torch.nn.functional.grid_sample(input, grid, mode=‘bilinear’, padding_mode=‘zeros’, align_corners=None) 为了简单起见,以下讨论都是基于如下参数进行实验及讲解的: torch.nn.functional.grid_sample(input, grid, mode=‘bilinear’, padding_mode=‘border’, align_corners=True) 给定维度为(N,C,Hin...
padding=0, output_padding=0, groups=1, bias=True, dilation=1, padding_mode='zeros) nn之创建池化层 # 1、最大池化 nn.MaxPool2d(kernel_size, stride=None, padding=0, dilation=1, return_indices=False, ceil_mode=False) 2、平均池化 nn.AvgPool2d(kernel_size, stride=None, padding=0, ceil...
class torchvision.transforms.Pad(padding, fill=0, padding_mode=‘constant’) 功能:对图像进行填充 参数: padding-(sequence or int, optional),此参数是设置填充多少个pixel。 当为int时,图像上下左右均填充int个,例如padding=4,则上下左右均填充4个pixel,若为3232,则会变成4040。 当为sequence时,若有2个数...
🐛 Describe the bug torch.nn.Conv2d can accept 3-dim tensor without batch, but when I set padding_mode="circular", Conv2d seemed to get some error at the underlying level. When it's set to other modes, Conv2d will run normally and success...
padding:填充个数 dilation:池化间隔大小 ceil_mode:尺寸向上取整,默认为False return_indices:记录池化像素索引 注意:stride一般设置的与窗口大小一致,以避免重叠 具体代码如下: 数据预处理: set_seed(1) # 设置随机种子# === load img ===path_img = os.path.join(os.path.dirname(os.path.abspath(__file...
torch.nn.Conv2d( in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, groups=1, bias=True, padding_mode="zeros", device=None, dtype=None, ) torch.nn.Conv2d 是PyTorch 中用于二维卷积操作的类。以下是该类构造函数的参数解释: in_channels: 输入的通道数。例如,对于RGB图像...
torchvision.transforms.functional.pad(img, padding, fill=0, padding_mode='constant') torchvision.transforms.functional.perspective(img, startpoints, endpoints, interpolation=3) torchvision.transforms.functional.resize(img, size, interpolation=2)
def aten〇grid_sampler〡dtype(input_rank_dtype: Tuple[int, int], grid_rank_dtype: Tuple[int, int], interpolation_mode: int, padding_mode: int, align_corners: bool) -> int: input_rank, input_dtype = input_rank_dtype grid_rank, grid_dtype = input_rank_dtype return input_dtype @check...
self.config = config# Construct model layers.self.lm_head = nn.Linear(config.embedding_dim, config.vocab_size, bias=config.lm_head_use_bias)self.tok_embedding = nn.Embedding(config.vocab_size, config.embedding_dim, padding_idx=0)self.transformer_blocks = nn.ModuleList(TransformerBlock(config)...
(maxpool):MaxPool2d(kernel_size=3,stride=2,padding=1,dilation=1,ceil_mode=False) 也就是kernel为3 stride 2 padding 1 dilation =1 ceil_mode = False 从下图中可以看出他的输入 resnet50网络 输入的图片为 1920*1080 大小 经过第一层卷积为 ...