero, one])
......@@ -71,7 +72,9 @@ class TestAssertOp(unittest.TestCase):
def test_assert_summary(self):
def net_func():
x = layers.fill_constant(shape=[10], dtype='float32', value=2.0)
x = paddle.tensor.fill_constant(
shape=[10], dtype='float32', value=2.0
)
condition = paddle.max(x) < 1.0
Assert(condition, (x,), 5)
......@@ -81,7 +84,9 @@ class TestAssertOp(unittest.TestCase):
def test_assert_summary_greater_than_size(self):
def net_func():
x = layers.fill_constant(shape=[2, 3], dtype='float32', value=2.0)
x = paddle.tensor.fill_constant(
shape=[2, 3], dtype='float32', value=2.0
)
condition = paddle.max(x) < 1.0
Assert(condition, [x], 10, name="test")
......
python/paddle/fluid/tests/unittests/test_assign_op.py
浏览文件 @ c985b1ac
......@@ -76,11 +76,11 @@ class TestAssignOpWithLoDTensorArray(unittest.TestCase):
with program_guard(main_program):
x = fluid.data(name='x', shape=[100, 10], dtype='float32')
x.stop_gradient = False
y = fluid.layers.fill_constant(
y = paddle.tensor.fill_constant(
shape=[100, 10], dtype='float32', value=1
)
z = paddle.add(x=x, y=y)
i = fluid.layers.fill_constant(shape=[1], dtype='int64', value=0)
i = paddle.tensor.fill_constant(shape=[1], dtype='int64', value=0)
init_array = paddle.tensor.array_write(x=z, i=i)
array = paddle.assign(init_array)
sums = paddle.tensor.array_read(array=init_array, i=i)
......@@ -129,11 +129,11 @@ class TestAssignOApi(unittest.TestCase):
with program_guard(main_program):
x = fluid.data(name='x', shape=[100, 10], dtype='float32')
x.stop_gradient = False
y = fluid.layers.fill_constant(
y = paddle.tensor.fill_constant(
shape=[100, 10], dtype='float32', value=1
)
z = paddle.add(x=x, y=y)
i = fluid.layers.fill_constant(shape=[1], dtype='int64', value=0)
i = paddle.tensor.fill_constant(shape=[1], dtype='int64', value=0)
init_array = paddle.tensor.array_write(x=z, i=i)
array = paddle.assign(init_array)
sums = paddle.tensor.array_read(array=init_array, i=i)
......
python/paddle/fluid/tests/unittests/test_broadcast_to_op.py
浏览文件 @ c985b1ac
......@@ -44,7 +44,7 @@ class TestBroadcastToAPI(unittest.TestCase):
input = np.random.random([12, 14]).astype("float32")
x = paddle.static.data(name='x', shape=[12, 14], dtype="float32")
positive_2 = fluid.layers.fill_constant([1], "int32", 12)
positive_2 = paddle.tensor.fill_constant([1], "int32", 12)
expand_shape = paddle.static.data(
name="expand_shape",
shape=[2],
......@@ -81,7 +81,7 @@ class TestBroadcastToAPI(unittest.TestCase):
name="x", shape=[12, 14], dtype="float16"
)
positive_2 = paddle.fluid.layers.fill_constant([1], "int32", 12)
positive_2 = paddle.tensor.fill_constant([1], "int32", 12)
expand_shape = paddle.static.data(
name="expand_shape",
shape=[2],
......
python/paddle/fluid/tests/unittests/test_case.py
浏览文件 @ c985b1ac
......@@ -20,7 +20,6 @@ import numpy as np
import paddle
import paddle.fluid as fluid
import paddle.fluid.core as core
import paddle.fluid.layers as layers
import paddle.fluid.optimizer as optimizer
from paddle.fluid.backward import append_backward
from paddle.fluid.framework import Program, program_guard
......@@ -31,20 +30,32 @@ paddle.enable_static()
class TestAPICase(unittest.TestCase):
def test_return_single_var(self):
def fn_1():
return layers.fill_constant(shape=[4, 2], dtype='int32', value=1)
return paddle.tensor.fill_constant(
shape=[4, 2], dtype='int32', value=1
)
def fn_2():
return layers.fill_constant(shape=[4, 2], dtype='int32', value=2)
return paddle.tensor.fill_constant(
shape=[4, 2], dtype='int32', value=2
)
def fn_3():
return layers.fill_constant(shape=[4, 3], dtype='int32', value=3)
return paddle.tensor.fill_constant(
shape=[4, 3], dtype='int32', value=3
)
main_program = Program()
startup_program = Program()
with program_guard(main_program, startup_program):
x = layers.fill_constant(shape=[1], dtype='float32', value=0.3)
y = layers.fill_constant(shape=[1], dtype='float32', value=0.1)
z = layers.fill_constant(shape=[1], dtype='float32', value=0.2)
x = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.3
)
y = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.1
)
z = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.2
)
pred_2 = paddle.less_than(x, y) # false: 0.3 < 0.1
pred_1 = paddle.less_than(z, x) # true: 0.2 < 0.3
......@@ -244,26 +255,32 @@ class TestAPICase(unittest.TestCase):
def test_return_var_tuple(self):
def fn_1():
return layers.fill_constant(
return paddle.tensor.fill_constant(
shape=[1, 2], dtype='int32', value=1
), layers.fill_constant(shape=[2, 3], dtype='float32', value=2)
), paddle.tensor.fill_constant(
shape=[2, 3], dtype='float32', value=2
)
def fn_2():
return layers.fill_constant(
return paddle.tensor.fill_constant(
shape=[3, 4], dtype='int32', value=3
), layers.fill_constant(shape=[4, 5], dtype='float32', value=4)
), paddle.tensor.fill_constant(
shape=[4, 5], dtype='float32', value=4
)
def fn_3():
return layers.fill_constant(
return paddle.tensor.fill_constant(
shape=[5], dtype='int32', value=5
), layers.fill_constant(shape=[5, 6], dtype='float32', value=6)
), paddle.tensor.fill_constant(
shape=[5, 6], dtype='float32', value=6
)
main_program = Program()
startup_program = Program()
with program_guard(main_program, startup_program):
x = layers.fill_constant(shape=[1], dtype='float32', value=1)
y = layers.fill_constant(shape=[1], dtype='float32', value=1)
z = layers.fill_constant(shape=[1], dtype='float32', value=3)
x = paddle.tensor.fill_constant(shape=[1], dtype='float32', value=1)
y = paddle.tensor.fill_constant(shape=[1], dtype='float32', value=1)
z = paddle.tensor.fill_constant(shape=[1], dtype='float32', value=3)
pred_1 = paddle.equal(x, y) # true
pred_2 = paddle.equal(x, z) # false
......@@ -291,14 +308,18 @@ class TestAPICase(unittest.TestCase):
class TestAPICase_Nested(unittest.TestCase):
def test_nested_case(self):
def fn_1(x=1):
var_5 = layers.fill_constant(shape=[1], dtype='int32', value=5)
var_6 = layers.fill_constant(shape=[1], dtype='int32', value=6)
var_5 = paddle.tensor.fill_constant(
shape=[1], dtype='int32', value=5
)
var_6 = paddle.tensor.fill_constant(
shape=[1], dtype='int32', value=6
)
out = paddle.static.nn.control_flow.case(
pred_fn_pairs=[
(
var_5 < var_6,
partial(
layers.fill_constant,
paddle.tensor.fill_constant,
shape=[1],
dtype='int32',
value=x,
......@@ -307,7 +328,7 @@ class TestAPICase_Nested(unittest.TestCase):
(
var_5 == var_6,
partial(
layers.fill_constant,
paddle.tensor.fill_constant,
shape=[2],
dtype='int32',
value=x,
......@@ -318,15 +339,19 @@ class TestAPICase_Nested(unittest.TestCase):
return out
def fn_2(x=2):
var_5 = layers.fill_constant(shape=[1], dtype='int32', value=5)
var_6 = layers.fill_constant(shape=[1], dtype='int32', value=6)
var_5 = paddle.tensor.fill_constant(
shape=[1], dtype='int32', value=5
)
var_6 = paddle.tensor.fill_constant(
shape=[1], dtype='int32', value=6
)
out = paddle.static.nn.control_flow.case(
pred_fn_pairs=[
(var_5 < var_6, partial(fn_1, x=x)),
(
var_5 == var_6,
partial(
layers.fill_constant,
paddle.tensor.fill_constant,
shape=[2],
dtype='int32',
value=x,
......@@ -337,15 +362,19 @@ class TestAPICase_Nested(unittest.TestCase):
return out
def fn_3():
var_5 = layers.fill_constant(shape=[1], dtype='int32', value=5)
var_6 = layers.fill_constant(shape=[1], dtype='int32', value=6)
var_5 = paddle.tensor.fill_constant(
shape=[1], dtype='int32', value=5
)
var_6 = paddle.tensor.fill_constant(
shape=[1], dtype='int32', value=6
)
out = paddle.static.nn.control_flow.case(
pred_fn_pairs=[
(var_5 < var_6, partial(fn_2, x=3)),
(
var_5 == var_6,
partial(
layers.fill_constant,
paddle.tensor.fill_constant,
shape=[2],
dtype='int32',
value=7,
......@@ -358,9 +387,15 @@ class TestAPICase_Nested(unittest.TestCase):
main_program = Program()
startup_program = Program()
with program_guard(main_program, startup_program):
x = layers.fill_constant(shape=[1], dtype='float32', value=0.3)
y = layers.fill_constant(shape=[1], dtype='float32', value=0.1)
z = layers.fill_constant(shape=[1], dtype='float32', value=0.2)
x = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.3
)
y = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.1
)
z = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.2
)
pred_2 = paddle.less_than(x, y) # false: 0.3 < 0.1
pred_1 = paddle.less_than(z, x) # true: 0.2 < 0.3
......@@ -496,13 +531,19 @@ class TestAPICase_Nested(unittest.TestCase):
class TestAPICase_Error(unittest.TestCase):
def test_error(self):
def fn_1():
return layers.fill_constant(shape=[4, 2], dtype='int32', value=1)
return paddle.tensor.fill_constant(
shape=[4, 2], dtype='int32', value=1
)
main_program = Program()
startup_program = Program()
with program_guard(main_program, startup_program):
x = layers.fill_constant(shape=[1], dtype='float32', value=0.23)
z = layers.fill_constant(shape=[1], dtype='float32', value=0.2)
x = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.23
)
z = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.2
)
pred_1 = paddle.less_than(z, x) # true
# The type of 'pred_fn_pairs' in case must be list or tuple
......@@ -570,7 +611,7 @@ class TestMutiTask(unittest.TestCase):
switch_id = fluid.data(name='switch_id', shape=[1], dtype='int32')
one = layers.fill_constant(shape=[1], dtype='int32', value=1)
one = paddle.tensor.fill_constant(shape=[1], dtype='int32', value=1)
adam = optimizer.Adam(learning_rate=0.001)
adagrad = optimizer.Adagrad(learning_rate=0.001)
......
python/paddle/fluid/tests/unittests/test_concat_op.py
浏览文件 @ c985b1ac
......@@ -347,8 +347,8 @@ class TestConcatAPI(unittest.TestCase):
input_3 = np.random.random([2, 2, 4, 5]).astype("int32")
x_2 = fluid.data(shape=[2, 1, 4, 5], dtype='int32', name='x_2')
x_3 = fluid.data(shape=[2, 2, 4, 5], dtype='int32', name='x_3')
positive_1_int32 = fluid.layers.fill_constant([1], "int32", 1)
positive_1_int64 = fluid.layers.fill_constant([1], "int64", 1)
positive_1_int32 = paddle.tensor.fill_constant([1], "int32", 1)
positive_1_int64 = paddle.tensor.fill_constant([1], "int64", 1)
out_1 = paddle.concat([x_2, x_3], axis=1)
out_2 = paddle.concat([x_2, x_3], axis=positive_1_int32)
out_3 = paddle.concat([x_2, x_3], axis=positive_1_int64)
......@@ -374,9 +374,9 @@ class TestConcatAPI(unittest.TestCase):
input_3 = np.random.random([2, 2, 4, 5]).astype("int32")
x_2 = fluid.data(shape=[2, 1, 4, 5], dtype='int32', name='x_2')
x_3 = fluid.data(shape=[2, 2, 4, 5], dtype='int32', name='x_3')
positive_1_int32 = paddle.fluid.layers.fill_constant([1], "int32", 1)
positive_1_int64 = paddle.fluid.layers.fill_constant([1], "int64", 1)
negative_int64 = paddle.fluid.layers.fill_constant([1], "int64", -3)
positive_1_int32 = paddle.tensor.fill_constant([1], "int32", 1)
positive_1_int64 = paddle.tensor.fill_constant([1], "int64", 1)
negative_int64 = paddle.tensor.fill_constant([1], "int64", -3)
out_1 = paddle.concat(x=[x_2, x_3], axis=1)
out_2 = paddle.concat(x=[x_2, x_3], axis=positive_1_int32)
out_3 = paddle.concat(x=[x_2, x_3], axis=positive_1_int64)
......@@ -464,7 +464,7 @@ class TestConcatAPIWithLoDTensorArray(unittest.TestCase):
with fluid.program_guard(self.program):
input = paddle.assign(self.x)
tensor_array = paddle.tensor.create_array(dtype='float32')
zero = fluid.layers.fill_constant(
zero = paddle.tensor.fill_constant(
shape=[1], value=0, dtype="int64"
)
......
python/paddle/fluid/tests/unittests/test_cond.py
浏览文件 @ c985b1ac
......@@ -21,7 +21,6 @@ import paddle
import paddle.fluid as fluid
import paddle.fluid.core as core
import paddle.fluid.framework as framework
import paddle.fluid.layers as layers
from paddle.fluid.backward import append_backward
from paddle.fluid.framework import Program, program_guard
......@@ -42,16 +41,24 @@ class TestCondInputOutput(unittest.TestCase):
paddle.enable_static()
def true_func():
return layers.fill_constant(shape=[2, 3], dtype='int32', value=2)
return paddle.tensor.fill_constant(
shape=[2, 3], dtype='int32', value=2
)
def false_func():
return layers.fill_constant(shape=[3, 2], dtype='int32', value=-1)
return paddle.tensor.fill_constant(
shape=[3, 2], dtype='int32', value=-1
)
main_program = Program()
startup_program = Program()
with program_guard(main_program, startup_program):
x = layers.fill_constant(shape=[1], dtype='float32', value=0.1)
y = layers.fill_constant(shape=[1], dtype='float32', value=0.23)
x = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.1
)
y = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.23
)
pred = paddle.less_than(y, x)
out = paddle.static.nn.cond(pred, true_func, false_func)
# out is one tensor
......@@ -217,19 +224,23 @@ class TestCondInputOutput(unittest.TestCase):
paddle.enable_static()
def true_func():
return layers.fill_constant(
return paddle.tensor.fill_constant(
shape=[1, 2], dtype='int32', value=1
), layers.fill_constant(shape=[2, 3], dtype='bool', value=True)
), paddle.tensor.fill_constant(
shape=[2, 3], dtype='bool', value=True
)
def false_func():
return layers.fill_constant(
return paddle.tensor.fill_constant(
shape=[3, 4], dtype='float32', value=3
), layers.fill_constant(shape=[4, 5], dtype='int64', value=2)
), paddle.tensor.fill_constant(shape=[4, 5], dtype='int64', value=2)
main_program = Program()
startup_program = Program()
with program_guard(main_program, startup_program):
pred = layers.fill_constant(shape=[1], dtype='bool', value=True)
pred = paddle.tensor.fill_constant(
shape=[1], dtype='bool', value=True
)
out = paddle.static.nn.cond(pred, true_func, false_func)
# out is a tuple containing 2 tensors
......@@ -271,7 +282,9 @@ class TestCondInputOutput(unittest.TestCase):
main_program = Program()
startup_program = Program()
with program_guard(main_program, startup_program):
a = layers.fill_constant(shape=[3, 2, 1], dtype='int32', value=7)
a = paddle.tensor.fill_constant(
shape=[3, 2, 1], dtype='int32', value=7
)
i = fluid.data(name="i", shape=[1], dtype='int32')
pred = (i % 2) == 0
a = paddle.static.nn.cond(
......@@ -346,12 +359,14 @@ class TestCondInputOutput(unittest.TestCase):
return None
def func_return_one_tensor():
return layers.fill_constant(shape=[2, 7], dtype='int32', value=3)
return paddle.tensor.fill_constant(
shape=[2, 7], dtype='int32', value=3
)
def func_return_two_tensors():
return layers.fill_constant(
return paddle.tensor.fill_constant(
shape=[3, 1], dtype='int32', value=7
), layers.fill_constant(shape=[3, 1], dtype='int32', value=8)
), paddle.tensor.fill_constant(shape=[3, 1], dtype='int32', value=8)
main_program = Program()
startup_program = Program()
......@@ -398,11 +413,11 @@ class TestCondInputOutput(unittest.TestCase):
main_program = fluid.Program()
startup_program = fluid.Program()
with fluid.program_guard(main_program, startup_program):
a = fluid.layers.fill_constant(
a = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=1.23
)
a.stop_gradient = False
b = fluid.layers.fill_constant(
b = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=1.25
)
b.stop_gradient = False
......@@ -567,11 +582,11 @@ class TestCondNestedControlFlow(unittest.TestCase):
startup_program = fluid.Program()
with fluid.program_guard(main_program, startup_program):
a = fluid.layers.fill_constant(
a = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=1.23
)
a.stop_gradient = False
b = fluid.layers.fill_constant(
b = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=1.24
)
b.stop_gradient = False
......
python/paddle/fluid/tests/unittests/test_conditional_block.py
浏览文件 @ c985b1ac
......@@ -19,7 +19,6 @@ import numpy as np
import paddle
import paddle.fluid as fluid
import paddle.fluid.core as core
import paddle.fluid.layers as layers
from paddle.fluid.backward import append_backward
from paddle.fluid.executor import Executor
from paddle.fluid.layers.control_flow import ConditionalBlock
......@@ -67,7 +66,7 @@ class TestConditionalBlockOpInferShape(unittest.TestCase):
step_scope = global_block.create_var(
type=core.VarDesc.VarType.STEP_SCOPES
)
cond_var = layers.fill_constant(
cond_var = paddle.tensor.fill_constant(
shape=[1], dtype='bool', value=False
)
......
python/paddle/fluid/tests/unittests/test_dist_fleet_minimize.py
浏览文件 @ c985b1ac
......@@ -41,7 +41,7 @@ class TestPSMinimize(unittest.TestCase):
cond_3 = paddle.sum(cond)
acc = paddle.divide(
cond_3,
fluid.layers.fill_constant(
paddle.tensor.fill_constant(
shape=[1], value=batch_size * 1.0, dtype='float64'
),
name="simnet_acc",
......
python/paddle/fluid/tests/unittests/test_dist_fleet_ps.py
浏览文件 @ c985b1ac
......@@ -41,7 +41,7 @@ class TestPSPassWithBow(unittest.TestCase):
cond_3 = paddle.sum(cond)
acc = paddle.divide(
cond_3,
fluid.layers.fill_constant(
paddle.tensor.fill_constant(
shape=[1], value=batch_size * 1.0, dtype='float64'
),
name="simnet_acc",
......
python/paddle/fluid/tests/unittests/test_dist_fleet_ps11.py
浏览文件 @ c985b1ac
......@@ -41,7 +41,7 @@ class TestPSPassWithBow(unittest.TestCase):
cond_3 = paddle.sum(cond)
acc = paddle.divide(
cond_3,
fluid.layers.fill_constant(
paddle.tensor.fill_constant(
shape=[1], value=batch_size * 1.0, dtype='float64'
),
name="simnet_acc",
......
python/paddle/fluid/tests/unittests/test_dist_fleet_ps12.py
浏览文件 @ c985b1ac
......@@ -44,7 +44,7 @@ class TestPSPassWithBow(unittest.TestCase):
cond_3 = paddle.sum(cond)
acc = paddle.divide(
cond_3,
fluid.layers.fill_constant(
paddle.tensor.fill_constant(
shape=[1], value=batch_size * 1.0, dtype='float64'
),
name="simnet_acc",
......
python/paddle/fluid/tests/unittests/test_dist_fleet_ps13.py
浏览文件 @ c985b1ac
......@@ -45,7 +45,7 @@ class TestPSPassWithBow(unittest.TestCase):
cond_3 = paddle.sum(cond)
acc = paddle.divide(
cond_3,
fluid.layers.fill_constant(
paddle.tensor.fill_constant(
shape=[1], value=batch_size * 1.0, dtype='float64'
),
name="simnet_acc",
......
python/paddle/fluid/tests/unittests/test_dist_fleet_ps2.py
浏览文件 @ c985b1ac
......@@ -44,7 +44,7 @@ class TestPSPassWithBow(unittest.TestCase):
cond_3 = paddle.sum(cond)
acc = paddle.divide(
cond_3,
fluid.layers.fill_constant(
paddle.tensor.fill_constant(
shape=[1], value=batch_size * 1.0, dtype='float64'
),
name="simnet_acc",
......
python/paddle/fluid/tests/unittests/test_dist_fleet_ps3.py
浏览文件 @ c985b1ac
......@@ -41,7 +41,7 @@ class TestPSPassWithBow(unittest.TestCase):
cond_3 = paddle.sum(cond)
acc = paddle.divide(
cond_3,
fluid.layers.fill_constant(
paddle.tensor.fill_constant(
shape=[1], value=batch_size * 1.0, dtype='float64'
),
name="simnet_acc",
......
python/paddle/fluid/tests/unittests/test_dist_fleet_ps4.py
浏览文件 @ c985b1ac
......@@ -41,7 +41,7 @@ class TestPSPassWithBow(unittest.TestCase):
cond_3 = paddle.sum(cond)
acc = paddle.divide(
cond_3,
fluid.layers.fill_constant(
paddle.tensor.fill_constant(
shape=[1], value=batch_size * 1.0, dtype='float64'
),
name="simnet_acc",
......
python/paddle/fluid/tests/unittests/test_dist_fleet_ps5.py
浏览文件 @ c985b1ac
......@@ -41,7 +41,7 @@ class TestPSPassWithBow(unittest.TestCase):
cond_3 = paddle.sum(cond)
acc = paddle.divide(
cond_3,
fluid.layers.fill_constant(
paddle.tensor.fill_constant(
shape=[1], value=batch_size * 1.0, dtype='float64'
),
name="simnet_acc",
......
python/paddle/fluid/tests/unittests/test_dist_fleet_ps6.py
浏览文件 @ c985b1ac
......@@ -41,7 +41,7 @@ class TestPSPassWithBow(unittest.TestCase):
cond_3 = paddle.sum(cond)
acc = paddle.divide(
cond_3,
fluid.layers.fill_constant(
paddle.tensor.fill_constant(
shape=[1], value=batch_size * 1.0, dtype='float64'
),
name="simnet_acc",
......
python/paddle/fluid/tests/unittests/test_dist_fleet_spmt.py
浏览文件 @ c985b1ac
......@@ -39,7 +39,7 @@ class TestSPMT(unittest.TestCase):
cond_3 = paddle.sum(cond)
acc = paddle.divide(
cond_3,
fluid.layers.fill_constant(
paddle.tensor.fill_constant(
shape=[1], value=batch_size * 1.0, dtype='float64'
),
name="simnet_acc",
......
python/paddle/fluid/tests/unittests/test_dynamic_rnn_stop_gradient.py
浏览文件 @ c985b1ac
......@@ -18,7 +18,6 @@ import numpy as np
import paddle
import paddle.fluid as fluid
import paddle.fluid.layers as layers
from paddle.tensor.manipulation import tensor_array_to_tensor
paddle.enable_static()
......@@ -33,10 +32,10 @@ def build_and_run_program(place, batch_size, beam_size, stop_gradient=False):
np.random.rand(batch_size, beam_size, 32).astype("float32")
)
indices = fluid.data(shape=[None, beam_size], dtype="int64", name="indices")
step_idx = layers.fill_constant(
step_idx = paddle.tensor.fill_constant(
shape=[1], dtype="int64", value=0, force_cpu=True
)
max_len = layers.fill_constant(
max_len = paddle.tensor.fill_constant(
shape=[1], dtype="int64", value=10, force_cpu=True
)
cond = paddle.less_than(x=step_idx, y=max_len)
......
python/paddle/fluid/tests/unittests/test_eager_deletion_while_op.py
浏览文件 @ c985b1ac
......@@ -73,14 +73,18 @@ class TestEagerDeletionWhileOpBase(unittest.TestCase):
i = layers.zeros(shape=[1], dtype='int64')
i.stop_gradient = True
array_len = layers.fill_constant(shape=[1], dtype='int64', value=1)
array_len = paddle.tensor.fill_constant(
shape=[1], dtype='int64', value=1
)
array_len.stop_gradient = True
cond = paddle.less_than(x=i, y=array_len)
j = layers.fill_constant(shape=[1], dtype='int64', value=1)
j = paddle.tensor.fill_constant(shape=[1], dtype='int64', value=1)
j.stop_gradient = True
array_len2 = layers.fill_constant(shape=[1], dtype='int64', value=3)
array_len2 = paddle.tensor.fill_constant(
shape=[1], dtype='int64', value=3
)
array_len2.stop_gradient = True
cond2 = paddle.less_than(x=j, y=array_len2)
......
python/paddle/fluid/tests/unittests/test_empty_op.py
浏览文件 @ c985b1ac
......@@ -239,8 +239,8 @@ class TestEmptyAPI(unittest.TestCase):
def test_static_graph(self):
dtype = 'float64'
positive_2_int32 = fluid.layers.fill_constant([1], "int32", 3)
positive_2_int64 = fluid.layers.fill_constant([1], "int64", 3)
positive_2_int32 = paddle.tensor.fill_constant([1], "int32", 3)
positive_2_int64 = paddle.tensor.fill_constant([1], "int64", 3)
shape_tensor_int32 = fluid.data(
name="shape_tensor_int32", shape=[2], dtype="int32"
......
python/paddle/fluid/tests/unittests/test_expand_v2_op.py
浏览文件 @ c985b1ac
......@@ -217,7 +217,7 @@ class TestExpandV2API(unittest.TestCase):
input = np.random.random([12, 14]).astype("float32")
x = paddle.static.data(name='x', shape=[12, 14], dtype="float32")
positive_2 = fluid.layers.fill_constant([1], "int32", 12)
positive_2 = paddle.tensor.fill_constant([1], "int32", 12)
expand_shape = paddle.static.data(
name="expand_shape",
shape=[2],
......
python/paddle/fluid/tests/unittests/test_fill_constant_op.py
浏览文件 @ c985b1ac
......@@ -282,8 +282,8 @@ class TestFillConstantOp2_ValueTensor(OpTest):
class TestFillConstantAPI(unittest.TestCase):
def test_api(self):
positive_2_int32 = fluid.layers.fill_constant([1], "int32", 2)
positive_2_int64 = fluid.layers.fill_constant([1], "int64", 2)
positive_2_int32 = paddle.tensor.fill_constant([1], "int32", 2)
positive_2_int64 = paddle.tensor.fill_constant([1], "int64", 2)
shape_tensor_int32 = fluid.data(
name="shape_tensor_int32", shape=[2], dtype="int32"
......@@ -292,41 +292,41 @@ class TestFillConstantAPI(unittest.TestCase):
name="shape_tensor_int64", shape=[2], dtype="int64"
)
out_1 = fluid.layers.fill_constant(
out_1 = paddle.tensor.fill_constant(
shape=[1, 2], dtype="float32", value=1.1
)
out_2 = fluid.layers.fill_constant(
out_2 = paddle.tensor.fill_constant(
shape=[1, positive_2_int32], dtype="float32", value=1.1
)
out_3 = fluid.layers.fill_constant(
out_3 = paddle.tensor.fill_constant(
shape=[1, positive_2_int64], dtype="float32", value=1.1
)
out_4 = fluid.layers.fill_constant(
out_4 = paddle.tensor.fill_constant(
shape=shape_tensor_int32, dtype="float32", value=1.1
)
out_5 = fluid.layers.fill_constant(
out_5 = paddle.tensor.fill_constant(
shape=shape_tensor_int64, dtype="float32", value=1.1
)
out_6 = fluid.layers.fill_constant(
out_6 = paddle.tensor.fill_constant(
shape=shape_tensor_int64, dtype=np.float32, value=1.1
)
val1 = fluid.layers.fill_constant(
val1 = paddle.tensor.fill_constant(
shape=[1], dtype=np.float32, value=1.1
)
val2 = fluid.layers.fill_constant(
val2 = paddle.tensor.fill_constant(
shape=[1], dtype=np.float64, value=1.1
)
out_7 = fluid.layers.fill_constant(
out_7 = paddle.tensor.fill_constant(
shape=shape_tensor_int64, dtype=np.float32, value=val1
)
out_8 = fluid.layers.fill_constant(
out_8 = paddle.tensor.fill_constant(
shape=shape_tensor_int64, dtype=np.float32, value=val2
)
......@@ -359,16 +359,16 @@ class TestFillConstantImperative(unittest.TestCase):
shape = fluid.dygraph.to_variable(data1)
val = fluid.dygraph.to_variable(data2)
value = fluid.dygraph.to_variable(data3)
res1 = fluid.layers.fill_constant(
res1 = paddle.tensor.fill_constant(
shape=[1, 2], dtype='float32', value=1.1
)
res2 = fluid.layers.fill_constant(
res2 = paddle.tensor.fill_constant(
shape=shape, dtype='float32', value=1.1
)
res3 = fluid.layers.fill_constant(
res3 = paddle.tensor.fill_constant(
shape=shape, dtype='float32', value=val
)
res4 = fluid.layers.fill_constant(
res4 = paddle.tensor.fill_constant(
shape=shape, dtype='int32', value=value
)
assert np.array_equal(
......@@ -386,17 +386,17 @@ class TestFillConstantImperative(unittest.TestCase):
def test_nan(self):
with fluid.dygraph.guard():
res = fluid.layers.fill_constant([1], 'float32', np.nan)
res = paddle.tensor.fill_constant([1], 'float32', np.nan)
self.assertTrue(np.isnan(res.numpy().item(0)))
def test_inf(self):
with fluid.dygraph.guard():
res = fluid.layers.fill_constant([1], 'float32', np.inf)
res = paddle.tensor.fill_constant([1], 'float32', np.inf)
self.assertTrue(np.isinf(res.numpy().item(0)))
def test_ninf(self):
with fluid.dygraph.guard():
res = fluid.layers.fill_constant([1], 'float32', np.NINF)
res = paddle.tensor.fill_constant([1], 'float32', np.NINF)
self.assertTrue(np.isinf(res.numpy().item(0)))
self.assertEqual(np.NINF, res.numpy().item(0))
......@@ -408,7 +408,7 @@ class TestFillConstantOpError(unittest.TestCase):
x1 = paddle.static.data(name='x1', shape=[-1, 1], dtype="int16")
self.assertRaises(
TypeError,
fluid.layers.fill_constant,
paddle.tensor.fill_constant,
shape=[1],
value=5,
dtype='uint4',
......@@ -416,7 +416,7 @@ class TestFillConstantOpError(unittest.TestCase):
self.assertRaises(
TypeError,
fluid.layers.fill_constant,
paddle.tensor.fill_constant,
shape=[1.1],
value=5,
dtype='float32',
......@@ -429,7 +429,7 @@ class TestFillConstantOpError(unittest.TestCase):
self.assertRaises(
TypeError,
fluid.layers.fill_constant,
paddle.tensor.fill_constant,
shape=[1],
value=5,
dtype='float64',
......@@ -439,7 +439,7 @@ class TestFillConstantOpError(unittest.TestCase):
x3 = np.random.randn(100, 100).astype('int32')
self.assertRaises(
TypeError,
fluid.layers.fill_constant,
paddle.tensor.fill_constant,
shape=[100, 100],
value=5,
dtype='float64',
......@@ -448,7 +448,7 @@ class TestFillConstantOpError(unittest.TestCase):
# The argument shape's type of fill_constant_op must be list, tuple or Variable.
def test_shape_type():
fluid.layers.fill_constant(shape=1, dtype="float32", value=1)
paddle.tensor.fill_constant(shape=1, dtype="float32", value=1)
self.assertRaises(TypeError, test_shape_type)
......@@ -457,7 +457,7 @@ class TestFillConstantOpError(unittest.TestCase):
shape = fluid.data(
name="shape_tensor", shape=[2], dtype="float32"
)
fluid.layers.fill_constant(
paddle.tensor.fill_constant(
shape=shape, dtype="float32", value=1
)
......@@ -467,7 +467,7 @@ class TestFillConstantOpError(unittest.TestCase):
shape = fluid.data(
name="shape_tensor_list", shape=[1], dtype="bool"
)
fluid.layers.fill_constant(
paddle.tensor.fill_constant(
shape=[shape, 2], dtype="float32", value=1
)
......
python/paddle/fluid/tests/unittests/test_full_op.py
浏览文件 @ c985b1ac
......@@ -24,9 +24,9 @@ from paddle.fluid import Program, program_guard
# Test python API
class TestFullAPI(unittest.TestCase):
def test_api(self):
positive_2_int32 = fluid.layers.fill_constant([1], "int32", 2)
positive_2_int32 = paddle.tensor.fill_constant([1], "int32", 2)
positive_2_int64 = fluid.layers.fill_constant([1], "int64", 2)
positive_2_int64 = paddle.tensor.fill_constant([1], "int64", 2)
shape_tensor_int32 = fluid.data(
name="shape_tensor_int32", shape=[2], dtype="int32"
)
......@@ -57,7 +57,9 @@ class TestFullAPI(unittest.TestCase):
shape=shape_tensor_int64, dtype=np.float32, fill_value=1.1
)
val = fluid.layers.fill_constant(shape=[1], dtype=np.float32, value=1.1)
val = paddle.tensor.fill_constant(
shape=[1], dtype=np.float32, value=1.1
)
out_7 = paddle.full(
shape=shape_tensor_int64, dtype=np.float32, fill_value=val
)
......@@ -82,9 +84,11 @@ class TestFullAPI(unittest.TestCase):
def test_api_eager(self):
with fluid.dygraph.base.guard():
positive_2_int32 = fluid.layers.fill_constant([1], "int32", 2)
positive_2_int64 = fluid.layers.fill_constant([1], "int64", 2)
positive_4_int64 = fluid.layers.fill_constant([1], "int64", 4, True)
positive_2_int32 = paddle.tensor.fill_constant([1], "int32", 2)
positive_2_int64 = paddle.tensor.fill_constant([1], "int64", 2)
positive_4_int64 = paddle.tensor.fill_constant(
[1], "int64", 4, True
)
out_1 = paddle.full(shape=[1, 2], dtype="float32", fill_value=1.1)
......@@ -106,7 +110,7 @@ class TestFullAPI(unittest.TestCase):
out_6 = paddle.full(shape=[1, 2], dtype=np.float32, fill_value=1.1)
val = fluid.layers.fill_constant(
val = paddle.tensor.fill_constant(
shape=[1], dtype=np.float32, value=1.1
)
out_7 = paddle.full(shape=[1, 2], dtype=np.float32, fill_value=val)
......
python/paddle/fluid/tests/unittests/test_fused_multi_transformer_op.py
浏览文件 @ c985b1ac
......@@ -21,7 +21,6 @@ from eager_op_test import OpTest
import paddle
import paddle.nn.functional as F
from paddle import tensor
from paddle.fluid import layers
from paddle.fluid.framework import default_main_program
from paddle.incubate.nn import FusedMultiTransformer
from paddle.incubate.nn.functional import fused_multi_transformer
......@@ -862,7 +861,7 @@ class TestFusedMultiTransformerOp(OpTest):
assert self.query_length == self.cache_length
cache_kv[:] = 0
else:
time_step = layers.fill_constant(
time_step = paddle.tensor.fill_constant(
shape=[1], dtype="int32", value=0, force_cpu=True
)
time_step_feed = self.cache_length
......@@ -947,7 +946,7 @@ class TestFusedMultiTransformerOp(OpTest):
for i in range(self.layers):
if self.has_cache_kv:
cache_kvs.append(
layers.fill_constant(
paddle.tensor.fill_constant(
shape=cache_kv.shape, dtype=cache_kv.dtype, value=0
)
)
......@@ -955,13 +954,13 @@ class TestFusedMultiTransformerOp(OpTest):
if self.has_pre_cache:
cache_kvs.append(
layers.fill_constant(
paddle.tensor.fill_constant(
shape=cache_kv.shape, dtype=cache_kv.dtype, value=0
)
)
cache_kvs_feed.append(cache_kv)
pre_caches.append(
layers.fill_constant(
paddle.tensor.fill_constant(
shape=self.pre_cache_kv.shape,
dtype=self.pre_cache_kv.dtype,
value=0,
......
python/paddle/fluid/tests/unittests/test_gaussian_random_op.py
浏览文件 @ c985b1ac
......@@ -209,9 +209,9 @@ class TestGaussianRandomOp1_ShapeTensor(TestGaussianRandomOp):
# Test python API
class TestGaussianRandomAPI(unittest.TestCase):
def test_api(self):
positive_2_int32 = fluid.layers.fill_constant([1], "int32", 2000)
positive_2_int32 = paddle.tensor.fill_constant([1], "int32", 2000)
positive_2_int64 = fluid.layers.fill_constant([1], "int64", 500)
positive_2_int64 = paddle.tensor.fill_constant([1], "int64", 500)
shape_tensor_int32 = fluid.data(
name="shape_tensor_int32", shape=[2], dtype="int32"
)
......
python/paddle/fluid/tests/unittests/test_histogram_op.py
浏览文件 @ c985b1ac
......@@ -82,7 +82,7 @@ class TestHistogramOpError(unittest.TestCase):
"""Test bins should be greater than or equal to 1."""
def net_func():
input_value = paddle.fluid.layers.fill_constant(
input_value = paddle.tensor.fill_constant(
shape=[3, 4], dtype='float32', value=3.0
)
paddle.histogram(input=input_value, bins=-1, min=1, max=5)
......@@ -94,7 +94,7 @@ class TestHistogramOpError(unittest.TestCase):
"""Test max must be larger or equal to min."""
def net_func():
input_value = paddle.fluid.layers.fill_constant(
input_value = paddle.tensor.fill_constant(
shape=[3, 4], dtype='float32', value=3.0
)
paddle.histogram(input=input_value, bins=1, min=5, max=1)
......@@ -106,7 +106,7 @@ class TestHistogramOpError(unittest.TestCase):
"""Test range of min, max is not finite"""
def net_func():
input_value = paddle.fluid.layers.fill_constant(
input_value = paddle.tensor.fill_constant(
shape=[3, 4], dtype='float32', value=3.0
)
paddle.histogram(input=input_value, bins=1, min=-np.inf, max=5)
......
python/paddle/fluid/tests/unittests/test_imperative_gan.py
浏览文件 @ c985b1ac
......@@ -77,7 +77,7 @@ class TestDygraphGAN(unittest.TestCase):
d_loss_real = paddle.mean(
paddle.nn.functional.binary_cross_entropy_with_logits(
logit=d_real,
label=fluid.layers.fill_constant(
label=paddle.tensor.fill_constant(
shape=[2, 1], dtype='float32', value=1.0
),
)
......@@ -87,7 +87,7 @@ class TestDygraphGAN(unittest.TestCase):
d_loss_fake = paddle.mean(
paddle.nn.functional.binary_cross_entropy_with_logits(
logit=d_fake,
label=fluid.layers.fill_constant(
label=paddle.tensor.fill_constant(
shape=[2, 1], dtype='float32', value=0.0
),
)
......@@ -108,7 +108,7 @@ class TestDygraphGAN(unittest.TestCase):
g_loss = paddle.mean(
paddle.nn.functional.binary_cross_entropy_with_logits(
logit=d_fake,
label=fluid.layers.fill_constant(
label=paddle.tensor.fill_constant(
shape=[2, 1], dtype='float32', value=1.0
),
)
......
python/paddle/fluid/tests/unittests/test_imperative_layer_apply.py
浏览文件 @ c985b1ac
......@@ -53,20 +53,20 @@ class LeNetDygraph(fluid.dygraph.Layer):
def init_weights(layer):
if type(layer) == nn.Linear:
new_weight = paddle.fluid.layers.fill_constant(
new_weight = paddle.tensor.fill_constant(
layer.weight.shape, layer.weight.dtype, value=0.9
)
layer.weight.set_value(new_weight)
new_bias = paddle.fluid.layers.fill_constant(
new_bias = paddle.tensor.fill_constant(
layer.bias.shape, layer.bias.dtype, value=-0.1
)
layer.bias.set_value(new_bias)
elif type(layer) == nn.Conv2D:
new_weight = paddle.fluid.layers.fill_constant(
new_weight = paddle.tensor.fill_constant(
layer.weight.shape, layer.weight.dtype, value=0.7
)
layer.weight.set_value(new_weight)
new_bias = paddle.fluid.layers.fill_constant(
new_bias = paddle.tensor.fill_constant(
layer.bias.shape, layer.bias.dtype, value=-0.2
)
layer.bias.set_value(new_bias)
......
python/paddle/fluid/tests/unittests/test_imperative_ocr_attention_model.py
浏览文件 @ c985b1ac
......@@ -212,7 +212,7 @@ class EncoderNet(fluid.dygraph.Layer):
)
h_0 = to_variable(h_0)
else:
h_0 = fluid.layers.fill_constant(
h_0 = paddle.tensor.fill_constant(
shape=[Config.batch_size, rnn_hidden_size],
dtype='float32',
value=0,
......
python/paddle/fluid/tests/unittests/test_increment.py
浏览文件 @ c985b1ac
......@@ -23,7 +23,7 @@ import paddle.fluid as fluid
class TestIncrement(unittest.TestCase):
def test_api(self):
with fluid.program_guard(fluid.Program(), fluid.Program()):
input = fluid.layers.fill_constant(
input = paddle.tensor.fill_constant(
shape=[1], dtype='int64', value=5
)
expected_result = np.array([8], dtype='int64')
......@@ -45,7 +45,7 @@ class TestInplaceApiWithDataTransform(unittest.TestCase):
if fluid.core.is_compiled_with_cuda():
paddle.enable_static()
with paddle.fluid.device_guard("gpu:0"):
x = paddle.fluid.layers.fill_constant([1], "float32", 0)
x = paddle.tensor.fill_constant([1], "float32", 0)
with paddle.fluid.device_guard("cpu"):
x = paddle.increment(x)
exe = paddle.static.Executor(paddle.CUDAPlace(0))
......
python/paddle/fluid/tests/unittests/test_input_spec.py
浏览文件 @ c985b1ac
......@@ -19,7 +19,6 @@ import unittest
import numpy as np
import paddle
import paddle.fluid as fluid
from paddle.fluid import core
from paddle.fluid.framework import convert_np_dtype_to_dtype_
from paddle.jit.dy2static.utils import _compatible_non_tensor_spec
......@@ -35,7 +34,9 @@ class TestInputSpec(unittest.TestCase):
self.assertIsNone(tensor_spec.name)
def test_from_tensor(self):
x_bool = fluid.layers.fill_constant(shape=[1], dtype='bool', value=True)
x_bool = paddle.tensor.fill_constant(
shape=[1], dtype='bool', value=True
)
bool_spec = InputSpec.from_tensor(x_bool)
self.assertEqual(bool_spec.dtype, x_bool.dtype)
self.assertEqual(list(bool_spec.shape), list(x_bool.shape))
......
python/paddle/fluid/tests/unittests/test_lambv2_op.py
浏览文件 @ c985b1ac
......@@ -18,7 +18,6 @@ import numpy as np
import paddle
import paddle.fluid as fluid
import paddle.fluid.layers as layers
from paddle.fluid import core
from paddle.fluid.dygraph.base import switch_to_static_graph
......@@ -39,13 +38,13 @@ class LAMBOptimizer(paddle.optimizer.Lamb):
self._beta2_pow_acc_str, param_and_grad[0]
)
beta_1 = layers.fill_constant(
beta_1 = paddle.tensor.fill_constant(
dtype='float32', shape=[1], value=self._beta1, name='lamb_beta_1'
)
beta_2 = layers.fill_constant(
beta_2 = paddle.tensor.fill_constant(
dtype='float32', shape=[1], value=self._beta2, name='lamb_beta_2'
)
epsilon = layers.fill_constant(
epsilon = paddle.tensor.fill_constant(
dtype='float32', shape=[1], value=self._epsilon, name='epsilon'
)
......
python/paddle/fluid/tests/unittests/test_layers.py
浏览文件 @ c985b1ac
......@@ -1030,8 +1030,10 @@ class TestLayer(LayerTest):
def test_while_loop(self):
with self.static_graph():
i = layers.fill_constant(shape=[1], dtype='int64', value=0)
ten = layers.fill_constant(shape=[1], dtype='int64', value=10)
i = paddle.tensor.fill_constant(shape=[1], dtype='int64', value=0)
ten = paddle.tensor.fill_constant(
shape=[1], dtype='int64', value=10
)
def cond(i):
return paddle.less_than(i, ten)
......@@ -1043,8 +1045,10 @@ class TestLayer(LayerTest):
static_ret = self.get_static_graph_result(feed={}, fetch_list=out)
with self.dynamic_graph():
i = layers.fill_constant(shape=[1], dtype='int64', value=0)
ten = layers.fill_constant(shape=[1], dtype='int64', value=10)
i = paddle.tensor.fill_constant(shape=[1], dtype='int64', value=0)
ten = paddle.tensor.fill_constant(
shape=[1], dtype='int64', value=10
)
def cond1(i):
return paddle.less_than(i, ten)
......@@ -1054,7 +1058,9 @@ class TestLayer(LayerTest):
dy_ret = paddle.static.nn.while_loop(cond1, body1, [i])
with self.assertRaises(ValueError):
j = layers.fill_constant(shape=[1], dtype='int64', value=0)
j = paddle.tensor.fill_constant(
shape=[1], dtype='int64', value=0
)
def body2(i):
return i + 1, i + 2
......@@ -1170,10 +1176,10 @@ class TestLayer(LayerTest):
return paddle.subtract(a, b)
with self.static_graph():
a = fluid.layers.fill_constant(
a = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.1
)
b = fluid.layers.fill_constant(
b = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.23
)
out = paddle.static.nn.cond(
......@@ -1215,18 +1221,30 @@ class TestLayer(LayerTest):
def test_case(self):
def fn_1():
return layers.fill_constant(shape=[1, 2], dtype='float32', value=1)
return paddle.tensor.fill_constant(
shape=[1, 2], dtype='float32', value=1
)
def fn_2():
return layers.fill_constant(shape=[2, 2], dtype='int32', value=2)
return paddle.tensor.fill_constant(
shape=[2, 2], dtype='int32', value=2
)
def fn_3():
return layers.fill_constant(shape=[3], dtype='int32', value=3)
return paddle.tensor.fill_constant(
shape=[3], dtype='int32', value=3
)
with self.static_graph():
x = layers.fill_constant(shape=[1], dtype='float32', value=0.3)
y = layers.fill_constant(shape=[1], dtype='float32', value=0.1)
z = layers.fill_constant(shape=[1], dtype='float32', value=0.2)
x = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.3
)
y = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.1
)
z = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.2
)
pred_1 = paddle.less_than(z, x) # true: 0.2 < 0.3
pred_2 = paddle.less_than(x, y) # false: 0.3 < 0.1
......@@ -1248,9 +1266,15 @@ class TestLayer(LayerTest):
static_res1, static_res2 = exe.run(fetch_list=[out_1, out_2])
with self.dynamic_graph():
x = layers.fill_constant(shape=[1], dtype='float32', value=0.3)
y = layers.fill_constant(shape=[1], dtype='float32', value=0.1)
z = layers.fill_constant(shape=[1], dtype='float32', value=0.2)
x = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.3
)
y = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.1
)
z = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.2
)
pred_1 = paddle.less_than(z, x) # true: 0.2 < 0.3
pred_2 = paddle.less_than(x, y) # false: 0.3 < 0.1
......@@ -1270,17 +1294,27 @@ class TestLayer(LayerTest):
def test_switch_case(self):
def fn_1():
return layers.fill_constant(shape=[1, 2], dtype='float32', value=1)
return paddle.tensor.fill_constant(
shape=[1, 2], dtype='float32', value=1
)
def fn_2():
return layers.fill_constant(shape=[2, 2], dtype='int32', value=2)
return paddle.tensor.fill_constant(
shape=[2, 2], dtype='int32', value=2
)
def fn_3():
return layers.fill_constant(shape=[3], dtype='int32', value=3)
return paddle.tensor.fill_constant(
shape=[3], dtype='int32', value=3
)
with self.static_graph():
index_1 = layers.fill_constant(shape=[1], dtype='int32', value=1)
index_2 = layers.fill_constant(shape=[1], dtype='int32', value=2)
index_1 = paddle.tensor.fill_constant(
shape=[1], dtype='int32', value=1
)
index_2 = paddle.tensor.fill_constant(
shape=[1], dtype='int32', value=2
)
out_1 = paddle.static.nn.switch_case(
branch_index=index_1,
......@@ -1308,8 +1342,12 @@ class TestLayer(LayerTest):
)
with self.dynamic_graph():
index_1 = layers.fill_constant(shape=[1], dtype='int32', value=1)
index_2 = layers.fill_constant(shape=[1], dtype='int32', value=2)
index_1 = paddle.tensor.fill_constant(
shape=[1], dtype='int32', value=1
)
index_2 = paddle.tensor.fill_constant(
shape=[1], dtype='int32', value=2
)
out_1 = paddle.static.nn.switch_case(
branch_index=index_1,
......@@ -1987,9 +2025,15 @@ class TestBook(LayerTest):
paddle.arange(0, 10, 2, 'int32')
paddle.arange(0.1, 10.0, 0.2, 'float32')
paddle.arange(0.1, 10.0, 0.2, 'float64')
start = layers.fill_constant(shape=[1], value=0.1, dtype="float32")
end = layers.fill_constant(shape=[1], value=10.0, dtype="float32")
step = layers.fill_constant(shape=[1], value=0.2, dtype="float32")
start = paddle.tensor.fill_constant(
shape=[1], value=0.1, dtype="float32"
)
end = paddle.tensor.fill_constant(
shape=[1], value=10.0, dtype="float32"
)
step = paddle.tensor.fill_constant(
shape=[1], value=0.2, dtype="float32"
)
y = paddle.arange(start, end, step, 'float64')
return y
......@@ -2088,7 +2132,7 @@ class TestBook(LayerTest):
def test_fill_constant_batch_size_like(self):
with self.static_graph():
like = fluid.layers.fill_constant(
like = paddle.tensor.fill_constant(
shape=[1, 200], value=10, dtype='int64'
)
out = layers.fill_constant_batch_size_like(
......
python/paddle/fluid/tests/unittests/test_lod_array_length_op.py
浏览文件 @ c985b1ac
......@@ -26,7 +26,7 @@ from paddle.fluid.executor import Executor
class TestLoDArrayLength(unittest.TestCase):
def test_array_length(self):
tmp = layers.zeros(shape=[10], dtype='int32')
i = layers.fill_constant(shape=[1], dtype='int64', value=10)
i = paddle.tensor.fill_constant(shape=[1], dtype='int64', value=10)
arr = paddle.tensor.array_write(tmp, i=i)
arr_len = paddle.tensor.array_length(arr)
cpu = core.CPUPlace()
......
python/paddle/fluid/tests/unittests/test_optimizer_in_control_flow.py
浏览文件 @ c985b1ac
......@@ -19,7 +19,6 @@ import numpy as np
import paddle
import paddle.fluid as fluid
import paddle.fluid.core as core
import paddle.fluid.layers as layers
import paddle.fluid.optimizer as optimizer
from paddle.fluid.framework import Program, program_guard
......@@ -98,7 +97,7 @@ def static(
sgd = optimizer.SGD(learning_rate=LR)
id = fluid.data('id', [1], 'int32')
two = layers.fill_constant([1], 'int32', 2)
two = paddle.tensor.fill_constant([1], 'int32', 2)
mod_two = paddle.remainder(id, two) == 0
if loss_in_switch:
......
python/paddle/fluid/tests/unittests/test_profiler.py
浏览文件 @ c985b1ac
......@@ -45,7 +45,7 @@ class TestProfiler(unittest.TestCase):
counter = fluid.layers.zeros(
shape=[1], dtype='int64', force_cpu=True
)
until = layers.fill_constant([1], dtype='int64', value=10)
until = paddle.tensor.fill_constant([1], dtype='int64', value=10)
data_arr = paddle.tensor.array_write(hidden1, i)
cond = paddle.less_than(x=counter, y=until)
while_op = paddle.static.nn.control_flow.While(cond=cond)
......
python/paddle/fluid/tests/unittests/test_program_code.py
浏览文件 @ c985b1ac
......@@ -16,7 +16,6 @@ import unittest
import paddle
import paddle.fluid as fluid
import paddle.fluid.layers as layers
class TestProgramToReadableCode(unittest.TestCase):
......@@ -37,14 +36,22 @@ class TestProgramToReadableCode(unittest.TestCase):
def append_cond_op(self, program):
def true_func():
return layers.fill_constant(shape=[2, 3], dtype='int32', value=2)
return paddle.tensor.fill_constant(
shape=[2, 3], dtype='int32', value=2
)
def false_func():
return layers.fill_constant(shape=[3, 2], dtype='int32', value=-1)
return paddle.tensor.fill_constant(
shape=[3, 2], dtype='int32', value=-1
)
with fluid.program_guard(program):
x = layers.fill_constant(shape=[1], dtype='float32', value=0.1)
y = layers.fill_constant(shape=[1], dtype='float32', value=0.23)
x = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.1
)
y = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=0.23
)
pred = paddle.less_than(y, x)
out = paddle.static.nn.cond(pred, true_func, false_func)
......
python/paddle/fluid/tests/unittests/test_program_prune_backward.py
浏览文件 @ c985b1ac
......@@ -72,7 +72,7 @@ def cond_net(use_feed=None):
avg_loss = paddle.mean(loss, name='mean_softmax_loss')
return avg_loss
two = fluid.layers.fill_constant([1], 'int32', 2)
two = paddle.tensor.fill_constant([1], 'int32', 2)
pred = two == 0
avg_loss = paddle.static.nn.case(
[(pred, lambda: loss1(prediction, label))],
......@@ -106,7 +106,7 @@ def optimization_in_cond_net(with_optimize=False):
return avg_loss
sgd = fluid.optimizer.SGD(learning_rate=0.1)
two = fluid.layers.fill_constant([1], 'int32', 2)
two = paddle.tensor.fill_constant([1], 'int32', 2)
pred = two == 0
avg_loss = paddle.static.nn.case(
[(pred, lambda: loss1(sgd, prediction, label, with_optimize))],
......
python/paddle/fluid/tests/unittests/test_rand_op.py
浏览文件 @ c985b1ac
......@@ -42,8 +42,8 @@ class TestRandOpError(unittest.TestCase):
self.assertRaises(TypeError, test_Variable)
def test_dtype():
dim_1 = fluid.layers.fill_constant([1], "int64", 3)
dim_2 = fluid.layers.fill_constant([1], "int32", 5)
dim_1 = paddle.tensor.fill_constant([1], "int64", 3)
dim_2 = paddle.tensor.fill_constant([1], "int32", 5)
rand(shape=[dim_1, dim_2], dtype='int32')
self.assertRaises(TypeError, test_dtype)
......@@ -64,8 +64,8 @@ class TestRandOp(unittest.TestCase):
result_0 = rand([3, 4])
result_1 = rand([3, 4], 'float64')
dim_1 = fluid.layers.fill_constant([1], "int64", 3)
dim_2 = fluid.layers.fill_constant([1], "int32", 5)
dim_1 = paddle.tensor.fill_constant([1], "int64", 3)
dim_2 = paddle.tensor.fill_constant([1], "int32", 5)
result_2 = rand(shape=[dim_1, dim_2])
var_shape = fluid.data(name='var_shape', shape=[2], dtype="int64")
......@@ -104,8 +104,8 @@ class TestRandOpForDygraph(unittest.TestCase):
rand([3, 4], 'float64')
dim_1 = fluid.layers.fill_constant([1], "int64", 3)
dim_2 = fluid.layers.fill_constant([1], "int32", 5)
dim_1 = paddle.tensor.fill_constant([1], "int64", 3)
dim_2 = paddle.tensor.fill_constant([1], "int32", 5)
rand(shape=[dim_1, dim_2])
var_shape = fluid.dygraph.to_variable(np.array([3, 4]))
......
python/paddle/fluid/tests/unittests/test_randint_op.py
浏览文件 @ c985b1ac
......@@ -126,8 +126,8 @@ class TestRandintAPI(unittest.TestCase):
low=-100, high=100, shape=(32, 32, 3), dtype='int64'
)
# shape is a tensorlist and dtype is 'float32'
dim_1 = paddle.fluid.layers.fill_constant([1], "int64", 32)
dim_2 = paddle.fluid.layers.fill_constant([1], "int32", 50)
dim_1 = paddle.tensor.fill_constant([1], "int64", 32)
dim_2 = paddle.tensor.fill_constant([1], "int32", 50)
out4 = paddle.randint(
low=-100, high=100, shape=[dim_1, 5, dim_2], dtype='int32'
)
......
python/paddle/fluid/tests/unittests/test_randn_op.py
浏览文件 @ c985b1ac
......@@ -30,8 +30,8 @@ class TestRandnOp(unittest.TestCase):
x1 = paddle.randn(shape, 'float32')
x2 = paddle.randn(shape, 'float64')
dim_1 = paddle.fluid.layers.fill_constant([1], "int64", 20)
dim_2 = paddle.fluid.layers.fill_constant([1], "int32", 50)
dim_1 = paddle.tensor.fill_constant([1], "int64", 20)
dim_2 = paddle.tensor.fill_constant([1], "int32", 50)
x3 = paddle.randn([dim_1, dim_2, 784])
var_shape = paddle.static.data('X', [2], 'int32')
......@@ -66,8 +66,8 @@ class TestRandnOpForDygraph(unittest.TestCase):
x1 = paddle.randn(shape, 'float32')
x2 = paddle.randn(shape, 'float64')
dim_1 = paddle.fluid.layers.fill_constant([1], "int64", 20)
dim_2 = paddle.fluid.layers.fill_constant([1], "int32", 50)
dim_1 = paddle.tensor.fill_constant([1], "int64", 20)
dim_2 = paddle.tensor.fill_constant([1], "int32", 50)
x3 = paddle.randn(shape=[dim_1, dim_2, 784])
var_shape = paddle.to_tensor(np.array(shape))
......
python/paddle/fluid/tests/unittests/test_reshape_op.py
浏览文件 @ c985b1ac
......@@ -327,7 +327,7 @@ class TestReshapeOpBool(TestReshapeOp):
# Test python API
class TestReshapeAPI(unittest.TestCase):
def _set_paddle_api(self):
self.fill_constant = paddle.fluid.layers.fill_constant
self.fill_constant = paddle.tensor.fill_constant
self.data = paddle.static.data
self.to_tensor = paddle.to_tensor
self._executed_api()
......
python/paddle/fluid/tests/unittests/test_retain_graph.py
浏览文件 @ c985b1ac
......@@ -80,7 +80,7 @@ class TestRetainGraph(unittest.TestCase):
fake_AB = paddle.concat((real_data.detach(), interpolatesv), 1)
disc_interpolates = netD(fake_AB)
outs = paddle.fluid.layers.fill_constant(
outs = paddle.tensor.fill_constant(
disc_interpolates.shape, disc_interpolates.dtype, 1.0
)
gradients = paddle.grad(
......@@ -125,7 +125,7 @@ class TestRetainGraph(unittest.TestCase):
fake_AB = paddle.concat((realA, fakeB), 1)
G_pred_fake = d(fake_AB.detach())
false_target = paddle.fluid.layers.fill_constant(
false_target = paddle.tensor.fill_constant(
G_pred_fake.shape, 'float32', 0.0
)
......@@ -140,7 +140,7 @@ class TestRetainGraph(unittest.TestCase):
optim_g.clear_gradients()
fake_AB = paddle.concat((realA, fakeB), 1)
G_pred_fake = d(fake_AB)
true_target = paddle.fluid.layers.fill_constant(
true_target = paddle.tensor.fill_constant(
G_pred_fake.shape, 'float32', 1.0
)
loss_g = l1_criterion(fakeB, realB) + gan_criterion(
......
python/paddle/fluid/tests/unittests/test_set_value_op.py
浏览文件 @ c985b1ac
......@@ -1306,19 +1306,13 @@ class TestGradientTruncated(unittest.TestCase):
numel = lambda input_shape: reduce(lambda x, y: x * y, input_shape)
def op1(x):
value = paddle.fluid.layers.fill_constant([1], "float32", 1)
value = paddle.tensor.fill_constant([1], "float32", 1)
# test stop_gradient
value.stop_gradient = True
x.stop_gradient = False
start = paddle.fluid.layers.fill_constant(
[1], "int32", 5, force_cpu=True
)
end = paddle.fluid.layers.fill_constant(
[1], "int32", 0, force_cpu=True
)
step = paddle.fluid.layers.fill_constant(
[1], "int32", -2, force_cpu=True
)
start = paddle.tensor.fill_constant([1], "int32", 5, force_cpu=True)
end = paddle.tensor.fill_constant([1], "int32", 0, force_cpu=True)
step = paddle.tensor.fill_constant([1], "int32", -2, force_cpu=True)
inputs = {
'Input': x,
......@@ -1347,7 +1341,7 @@ class TestGradientTruncated(unittest.TestCase):
return y, value
def op2(x):
value = paddle.fluid.layers.fill_constant([1, 3, 2], "float32", 1)
value = paddle.tensor.fill_constant([1, 3, 2], "float32", 1)
# test stop_gradient
value.stop_gradient = False
x.stop_gradient = False
......@@ -1372,18 +1366,12 @@ class TestGradientTruncated(unittest.TestCase):
return y, value
def op3(x):
value = paddle.fluid.layers.fill_constant([1], "float32", 1)
value = paddle.tensor.fill_constant([1], "float32", 1)
x.stop_gradient = True
value.stop_gradient = False
start = paddle.fluid.layers.fill_constant(
[1], "int32", 0, force_cpu=True
)
end = paddle.fluid.layers.fill_constant(
[1], "int32", 5, force_cpu=True
)
step = paddle.fluid.layers.fill_constant(
[1], "int32", 3, force_cpu=True
)
start = paddle.tensor.fill_constant([1], "int32", 0, force_cpu=True)
end = paddle.tensor.fill_constant([1], "int32", 5, force_cpu=True)
step = paddle.tensor.fill_constant([1], "int32", 3, force_cpu=True)
inputs = {
'Input': x,
......
python/paddle/fluid/tests/unittests/test_sgd_op.py
浏览文件 @ c985b1ac
......@@ -196,8 +196,8 @@ class TestSGDOpOptimizeSelectedRows(unittest.TestCase):
class TestSGDOpWithLargeInput(unittest.TestCase):
def runTest(self):
paddle.enable_static()
data = fluid.layers.fill_constant(shape=[1], value=128, dtype='int64')
label = fluid.layers.fill_constant(
data = paddle.tensor.fill_constant(shape=[1], value=128, dtype='int64')
label = paddle.tensor.fill_constant(
shape=[1, 150], value=0.5, dtype='float32'
)
emb = paddle.static.nn.embedding(
......
python/paddle/fluid/tests/unittests/test_slice_op.py
浏览文件 @ c985b1ac
......@@ -582,8 +582,8 @@ class TestBF16(OpTest):
class TestSliceAPI(unittest.TestCase):
def test_1(self):
input = np.random.random([3, 4, 5, 6]).astype("float64")
minus_1 = fluid.layers.fill_constant([1], "int32", -1)
minus_3 = fluid.layers.fill_constant([1], "int64", -3)
minus_1 = paddle.tensor.fill_constant([1], "int32", -1)
minus_3 = paddle.tensor.fill_constant([1], "int64", -3)
starts = paddle.static.data(
name='starts', shape=[1, 3], dtype="float32"
)
......@@ -597,7 +597,7 @@ class TestSliceAPI(unittest.TestCase):
)
# value_int64 is greater than 2147483647 which is the max of int32
value_int64 = fluid.layers.fill_constant([1], "int64", 2147483648)
value_int64 = paddle.tensor.fill_constant([1], "int64", 2147483648)
out_1 = paddle.slice(
x, axes=[0, 1, 2], starts=[-3, 0, 2], ends=[value_int64, 100, -1]
......@@ -739,7 +739,7 @@ class TestSliceApiWithLoDTensorArray(unittest.TestCase):
slice_arr, axis=self.axis, use_stack=True
)
elif case_num == 3:
value_int64 = fluid.layers.fill_constant(
value_int64 = paddle.tensor.fill_constant(
[1], "int64", 2147483648
)
self.sliced_arr = slice_arr = arr[self.start : value_int64]
......
python/paddle/jit/api.py
浏览文件 @ c985b1ac
此差异已折叠。
python/paddle/static/nn/metric.py
浏览文件 @ c985b1ac
此差异已折叠。
python/paddle/tensor/__init__.py
浏览文件 @ c985b1ac
此差异已折叠。
python/paddle/tensor/creation.py
浏览文件 @ c985b1ac
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python/paddle/utils/layers_utils.py
浏览文件 @ c985b1ac
此差异已折叠。
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