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[xdoctest] reformat example code with google style in No.286-290 #56797

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Sep 7, 2023
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[xdoctest] reformat example code with google style in No.286-290 #56797

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75bc5d5
8.30下午
yuchen202 Aug 30, 2023
0a05bc9
Update softmax_mask_fuse.py
yuchen202 Sep 1, 2023
d7d183a
Update graph_reindex.py
yuchen202 Sep 5, 2023
9d08315
Update graph_sample_neighbors.py
yuchen202 Sep 6, 2023
50fb3c6
fix cases on cpu
SigureMo Sep 6, 2023
3b0b3d1
fix gpu cases
SigureMo Sep 6, 2023
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68 changes: 41 additions & 27 deletions python/paddle/incubate/operators/graph_reindex.py
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Original file line number Diff line number Diff line change
Expand Up @@ -80,33 +80,47 @@ def graph_reindex(
Examples:
.. code-block:: python

import paddle

x = [0, 1, 2]
neighbors_e1 = [8, 9, 0, 4, 7, 6, 7]
count_e1 = [2, 3, 2]
x = paddle.to_tensor(x, dtype="int64")
neighbors_e1 = paddle.to_tensor(neighbors_e1, dtype="int64")
count_e1 = paddle.to_tensor(count_e1, dtype="int32")

reindex_src, reindex_dst, out_nodes = \
paddle.incubate.graph_reindex(x, neighbors_e1, count_e1)
# reindex_src: [3, 4, 0, 5, 6, 7, 6]
# reindex_dst: [0, 0, 1, 1, 1, 2, 2]
# out_nodes: [0, 1, 2, 8, 9, 4, 7, 6]

neighbors_e2 = [0, 2, 3, 5, 1]
count_e2 = [1, 3, 1]
neighbors_e2 = paddle.to_tensor(neighbors_e2, dtype="int64")
count_e2 = paddle.to_tensor(count_e2, dtype="int32")

neighbors = paddle.concat([neighbors_e1, neighbors_e2])
count = paddle.concat([count_e1, count_e2])
reindex_src, reindex_dst, out_nodes = \
paddle.incubate.graph_reindex(x, neighbors, count)
# reindex_src: [3, 4, 0, 5, 6, 7, 6, 0, 2, 8, 9, 1]
# reindex_dst: [0, 0, 1, 1, 1, 2, 2, 0, 1, 1, 1, 2]
# out_nodes: [0, 1, 2, 8, 9, 4, 7, 6, 3, 5]
>>> import paddle

>>> x = [0, 1, 2]
>>> neighbors_e1 = [8, 9, 0, 4, 7, 6, 7]
>>> count_e1 = [2, 3, 2]
>>> x = paddle.to_tensor(x, dtype="int64")
>>> neighbors_e1 = paddle.to_tensor(neighbors_e1, dtype="int64")
>>> count_e1 = paddle.to_tensor(count_e1, dtype="int32")

>>> reindex_src, reindex_dst, out_nodes = paddle.incubate.graph_reindex(
... x,
... neighbors_e1,
... count_e1,
... )
>>> print(reindex_src)
Tensor(shape=[7], dtype=int64, place=Place(cpu), stop_gradient=True,
[3, 4, 0, 5, 6, 7, 6])
>>> print(reindex_dst)
Tensor(shape=[7], dtype=int64, place=Place(cpu), stop_gradient=True,
[0, 0, 1, 1, 1, 2, 2])
>>> print(out_nodes)
Tensor(shape=[8], dtype=int64, place=Place(cpu), stop_gradient=True,
[0, 1, 2, 8, 9, 4, 7, 6])

>>> neighbors_e2 = [0, 2, 3, 5, 1]
>>> count_e2 = [1, 3, 1]
>>> neighbors_e2 = paddle.to_tensor(neighbors_e2, dtype="int64")
>>> count_e2 = paddle.to_tensor(count_e2, dtype="int32")

>>> neighbors = paddle.concat([neighbors_e1, neighbors_e2])
>>> count = paddle.concat([count_e1, count_e2])
>>> reindex_src, reindex_dst, out_nodes = paddle.incubate.graph_reindex(x, neighbors, count)
>>> print(reindex_src)
Tensor(shape=[12], dtype=int64, place=Place(cpu), stop_gradient=True,
[3, 4, 0, 5, 6, 7, 6, 0, 2, 8, 9, 1])
>>> print(reindex_dst)
Tensor(shape=[12], dtype=int64, place=Place(cpu), stop_gradient=True,
[0, 0, 1, 1, 1, 2, 2, 0, 1, 1, 1, 2])
>>> print(out_nodes)
Tensor(shape=[10], dtype=int64, place=Place(cpu), stop_gradient=True,
[0, 1, 2, 8, 9, 4, 7, 6, 3, 5])

"""
if flag_buffer_hashtable:
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29 changes: 16 additions & 13 deletions python/paddle/incubate/operators/graph_sample_neighbors.py
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Expand Up @@ -80,19 +80,22 @@ def graph_sample_neighbors(
Examples:
.. code-block:: python

import paddle
# edges: (3, 0), (7, 0), (0, 1), (9, 1), (1, 2), (4, 3), (2, 4),
# (9, 5), (3, 5), (9, 6), (1, 6), (9, 8), (7, 8)
row = [3, 7, 0, 9, 1, 4, 2, 9, 3, 9, 1, 9, 7]
colptr = [0, 2, 4, 5, 6, 7, 9, 11, 11, 13, 13]
nodes = [0, 8, 1, 2]
sample_size = 2
row = paddle.to_tensor(row, dtype="int64")
colptr = paddle.to_tensor(colptr, dtype="int64")
nodes = paddle.to_tensor(nodes, dtype="int64")
out_neighbors, out_count = \
paddle.incubate.graph_sample_neighbors(row, colptr, nodes,
sample_size=sample_size)
>>> import paddle
>>> # edges: (3, 0), (7, 0), (0, 1), (9, 1), (1, 2), (4, 3), (2, 4),
>>> # (9, 5), (3, 5), (9, 6), (1, 6), (9, 8), (7, 8)
>>> row = [3, 7, 0, 9, 1, 4, 2, 9, 3, 9, 1, 9, 7]
>>> colptr = [0, 2, 4, 5, 6, 7, 9, 11, 11, 13, 13]
>>> nodes = [0, 8, 1, 2]
>>> sample_size = 2
>>> row = paddle.to_tensor(row, dtype="int64")
>>> colptr = paddle.to_tensor(colptr, dtype="int64")
>>> nodes = paddle.to_tensor(nodes, dtype="int64")
>>> out_neighbors, out_count = paddle.incubate.graph_sample_neighbors(
... row,
... colptr,
... nodes,
... sample_size=sample_size
... )

"""

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58 changes: 34 additions & 24 deletions python/paddle/incubate/operators/graph_send_recv.py
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Expand Up @@ -91,30 +91,40 @@ def graph_send_recv(

.. code-block:: python

import paddle

x = paddle.to_tensor([[0, 2, 3], [1, 4, 5], [2, 6, 7]], dtype="float32")
indexes = paddle.to_tensor([[0, 1], [1, 2], [2, 1], [0, 0]], dtype="int32")
src_index = indexes[:, 0]
dst_index = indexes[:, 1]
out = paddle.incubate.graph_send_recv(x, src_index, dst_index, pool_type="sum")
# Outputs: [[0., 2., 3.], [2., 8., 10.], [1., 4., 5.]]

x = paddle.to_tensor([[0, 2, 3], [1, 4, 5], [2, 6, 7]], dtype="float32")
indexes = paddle.to_tensor([[0, 1], [2, 1], [0, 0]], dtype="int32")
src_index = indexes[:, 0]
dst_index = indexes[:, 1]
out_size = paddle.max(dst_index) + 1
out = paddle.incubate.graph_send_recv(x, src_index, dst_index, pool_type="sum", out_size=out_size)
# Outputs: [[0., 2., 3.], [[2., 8., 10.]]]

x = paddle.to_tensor([[0, 2, 3], [1, 4, 5], [2, 6, 7]], dtype="float32")
indexes = paddle.to_tensor([[0, 1], [2, 1], [0, 0]], dtype="int32")
src_index = indexes[:, 0]
dst_index = indexes[:, 1]
out = paddle.incubate.graph_send_recv(x, src_index, dst_index, pool_type="sum")
# Outputs: [[0., 2., 3.], [2., 8., 10.], [0., 0., 0.]]

>>> import paddle

>>> x = paddle.to_tensor([[0, 2, 3], [1, 4, 5], [2, 6, 7]], dtype="float32")
>>> indexes = paddle.to_tensor([[0, 1], [1, 2], [2, 1], [0, 0]], dtype="int32")
>>> src_index = indexes[:, 0]
>>> dst_index = indexes[:, 1]
>>> out = paddle.incubate.graph_send_recv(x, src_index, dst_index, pool_type="sum")
>>> print(out)
Tensor(shape=[3, 3], dtype=float32, place=Place(cpu), stop_gradient=True,
[[0. , 2. , 3. ],
[2. , 8. , 10.],
[1. , 4. , 5. ]])

>>> x = paddle.to_tensor([[0, 2, 3], [1, 4, 5], [2, 6, 7]], dtype="float32")
>>> indexes = paddle.to_tensor([[0, 1], [2, 1], [0, 0]], dtype="int32")
>>> src_index = indexes[:, 0]
>>> dst_index = indexes[:, 1]
>>> out_size = paddle.max(dst_index) + 1
>>> out = paddle.incubate.graph_send_recv(x, src_index, dst_index, pool_type="sum", out_size=out_size)
>>> print(out)
Tensor(shape=[2, 3], dtype=float32, place=Place(cpu), stop_gradient=True,
[[0. , 2. , 3. ],
[2. , 8. , 10.]])

>>> x = paddle.to_tensor([[0, 2, 3], [1, 4, 5], [2, 6, 7]], dtype="float32")
>>> indexes = paddle.to_tensor([[0, 1], [2, 1], [0, 0]], dtype="int32")
>>> src_index = indexes[:, 0]
>>> dst_index = indexes[:, 1]
>>> out = paddle.incubate.graph_send_recv(x, src_index, dst_index, pool_type="sum")
>>> print(out)
Tensor(shape=[3, 3], dtype=float32, place=Place(cpu), stop_gradient=True,
[[0. , 2. , 3. ],
[2. , 8. , 10.],
[0. , 0. , 0. ]])
"""

if pool_type not in ["sum", "mean", "max", "min"]:
Expand Down
17 changes: 9 additions & 8 deletions python/paddle/incubate/operators/softmax_mask_fuse.py
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Expand Up @@ -40,20 +40,21 @@ def softmax_mask_fuse(x, mask, name=None):
For more information, please refer to :ref:`api_guide_Name`.

Returns:
4-D Tensor. A location into which the result is stored. It’s dimension is 4D. Has same shape with x.
4-D Tensor. A location into which the result is stored. It's dimension is 4D. Has same shape with x.

Examples:
.. code-block:: python

# required: gpu
import paddle
import paddle.incubate as incubate
>>> # doctest: +REQUIRES(env:GPU)
>>> import paddle
>>> import paddle.incubate as incubate

x = paddle.rand([2, 8, 8, 32])
mask = paddle.rand([2, 1, 8, 32])
>>> x = paddle.rand([2, 8, 8, 32])
>>> mask = paddle.rand([2, 1, 8, 32])

rst = incubate.softmax_mask_fuse(x, mask)
# [[[[0.02404429, 0.04658398, 0.02746007, ..., 0.01489375, 0.02397441, 0.02851614] ... ]]]
>>> rst = incubate.softmax_mask_fuse(x, mask)
>>> rst.shape
[2, 8, 8, 32]
"""
if in_dynamic_mode():
out = _legacy_C_ops.fused_softmax_mask(x, mask)
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33 changes: 23 additions & 10 deletions python/paddle/incubate/operators/softmax_mask_fuse_upper_triangle.py
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Expand Up @@ -38,22 +38,35 @@ def softmax_mask_fuse_upper_triangle(x):
The third dimension of x must be same with the fourth dimension of x.

Returns:
4-D Tensor. A location into which the result is stored. It’s dimension is 4D. Has same dimension with x.
4-D Tensor. A location into which the result is stored. It's dimension is 4D. Has same dimension with x.

Examples:
.. code-block:: python

# required: gpu
import paddle
import paddle.incubate as incubate
>>> # doctest: +REQUIRES(env:GPU)
>>> import paddle
>>> import paddle.incubate as incubate

x = paddle.rand((1, 1, 32, 32))
>>> paddle.seed(1)
>>> paddle.set_device("gpu")
>>> x = paddle.rand((1, 1, 32, 32))

rst = incubate.softmax_mask_fuse_upper_triangle(x)
# [[[[1. , 0. , 0. , ..., 0., 0., 0.],
# [0.45324376, 0.54675621, 0. , ..., 0., 0., 0.],
# [0.32674268, 0.28156221, 0.39169508, ..., 0., 0., 0.]
# ... ]]]
>>> rst = incubate.softmax_mask_fuse_upper_triangle(x)
>>> print(rst)
Tensor(shape=[1, 1, 32, 32], dtype=float32, place=Place(gpu:0), stop_gradient=True,
[[[[1. , 0. , 0. , ..., 0. ,
0. , 0. ],
[0.49575609, 0.50424391, 0. , ..., 0. ,
0. , 0. ],
[0.26035303, 0.25114325, 0.48850375, ..., 0. ,
0. , 0. ],
...,
[0.04379999, 0.04194880, 0.05150032, ..., 0.02721255,
0. , 0. ],
[0.02348574, 0.01959674, 0.02609110, ..., 0.04046615,
0.02248267, 0. ],
[0.02280738, 0.03144657, 0.02892209, ..., 0.03885521,
0.03342311, 0.02842640]]]])
"""
if in_dynamic_mode():
out = _legacy_C_ops.fused_softmax_mask_upper_triangle(x)
Expand Down