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Fix torchscript for vit-hybrid dynamic_resize
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@ -38,7 +38,7 @@ from torch.jit import Final
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from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD, IMAGENET_INCEPTION_MEAN, IMAGENET_INCEPTION_STD, \
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from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD, IMAGENET_INCEPTION_MEAN, IMAGENET_INCEPTION_STD, \
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OPENAI_CLIP_MEAN, OPENAI_CLIP_STD
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OPENAI_CLIP_MEAN, OPENAI_CLIP_STD
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from timm.layers import PatchEmbed, Mlp, DropPath, trunc_normal_, lecun_normal_, resample_patch_embed, \
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from timm.layers import PatchEmbed, Mlp, DropPath, trunc_normal_, lecun_normal_, resample_patch_embed, \
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resample_abs_pos_embed, resample_abs_pos_embed_nhwc, RmsNorm, PatchDropout, use_fused_attn, SwiGLUPacked
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resample_abs_pos_embed, RmsNorm, PatchDropout, use_fused_attn, SwiGLUPacked
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from ._builder import build_model_with_cfg
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from ._builder import build_model_with_cfg
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from ._manipulate import named_apply, checkpoint_seq, adapt_input_conv
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from ._manipulate import named_apply, checkpoint_seq, adapt_input_conv
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from ._registry import generate_default_cfgs, register_model, register_model_deprecations
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from ._registry import generate_default_cfgs, register_model, register_model_deprecations
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@ -31,6 +31,8 @@ class HybridEmbed(nn.Module):
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""" CNN Feature Map Embedding
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""" CNN Feature Map Embedding
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Extract feature map from CNN, flatten, project to embedding dim.
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Extract feature map from CNN, flatten, project to embedding dim.
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"""
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"""
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output_fmt: Format
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def __init__(
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def __init__(
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self,
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self,
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backbone,
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backbone,
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