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8d08c9e0
编写于
11月 17, 2022
作者:
傅
傅剑寒
提交者:
GitHub
11月 17, 2022
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[fluid clear] remove unstack in nn.py under fluid (#47927)
* remove unstack in nn.py under fluid * remove unstack under fluid
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python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
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python/paddle/fluid/layers/nn.py
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...
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@@ -140,7 +140,6 @@ __all__ = [
'flatten',
'stack',
'pad2d',
'unstack',
'unique',
'unique_with_counts',
'expand',
...
...
@@ -10510,68 +10509,6 @@ def filter_by_instag(ins, ins_tag, filter_tag, is_lod, out_val_if_empty=0):
return [out, loss_weight]
def unstack(x, axis=0, num=None):
"""
:alias_main: paddle.unstack
:alias: paddle.unstack,paddle.tensor.unstack,paddle.tensor.manipulation.unstack
:old_api: paddle.fluid.layers.unstack
**UnStack Layer**
This layer unstacks input Tensor :code:`x` into several Tensors along :code:`axis`.
If :code:`axis` < 0, it would be replaced with :code:`axis+rank(x)`.
If :code:`num` is None, it would be inferred from :code:`x.shape[axis]`,
and if :code:`x.shape[axis]` <= 0 or is unknown, :code:`ValueError` is
raised.
Args:
x (Tensor): Input Tensor. It is a N-D Tensors of data types float32, float64, int32, int64.
axis (int): The axis along which the input is unstacked.
num (int|None): The number of output variables.
Returns:
list(Tensor): The unstacked Tensors list. The list elements are N-D Tensors of data types float32, float64, int32, int64.
Raises:
ValueError: If x.shape[axis] <= 0 or axis is not in range [-D, D).
Examples:
.. code-block:: python
import paddle
x = paddle.ones(name='x', shape=[2, 3, 5], dtype='float32') # create a tensor with shape=[2, 3, 5]
y = paddle.unstack(x, axis=1) # unstack with second axis, which results 3 tensors with shape=[2, 5]
"""
if _non_static_mode():
if num is None:
num = x.shape[axis]
if num == 0:
return []
return _legacy_C_ops.unstack(x, num, 'axis', int(axis), 'num', num)
helper = LayerHelper('unstack', **locals())
if num is None:
if axis is None or x.shape[axis] <= 0:
raise ValueError('unknown unstack number')
else:
num = x.shape[axis]
outs = []
for _ in range(num):
outs.append(helper.create_variable_for_type_inference(x.dtype))
helper.append_op(
type='unstack',
inputs={'X': [x]},
outputs={'Y': outs},
attrs={'axis': axis, 'num': num},
)
return outs
@deprecated(since='2.0.0', update_to="paddle.expand")
def expand(x, expand_times, name=None):
"""
...
...
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