| 297 | """ |
| 298 | |
| 299 | def __init__(self, patch_size=4, in_chans=3, embed_dim=96, norm_layer=None, use_conv_embed=False, is_stem=False): |
| 300 | super().__init__() |
| 301 | patch_size = to_2tuple(patch_size) |
| 302 | self.patch_size = patch_size |
| 303 | |
| 304 | self.in_chans = in_chans |
| 305 | self.embed_dim = embed_dim |
| 306 | |
| 307 | if use_conv_embed: |
| 308 | # if we choose to use conv embedding, then we treat the stem and non-stem differently |
| 309 | if is_stem: |
| 310 | kernel_size = 7; padding = 2; stride = 4 |
| 311 | else: |
| 312 | kernel_size = 3; padding = 1; stride = 2 |
| 313 | self.proj = nn.Conv2d(in_chans, embed_dim, kernel_size=kernel_size, stride=stride, padding=padding) |
| 314 | else: |
| 315 | self.proj = nn.Conv2d(in_chans, embed_dim, kernel_size=patch_size, stride=patch_size) |
| 316 | |
| 317 | if norm_layer is not None: |
| 318 | self.norm = norm_layer(embed_dim) |
| 319 | else: |
| 320 | self.norm = None |
| 321 | |
| 322 | def forward(self, x): |
| 323 | """Forward function.""" |