Skip to content
GitLab
Menu
Projects
Groups
Snippets
Loading...
Help
Help
Support
Community forum
Keyboard shortcuts
?
Submit feedback
Contribute to GitLab
Sign in / Register
Toggle navigation
Menu
Open sidebar
OpenDAS
ColossalAI
Commits
d70f43dd
Unverified
Commit
d70f43dd
authored
Mar 21, 2022
by
ver217
Committed by
GitHub
Mar 21, 2022
Browse files
embedding remove attn mask (#474)
parent
75443471
Changes
1
Hide whitespace changes
Inline
Side-by-side
Showing
1 changed file
with
4 additions
and
4 deletions
+4
-4
model_zoo/gpt/gpt.py
model_zoo/gpt/gpt.py
+4
-4
No files found.
model_zoo/gpt/gpt.py
View file @
d70f43dd
...
@@ -43,7 +43,7 @@ class GPTEmbedding(nn.Module):
...
@@ -43,7 +43,7 @@ class GPTEmbedding(nn.Module):
def
word_embedding_weight
(
self
):
def
word_embedding_weight
(
self
):
return
self
.
word_embeddings
.
weight
return
self
.
word_embeddings
.
weight
def
forward
(
self
,
input_ids
,
attention_mask
=
None
,
position_ids
=
None
,
tokentype_ids
=
None
):
def
forward
(
self
,
input_ids
,
position_ids
=
None
,
tokentype_ids
=
None
):
seq_length
=
input_ids
.
size
(
1
)
seq_length
=
input_ids
.
size
(
1
)
if
position_ids
is
None
:
if
position_ids
is
None
:
position_ids
=
torch
.
arange
(
seq_length
,
dtype
=
torch
.
long
,
device
=
get_current_device
()).
unsqueeze
(
0
)
position_ids
=
torch
.
arange
(
seq_length
,
dtype
=
torch
.
long
,
device
=
get_current_device
()).
unsqueeze
(
0
)
...
@@ -52,7 +52,7 @@ class GPTEmbedding(nn.Module):
...
@@ -52,7 +52,7 @@ class GPTEmbedding(nn.Module):
x
=
x
+
self
.
tokentype_embeddings
(
tokentype_ids
)
x
=
x
+
self
.
tokentype_embeddings
(
tokentype_ids
)
x
=
self
.
dropout
(
x
)
x
=
self
.
dropout
(
x
)
return
x
,
attention_mask
return
x
@
LAYERS
.
register_module
@
LAYERS
.
register_module
...
@@ -285,7 +285,7 @@ class GPT(nn.Module):
...
@@ -285,7 +285,7 @@ class GPT(nn.Module):
dtype
=
dtype
)
dtype
=
dtype
)
def
forward
(
self
,
input_ids
,
attention_mask
=
None
):
def
forward
(
self
,
input_ids
,
attention_mask
=
None
):
x
,
attention_mask
=
self
.
embed
(
input_ids
,
attention_mask
)
x
=
self
.
embed
(
input_ids
)
# We create a 3D attention mask from a 2D tensor mask.
# We create a 3D attention mask from a 2D tensor mask.
# Sizes are [batch_size, 1, 1, to_seq_length]
# Sizes are [batch_size, 1, 1, to_seq_length]
...
@@ -362,7 +362,7 @@ class PipelineGPT(nn.Module):
...
@@ -362,7 +362,7 @@ class PipelineGPT(nn.Module):
def
forward
(
self
,
x
=
None
,
input_ids
=
None
,
attention_mask
=
None
):
def
forward
(
self
,
x
=
None
,
input_ids
=
None
,
attention_mask
=
None
):
if
self
.
first
:
if
self
.
first
:
x
,
attention_mask
=
self
.
embed
(
input_ids
,
attention_mask
)
x
=
self
.
embed
(
input_ids
)
# We create a 3D attention mask from a 2D tensor mask.
# We create a 3D attention mask from a 2D tensor mask.
# Sizes are [batch_size, 1, 1, to_seq_length]
# Sizes are [batch_size, 1, 1, to_seq_length]
...
...
Write
Preview
Markdown
is supported
0%
Try again
or
attach a new file
.
Attach a file
Cancel
You are about to add
0
people
to the discussion. Proceed with caution.
Finish editing this message first!
Cancel
Please
register
or
sign in
to comment