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[PPDiffusers] Not use recompute #374

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[PPDiffusers] Not use recompute #374

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5122192
Fix
co63oc Jan 6, 2024
9a0c182
Fix
co63oc Jan 6, 2024
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37 changes: 31 additions & 6 deletions ppdiffusers/ppdiffusers/models/unet_3d_blocks.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,7 @@
from paddle import nn
from paddle.distributed.fleet.utils import recompute

from ..utils import recompute_use_reentrant
from ..utils import recompute_use_reentrant, use_old_recompute
from ..utils.paddle_utils import apply_freeu
from .attention import Attention
from .dual_transformer_2d import DualTransformer2DModel
Expand Down Expand Up @@ -1013,7 +1013,12 @@ def forward(

blocks = zip(self.resnets, self.motion_modules)
for resnet, motion_module in blocks:
if self.training and self.gradient_checkpointing and not hidden_states.stop_gradient:
if (
self.training
and self.gradient_checkpointing
and not hidden_states.stop_gradient
and not use_old_recompute()
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这些应该不用加吧？之前都没有这些模块的。0.19.4

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@co63oc co63oc Jan 15, 2024 •
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https://github.com/PaddlePaddle/PaddleMIX/blob/ppdiffusers0.19.4/ppdiffusers/ppdiffusers/models/unet_3d_blocks.py
DownBlockMotion 是没有这些模块，升级增加的，不是要测试 recompute吗
增加 and not use_old_recompute() 用来测试 recompute

):

def create_custom_forward(module):
def custom_forward(*inputs):
Expand Down Expand Up @@ -1183,7 +1188,12 @@ def forward(

blocks = list(zip(self.resnets, self.attentions, self.motion_modules))
for i, (resnet, attn, motion_module) in enumerate(blocks):
if self.training and self.gradient_checkpointing and not hidden_states.stop_gradient:
if (
self.training
and self.gradient_checkpointing
and not hidden_states.stop_gradient
and not use_old_recompute()
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这些应该不用加吧？之前都没有这些模块的。0.19.4

):

def create_custom_forward(module, return_dict=None):
def custom_forward(*inputs):
Expand Down Expand Up @@ -1387,7 +1397,12 @@ def forward(

hidden_states = paddle.concat([hidden_states, res_hidden_states], axis=1)

if self.training and self.gradient_checkpointing and not hidden_states.stop_gradient:
if (
self.training
and self.gradient_checkpointing
and not hidden_states.stop_gradient
and not use_old_recompute()
):
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这些应该不用加吧？之前都没有这些模块的。0.19.4


def create_custom_forward(module, return_dict=None):
def custom_forward(*inputs):
Expand Down Expand Up @@ -1542,7 +1557,12 @@ def forward(

hidden_states = paddle.concat([hidden_states, res_hidden_states], axis=1)

if self.training and self.gradient_checkpointing and not hidden_states.stop_gradient:
if (
self.training
and self.gradient_checkpointing
and not hidden_states.stop_gradient
and not use_old_recompute()
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这些应该不用加吧？之前就没有这

):

def create_custom_forward(module):
def custom_forward(*inputs):
Expand Down Expand Up @@ -1699,7 +1719,12 @@ def forward(

blocks = zip(self.attentions, self.resnets[1:], self.motion_modules)
for attn, resnet, motion_module in blocks:
if self.training and self.gradient_checkpointing and not hidden_states.stop_gradient:
if (
self.training
and self.gradient_checkpointing
and not hidden_states.stop_gradient
and not use_old_recompute()
Copy link
Member

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The reason will be displayed to describe this comment to others. Learn more.

这些应该不用加吧？之前都没有这些模块的。0.19.4

):

def create_custom_forward(module, return_dict=None):
def custom_forward(*inputs):
Expand Down
6 changes: 3 additions & 3 deletions ppdiffusers/ppdiffusers/models/vae.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,7 @@
import paddle.nn as nn
from paddle.distributed.fleet.utils import recompute

from ..utils import BaseOutput, recompute_use_reentrant
from ..utils import BaseOutput, recompute_use_reentrant, use_old_recompute
from ..utils.paddle_utils import randn_tensor
from .activations import get_activation
from .attention_processor import SpatialNorm
Expand Down Expand Up @@ -850,7 +850,7 @@ def __init__(

def forward(self, x: paddle.Tensor) -> paddle.Tensor:
r"""The forward method of the `EncoderTiny` class."""
if self.training and self.gradient_checkpointing and not x.stop_gradient:
if self.training and self.gradient_checkpointing and not x.stop_gradient and not use_old_recompute():

def create_custom_forward(module):
def custom_forward(*inputs):
Expand Down Expand Up @@ -932,7 +932,7 @@ def forward(self, x: paddle.Tensor) -> paddle.Tensor:
# Clamp.
x = nn.functional.tanh(x / 3) * 3

if self.training and self.gradient_checkpointing and not x.stop_gradient:
if self.training and self.gradient_checkpointing and not x.stop_gradient and not use_old_recompute():

def create_custom_forward(module):
def custom_forward(*inputs):
Expand Down