Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

【易用性提升No.7】为transformerDecoderLayer新增layer_norm_eps参数 #60084

Merged
merged 2 commits into from
Dec 22, 2023
Merged

【易用性提升No.7】为transformerDecoderLayer新增layer_norm_eps参数 #60084

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
ec2c81b
add layer_norm_eps
YibinLiu666 Dec 17, 2023
00ac467
fix ci
YibinLiu666 Dec 19, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
8 changes: 5 additions & 3 deletions python/paddle/nn/layer/transformer.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -806,6 +806,7 @@ class TransformerDecoderLayer(Layer):
corresponding layer would not have trainable bias parameter. See
usage for details in :code:`ParamAttr` . Default: None,which means
the default bias parameter property is used.
layer_norm_eps: the eps value in layer normalization components. Default=1e-5.

Examples:

Expand Down Expand Up @@ -843,6 +844,7 @@ def __init__(
normalize_before=False,
weight_attr=None,
bias_attr=None,
layer_norm_eps=1e-5,
):
self._config = locals()
self._config.pop("self")
Expand Down Expand Up @@ -889,9 +891,9 @@ def __init__(
self.linear2 = Linear(
dim_feedforward, d_model, weight_attrs[2], bias_attr=bias_attrs[2]
)
self.norm1 = LayerNorm(d_model)
self.norm2 = LayerNorm(d_model)
self.norm3 = LayerNorm(d_model)
self.norm1 = LayerNorm(d_model, layer_norm_eps)
self.norm2 = LayerNorm(d_model, layer_norm_eps)
self.norm3 = LayerNorm(d_model, layer_norm_eps)
self.dropout1 = Dropout(dropout, mode="upscale_in_train")
self.dropout2 = Dropout(dropout, mode="upscale_in_train")
self.dropout3 = Dropout(dropout, mode="upscale_in_train")
Expand Down