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体验新版 GitCode,发现更多精彩内容 >>
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f6e8bf0d
编写于
4月 23, 2020
作者:
X
Xing Wu
提交者:
GitHub
4月 23, 2020
浏览文件
操作
浏览文件
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电子邮件补丁
差异文件
update cudnn rnn weights, test=develop (#23929)
上级
720d1899
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
24 addition
and
31 deletion
+24
-31
python/paddle/fluid/dygraph/rnn.py
python/paddle/fluid/dygraph/rnn.py
+10
-20
python/paddle/fluid/tests/unittests/test_cudnn_grucell.py
python/paddle/fluid/tests/unittests/test_cudnn_grucell.py
+2
-2
python/paddle/fluid/tests/unittests/test_cudnn_lstmcell.py
python/paddle/fluid/tests/unittests/test_cudnn_lstmcell.py
+12
-9
未找到文件。
python/paddle/fluid/dygraph/rnn.py
浏览文件 @
f6e8bf0d
...
...
@@ -39,7 +39,6 @@ class LSTMCell(Layer):
\\
tilde{c_t} &= tanh(W_{cx}x_t + W_{ch}h_{t-1} + b_c)
c_t &= f_t
\\
odot c_{t-1} + i_t
\\
odot
\\
tilde{c_t}
h_t &= o_t
\\
odot tanh(c_t)
Args:
hidden_size (integer): The hidden size used in the Cell.
input_size (integer): The input size used in the Cell.
...
...
@@ -64,30 +63,25 @@ class LSTMCell(Layer):
Returns:
None
Examples:
.. code-block:: python
from paddle import fluid
import paddle.fluid.core as core
from paddle.fluid.dygraph.rnn import LSTMCell
import numpy as np
batch_size = 64
input_size = 128
hidden_size = 256
step_input_np = np.random.uniform(-0.1, 0.1, (
batch_size, input_size)).astype('float64')
pre_hidden_np = np.random.uniform(-0.1, 0.1, (
batch_size, hidden_size)).astype('float64')
pre_cell_np = np.random.uniform(-0.1, 0.1, (
batch_size, hidden_size)).astype('float64')
if core.is_compiled_with_cuda():
place = core.CUDAPlace(0)
else:
place = core.CPUPlace()
with fluid.dygraph.guard(place):
cudnn_lstm = LSTMCell(hidden_size, input_size)
step_input_var = fluid.dygraph.to_variable(step_input_np)
...
...
@@ -139,12 +133,12 @@ class LSTMCell(Layer):
self
.
_weight_ih
=
self
.
create_parameter
(
attr
=
weight_ih_param_attr
,
shape
=
[
self
.
_input_size
,
4
*
self
.
_hidden
_size
],
shape
=
[
4
*
self
.
_hidden_size
,
self
.
_input
_size
],
dtype
=
self
.
_dtype
)
self
.
_weight_hh
=
self
.
create_parameter
(
attr
=
weight_hh_param_attr
,
shape
=
[
self
.
_hidden_size
,
4
*
self
.
_hidden_size
],
shape
=
[
4
*
self
.
_hidden_size
,
self
.
_hidden_size
],
dtype
=
self
.
_dtype
)
self
.
_bias_ih
=
self
.
create_parameter
(
...
...
@@ -180,10 +174,10 @@ class LSTMCell(Layer):
def
forward
(
self
,
input
,
pre_hidden
,
pre_cell
):
if
self
.
_use_cudnn_impl
:
igates
=
layers
.
matmul
(
input
,
y
=
self
.
_weight_ih
)
igates
=
layers
.
matmul
(
input
,
y
=
self
.
_weight_ih
,
transpose_y
=
True
)
igates
=
layers
.
elementwise_add
(
igates
,
self
.
_bias_ih
)
hgates
=
layers
.
matmul
(
pre_hidden
,
self
.
_weight_hh
)
hgates
=
layers
.
matmul
(
pre_hidden
,
self
.
_weight_hh
,
transpose_y
=
True
)
hgates
=
layers
.
elementwise_add
(
hgates
,
self
.
_bias_hh
)
chunked_igates
=
layers
.
split
(
igates
,
num_or_sections
=
4
,
dim
=
1
)
...
...
@@ -264,28 +258,23 @@ class GRUCell(Layer):
Returns:
None
Examples:
.. code-block:: python
from paddle import fluid
import paddle.fluid.core as core
from paddle.fluid.dygraph.rnn import GRUCell
import numpy as np
batch_size = 64
input_size = 128
hidden_size = 256
step_input_np = np.random.uniform(-0.1, 0.1, (
batch_size, input_size)).astype('float64')
pre_hidden_np = np.random.uniform(-0.1, 0.1, (
batch_size, hidden_size)).astype('float64')
if core.is_compiled_with_cuda():
place = core.CUDAPlace(0)
else:
place = core.CPUPlace()
with fluid.dygraph.guard(place):
cudnn_gru = GRUCell(hidden_size, input_size)
step_input_var = fluid.dygraph.to_variable(step_input_np)
...
...
@@ -334,12 +323,12 @@ class GRUCell(Layer):
self
.
_weight_ih
=
self
.
create_parameter
(
attr
=
weight_ih_param_attr
,
shape
=
[
self
.
_input_size
,
3
*
self
.
_hidden
_size
],
shape
=
[
3
*
self
.
_hidden_size
,
self
.
_input
_size
],
dtype
=
self
.
_dtype
)
self
.
_weight_hh
=
self
.
create_parameter
(
attr
=
weight_hh_param_attr
,
shape
=
[
self
.
_hidden_size
,
3
*
self
.
_hidden_size
],
shape
=
[
3
*
self
.
_hidden_size
,
self
.
_hidden_size
],
dtype
=
self
.
_dtype
)
self
.
_bias_ih
=
self
.
create_parameter
(
...
...
@@ -402,9 +391,10 @@ class GRUCell(Layer):
if
self
.
_use_cudnn_impl
:
igates
=
layers
.
matmul
(
input
,
y
=
self
.
_weight_ih
)
igates
=
layers
.
matmul
(
input
,
y
=
self
.
_weight_ih
,
transpose_y
=
True
)
igates
=
layers
.
elementwise_add
(
igates
,
self
.
_bias_ih
)
hgates
=
layers
.
matmul
(
pre_hidden
,
self
.
_weight_hh
)
hgates
=
layers
.
matmul
(
pre_hidden
,
self
.
_weight_hh
,
transpose_y
=
True
)
hgates
=
layers
.
elementwise_add
(
hgates
,
self
.
_bias_hh
)
chunked_igates
=
layers
.
split
(
igates
,
num_or_sections
=
3
,
dim
=
1
)
...
...
python/paddle/fluid/tests/unittests/test_cudnn_grucell.py
浏览文件 @
f6e8bf0d
...
...
@@ -34,9 +34,9 @@ def tanh(x):
def
cudnn_step
(
step_input_np
,
pre_hidden_np
,
weight_ih
,
bias_ih
,
weight_hh
,
bias_hh
):
igates
=
np
.
matmul
(
step_input_np
,
weight_ih
)
igates
=
np
.
matmul
(
step_input_np
,
weight_ih
.
transpose
(
1
,
0
)
)
igates
+=
bias_ih
hgates
=
np
.
matmul
(
pre_hidden_np
,
weight_hh
)
hgates
=
np
.
matmul
(
pre_hidden_np
,
weight_hh
.
transpose
(
1
,
0
)
)
hgates
+=
bias_hh
chunked_igates
=
np
.
split
(
igates
,
indices_or_sections
=
3
,
axis
=
1
)
...
...
python/paddle/fluid/tests/unittests/test_cudnn_lstmcell.py
浏览文件 @
f6e8bf0d
...
...
@@ -32,7 +32,12 @@ def tanh(x):
return
2.
*
sigmoid
(
2.
*
x
)
-
1.
def
cudnn_step
(
step_in
,
pre_hidden
,
pre_cell
,
gate_w
,
gate_b
,
forget_bias
=
1.0
):
def
non_cudnn_step
(
step_in
,
pre_hidden
,
pre_cell
,
gate_w
,
gate_b
,
forget_bias
=
1.0
):
concat_1
=
np
.
concatenate
([
step_in
,
pre_hidden
],
1
)
gate_input
=
np
.
matmul
(
concat_1
,
gate_w
)
...
...
@@ -45,12 +50,12 @@ def cudnn_step(step_in, pre_hidden, pre_cell, gate_w, gate_b, forget_bias=1.0):
return
new_hidden
,
new_cell
def
non_cudnn_step
(
step_input_np
,
pre_hidden_np
,
pre_cell_np
,
weight
_ih
,
bias_ih
,
weight_hh
,
bias_hh
):
def
cudnn_step
(
step_input_np
,
pre_hidden_np
,
pre_cell_np
,
weight_ih
,
bias
_ih
,
weight_hh
,
bias_hh
):
igates
=
np
.
matmul
(
step_input_np
,
weight_ih
)
igates
=
np
.
matmul
(
step_input_np
,
weight_ih
.
transpose
(
1
,
0
)
)
igates
=
igates
+
bias_ih
hgates
=
np
.
matmul
(
pre_hidden_np
,
weight_hh
)
hgates
=
np
.
matmul
(
pre_hidden_np
,
weight_hh
.
transpose
(
1
,
0
)
)
hgates
=
hgates
+
bias_hh
chunked_igates
=
np
.
split
(
igates
,
indices_or_sections
=
4
,
axis
=
1
)
...
...
@@ -102,7 +107,6 @@ class TestCudnnLSTM(unittest.TestCase):
bias_ih_name
=
"_bias_ih"
weight_hh_name
=
"_weight_hh"
bias_hh_name
=
"_bias_hh"
weight_ih
=
param_list
[
weight_ih_name
].
numpy
()
weight_ih
=
np
.
random
.
uniform
(
-
0.1
,
0.1
,
size
=
weight_ih
.
shape
).
astype
(
'float64'
)
...
...
@@ -146,10 +150,9 @@ class TestCudnnLSTM(unittest.TestCase):
named_api_hidden_out
=
named_api_out
[
0
]
named_api_cell_out
=
named_api_out
[
1
]
np_hidden_out
,
np_cell_out
=
non_
cudnn_step
(
np_hidden_out
,
np_cell_out
=
cudnn_step
(
step_input_np
,
pre_hidden_np
,
pre_cell_np
,
weight_ih
,
bias_ih
,
weight_hh
,
bias_hh
)
self
.
assertTrue
(
np
.
allclose
(
api_hidden_out
.
numpy
(),
np_hidden_out
,
rtol
=
1e-5
,
atol
=
0
))
...
...
@@ -230,7 +233,7 @@ class TestNonCudnnLSTM(unittest.TestCase):
named_api_hidden_out
=
named_api_out
[
0
]
named_api_cell_out
=
named_api_out
[
1
]
np_hidden_out
,
np_cell_out
=
cudnn_step
(
np_hidden_out
,
np_cell_out
=
non_
cudnn_step
(
step_input_np
,
pre_hidden_np
,
pre_cell_np
,
gate_w
,
gate_b
)
self
.
assertTrue
(
...
...
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