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remove requirements to avoid a low version of timm

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yuze.zyz
2025-02-12 14:55:12 +08:00
parent 6d1598fcfc
commit 4f555551a1
2 changed files with 10 additions and 3 deletions
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10
modelscope/models/cv/robust_image_classification/easyrobust_model.py
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@@ -4,11 +4,14 @@ import os
import torch import torch
import torch.nn as nn import torch.nn as nn
from modelscope import get_logger
from modelscope.metainfo import Models from modelscope.metainfo import Models
from modelscope.models.base.base_torch_model import TorchModel from modelscope.models.base.base_torch_model import TorchModel
from modelscope.models.builder import MODELS from modelscope.models.builder import MODELS
from modelscope.utils.constant import ModelFile, Tasks from modelscope.utils.constant import ModelFile, Tasks
logger = get_logger()
def normalize_fn(tensor, mean, std): def normalize_fn(tensor, mean, std):
"""Differentiable version of torchvision.functional.normalize""" """Differentiable version of torchvision.functional.normalize"""
@@ -41,10 +44,15 @@ class NormalizeByChannelMeanStd(nn.Module):
class EasyRobustModel(TorchModel): class EasyRobustModel(TorchModel):
def __init__(self, model_dir: str, **kwargs): def __init__(self, model_dir: str, **kwargs):
try:
import easyrobust.models import easyrobust.models
except ImportError as e:
logger.error(
'You are using `EasyRobustModel`, but this model requires `easyrobust`,'
'please install it with command `pip install easyrobust`')
raise e
from timm.models import create_model from timm.models import create_model
from mmcls.datasets import ImageNet from mmcls.datasets import ImageNet
import modelscope.models.cv.image_classification.backbones
from modelscope.utils.hub import read_config from modelscope.utils.hub import read_config
super().__init__(model_dir) super().__init__(model_dir)

1
requirements/cv.txt
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@@ -8,7 +8,6 @@ control_ldm
ddpm_guided_diffusion ddpm_guided_diffusion
diffusers diffusers
easydict easydict
easyrobust
edit_distance edit_distance
face_alignment>=1.3.5 face_alignment>=1.3.5
fairscale>=0.4.1 fairscale>=0.4.1