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08fb079d
编写于
11月 30, 2020
作者:
L
lilong12
提交者:
GitHub
11月 30, 2020
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Fix the doc for shard_index api (#29183)
* update, test=develop
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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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@@ -14696,9 +14696,10 @@ def deformable_roi_pooling(input,
return output
@deprecated(since="2.0.0", update_to="paddle.shard_index")
def shard_index(input, index_num, nshards, shard_id, ignore_value=-1):
"""
This operator recomputes
the `input` indices according to the offset of the
Recompute
the `input` indices according to the offset of the
shard. The length of the indices is evenly divided into N shards, and if
the `shard_id` matches the shard with the input index inside, the index is
recomputed on the basis of the shard offset, elsewise it is set to
...
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@@ -14711,44 +14712,27 @@ def shard_index(input, index_num, nshards, shard_id, ignore_value=-1):
NOTE: If the length of indices cannot be evely divided by the shard number,
the size of the last shard will be less than the calculated `shard_size`
Examples:
::
Input:
X.shape = [4, 1]
X.data = [[1], [6], [12], [19]]
index_num = 20
nshards = 2
ignore_value = -1
if shard_id == 0, we get:
Out.shape = [4, 1]
Out.data = [[1], [6], [-1], [-1]]
if shard_id == 1, we get:
Out.shape = [4, 1]
Out.data = [[-1], [-1], [2], [9]]
Args:
- **input** (Variable): Input indices,
last dimension must be 1.
- **index_num** (scalar
): An integer defining the range of the index.
- **nshards** (scalar): The number of shards
- **shard_id** (scalar): The index of the current shard
- **ignore_value** (scalar): An integer value out of sharded index range
input (Tensor): Input indices with data type int64. It's
last dimension must be 1.
index_num (int
): An integer defining the range of the index.
nshards (int): The number of shards.
shard_id (int): The index of the current shard.
ignore_value (int): An integer value out of sharded index range.
Returns:
Variable
: The sharded index of input.
Tensor
: The sharded index of input.
Examples:
.. code-block:: python
import paddle.fluid as fluid
batch_size = 32
label = fluid.data(name="label", shape=[batch_size, 1], dtype="int64")
shard_label = fluid.layers.shard_index(input=label,
index_num=20,
nshards=2,
shard_id=0)
import paddle
label = paddle.to_tensor([[16], [1]], "int64")
shard_label = paddle.shard_index(input=label,
index_num=20,
nshards=2,
shard_id=0)
print(shard_label)
# [[-1], [1]]
"""
check_variable_and_dtype(input, 'input', ['int64'], 'shard_index')
op_type = 'shard_index'
...
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