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体验新版 GitCode,发现更多精彩内容 >>
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7567c76c
编写于
11月 13, 2021
作者:
O
Olatunji Ruwase
提交者:
GitHub
11月 13, 2021
浏览文件
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电子邮件补丁
差异文件
Update offload parameter names (#1536)
Co-authored-by:
N
Jeff Rasley
<
jerasley@microsoft.com
>
上级
9caa74e5
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
18 addition
and
13 deletion
+18
-13
deepspeed/runtime/zero/stage2.py
deepspeed/runtime/zero/stage2.py
+3
-1
deepspeed/runtime/zero/stage3.py
deepspeed/runtime/zero/stage3.py
+5
-2
docs/code-docs/source/memory.rst
docs/code-docs/source/memory.rst
+10
-10
未找到文件。
deepspeed/runtime/zero/stage2.py
浏览文件 @
7567c76c
...
@@ -15,6 +15,7 @@ import collections
...
@@ -15,6 +15,7 @@ import collections
from
deepspeed.runtime.fp16.loss_scaler
import
LossScaler
,
DynamicLossScaler
from
deepspeed.runtime.fp16.loss_scaler
import
LossScaler
,
DynamicLossScaler
from
deepspeed.runtime.utils
import
bwc_tensor_model_parallel_rank
,
get_global_norm
,
see_memory_usage
,
is_model_parallel_parameter
from
deepspeed.runtime.utils
import
bwc_tensor_model_parallel_rank
,
get_global_norm
,
see_memory_usage
,
is_model_parallel_parameter
from
deepspeed.runtime.zero.config
import
ZERO_OPTIMIZATION_GRADIENTS
from
deepspeed.runtime.zero.config
import
ZERO_OPTIMIZATION_GRADIENTS
from
deepspeed.runtime.zero.offload_constants
import
OFFLOAD_CPU_DEVICE
,
OFFLOAD_OPTIMIZER
,
OFFLOAD_OPTIMIZER_DEVICE
from
deepspeed.ops.adam
import
DeepSpeedCPUAdam
from
deepspeed.ops.adam
import
DeepSpeedCPUAdam
from
deepspeed.ops.op_builder
import
UtilsBuilder
from
deepspeed.ops.op_builder
import
UtilsBuilder
from
deepspeed.utils
import
logger
from
deepspeed.utils
import
logger
...
@@ -2242,7 +2243,8 @@ def estimate_zero2_model_states_mem_needs_all_cold(total_params,
...
@@ -2242,7 +2243,8 @@ def estimate_zero2_model_states_mem_needs_all_cold(total_params,
"""
"""
def
format_options
(
cpu_offload
):
def
format_options
(
cpu_offload
):
enabled
=
[]
enabled
=
[]
enabled
.
append
(
f
"cpu_offload=
{
1
if
cpu_offload
else
0
}
"
)
device
=
f
'
{
OFFLOAD_CPU_DEVICE
:
4
}
'
if
cpu_offload
else
"none"
enabled
.
append
(
f
"
{
OFFLOAD_OPTIMIZER
}
=
{
device
}
"
)
return
", "
.
join
(
enabled
)
return
", "
.
join
(
enabled
)
nodes_str
=
"nodes"
if
num_nodes
>
1
else
"node"
nodes_str
=
"nodes"
if
num_nodes
>
1
else
"node"
...
...
deepspeed/runtime/zero/stage3.py
浏览文件 @
7567c76c
...
@@ -3431,8 +3431,11 @@ def estimate_zero3_model_states_mem_needs_all_cold(total_params,
...
@@ -3431,8 +3431,11 @@ def estimate_zero3_model_states_mem_needs_all_cold(total_params,
"""
"""
def
format_options
(
cpu_offload
,
cpu_offload_params
,
zero_init
):
def
format_options
(
cpu_offload
,
cpu_offload_params
,
zero_init
):
enabled
=
[]
enabled
=
[]
enabled
.
append
(
f
"cpu_offload=
{
1
if
cpu_offload
else
0
}
"
)
padded_cpu_str
=
f
'
{
OFFLOAD_CPU_DEVICE
:
4
}
'
enabled
.
append
(
f
"cpu_offload_params=
{
1
if
cpu_offload_params
else
0
}
"
)
param_device
=
padded_cpu_str
if
cpu_offload_params
else
"none"
enabled
.
append
(
f
"
{
OFFLOAD_PARAM
}
=
{
param_device
}
"
)
optimizer_device
=
padded_cpu_str
if
cpu_offload
else
"none"
enabled
.
append
(
f
"
{
OFFLOAD_OPTIMIZER
}
=
{
optimizer_device
}
"
)
enabled
.
append
(
f
"zero_init=
{
1
if
zero_init
else
0
}
"
)
enabled
.
append
(
f
"zero_init=
{
1
if
zero_init
else
0
}
"
)
return
", "
.
join
(
enabled
)
return
", "
.
join
(
enabled
)
...
...
docs/code-docs/source/memory.rst
浏览文件 @
7567c76c
...
@@ -128,19 +128,19 @@ The big question is how big of a model you can fit on the hardware you have? Or
...
@@ -128,19 +128,19 @@ The big question is how big of a model you can fit on the hardware you have? Or
*
ZeRO
-
2
:
*
ZeRO
-
2
:
-
``
"
cpu_offload"
:
true
``:
2
*
params
-
``
"
offload_optimizer"
:
{
"device"
:
"cpu"
}
``:
2
*
params
Example
:
a
40
GB
GPU
can
fit
~
11
B
param
model
(
regardless
of
how
many
GPUs
are
used
).
Here
the
model
is
loaded
in
``
fp16
``
so
just
the
model
weights
take
about
22
GB
and
the
remaining
18
GB
are
used
by
other
components
.
You
can
barely
fit
a
very
small
batch
size
in
this
scenario
.
Example
:
a
40
GB
GPU
can
fit
~
11
B
param
model
(
regardless
of
how
many
GPUs
are
used
).
Here
the
model
is
loaded
in
``
fp16
``
so
just
the
model
weights
take
about
22
GB
and
the
remaining
18
GB
are
used
by
other
components
.
You
can
barely
fit
a
very
small
batch
size
in
this
scenario
.
-
``
"
cpu_offload"
:
false
``:
4
params
+
16
params
/
(
total
number
of
gpus
)
-
``
"
offload_optimizer"
:
{
"device"
:
"none"
}``:
4
*
params
+
16
*
params
/
(
total
number
of
gpus
)
*
ZeRO
-
3
:
*
ZeRO
-
3
:
``
largest_layer_memory
=
4
*
largest_layer_params
``
-
GPU
memory
needed
to
gather
the
largest
layer
on
a
single
GPU
.
2
bytes
fp16
params
are
gathered
and
2
bytes
fp16
grads
are
computed
(
total
4
x
).
The
optimizer
states
and
fp32
parameters
are
updated
in
partitioned
form
and
copied
to
fp16
params
in
partitioned
form
.
This
happens
during
the
optimizer
step
.
After
that
the
fp16
params
are
sufficient
.
``
largest_layer_memory
=
4
*
largest_layer_params
``
-
GPU
memory
needed
to
gather
the
largest
layer
on
a
single
GPU
.
2
bytes
fp16
params
are
gathered
and
2
bytes
fp16
grads
are
computed
(
total
4
x
).
The
optimizer
states
and
fp32
parameters
are
updated
in
partitioned
form
and
copied
to
fp16
params
in
partitioned
form
.
This
happens
during
the
optimizer
step
.
After
that
the
fp16
params
are
sufficient
.
-
case
1
:
``
"
cpu_offload"
:
false
,
"cpu_offload_params"
:
false
``
-
largest_layer_memory
+
18
*
params
/
total
number
of
gpus
across
all
nodes
-
case
1
:
``
"
offload_param"
:
{
"device"
:
"none"
},
"offload_optimizer"
:
{
"device"
:
"none"
}
``
-
largest_layer_memory
+
18
*
params
/
total
number
of
gpus
across
all
nodes
-
case
2
:
``
"
cpu_offload"
:
true
,
"cpu_offload_params"
:
true
``-
largest_layer_memory
.
The
main
limit
here
is
general
RAM
.
-
case
2
:
``
"
offload_param"
:
{
"device"
:
"cpu"
},
"offload_optimizer"
:
{
"device"
:
"cpu"
}
``-
largest_layer_memory
.
The
main
limit
here
is
general
RAM
.
-
case
3
:
``
"
cpu_offload"
:
true
,
"cpu_offload_params"
:
false
``-
largest_layer_memory
+
2
*
params
/
total
number
of
gpus
across
all
nodes
-
case
3
:
``
"
offload_param"
:
{
"device"
:
"none"
},
"offload_optimizer"
:
{
"device"
:
"cpu"
}
``-
largest_layer_memory
+
2
*
params
/
total
number
of
gpus
across
all
nodes
Example
:
Example
:
...
@@ -194,11 +194,11 @@ In the following calculations we will use:
...
@@ -194,11 +194,11 @@ In the following calculations we will use:
* ZeRO-2:
* ZeRO-2:
- ``"
cpu_offload": false
``:
- ``"
offload_optimizer": {"device": "none"}
``:
params * 4 * n_gpus * additional_buffer_factor - this is the memory needed only at the beginning to initialize the model on CPU memory
params * 4 * n_gpus * additional_buffer_factor - this is the memory needed only at the beginning to initialize the model on CPU memory
- ``"
cpu_offload": true
``:
- ``"
offload_optimizer": {"device": "cpu"}
``:
params * max(4 * n_gpus, 16) * additional_buffer_factor
params * max(4 * n_gpus, 16) * additional_buffer_factor
...
@@ -208,7 +208,7 @@ In the following calculations we will use:
...
@@ -208,7 +208,7 @@ In the following calculations we will use:
gpus_factor = n_gpus / total_gpus
gpus_factor = n_gpus / total_gpus
- case 1: ``"
cpu_offload": false
``:
- case 1: ``"
offload_param": {"device": "none"}, "offload_optimizer": {"device": "none"}
``:
Without ``zero.Init``:
Without ``zero.Init``:
...
@@ -222,7 +222,7 @@ In the following calculations we will use:
...
@@ -222,7 +222,7 @@ In the following calculations we will use:
assuming Pytorch is deallocating the memory once the tensors are moved to the GPU by ZeRO.Init
assuming Pytorch is deallocating the memory once the tensors are moved to the GPU by ZeRO.Init
- case 2: ``"
cpu_offload": true, cpu_offload_params true
``:
- case 2: ``"
offload_param": {"device": "cpu"}, "offload_optimizer": {"device": "cpu"}
``:
Without ``zero.Init``:
Without ``zero.Init``:
...
@@ -232,7 +232,7 @@ In the following calculations we will use:
...
@@ -232,7 +232,7 @@ In the following calculations we will use:
params * 18 * gpus_factor * additional_buffer_factor
params * 18 * gpus_factor * additional_buffer_factor
- case 3: ``"
cpu_offload": true, cpu_offload_params false
``:
- case 3: ``"
offload_param": {"device": "none"}, "offload_optimizer": {"device": "cpu"}
``:
Without ``zero.Init``:
Without ``zero.Init``:
...
...
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