Delete unused positional embedding functions

lightly/models/modules/ijepa.py

@@ -431,66 +431,3 @@ def images_to_tokens(
  if prepend_class_token:
  tokens = utils.prepend_class_token(tokens, self.class_token)
  return tokens
-
-
-def _get_2d_sincos_pos_embed(embed_dim, grid_size, cls_token=False):
- """
- grid_size: int of the grid height and width
- return:
- pos_embed: [grid_size*grid_size, embed_dim] or [1+grid_size*grid_size, embed_dim] (w/ or w/o cls_token)
- """
- grid_h = np.arange(grid_size, dtype=float)
- grid_w = np.arange(grid_size, dtype=float)
- grid = np.meshgrid(grid_w, grid_h) # here w goes first
- grid = np.stack(grid, axis=0)
-
- grid = grid.reshape([2, 1, grid_size, grid_size])
- pos_embed = _get_2d_sincos_pos_embed_from_grid(embed_dim, grid)
- if cls_token:
- pos_embed = np.concatenate([np.zeros([1, embed_dim]), pos_embed], axis=0)
- return pos_embed
-
-
-def _get_2d_sincos_pos_embed_from_grid(embed_dim, grid):
- assert embed_dim % 2 == 0
-
- # use half of dimensions to encode grid_h
- emb_h = _get_1d_sincos_pos_embed_from_grid(embed_dim // 2, grid[0]) # (H*W, D/2)
- emb_w = _get_1d_sincos_pos_embed_from_grid(embed_dim // 2, grid[1]) # (H*W, D/2)
-
- emb = np.concatenate([emb_h, emb_w], axis=1) # (H*W, D)
- return emb
-
-
-def _get_1d_sincos_pos_embed(embed_dim, grid_size, cls_token=False):
- """
- grid_size: int of the grid length
- return:
- pos_embed: [grid_size, embed_dim] or [1+grid_size, embed_dim] (w/ or w/o cls_token)
- """
- grid = np.arange(grid_size, dtype=float)
- pos_embed = _get_1d_sincos_pos_embed_from_grid(embed_dim, grid)
- if cls_token:
- pos_embed = np.concatenate([np.zeros([1, embed_dim]), pos_embed], axis=0)
- return pos_embed
-
-
-def _get_1d_sincos_pos_embed_from_grid(embed_dim, pos):
- """
- embed_dim: output dimension for each position
- pos: a list of positions to be encoded: size (M,)
- out: (M, D)
- """
- assert embed_dim % 2 == 0
- omega = np.arange(embed_dim // 2, dtype=float)
- omega /= embed_dim / 2.0
- omega = 1.0 / 10000**omega # (D/2,)
-
- pos = pos.reshape(-1) # (M,)
- out = np.einsum("m,d->md", pos, omega) # (M, D/2), outer product
-
- emb_sin = np.sin(out) # (M, D/2)
- emb_cos = np.cos(out) # (M, D/2)
-
- emb = np.concatenate([emb_sin, emb_cos], axis=1) # (M, D)
- return emb