remove requirements to avoid a low version of timm

modelscope/models/cv/robust_image_classification/easyrobust_model.py

@@ -4,11 +4,14 @@ import os
 import torch
 import torch.nn as nn
 
+from modelscope import get_logger
 from modelscope.metainfo import Models
 from modelscope.models.base.base_torch_model import TorchModel
 from modelscope.models.builder import MODELS
 from modelscope.utils.constant import ModelFile, Tasks
 
+logger = get_logger()
+
 
 def normalize_fn(tensor, mean, std):
     """Differentiable version of torchvision.functional.normalize"""
@@ -41,10 +44,15 @@ class NormalizeByChannelMeanStd(nn.Module):
 class EasyRobustModel(TorchModel):
 
     def __init__(self, model_dir: str, **kwargs):
+        try:
             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 mmcls.datasets import ImageNet
-        import modelscope.models.cv.image_classification.backbones
         from modelscope.utils.hub import read_config
 
         super().__init__(model_dir)

requirements/cv.txt

@@ -8,7 +8,6 @@ control_ldm
 ddpm_guided_diffusion
 diffusers
 easydict
-easyrobust
 edit_distance
 face_alignment>=1.3.5
 fairscale>=0.4.1