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dilbert -> distilbert

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thomwolf
2019-08-28 13:59:42 +02:00
parent c9bce1811c
commit 912a377e90
15 changed files with 144 additions and 144 deletions
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2
examples/distillation/scripts/binarized_data.py
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@@ -13,7 +13,7 @@
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Preprocessing script before training DilBERT.
Preprocessing script before training DistilBERT.
"""
import argparse
import pickle

22
examples/distillation/scripts/extract_for_distil.py
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@@ -13,7 +13,7 @@
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Preprocessing script before training DilBERT.
Preprocessing script before training DistilBERT.
"""
from pytorch_transformers import BertForPreTraining
import torch
@@ -33,32 +33,32 @@ if __name__ == '__main__':
compressed_sd = {}
for w in ['word_embeddings', 'position_embeddings']:
compressed_sd[f'dilbert.embeddings.{w}.weight'] = \
compressed_sd[f'distilbert.embeddings.{w}.weight'] = \
state_dict[f'bert.embeddings.{w}.weight']
for w in ['weight', 'bias']:
compressed_sd[f'dilbert.embeddings.LayerNorm.{w}'] = \
compressed_sd[f'distilbert.embeddings.LayerNorm.{w}'] = \
state_dict[f'bert.embeddings.LayerNorm.{w}']
std_idx = 0
for teacher_idx in [0, 2, 4, 7, 9, 11]:
for w in ['weight', 'bias']:
compressed_sd[f'dilbert.transformer.layer.{std_idx}.attention.q_lin.{w}'] = \
compressed_sd[f'distilbert.transformer.layer.{std_idx}.attention.q_lin.{w}'] = \
state_dict[f'bert.encoder.layer.{teacher_idx}.attention.self.query.{w}']
compressed_sd[f'dilbert.transformer.layer.{std_idx}.attention.k_lin.{w}'] = \
compressed_sd[f'distilbert.transformer.layer.{std_idx}.attention.k_lin.{w}'] = \
state_dict[f'bert.encoder.layer.{teacher_idx}.attention.self.key.{w}']
compressed_sd[f'dilbert.transformer.layer.{std_idx}.attention.v_lin.{w}'] = \
compressed_sd[f'distilbert.transformer.layer.{std_idx}.attention.v_lin.{w}'] = \
state_dict[f'bert.encoder.layer.{teacher_idx}.attention.self.value.{w}']
compressed_sd[f'dilbert.transformer.layer.{std_idx}.attention.out_lin.{w}'] = \
compressed_sd[f'distilbert.transformer.layer.{std_idx}.attention.out_lin.{w}'] = \
state_dict[f'bert.encoder.layer.{teacher_idx}.attention.output.dense.{w}']
compressed_sd[f'dilbert.transformer.layer.{std_idx}.sa_layer_norm.{w}'] = \
compressed_sd[f'distilbert.transformer.layer.{std_idx}.sa_layer_norm.{w}'] = \
state_dict[f'bert.encoder.layer.{teacher_idx}.attention.output.LayerNorm.{w}']
compressed_sd[f'dilbert.transformer.layer.{std_idx}.ffn.lin1.{w}'] = \
compressed_sd[f'distilbert.transformer.layer.{std_idx}.ffn.lin1.{w}'] = \
state_dict[f'bert.encoder.layer.{teacher_idx}.intermediate.dense.{w}']
compressed_sd[f'dilbert.transformer.layer.{std_idx}.ffn.lin2.{w}'] = \
compressed_sd[f'distilbert.transformer.layer.{std_idx}.ffn.lin2.{w}'] = \
state_dict[f'bert.encoder.layer.{teacher_idx}.output.dense.{w}']
compressed_sd[f'dilbert.transformer.layer.{std_idx}.output_layer_norm.{w}'] = \
compressed_sd[f'distilbert.transformer.layer.{std_idx}.output_layer_norm.{w}'] = \
state_dict[f'bert.encoder.layer.{teacher_idx}.output.LayerNorm.{w}']
std_idx += 1

2
examples/distillation/scripts/token_counts.py
View File

@@ -13,7 +13,7 @@
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Preprocessing script before training DilBERT.
Preprocessing script before training DistilBERT.
"""
from collections import Counter
import argparse