# PyTorch训练项目转换支持API列表 > 目前PyTorch训练项目转换支持6个优化器相关API，70+的NN类API，10+Utils类API，2个Autograd类API，40+的基础操作API以及30+Torchvision API，我们在如下列表中给出了目前的全部API。 ## 优化器相关API | 序号 | API | 序号 | API | | ---- | ------------------------------------------ | ---- | ------------------------------------------ | | 1 | torch.optim | 2 | torch.optim.lr_scheduler.ReduceLROnPlateau | | 3 | torch.optim.lr_scheduler.CosineAnnealingLR | 4 | torch.optim.lr_scheduler.MultiStepLR | | 5 | torch.optim.Adam | 6 | torch.optim.SGD | ## NN类API | 序号 | API | 序号 | API | | ---- | ---------------------------------------------------- | ---- | --------------------------------- | | 1 | torch.nn | 2 | torch.nn.Module | | 3 | torch.nn.ModuleList | 4 | torch.nn.Sequential | | 5 | torch.nn.utils | 6 | torch.nn.utils.clip_grad_value_ | | 7 | torch.nn.Parameter | 8 | torch.nn.DataParallel | | 9 | torch.nn.functional | 10 | torch.nn.BatchNorm1d | | 11 | torch.nn.BatchNorm2d | 12 | torch.nn.BatchNorm3d | | 13 | torch.nn.Conv1d | 14 | torch.nn.Conv2d | | 15 | torch.nn.Conv3d | 16 | torch.nn.ConvTranspose2d | | 17 | torch.nn.Dropout | 18 | torch.nn.Embedding | | 19 | torch.nn.InstanceNorm2d | 20 | torch.nn.LeakyReLU | | 21 | torch.nn.Linear | 22 | torch.nn.MaxPool1d | | 23 | torch.nn.MaxPool2d | 24 | torch.nn.MaxPool3d | | 25 | torch.nn.ReLU | 26 | torch.nn.Sigmoid | | 27 | torch.nn.Softmax | 28 | torch.nn.Tanh | | 29 | torch.nn.Upsample | 30 | torch.nn.CrossEntropyLoss | | 31 | torch.nn.BCEWithLogitsLoss | 32 | torch.nn.BCELoss | | 33 | torch.nn.functional.avg_pool1d | 34 | torch.nn.functional.avg_pool2d | | 35 | torch.nn.functional.avg_pool3d | 36 | torch.nn.functional.dropout | | 37 | torch.nn.functional.log_softmax | 38 | torch.nn.functional.pad | | 39 | torch.sigmoid | 40 | torch.nn.functional.sigmoid | | 41 | torch.nn.functional.softmax | 42 | torch.nn.init.xavier_uniform_ | | 43 | torch.nn.functional.binary_cross_entropy_with_logits | 44 | torch.nn.functional.cross_entropy | | 45 | torch.nn.functional.dropout | 46 | torch.nn.functional.relu | | 47 | torch.nn.functional.smooth_l1_loss | 48 | torch.nn.AdaptiveAvgPool1d | | 49 | torch.nn.AdaptiveAvgPool2d | 50 | torch.nn.AdaptiveAvgPool3d | | 51 | torch.nn.AvgPool1d | 52 | torch.nn.AvgPool2d | | 53 | torch.nn.AvgPool3d | 54 | torch.nn.ConstantPad2d | | 55 | torch.nn.Dropout2d | 56 | torch.nn.GELU | | 57 | torch.nn.GroupNorm | 58 | torch.nn.Identity | | 59 | torch.nn.LayerNorm | 60 | torch.nn.MaxUnpool2d | | 61 | torch.nn.ReflectionPad2d | 62 | torch.nn.ReplicationPad2d | | 63 | torch.nn.PReLU | 64 | torch.nn.SyncBatchNorm | | 65 | torch.nn.ZeroPad2d | 66 | torch.nn.KLDivLoss | | 67 | torch.nn.L1Loss | 68 | paddle.nn.functional.interpolate | | 69 | torch.nn.functional.mse_loss | 70 | torch.nn.init.constant_ | | 71 | torch.nn.init.normal_ | 72 | torch.nn.init.ones_ | | 73 | torch.nn.init.zeros_ | 74 | torch.nn.init.orthogonal_ | ## Utils类API | 序号 | API | 序号 | API | | ---- | ------------------------------ | ---- | --------------------------- | | 1 | torch.utils.data | 2 | torch.utils.data.DataLoader | | 3 | torch.utils.data.random_split | 4 | torch.utils.data.Dataset | | 5 | torch.utils.data.ConcatDataset | 6 | torch.utils.data.distributed | | 7 | torch.utils.data.distributed.DistributedSampler | 8 | torch.utils.model_zoo | | 9 | torch.utils.model_zoo.load_url | 10 | torch.multiprocessing | | 11 | torch.multiprocessing.spawn | 12 | torch.distributed | | 13 | torch.distributed.init_process_group | 14 | | ## Autograd类API | 序号 | API | 序号 | API | | ---- | ----------------------- | ---- | ------------------- | | 1 | torch.autograd.Variable | 2 | torch.autograd.grad | ## 基础操作API | 序号 | API | 序号 | API | | ---- | ----------------------- | ---- | ----------------------- | | 1 | torch | 2 | torch.Tensor | | 3 | torch.FloatTensor | 4 | torch.load | | 5 | torch.save | 6 | torch.device | | 7 | torch.cat | 8 | torch.cuda.is_available | | 9 | torch.no_grad | 10 | torch.from_numpy | | 11 | torch.cuda.device_count | 12 | torch.manual_seed | | 13 | torch.unsqueeze | 14 | torch.squeeze | | 15 | torch.sum | 16 | torch.mean | | 17 | torch.full | 18 | torch.full_like | | 19 | torch.ones | 20 | torch.ones_like | | 21 | torch.zeros | 22 | torch.zeros_like | | 23 | torch.sqrt | 24 | torch.arange | | 25 | torch.matmul | 26 | torch.set_grad_enabled | | 27 | torch.tensor | 28 | torch.clamp | | 29 | torch.exp | 30 | torch.max | | 31 | torch.min | 32 | torch.argmax | | 33 | torch.argmin | 34 | torch.stack | | 35 | torch.log | 36 | torch.randperm | | 37 | torch.rand | 38 | torch.abs | | 39 | torch.bitwise_or | 40 | torch.bitwise_xor | | 41 | torch.bitwise_and | 42 | torch.bitwise_not | | 43 | torch.randn | 44 | torch.add | | 45 | torch.mul | 46 | torch.linspace | | 47 | torch.einsum| | | ## Torchvision API | 序号 | API | 序号 | API | | ---- | --------------------------------- | ---- | ------------------------------------------- | | 1 | torchvision.transforms | 2 | torchvision.transforms.Compose | | 3 | torchvision.transforms.ToPILImage | 4 | torchvision.transforms.Resize | | 5 | torchvision.transforms.ToTensor | 6 | torchvision.transforms.RandomHorizontalFlip | | 7 | torchvision.transforms.CenterCrop | 8 | torchvision.transforms.Normalize | | 9 | torchvision.utils.save_image | 10 | torchvision.datasets.ImageFolder | | 11 | torchvision.transforms.RandomResizedCrop | 12 | torchvision.transforms.Lambda | | 13 | torchvision.utils | 14 | torchvision.utils.save_image | | 15 | torchvision.datasets | 16 | torchvision.datasets.ImageFolder | | 17 | torchvision.models | 18 | torchvision.models.vgg_pth_urls | | 19 | torchvision.models.vgg11 | 20 | torchvision.models.vgg13 | | 21 | torchvision.models.vgg16 | 22 | torchvision.models.vgg19 | | 23 | torchvision.models.vgg11_bn | 24 | torchvision.models.vgg13_bn | | 25 | torchvision.models.vgg16_bn | 26 | torchvision.models.vgg19_bn | | 27 | torchvision.models.resnet34 | 28 | torchvision.models.resnet50 | | 29 | torchvision.models.resnet101 | 30 | torchvision.models.resnet152 | | 31 | torchvision.models.resnext50_32x4d | 32 | torchvision.models.resnext101_32x8d | | 33 | torchvision.models.wide_resnet50_2 | 34 | torchvision.models.wide_resnet101_2 | ***持续更新...***