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Dec 5, 2019
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Update Dynamic Quant for BERT tutorial #748

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65 changes: 15 additions & 50 deletions intermediate_source/dynamic_quantization_bert_tutorial.py
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Original file line number Diff line number Diff line change
Expand Up @@ -86,8 +86,9 @@
#
# .. code:: shell
#
# !pip install sklearn
# !pip install transformers
# pip install sklearn
# pip install transformers
#


######################################################################
Expand All @@ -98,8 +99,10 @@
# Mac:
#
# .. code:: shell
# !yes y | pip uninstall torch tochvision
# !yes y | pip install --pre torch -f https://download.pytorch.org/whl/nightly/cu101/torch_nightly.html
#
# yes y | pip uninstall torch tochvision
# yes y | pip install --pre torch -f https://download.pytorch.org/whl/nightly/cu101/torch_nightly.html
#


######################################################################
Expand Down Expand Up @@ -155,13 +158,13 @@
# https://github.com/nyu-mll/GLUE-baselines/blob/master/download_glue_data.py)
# and unpack it to some directory “glue_data/MRPC”.
#

# !python download_glue_data.py --data_dir='glue_data' --tasks='MRPC' --test_labels=True
!pwd
!ls
!wget https://gist.githubusercontent.com/W4ngatang/60c2bdb54d156a41194446737ce03e2e/raw/17b8dd0d724281ed7c3b2aeeda662b92809aadd5/download_glue_data.py
!python download_glue_data.py --data_dir='glue_data' --tasks='MRPC'
!ls glue_data/MRPC
#
# .. code:: shell
#
# wget https://gist.githubusercontent.com/W4ngatang/60c2bdb54d156a41194446737ce03e2e/raw/17b8dd0d724281ed7c3b2aeeda662b92809aadd5/download_glue_data.py
# python download_glue_data.py --data_dir='glue_data' --tasks='MRPC'
# ls glue_data/MRPC
#


######################################################################
Expand Down Expand Up @@ -255,9 +258,6 @@
from google.colab import drive
drive.mount('/content/drive')

!ls
!pwd


######################################################################
# Set global configurations
Expand All @@ -273,13 +273,9 @@
configs = Namespace()

# The output directory for the fine-tuned model.
# configs.output_dir = "/mnt/homedir/jianyuhuang/public/bert/MRPC/"
configs.output_dir = "/content/drive/My Drive/BERT_Quant_Tutorial/MRPC/"
# configs.output_dir = "./MRPC/"

# The data directory for the MRPC task in the GLUE benchmark.
# configs.data_dir = "/mnt/homedir/jianyuhuang/public/bert/glue_data/MRPC"
# configs.data_dir = "./glue_data/MRPC"
configs.data_dir = "/content/glue_data/MRPC"

# The model name or path for the pre-trained model.
Expand Down Expand Up @@ -493,30 +489,6 @@ def load_and_cache_examples(args, task, tokenizer, evaluate=False):
print(quantized_model)



######################################################################
# In PyTorch 1.4 release, we further add the per-channel quantization
# support for dynamic quantization.
#
# .. figure:: https://drive.google.com/open?id=1N6P70MR6jJ2tcFnFJ2lROLSFqmiOY--g
# :alt: Per Tensor Quantization for Weight
#
# Per Tensor Quantization for Weight
#
# .. figure:: https://drive.google.com/open?id=1nyjUKP5qtkRCJPKtUaXXwhglLMQQ0Dfs
# :alt: Per Channel Quantization for Weight
#
# Per Channel Quantization for Weight
#

qconfig_dict = {
torch.nn.Linear: torch.quantization.per_channel_dynamic_qconfig
}
per_channel_quantized_model = torch.quantization.quantize_dynamic(
model, qconfig_dict, dtype=torch.qint8
)


######################################################################
# Check the model size
# --------------------
Expand All @@ -532,9 +504,6 @@ def print_size_of_model(model):

print_size_of_model(model)
print_size_of_model(quantized_model)
# print_size_of_model(per_channel_quantized_model)




######################################################################
Expand Down Expand Up @@ -606,10 +575,6 @@ def time_model_evaluation(model, configs, tokenizer):
# processing the evaluation of MRPC dataset.
#

# Evaluate the INT8 BERT model after the per-channel dynamic quantization
time_model_evaluation(per_channel_quantized_model, configs, tokenizer)



######################################################################
# Serialize the quantized model
Expand All @@ -621,7 +586,7 @@ def time_model_evaluation(model, configs, tokenizer):
quantized_output_dir = configs.output_dir + "quantized/"
if not os.path.exists(quantized_output_dir):
os.makedirs(quantized_output_dir)
quantized_model.save_pretrained(quantized_output_dir)
quantized_model.save_pretrained(quantized_output_dir)


######################################################################
Expand Down