From 5768afc776a66bb94e77a9c1daebeea58fa731d5 Mon Sep 17 00:00:00 2001 From: Aarni Koskela Date: Sun, 31 Dec 2023 00:20:30 +0200 Subject: Add utility to inspect a model's parameters (to get dtype/device) --- modules/xlmr.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) (limited to 'modules/xlmr.py') diff --git a/modules/xlmr.py b/modules/xlmr.py index a407a3ca..6e000a56 100644 --- a/modules/xlmr.py +++ b/modules/xlmr.py @@ -5,6 +5,9 @@ from transformers.models.xlm_roberta.configuration_xlm_roberta import XLMRoberta from transformers import XLMRobertaModel,XLMRobertaTokenizer from typing import Optional +from modules.torch_utils import get_param + + class BertSeriesConfig(BertConfig): def __init__(self, vocab_size=30522, hidden_size=768, num_hidden_layers=12, num_attention_heads=12, intermediate_size=3072, hidden_act="gelu", hidden_dropout_prob=0.1, attention_probs_dropout_prob=0.1, max_position_embeddings=512, type_vocab_size=2, initializer_range=0.02, layer_norm_eps=1e-12, pad_token_id=0, position_embedding_type="absolute", use_cache=True, classifier_dropout=None,project_dim=512, pooler_fn="average",learn_encoder=False,model_type='bert',**kwargs): @@ -62,7 +65,7 @@ class BertSeriesModelWithTransformation(BertPreTrainedModel): self.post_init() def encode(self,c): - device = next(self.parameters()).device + device = get_param(self).device text = self.tokenizer(c, truncation=True, max_length=77, -- cgit v1.2.3 From a70dfb64a86b9b6d869deffdb0ffebe980365473 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Sun, 31 Dec 2023 22:38:30 +0300 Subject: change import statements for #14478 --- modules/xlmr.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) (limited to 'modules/xlmr.py') diff --git a/modules/xlmr.py b/modules/xlmr.py index 6e000a56..319771b7 100644 --- a/modules/xlmr.py +++ b/modules/xlmr.py @@ -5,7 +5,7 @@ from transformers.models.xlm_roberta.configuration_xlm_roberta import XLMRoberta from transformers import XLMRobertaModel,XLMRobertaTokenizer from typing import Optional -from modules.torch_utils import get_param +from modules import torch_utils class BertSeriesConfig(BertConfig): @@ -65,7 +65,7 @@ class BertSeriesModelWithTransformation(BertPreTrainedModel): self.post_init() def encode(self,c): - device = get_param(self).device + device = torch_utils.get_param(self).device text = self.tokenizer(c, truncation=True, max_length=77, -- cgit v1.2.3