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8c214b6a
编写于
6月 15, 2023
作者:
R
ronnywang
提交者:
GitHub
6月 15, 2023
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
[CustomDevice] add MOE support, PART2 (#54573)
上级
8771fff3
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
500 addition
and
99 deletion
+500
-99
paddle/fluid/distributed/collective/process_group_custom.cc
paddle/fluid/distributed/collective/process_group_custom.cc
+391
-26
paddle/fluid/distributed/collective/process_group_custom.h
paddle/fluid/distributed/collective/process_group_custom.h
+54
-19
paddle/fluid/distributed/collective/process_group_nccl.cc
paddle/fluid/distributed/collective/process_group_nccl.cc
+0
-54
paddle/fluid/distributed/collective/utils.h
paddle/fluid/distributed/collective/utils.h
+55
-0
未找到文件。
paddle/fluid/distributed/collective/process_group_custom.cc
浏览文件 @
8c214b6a
...
...
@@ -298,15 +298,6 @@ std::shared_ptr<ProcessGroup::Task> ProcessGroupCustom::AllGather(
use_calc_stream
);
}
std
::
shared_ptr
<
ProcessGroup
::
Task
>
ProcessGroupCustom
::
AllGather
(
phi
::
DenseTensor
*
out_tensor
,
const
phi
::
DenseTensor
&
in_tensor
,
int64_t
offset
,
int64_t
numel
,
bool
sync_op
)
{
return
AllGather
(
out_tensor
,
in_tensor
,
offset
,
numel
,
sync_op
,
false
);
}
// TODO(sunyilun): methods below will be removed later
std
::
shared_ptr
<
ProcessGroup
::
Task
>
ProcessGroupCustom
::
AllGather
(
std
::
vector
<
phi
::
DenseTensor
>&
in_tensors
,
...
...
@@ -382,15 +373,6 @@ std::shared_ptr<ProcessGroup::Task> ProcessGroupCustom::AllReduce(
use_calc_stream
);
}
std
::
shared_ptr
<
ProcessGroup
::
Task
>
ProcessGroupCustom
::
AllReduce
(
phi
::
DenseTensor
*
out_tensor
,
const
phi
::
DenseTensor
&
in_tensor
,
const
AllreduceOptions
&
opts
,
bool
sync_op
// for compatibility, no use now
)
{
return
AllReduce
(
out_tensor
,
in_tensor
,
opts
,
sync_op
,
false
);
}
std
::
shared_ptr
<
ProcessGroup
::
Task
>
ProcessGroupCustom
::
AllReduce
(
std
::
vector
<
phi
::
DenseTensor
>&
in_tensors
,
// NOLINT
std
::
vector
<
phi
::
DenseTensor
>&
out_tensors
,
// NOLINT
...
...
@@ -478,14 +460,6 @@ std::shared_ptr<ProcessGroup::Task> ProcessGroupCustom::Broadcast(
use_calc_stream
);
}
std
::
shared_ptr
<
ProcessGroup
::
Task
>
ProcessGroupCustom
::
Broadcast
(
phi
::
DenseTensor
*
out_tensor
,
const
phi
::
DenseTensor
&
in_tensor
,
const
BroadcastOptions
&
opts
,
bool
sync_op
)
{
return
Broadcast
(
out_tensor
,
in_tensor
,
opts
,
sync_op
,
false
);
}
std
::
shared_ptr
<
ProcessGroup
::
Task
>
ProcessGroupCustom
::
Barrier
(
const
BarrierOptions
&
opts
)
{
// Only support single card single process
...
...
@@ -759,6 +733,397 @@ std::shared_ptr<ProcessGroup::Task> ProcessGroupCustom::Reduce(
use_calc_stream
);
}
std
::
shared_ptr
<
ProcessGroup
::
Task
>
ProcessGroupCustom
::
Reduce
(
std
::
vector
<
phi
::
DenseTensor
>&
in_tensors
,
std
::
vector
<
phi
::
DenseTensor
>&
out_tensors
,
const
ReduceOptions
&
opts
)
{
PADDLE_ENFORCE_EQ
(
CheckTensorsInCustomPlace
(
in_tensors
,
device_type_
),
true
,
phi
::
errors
::
InvalidArgument
(
"All inputs should be in CustomPlace."
));
return
Collective
(
in_tensors
,
out_tensors
,
[
&
](
phi
::
DenseTensor
&
input
,
phi
::
DenseTensor
&
output
,
phi
::
ccl
::
CCLComm
comm
,
const
phi
::
stream
::
Stream
&
stream
)
{
phi
::
DeviceManager
::
CCLReduce
(
device_type_
,
input
.
data
(),
output
.
data
(),
input
.
numel
(),
phi
::
ccl
::
ToCCLDataType
(
input
.
dtype
()),
ToCustomCCLRedType
(
opts
.
reduce_op
),
opts
.
root_rank
,
comm
,
stream
);
},
CommType
::
REDUCE
,
false
,
false
);
}
std
::
shared_ptr
<
ProcessGroup
::
Task
>
ProcessGroupCustom
::
AllToAll
(
phi
::
DenseTensor
*
out_tensor
,
const
phi
::
DenseTensor
&
in_tensor
,
const
std
::
vector
<
int64_t
>&
out_size_each_rank
,
const
std
::
vector
<
int64_t
>&
in_size_each_rank
,
bool
sync_op
,
bool
use_calc_stream
)
{
const
phi
::
DDim
&
out_dim
=
out_tensor
->
dims
();
const
phi
::
DDim
&
in_dim
=
in_tensor
.
dims
();
CheckSizeOnEachRank
(
out_dim
,
out_size_each_rank
,
size_
);
CheckSizeOnEachRank
(
in_dim
,
in_size_each_rank
,
size_
);
// NOTE: Since `all_to_all` needs other processes' participation, it cannot
// simply be covered by static checks. Factors are set to 0 here to skip the
// shape check. Its shape check will be done by dynamic checks with
// FLAGS_enable_nccl_dynamic_check.
phi
::
distributed
::
CommStaticCheck
::
CheckShape
(
*
out_tensor
,
in_tensor
,
/*dst_rank*/
rank_
,
/*cur_rank*/
rank_
,
size_
,
/*out_size_factor*/
0
,
/*in_size_factor*/
0
,
phi
::
AllocationType
::
CUSTOM
);
std
::
vector
<
phi
::
DenseTensor
>
in_wrapper
{
in_tensor
};
std
::
vector
<
phi
::
DenseTensor
>
out_wrapper
{
*
out_tensor
};
return
Collective
(
in_wrapper
,
out_wrapper
,
[
&
](
phi
::
DenseTensor
&
input
,
phi
::
DenseTensor
&
output
,
phi
::
ccl
::
CCLComm
comm
,
const
phi
::
stream
::
Stream
&
stream
)
{
int64_t
in_row_size
=
in_tensor
.
numel
()
/
in_dim
[
0
],
out_row_size
=
out_tensor
->
numel
()
/
out_dim
[
0
];
int64_t
in_offset
=
0
,
in_numel
=
0
,
out_offset
=
0
,
out_numel
=
0
;
phi
::
DenseTensor
input_partial
,
output_partial
;
std
::
vector
<
void
*>
send_buf
,
recv_buf
;
std
::
vector
<
size_t
>
send_count
,
recv_count
;
std
::
vector
<
phi
::
ccl
::
CCLDataType
>
send_dtype
,
recv_dtype
;
for
(
auto
i
=
0
;
i
<
size_
;
i
++
)
{
in_numel
=
in_size_each_rank
[
i
]
*
in_row_size
;
input_partial
=
GetPartialTensor
(
in_tensor
,
in_offset
,
in_numel
);
out_numel
=
out_size_each_rank
[
i
]
*
out_row_size
;
output_partial
=
GetPartialTensor
(
*
out_tensor
,
out_offset
,
out_numel
);
in_offset
+=
in_numel
;
out_offset
+=
out_numel
;
send_buf
.
push_back
(
input_partial
.
data
());
recv_buf
.
push_back
(
output_partial
.
data
());
send_count
.
push_back
(
in_numel
);
recv_count
.
push_back
(
out_numel
);
send_dtype
.
push_back
(
phi
::
ccl
::
ToCCLDataType
(
input_partial
.
dtype
()));
recv_dtype
.
push_back
(
phi
::
ccl
::
ToCCLDataType
(
output_partial
.
dtype
()));
}
phi
::
DeviceManager
::
CCLAllToAll
(
device_type_
,
const_cast
<
const
void
**>
(
send_buf
.
data
()),
send_count
.
data
(),
send_dtype
.
data
(),
recv_buf
.
data
(),
recv_count
.
data
(),
recv_dtype
.
data
(),
rank_
,
size_
,
comm
,
stream
);
},
CommType
::
ALLTOALL
,
sync_op
,
use_calc_stream
);
}
std
::
shared_ptr
<
ProcessGroup
::
Task
>
ProcessGroupCustom
::
AllToAll
(
std
::
vector
<
phi
::
DenseTensor
>&
in_tensors
,
std
::
vector
<
phi
::
DenseTensor
>&
out_tensors
)
{
PADDLE_ENFORCE_EQ
(
CheckTensorsInCustomPlace
(
in_tensors
,
device_type_
),
true
,
phi
::
errors
::
InvalidArgument
(
"All inputs should be in CustomPlace."
));
PADDLE_ENFORCE_EQ
(
CheckTensorsInCustomPlace
(
out_tensors
,
device_type_
),
true
,
phi
::
errors
::
InvalidArgument
(
"All inputs should be in CustomPlace."
));
return
Collective
(
in_tensors
,
out_tensors
,
[
&
](
phi
::
DenseTensor
&
input
,
phi
::
DenseTensor
&
output
,
phi
::
ccl
::
CCLComm
comm
,
const
phi
::
stream
::
Stream
&
stream
)
{
size_t
offset
=
0
;
std
::
vector
<
void
*>
send_buf
,
recv_buf
;
std
::
vector
<
size_t
>
send_count
(
size_
,
input
.
numel
()
/
size_
),
recv_count
(
size_
,
input
.
numel
()
/
size_
);
std
::
vector
<
phi
::
ccl
::
CCLDataType
>
send_dtype
(
size_
,
phi
::
ccl
::
ToCCLDataType
(
input
.
dtype
())),
recv_dtype
(
size_
,
phi
::
ccl
::
ToCCLDataType
(
input
.
dtype
()));
for
(
auto
i
=
0
;
i
<
size_
;
i
++
)
{
send_buf
.
push_back
(
GetPointerByOffset
(
input
.
data
(),
offset
,
input
.
dtype
()));
recv_buf
.
push_back
(
GetPointerByOffset
(
output
.
data
(),
offset
,
input
.
dtype
()));
offset
+=
input
.
numel
()
/
size_
;
}
phi
::
DeviceManager
::
CCLAllToAll
(
device_type_
,
const_cast
<
const
void
**>
(
send_buf
.
data
()),
send_count
.
data
(),
send_dtype
.
data
(),
recv_buf
.
data
(),
recv_count
.
data
(),
recv_dtype
.
data
(),
rank_
,
size_
,
comm
,
stream
);
},
CommType
::
ALLTOALL
,
false
,
false
);
}
std
::
shared_ptr
<
ProcessGroup
::
Task
>
ProcessGroupCustom
::
ReduceScatter
(
phi
::
DenseTensor
*
out_tensor
,
const
phi
::
DenseTensor
&
in_tensor
,
const
ReduceScatterOptions
&
opts
,
bool
sync_op
,
bool
use_calc_stream
)
{
phi
::
distributed
::
CommStaticCheck
::
ScatterLikeShape
(
*
out_tensor
,
in_tensor
,
/*dst_rank*/
rank_
,
/*cur_rank*/
rank_
,
size_
,
phi
::
AllocationType
::
CUSTOM
);
std
::
vector
<
phi
::
DenseTensor
>
in_wrapper
{
in_tensor
};
std
::
vector
<
phi
::
DenseTensor
>
out_wrapper
{
*
out_tensor
};
return
Collective
(
in_wrapper
,
out_wrapper
,
[
&
](
phi
::
DenseTensor
&
input
,
phi
::
DenseTensor
&
output
,
phi
::
ccl
::
CCLComm
comm
,
const
phi
::
stream
::
Stream
&
stream
)
{
phi
::
DeviceManager
::
CCLReduceScatter
(
device_type_
,
const_cast
<
void
*>
(
in_tensor
.
data
()),
out_tensor
->
data
(),
out_tensor
->
numel
(),
phi
::
ccl
::
ToCCLDataType
(
in_tensor
.
dtype
()),
paddle
::
distributed
::
ToCustomCCLRedType
(
opts
.
reduce_op
),
comm
,
stream
);
},
CommType
::
REDUCE_SCATTER
,
false
,
false
);
}
std
::
shared_ptr
<
ProcessGroup
::
Task
>
ProcessGroupCustom
::
Scatter
(
phi
::
DenseTensor
*
out_tensor
,
const
phi
::
DenseTensor
&
in_tensor
,
const
ScatterOptions
&
opts
,
bool
sync_op
,
bool
use_calc_stream
)
{
phi
::
distributed
::
CommStaticCheck
::
ScatterLikeShape
(
*
out_tensor
,
in_tensor
,
/*dst_rank*/
opts
.
root_rank
,
/*cur_rank*/
rank_
,
size_
,
phi
::
AllocationType
::
CUSTOM
);
std
::
vector
<
phi
::
DenseTensor
>
in_wrapper
{
in_tensor
};
std
::
vector
<
phi
::
DenseTensor
>
out_wrapper
{
*
out_tensor
};
return
Collective
(
in_wrapper
,
out_wrapper
,
[
&
](
phi
::
DenseTensor
&
input
,
phi
::
DenseTensor
&
output
,
phi
::
ccl
::
CCLComm
comm
,
const
phi
::
stream
::
Stream
&
stream
)
{
int64_t
numel
=
in_tensor
.
numel
()
/
size_
;
if
(
rank_
==
opts
.
root_rank
)
{
int64_t
offset
=
0
;
phi
::
DenseTensor
partial_tensor
;
for
(
auto
i
=
0
;
i
<
size_
;
i
++
)
{
partial_tensor
=
GetPartialTensor
(
in_tensor
,
offset
,
numel
);
if
(
i
!=
rank_
)
{
phi
::
DeviceManager
::
CCLSend
(
device_type_
,
partial_tensor
.
data
(),
numel
,
phi
::
ccl
::
ToCCLDataType
(
partial_tensor
.
dtype
()),
i
,
comm
,
stream
);
}
else
{
phi
::
DeviceManager
::
GetDeviceWithPlace
(
stream
.
GetPlace
())
->
MemoryCopyD2D
(
out_tensor
->
data
(),
partial_tensor
.
data
(),
numel
*
phi
::
SizeOf
(
partial_tensor
.
dtype
()),
&
stream
);
}
offset
+=
numel
;
}
}
else
{
phi
::
DeviceManager
::
CCLRecv
(
device_type_
,
out_tensor
->
data
(),
numel
,
phi
::
ccl
::
ToCCLDataType
(
out_tensor
->
dtype
()),
opts
.
root_rank
,
comm
,
stream
);
}
},
CommType
::
SCATTER
,
sync_op
,
use_calc_stream
);
}
std
::
shared_ptr
<
ProcessGroup
::
Task
>
ProcessGroupCustom
::
Scatter
(
std
::
vector
<
phi
::
DenseTensor
>&
in_tensors
,
std
::
vector
<
phi
::
DenseTensor
>&
out_tensors
,
const
ScatterOptions
&
opts
)
{
PADDLE_ENFORCE_EQ
(
CheckTensorsInCustomPlace
(
in_tensors
,
device_type_
),
true
,
phi
::
errors
::
InvalidArgument
(
"All inputs should be in CudaPlace."
));
PADDLE_ENFORCE_EQ
(
CheckTensorsInCustomPlace
(
out_tensors
,
device_type_
),
true
,
phi
::
errors
::
InvalidArgument
(
"All inputs should be in CudaPlace."
));
return
Collective
(
in_tensors
,
out_tensors
,
[
&
](
phi
::
DenseTensor
&
input
,
phi
::
DenseTensor
&
output
,
phi
::
ccl
::
CCLComm
comm
,
const
phi
::
stream
::
Stream
&
stream
)
{
int64_t
numel
=
input
.
numel
()
/
size_
;
if
(
rank_
==
opts
.
root_rank
)
{
int64_t
offset
=
0
;
phi
::
DenseTensor
partial_tensor
;
for
(
auto
i
=
0
;
i
<
size_
;
i
++
)
{
partial_tensor
=
GetPartialTensor
(
input
,
offset
,
numel
);
if
(
i
!=
rank_
)
{
phi
::
DeviceManager
::
CCLSend
(
device_type_
,
partial_tensor
.
data
(),
numel
,
phi
::
ccl
::
ToCCLDataType
(
partial_tensor
.
dtype
()),
i
,
comm
,
stream
);
}
else
{
phi
::
DeviceManager
::
GetDeviceWithPlace
(
stream
.
GetPlace
())
->
MemoryCopyD2D
(
output
.
data
(),
partial_tensor
.
data
(),
numel
*
phi
::
SizeOf
(
partial_tensor
.
dtype
()),
&
stream
);
}
offset
+=
numel
;
}
}
else
{
phi
::
DeviceManager
::
CCLRecv
(
device_type_
,
output
.
data
(),
numel
,
phi
::
ccl
::
ToCCLDataType
(
output
.
dtype
()),
opts
.
root_rank
,
comm
,
stream
);
}
},
CommType
::
SCATTER
,
false
,
false
);
}
std
::
shared_ptr
<
ProcessGroup
::
Task
>
ProcessGroupCustom
::
Gather
(
phi
::
DenseTensor
*
out_tensor
,
const
phi
::
DenseTensor
&
in_tensor
,
const
GatherOptions
&
opts
,
bool
sync_op
,
bool
use_calc_stream
)
{
std
::
vector
<
phi
::
DenseTensor
>
partial_tensors
;
if
(
rank_
==
opts
.
root_rank
)
{
partial_tensors
.
reserve
(
size_
);
size_t
offset
=
0
;
size_t
numel
=
out_tensor
->
numel
()
/
size_
;
for
(
auto
i
=
0
;
i
<
size_
;
i
++
)
{
partial_tensors
.
push_back
(
GetPartialTensor
(
*
out_tensor
,
offset
,
numel
));
offset
+=
numel
;
}
}
return
Gather
(
&
partial_tensors
,
in_tensor
,
opts
,
sync_op
,
use_calc_stream
);
}
std
::
shared_ptr
<
ProcessGroup
::
Task
>
ProcessGroupCustom
::
Gather
(
std
::
vector
<
phi
::
DenseTensor
>*
gather_tensors_ptr
,
const
phi
::
DenseTensor
&
in_tensor
,
const
GatherOptions
&
opts
,
bool
sync_op
,
bool
use_calc_stream
)
{
auto
&
gather_tensors
=
*
gather_tensors_ptr
;
PADDLE_ENFORCE_GT
(
size_
,
opts
.
root_rank
,
phi
::
errors
::
InvalidArgument
(
"root world size [%d] is less than root rank [%d]"
,
size_
,
opts
.
root_rank
));
std
::
vector
<
phi
::
DenseTensor
>
in_wrapper
{
in_tensor
};
return
Collective
(
in_wrapper
,
in_wrapper
,
[
&
](
phi
::
DenseTensor
&
input
,
phi
::
DenseTensor
&
output
,
phi
::
ccl
::
CCLComm
comm
,
const
phi
::
stream
::
Stream
&
stream
)
{
// root receive from all devices
if
(
rank_
==
opts
.
root_rank
)
{
for
(
auto
i
=
0
;
i
<
size_
;
i
++
)
{
auto
&
gather_tensor
=
gather_tensors
[
i
];
if
(
i
!=
rank_
)
{
phi
::
DeviceManager
::
CCLRecv
(
device_type_
,
gather_tensor
.
data
(),
gather_tensor
.
numel
(),
phi
::
ccl
::
ToCCLDataType
(
gather_tensor
.
dtype
()),
i
,
comm
,
stream
);
}
else
{
phi
::
DeviceManager
::
GetDeviceWithPlace
(
stream
.
GetPlace
())
->
MemoryCopyD2D
(
gather_tensor
.
data
(),
in_tensor
.
data
(),
in_tensor
.
numel
()
*
phi
::
SizeOf
(
in_tensor
.
dtype
()),
&
stream
);
}
}
}
else
{
// send to root
phi
::
DeviceManager
::
CCLSend
(
device_type_
,
const_cast
<
void
*>
(
in_tensor
.
data
()),
in_tensor
.
numel
(),
phi
::
ccl
::
ToCCLDataType
(
in_tensor
.
dtype
()),
opts
.
root_rank
,
comm
,
stream
);
}
},
CommType
::
GATHER
,
sync_op
,
use_calc_stream
);
}
std
::
shared_ptr
<
ProcessGroupCustom
>
ProcessGroupCustom
::
CreateProcessGroupCustom
(
const
std
::
shared_ptr
<
phi
::
distributed
::
Store
>&
store
,
...
...
paddle/fluid/distributed/collective/process_group_custom.h
浏览文件 @
8c214b6a
...
...
@@ -100,13 +100,6 @@ class ProcessGroupCustom : public ProcessGroupWithStream {
bool
sync_op
,
bool
use_calc_stream
)
override
;
std
::
shared_ptr
<
ProcessGroup
::
Task
>
AllGather
(
phi
::
DenseTensor
*
out_tensor
,
const
phi
::
DenseTensor
&
in_tensor
,
int64_t
offset
,
int64_t
numel
,
bool
sync_op
)
override
;
std
::
shared_ptr
<
ProcessGroup
::
Task
>
AllReduce
(
std
::
vector
<
phi
::
DenseTensor
>&
in_tensors
,
std
::
vector
<
phi
::
DenseTensor
>&
out_tensors
,
...
...
@@ -119,12 +112,6 @@ class ProcessGroupCustom : public ProcessGroupWithStream {
bool
sync_op
,
bool
use_calc_stream
)
override
;
std
::
shared_ptr
<
ProcessGroup
::
Task
>
AllReduce
(
phi
::
DenseTensor
*
out_tensor
,
const
phi
::
DenseTensor
&
in_tensor
,
const
AllreduceOptions
&
opts
,
bool
sync_op
)
override
;
std
::
shared_ptr
<
ProcessGroup
::
Task
>
Broadcast
(
std
::
vector
<
phi
::
DenseTensor
>&
in_tensors
,
std
::
vector
<
phi
::
DenseTensor
>&
out_tensors
,
...
...
@@ -137,12 +124,6 @@ class ProcessGroupCustom : public ProcessGroupWithStream {
bool
sync_op
,
bool
use_calc_stream
)
override
;
std
::
shared_ptr
<
ProcessGroup
::
Task
>
Broadcast
(
phi
::
DenseTensor
*
out_tensor
,
const
phi
::
DenseTensor
&
in_tensor
,
const
BroadcastOptions
&
opts
,
bool
sync_op
)
override
;
std
::
shared_ptr
<
ProcessGroup
::
Task
>
Send
(
const
phi
::
DenseTensor
&
tensor
,
int
dst_rank
,
int64_t
offset
,
...
...
@@ -169,6 +150,54 @@ class ProcessGroupCustom : public ProcessGroupWithStream {
bool
sync_op
,
bool
use_calc_stream
)
override
;
std
::
shared_ptr
<
ProcessGroup
::
Task
>
Reduce
(
std
::
vector
<
phi
::
DenseTensor
>&
tensors
,
std
::
vector
<
phi
::
DenseTensor
>&
out_tensors
,
const
ReduceOptions
&
opts
)
override
;
std
::
shared_ptr
<
ProcessGroup
::
Task
>
AllToAll
(
phi
::
DenseTensor
*
out_tensor
,
const
phi
::
DenseTensor
&
in_tensor
,
const
std
::
vector
<
int64_t
>&
out_size_each_rank
,
const
std
::
vector
<
int64_t
>&
in_size_each_rank
,
bool
sync_op
,
bool
use_calc_stream
)
override
;
std
::
shared_ptr
<
ProcessGroup
::
Task
>
AllToAll
(
std
::
vector
<
phi
::
DenseTensor
>&
in_tensors
,
std
::
vector
<
phi
::
DenseTensor
>&
out_tensors
)
override
;
std
::
shared_ptr
<
ProcessGroup
::
Task
>
ReduceScatter
(
phi
::
DenseTensor
*
out_tensor
,
const
phi
::
DenseTensor
&
in_tensor
,
const
ReduceScatterOptions
&
opts
,
bool
sync_op
,
bool
use_calc_stream
)
override
;
std
::
shared_ptr
<
ProcessGroup
::
Task
>
Scatter
(
phi
::
DenseTensor
*
out_tensor
,
const
phi
::
DenseTensor
&
in_tensor
,
const
ScatterOptions
&
opts
,
bool
sync_op
,
bool
use_calc_stream
)
override
;
std
::
shared_ptr
<
ProcessGroup
::
Task
>
Scatter
(
std
::
vector
<
phi
::
DenseTensor
>&
in_tensors
,
std
::
vector
<
phi
::
DenseTensor
>&
out_tensors
,
const
ScatterOptions
&
opts
)
override
;
std
::
shared_ptr
<
ProcessGroup
::
Task
>
Gather
(
phi
::
DenseTensor
*
out_tensor
,
const
phi
::
DenseTensor
&
in_tensor
,
const
GatherOptions
&
opts
,
bool
sync_op
,
bool
use_calc_stream
)
override
;
std
::
shared_ptr
<
ProcessGroup
::
Task
>
Gather
(
std
::
vector
<
phi
::
DenseTensor
>*
gather_tensors_ptr
,
const
phi
::
DenseTensor
&
in_tensor
,
const
GatherOptions
&
opts
,
bool
sync_op
,
bool
use_calc_stream
)
override
;
protected:
virtual
std
::
shared_ptr
<
ProcessGroupCustom
::
CustomTask
>
CreateTask
(
std
::
vector
<
Place
>
places
,
...
...
@@ -206,6 +235,12 @@ class ProcessGroupCustom : public ProcessGroupWithStream {
bool
sync_op
,
bool
use_calc_stream
);
template
<
typename
Fn
>
std
::
shared_ptr
<
ProcessGroup
::
Task
>
Collective
(
Fn
fn
,
CommType
op_type
,
bool
sync_op
,
bool
use_calc_stream
);
void
CreateCustomManagerCache
(
const
std
::
string
&
places_key
,
const
std
::
vector
<
Place
>&
places
);
const
std
::
string
device_type_
;
...
...
paddle/fluid/distributed/collective/process_group_nccl.cc
浏览文件 @
8c214b6a
...
...
@@ -205,25 +205,6 @@ std::shared_ptr<ProcessGroup::Task> ProcessGroupNCCL::AllReduce(
use_calc_stream
);
}
void
CheckSizeOnEachRank
(
const
phi
::
DDim
&
tensor_dim
,
const
std
::
vector
<
int64_t
>&
size_on_each_rank
,
int
world_size
)
{
int
length_size_on_each_rank
=
size_on_each_rank
.
size
();
PADDLE_ENFORCE_EQ
(
length_size_on_each_rank
,
world_size
,
phi
::
errors
::
InvalidArgument
(
"The length of size_on_each_rank must be equal to world_size."
));
int64_t
sum_size_on_each_rank
=
std
::
accumulate
(
size_on_each_rank
.
begin
(),
size_on_each_rank
.
end
(),
0
);
PADDLE_ENFORCE_EQ
(
sum_size_on_each_rank
,
tensor_dim
[
0
],
phi
::
errors
::
InvalidArgument
(
"The sum of size_on_each_rank must be equal to tensor's dim[0]."
));
}
std
::
shared_ptr
<
ProcessGroup
::
Task
>
ProcessGroupNCCL
::
AllToAll
(
phi
::
DenseTensor
*
out_tensor
,
const
phi
::
DenseTensor
&
in_tensor
,
...
...
@@ -1059,41 +1040,6 @@ std::shared_ptr<ProcessGroup::Task> ProcessGroupNCCL::AllGather(
CommType
::
ALLGATHER
);
}
void
*
GetPointerByOffset
(
void
*
raw_pointer
,
size_t
offset
,
phi
::
DataType
type
)
{
if
(
type
==
phi
::
DataType
::
FLOAT32
)
{
return
reinterpret_cast
<
void
*>
(
reinterpret_cast
<
float
*>
(
raw_pointer
)
+
offset
);
}
else
if
(
type
==
phi
::
DataType
::
FLOAT64
)
{
return
reinterpret_cast
<
void
*>
(
reinterpret_cast
<
double
*>
(
raw_pointer
)
+
offset
);
}
else
if
(
type
==
phi
::
DataType
::
FLOAT16
)
{
return
reinterpret_cast
<
void
*>
(
reinterpret_cast
<
int16_t
*>
(
raw_pointer
)
+
offset
);
}
else
if
(
type
==
phi
::
DataType
::
INT32
)
{
return
reinterpret_cast
<
void
*>
(
reinterpret_cast
<
int32_t
*>
(
raw_pointer
)
+
offset
);
}
else
if
(
type
==
phi
::
DataType
::
INT64
)
{
return
reinterpret_cast
<
void
*>
(
reinterpret_cast
<
int64_t
*>
(
raw_pointer
)
+
offset
);
}
else
if
(
type
==
phi
::
DataType
::
INT8
)
{
return
reinterpret_cast
<
void
*>
(
reinterpret_cast
<
int8_t
*>
(
raw_pointer
)
+
offset
);
}
else
if
(
type
==
phi
::
DataType
::
UINT8
)
{
return
reinterpret_cast
<
void
*>
(
reinterpret_cast
<
uint8_t
*>
(
raw_pointer
)
+
offset
);
}
else
if
(
type
==
phi
::
DataType
::
BOOL
)
{
return
reinterpret_cast
<
void
*>
(
reinterpret_cast
<
bool
*>
(
raw_pointer
)
+
offset
);
}
else
if
(
type
==
phi
::
DataType
::
BFLOAT16
)
{
return
reinterpret_cast
<
void
*>
(
reinterpret_cast
<
uint16_t
*>
(
raw_pointer
)
+
offset
);
}
else
{
PADDLE_THROW
(
phi
::
errors
::
Unimplemented
(
"Datatype %s in NCCL is not supported."
,
type
));
}
return
nullptr
;
}
std
::
shared_ptr
<
ProcessGroup
::
Task
>
ProcessGroupNCCL
::
AllToAll
(
std
::
vector
<
phi
::
DenseTensor
>&
in_tensors
,
std
::
vector
<
phi
::
DenseTensor
>&
out_tensors
)
{
...
...
paddle/fluid/distributed/collective/utils.h
浏览文件 @
8c214b6a
...
...
@@ -28,5 +28,60 @@ inline phi::DenseTensor GetPartialTensor(const phi::DenseTensor& tensor,
return
tensor_flattened
.
Slice
(
offset
,
offset
+
numel
);
}
inline
void
*
GetPointerByOffset
(
void
*
raw_pointer
,
size_t
offset
,
phi
::
DataType
type
)
{
if
(
type
==
phi
::
DataType
::
FLOAT32
)
{
return
reinterpret_cast
<
void
*>
(
reinterpret_cast
<
float
*>
(
raw_pointer
)
+
offset
);
}
else
if
(
type
==
phi
::
DataType
::
FLOAT64
)
{
return
reinterpret_cast
<
void
*>
(
reinterpret_cast
<
double
*>
(
raw_pointer
)
+
offset
);
}
else
if
(
type
==
phi
::
DataType
::
FLOAT16
)
{
return
reinterpret_cast
<
void
*>
(
reinterpret_cast
<
int16_t
*>
(
raw_pointer
)
+
offset
);
}
else
if
(
type
==
phi
::
DataType
::
INT32
)
{
return
reinterpret_cast
<
void
*>
(
reinterpret_cast
<
int32_t
*>
(
raw_pointer
)
+
offset
);
}
else
if
(
type
==
phi
::
DataType
::
INT64
)
{
return
reinterpret_cast
<
void
*>
(
reinterpret_cast
<
int64_t
*>
(
raw_pointer
)
+
offset
);
}
else
if
(
type
==
phi
::
DataType
::
INT8
)
{
return
reinterpret_cast
<
void
*>
(
reinterpret_cast
<
int8_t
*>
(
raw_pointer
)
+
offset
);
}
else
if
(
type
==
phi
::
DataType
::
UINT8
)
{
return
reinterpret_cast
<
void
*>
(
reinterpret_cast
<
uint8_t
*>
(
raw_pointer
)
+
offset
);
}
else
if
(
type
==
phi
::
DataType
::
BOOL
)
{
return
reinterpret_cast
<
void
*>
(
reinterpret_cast
<
bool
*>
(
raw_pointer
)
+
offset
);
}
else
if
(
type
==
phi
::
DataType
::
BFLOAT16
)
{
return
reinterpret_cast
<
void
*>
(
reinterpret_cast
<
uint16_t
*>
(
raw_pointer
)
+
offset
);
}
else
{
PADDLE_THROW
(
phi
::
errors
::
Unimplemented
(
"Datatype %s in NCCL is not supported."
,
type
));
}
return
nullptr
;
}
inline
void
CheckSizeOnEachRank
(
const
phi
::
DDim
&
tensor_dim
,
const
std
::
vector
<
int64_t
>&
size_on_each_rank
,
int
world_size
)
{
int
length_size_on_each_rank
=
size_on_each_rank
.
size
();
PADDLE_ENFORCE_EQ
(
length_size_on_each_rank
,
world_size
,
phi
::
errors
::
InvalidArgument
(
"The length of size_on_each_rank must be equal to world_size."
));
int64_t
sum_size_on_each_rank
=
std
::
accumulate
(
size_on_each_rank
.
begin
(),
size_on_each_rank
.
end
(),
0
);
PADDLE_ENFORCE_EQ
(
sum_size_on_each_rank
,
tensor_dim
[
0
],
phi
::
errors
::
InvalidArgument
(
"The sum of size_on_each_rank must be equal to tensor's dim[0]."
));
}
}
// namespace distributed
}
// namespace paddle
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