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Functions560 in github.com/VITA-Group/TransGAN

⨍ Functions 560◇ Types & classes 139

models_search/ViT_custom_rp.py:24

(self, act_layer)

models_search/ViT_custom_rp.py:42

(self, dim, num_heads=8, qkv_bias=False, qk_scale=None, attn_drop=0., proj_drop=0., window_size=16)

models_search/ViT_custom_rp.py:72

(self, norm_layer, dim)

models_search/ViT_custom_rp.py:122

(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., dr

models_search/ViT_custom_rp.py:145

(self, depth, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., drop_path=0.

models_search/ViT_custom_rp.py:164

(self, args, img_size=224, patch_size=16, in_chans=3, num_classes=10, embed_dim=384, depth=5,

models_search/ViT_custom_rp.py:199

(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., dr

models_search/ViT_custom_rp.py:324

(self, args, img_size=32, patch_size=None, in_chans=3, num_classes=1, embed_dim=None, depth=7,

models_search/ViT_custom_rp.py:346

(self, drop_prob=None)

models_search/ViT_helper.py:25

models_search/Celeba256_dis.py:37

models_search/Celeba256_dis.py:50

(self, act_layer)

models_search/Celeba256_dis.py:68

(self, dim, num_heads=8, qkv_bias=False, qk_scale=None, attn_drop=0., proj_drop=0., is_mask=0)

models_search/Celeba256_dis.py:98

(self, norm_layer, dim)

models_search/Celeba256_dis.py:162

(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., dr

models_search/Celeba256_dis.py:217

(self, depth, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., drop_path=0.

models_search/Celeba256_dis.py:236

(self, args, img_size=224, patch_size=16, in_chans=3, num_classes=10, embed_dim=384, depth=5,

models_search/Celeba256_dis.py:270

(self, block_size=2)

models_search/Celeba256_dis.py:391

(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., dr

models_search/Celeba256_dis.py:406

(self, args, img_size=32, patch_size=None, in_chans=3, num_classes=1, embed_dim=None, depth=7,

models_search/Celeba256_dis.py:426

models_search/ViT_scale3_local_new_rp.py:35

models_search/ViT_scale3_local_new_rp.py:48

(self, act_layer)

models_search/ViT_scale3_local_new_rp.py:66

(self, dim, num_heads=8, qkv_bias=False, qk_scale=None, attn_drop=0., proj_drop=0., window_size=16)

models_search/ViT_scale3_local_new_rp.py:96

(self, norm_layer, dim)

models_search/ViT_scale3_local_new_rp.py:146

(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., dr

models_search/ViT_scale3_local_new_rp.py:201

(self, depth, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., drop_path=0.

models_search/ViT_scale3_local_new_rp.py:220

(self, args, img_size=224, patch_size=16, in_chans=3, num_classes=10, embed_dim=384, depth=5,

models_search/ViT_scale3_local_new_rp.py:254

(self, block_size=2)

models_search/ViT_scale3_local_new_rp.py:375

(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., dr

models_search/ViT_scale3_local_new_rp.py:390

(self, args, img_size=32, patch_size=None, in_chans=3, num_classes=1, embed_dim=None, depth=7,

models_search/ViT_scale3_local_new_rp.py:410

models_search/ViT_custom_scale2_rp_noise.py:35

models_search/ViT_custom_scale2_rp_noise.py:48

(self, act_layer)

models_search/ViT_custom_scale2_rp_noise.py:66

(self, dim, num_heads=8, qkv_bias=False, qk_scale=None, attn_drop=0., proj_drop=0., window_size=16)

models_search/ViT_custom_scale2_rp_noise.py:96

(self, norm_layer, dim)

models_search/ViT_custom_scale2_rp_noise.py:149

(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., dr

models_search/ViT_custom_scale2_rp_noise.py:204

(self, depth, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., drop_path=0.

models_search/ViT_custom_scale2_rp_noise.py:223

(self, args, img_size=224, patch_size=16, in_chans=3, num_classes=10, embed_dim=384, depth=5,

models_search/ViT_custom_scale2_rp_noise.py:258

(self, block_size=2)

models_search/ViT_custom_scale2_rp_noise.py:382

(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., dr

models_search/ViT_custom_scale2_rp_noise.py:397

(self, args, img_size=32, patch_size=None, in_chans=3, num_classes=1, embed_dim=None, depth=7,

models_search/ViT_custom_scale2_rp_noise.py:417

models_search/ViT_custom_local544444_256_rp_noise.py:11

models_search/ViT_custom_local544444_256_rp_noise.py:23

(self, act_layer)

models_search/ViT_custom_local544444_256_rp_noise.py:37

(self, dim, num_heads=8, qkv_bias=False, qk_scale=None, attn_drop=0., proj_drop=0., window_size=16)

models_search/ViT_custom_local544444_256_rp_noise.py:71

(self, norm_layer, dim)

models_search/ViT_custom_local544444_256_rp_noise.py:125

(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., dr

models_search/ViT_custom_local544444_256_rp_noise.py:147

(self, depth, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., drop_path=0.

models_search/ViT_custom_local544444_256_rp_noise.py:164

(self, args, img_size=224, patch_size=16, in_chans=3, num_classes=10, embed_dim=384, depth=5,

models_search/ViT_custom_local544444_256_rp_noise.py:237

(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., dr

models_search/ViT_custom_local544444_256_rp_noise.py:458

(self, args, img_size=32, patch_size=None, in_chans=3, num_classes=1, embed_dim=None, depth=7,

models_search/ViT_custom_local544444_256_rp_noise.py:478

models_search/ViT_custom_local544444_256_rp.py:11

models_search/ViT_custom_local544444_256_rp.py:23

(self, act_layer)

models_search/ViT_custom_local544444_256_rp.py:37

(self, dim, num_heads=8, qkv_bias=False, qk_scale=None, attn_drop=0., proj_drop=0., window_size=16)

models_search/ViT_custom_local544444_256_rp.py:67

(self, norm_layer, dim)

models_search/ViT_custom_local544444_256_rp.py:118

(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., dr

models_search/ViT_custom_local544444_256_rp.py:140

(self, depth, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., drop_path=0.

models_search/ViT_custom_local544444_256_rp.py:157

(self, args, img_size=224, patch_size=16, in_chans=3, num_classes=10, embed_dim=384, depth=5,

models_search/ViT_custom_local544444_256_rp.py:230

(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., dr

models_search/ViT_custom_local544444_256_rp.py:451

(self, args, img_size=32, patch_size=None, in_chans=3, num_classes=1, embed_dim=None, depth=7,

models_search/ViT_custom_local544444_256_rp.py:471

models_search/Celeba256_gen.py:11

models_search/Celeba256_gen.py:23

(self, act_layer)

models_search/Celeba256_gen.py:40

(self, que_dim, key_dim, num_heads=4, qkv_bias=False, qk_scale=None, attn_drop=0., proj_drop=0.)

models_search/Celeba256_gen.py:72

(self, dim, num_heads=8, qkv_bias=False, qk_scale=None, attn_drop=0., proj_drop=0., window_size=16)

models_search/Celeba256_gen.py:116

(self, norm_layer, dim)

models_search/Celeba256_gen.py:170

(self, dim, embedding_dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0.,

models_search/Celeba256_gen.py:192

(self, depth, dim, embedding_dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0

models_search/Celeba256_gen.py:221

(self, args, img_size=224, patch_size=16, in_chans=3, num_classes=10, embed_dim=384, depth=5,

models_search/Celeba256_gen.py:308

(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., dr

models_search/Celeba256_gen.py:535

(self, args, img_size=32, patch_size=None, in_chans=3, num_classes=1, embed_dim=None, depth=7,

models_search/Celeba256_gen.py:555

models_search/ViT_custom.py:11

models_search/ViT_custom.py:24

(self, act_layer)

models_search/ViT_custom.py:42

(self, dim, num_heads=8, qkv_bias=False, qk_scale=None, attn_drop=0., proj_drop=0.)

models_search/ViT_custom.py:72

(self, norm_layer, dim)

models_search/ViT_custom.py:102

(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., dr

models_search/ViT_custom.py:125

(self, depth, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., drop_path=0.

models_search/ViT_custom.py:144

(self, args, img_size=224, patch_size=16, in_chans=3, num_classes=10, embed_dim=384, depth=5,

models_search/ViT_custom.py:178

(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., dr

models_search/ViT_custom.py:300

(self, args, img_size=32, patch_size=None, in_chans=3, num_classes=1, embed_dim=None, depth=7,

models_search/ViT_custom.py:322

(self, dataset, rank=0, num_replicas=1, shuffle=True, seed=0, window_size=0.5)

torch_utils/misc.py:110

(self, *args, **kwargs)

torch_utils/persistence.py:103

(self, regex='.*', keep_previous=True)

torch_utils/training_stats.py:133

(self, file_name: str = None, file_mode: str = "w", should_flush: bool = True)

dnnlib/util.py:59

torch_utils/misc.py:123

compute the length of the dataset :return: len => length of dataset

compute the length of the dataset :return: len => length of dataset

Method__setattr__

(self, name: str, value: Any)

dnnlib/util.py:49

Method__setstate__

utils/utils.py:247

Function_downsample

models_search/ViT_custom_scale2.py:370

Function_downsample

models_search/ViT_custom_rp.py:318

Function_downsample

models_search/Celeba256_dis.py:386

Function_downsample

models_search/ViT_scale3_local_new_rp.py:370

Function_downsample

models_search/ViT_custom_scale2_rp_noise.py:377

Function_downsample

models_search/ViT_custom_local544444_256_rp_noise.py:453

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