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c5137b22
编写于
1月 03, 2023
作者:
J
Jianghai
提交者:
GitHub
1月 03, 2023
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差异文件
[Auto Parallel] Add All Relu Flops (#48083)
* relu flops all * add annotations and tests * revision for codestyle
上级
18c0a002
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
87 addition
and
10 deletion
+87
-10
python/paddle/fluid/tests/unittests/test_profiler.py
python/paddle/fluid/tests/unittests/test_profiler.py
+50
-3
python/paddle/utils/flops.py
python/paddle/utils/flops.py
+37
-7
未找到文件。
python/paddle/fluid/tests/unittests/test_profiler.py
浏览文件 @
c5137b22
...
...
@@ -293,9 +293,6 @@ class TestFLOPSAPI(unittest.TestCase):
)
==
3
*
12
*
12
*
12
*
2
*
8
)
self
.
assertTrue
(
flops
(
'relu'
,
{
'X'
:
[[
12
,
12
,
12
]]},
{})
==
12
*
12
*
12
)
self
.
assertTrue
(
flops
(
'softmax'
,
{
'X'
:
[[
12
,
12
,
12
]]},
{})
==
3
*
12
*
12
*
12
)
...
...
@@ -303,6 +300,56 @@ class TestFLOPSAPI(unittest.TestCase):
flops
(
'c_embedding'
,
{
'Ids'
:
[[
12
,
12
]],
'W'
:
[[
12
,
12
,
3
]]},
{})
==
0
)
self
.
assertTrue
(
flops
(
'elu'
,
{
'X'
:
[[
12
,
12
]],
},
{},
)
==
144
)
self
.
assertTrue
(
flops
(
'leaky_relu'
,
{
'X'
:
[[
12
,
12
]],
},
{},
)
==
144
)
self
.
assertTrue
(
flops
(
'prelu'
,
{
'X'
:
[[
12
,
12
]],
},
{},
)
==
144
)
self
.
assertTrue
(
flops
(
'relu6'
,
{
'X'
:
[[
12
,
12
]],
},
{},
)
==
144
)
self
.
assertTrue
(
flops
(
'silu'
,
{
'X'
:
[[
12
,
12
]],
},
{},
)
==
144
)
if
__name__
==
'__main__'
:
...
...
python/paddle/utils/flops.py
浏览文件 @
c5137b22
...
...
@@ -73,7 +73,7 @@ def _c_embedding_flops(input_shapes, attrs):
def
_dropout_flops
(
input_shapes
,
attrs
):
"""FLOPs computation for dropout op.
For dropout(input):
equation: flops = 0
equation: flops = 0
"""
return
0
...
...
@@ -191,7 +191,7 @@ def _matmul_v2_flops(input_shapes, attrs):
"""FLOPs computation for matmul_v2 op.
For matmul_v2(input,other):
input_shapes = [shape_of_input, shape_of_ohther]
shape_of_input = [dim1, dim2 ...dim_n_1, dim_n] length:n
shape_of_input =
[dim1, dim2 ...dim_n_1, dim_n] length:n
shape_of_other = [odim1, odim2 ... odim(n-m) ... odim_m_1, dim_m] length:m
suppose n > m and dim_n = odim_m_1:
shape_of_output = [dim1, dim2 ... max(dim(n-m), odim(n-m)), max(dim(n-m+1), odim(n-m+1))...dim_n_1, dim_m]
...
...
@@ -216,13 +216,43 @@ def _matmul_v2_flops(input_shapes, attrs):
return
2
*
macs
@
register_flops
(
"relu"
)
def
_relu_flops
(
input_shapes
,
attrs
):
"""FLOPs computation for relu op.
For relu(input):
def
_relu_class_flops
(
input_shapes
,
attrs
):
"""FLOPs computation for relu_like ops.
For elu/leaky_relu/prelu/relu/relu6/silu (input):
equation: flops = (numel)total number of elements in the input tensor.
"""
return
prod
(
input_shapes
.
get
(
'X'
)[
0
])
input
=
input_shapes
.
get
(
'X'
)[
0
]
return
prod
(
input
)
@
register_flops
(
"elu"
)
def
_elu_flops
(
input_shapes
,
attrs
):
return
_relu_class_flops
(
input_shapes
,
attrs
)
@
register_flops
(
"leaky_relu"
)
def
_leaky_relu_flops
(
input_shapes
,
attrs
):
return
_relu_class_flops
(
input_shapes
,
attrs
)
@
register_flops
(
"prelu"
)
def
_prelu_flops
(
input_shapes
,
attrs
):
return
_relu_class_flops
(
input_shapes
,
attrs
)
@
register_flops
(
"relu"
)
def
_relu_flops
(
input_shapes
,
attrs
):
return
_relu_class_flops
(
input_shapes
,
attrs
)
@
register_flops
(
"relu6"
)
def
_relu6_flops
(
input_shapes
,
attrs
):
return
_relu_class_flops
(
input_shapes
,
attrs
)
@
register_flops
(
"silu"
)
def
_silu_flops
(
input_shapes
,
attrs
):
return
_relu_class_flops
(
input_shapes
,
attrs
)
@
register_flops
(
"reshape2"
)
...
...
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