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hf_co_models.py
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hf_co_models.py
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# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
# Maps model class name to a tuple of model class
MODEL_CLASSES = [
'AutoModel', 'AutoModelWithLMHead', 'AutoModelForSequenceClassification', 'AutoModelForQuestionAnswering'
]
# List of pretrained models: https://huggingface.co/transformers/pretrained_models.html
# Pretrained model name to a tuple of input names, opset_version, use_external_data_format, optimization model type
MODELS = {
# BERT
"bert-base-uncased": (["input_ids", "attention_mask", "token_type_ids"], 12, False, "bert"),
"bert-large-uncased": (["input_ids", "attention_mask", "token_type_ids"], 12, False, "bert"),
"bert-base-cased": (["input_ids", "attention_mask", "token_type_ids"], 12, False, "bert"),
"philschmid/MiniLM-L6-H384-uncased-sst2": (["input_ids", "attention_mask", "token_type_ids"], 12, False, "bert"),
# "bert-large-cased": (["input_ids", "attention_mask", "token_type_ids"], 12, False, "bert"),
# "bert-base-multilingual-uncased": (["input_ids", "attention_mask", "token_type_ids"], 12, False, "bert"),
# "bert-base-multilingual-cased": (["input_ids", "attention_mask", "token_type_ids"], 12, False, "bert"),
# "bert-base-chinese": (["input_ids", "attention_mask", "token_type_ids"], 12, False, "bert"),
# "bert-base-german-cased": (["input_ids", "attention_mask", "token_type_ids"], 12, False, "bert"),
# "bert-large-uncased-whole-word-masking": (["input_ids", "attention_mask", "token_type_ids"], 12, False, "bert"),
# "bert-large-cased-whole-word-masking": (["input_ids", "attention_mask", "token_type_ids"], 12, False, "bert"),
# "bert-large-uncased-whole-word-masking-finetuned-squad": (["input_ids", "attention_mask",
# "token_type_ids"], 12, False, "bert"),
# "bert-large-cased-whole-word-masking-finetuned-squad": (["input_ids", "attention_mask",
# "token_type_ids"], 12, False, "bert"),
# "bert-base-cased-finetuned-mrpc": (["input_ids", "attention_mask", "token_type_ids"], 12, False, "bert"),
# "bert-base-german-dbmdz-cased": (["input_ids", "attention_mask", "token_type_ids"], 12, False, "bert"),
# "bert-base-german-dbmdz-uncased": (["input_ids", "attention_mask", "token_type_ids"], 12, False, "bert"),
# todo: more models to add
# GPT (no past state)
"openai-gpt": (["input_ids"], 11, False, "gpt2"),
# GPT-2 (no past state, use benchmark_gpt2.py for past_key_values)
"gpt2": (["input_ids"], 11, False, "gpt2"),
"gpt2-medium": (["input_ids"], 11, False, "gpt2"),
"gpt2-large": (["input_ids"], 11, True, "gpt2"),
"gpt2-xl": (["input_ids"], 11, True, "gpt2"),
"distilgpt2": (["input_ids"], 11, False, "gpt2"),
# Transformer-XL (Models uses Einsum, which need opset version 12 or later.)
"transfo-xl-wt103": (["input_ids", "mems"], 12, False, "bert"),
# XLNet
"xlnet-base-cased": (["input_ids"], 12, False, "bert"),
"xlnet-large-cased": (["input_ids"], 12, False, "bert"),
# XLM
"xlm-mlm-en-2048": (["input_ids"], 11, True, "bert"),
"xlm-mlm-ende-1024": (["input_ids"], 11, False, "bert"),
"xlm-mlm-enfr-1024": (["input_ids"], 11, False, "bert"),
# RoBERTa
"roberta-base": (["input_ids", "attention_mask"], 12, False, "bert"),
"roberta-large": (["input_ids", "attention_mask"], 12, False, "bert"),
"roberta-large-mnli": (["input_ids", "attention_mask"], 12, False, "bert"),
"deepset/roberta-base-squad2": (["input_ids", "attention_mask"], 11, False, "bert"),
"distilroberta-base": (["input_ids", "attention_mask"], 12, False, "bert"),
# DistilBERT
"distilbert-base-uncased": (["input_ids", "attention_mask"], 11, False, "bert"),
"distilbert-base-uncased-distilled-squad": (["input_ids", "attention_mask"], 11, False, "bert"),
# CTRL
"ctrl": (["input_ids"], 11, True, "bert"),
# CamemBERT
"camembert-base": (["input_ids"], 11, False, "bert"),
# ALBERT
"albert-base-v1": (["input_ids"], 12, False, "bert"),
"albert-large-v1": (["input_ids"], 12, False, "bert"),
"albert-xlarge-v1": (["input_ids"], 12, True, "bert"),
#"albert-xxlarge-v1": (["input_ids"], 12, True, "bert"),
"albert-base-v2": (["input_ids"], 12, False, "bert"),
"albert-large-v2": (["input_ids"], 12, False, "bert"),
"albert-xlarge-v2": (["input_ids"], 12, True, "bert"),
#"albert-xxlarge-v2": (["input_ids"], 12, True, "bert"),
# T5 (use benchmark_t5.py instead)
# "t5-small": (["input_ids", "decoder_input_ids"], 12, False, "bert"),
# "t5-base": (["input_ids", "decoder_input_ids"], 12, False, "bert"),
# "t5-large": (["input_ids", "decoder_input_ids"], 12, True, "bert"),
# "t5-3b": (["input_ids", "decoder_input_ids"], 12, True, "bert"),
# "t5-11b": (["input_ids", "decoder_input_ids"], 12, True, "bert"),
#"valhalla/t5-small-qa-qg-hl": (["input_ids"], 12, True, "bert"),
# XLM-RoBERTa
"xlm-roberta-base": (["input_ids"], 11, False, "bert"),
"xlm-roberta-large": (["input_ids"], 11, True, "bert"),
# FlauBERT
"flaubert/flaubert_small_cased": (["input_ids"], 11, False, "bert"),
#"flaubert/flaubert_base_uncased": (["input_ids"], 11, False, "bert"),
"flaubert/flaubert_base_cased": (["input_ids"], 11, False, "bert"),
#"flaubert/flaubert_large_cased": (["input_ids"], 11, False, "bert"),
# Bart
"facebook/bart-large": (["input_ids", "attention_mask"], 11, False, "bart"),
"facebook/bart-base": (["input_ids", "attention_mask"], 11, False, "bart"),
"facebook/bart-large-mnli": (["input_ids", "attention_mask"], 11, False, "bart"),
"facebook/bart-large-cnn": (["input_ids", "attention_mask"], 11, False, "bart"),
# DialoGPT
"microsoft/DialoGPT-small": (["input_ids"], 11, False, "gpt2"),
"microsoft/DialoGPT-medium": (["input_ids"], 11, False, "gpt2"),
#"microsoft/DialoGPT-large": (["input_ids"], 11, True, "gpt2"),
# Reformer
#"google/reformer-enwik8": (["input_ids"], 11, False, "bert"),
#"google/reformer-crime-and-punishment": (["input_ids"], 11, False, "bert"),
# MarianMT
#"Helsinki-NLP/opus-mt-ROMANCE-en": (["input_ids"], 12, False, "bert"),
# Longformer (use benchmark_longformer.py instead)
#"allenai/longformer-base-4096": (["input_ids"], 12, False, "bert"),
#"allenai/longformer-large-4096": (["input_ids"], 12, False, "bert"),
# MBart
"facebook/mbart-large-cc25": (["input_ids"], 11, True, "bert"),
"facebook/mbart-large-en-ro": (["input_ids"], 11, True, "bert"),
# "Helsinki-NLP/opus-mt-ROMANCE-en": (["input_ids"], 12, False, "bert"),
# # Longformer
# "allenai/longformer-base-4096": (["input_ids"], 12, False, "bert"),
# "allenai/longformer-large-4096": (["input_ids"], 12, True, "bert"),
# "funnel-transformer/small": (["input_ids"], 12, False, "bert"),
# "funnel-transformer/small-base": (["input_ids"], 12, False, "bert"),
# "funnel-transformer/medium": (["input_ids"], 12, False, "bert"),
# "funnel-transformer/medium-base": (["input_ids"], 12, False, "bert"),
# "funnel-transformer/intermediate": (["input_ids"], 12, False, "bert"),
# "funnel-transformer/intermediate-base": (["input_ids"], 12, False, "bert"),
# "funnel-transformer/large": (["input_ids"], 12, True, "bert"),
# "funnel-transformer/large-base": (["input_ids"], 12, True, "bert"),
# "funnel-transformer/xlarge": (["input_ids"], 12, True, "bert"),
# "funnel-transformer/xlarge-base": (["input_ids"], 12, True, "bert"),
# Layoutlm
"microsoft/layoutlm-base-uncased": (["input_ids"], 11, False, "bert"),
"microsoft/layoutlm-large-uncased": (["input_ids"], 11, False, "bert"),
# Squeezebert
"squeezebert/squeezebert-uncased": (["input_ids"], 11, False, "bert"),
"squeezebert/squeezebert-mnli": (["input_ids"], 11, False, "bert"),
"squeezebert/squeezebert-mnli-headless": (["input_ids"], 11, False, "bert"),
"unc-nlp/lxmert-base-uncased": (["input_ids", "visual_feats", "visual_pos"], 11, False, "bert"),
# "google/pegasus-xsum": (["input_ids"], 11, False, "bert"),
# "google/pegasus-large": (["input_ids"], 11, False, "bert"),
}