如果torch.cuda.is_available()返回False,那么很可能是PyTorch没有安装CUDA支持。 2. 如果不支持,重新安装支持CUDA的PyTorch版本 如果确认PyTorch版本不支持CUDA,您需要根据您的CUDA版本重新安装PyTorch。可以通过PyTorch的官方网站找到适合您CUDA版本的安装命令。例如,如果您的CUDA版本是12.1,可以使用以下命令安装(请根据实...
张量（tensor）理论是数学的一个分支学科，在力学中有重要应用。张量这一术语起源于力学，它最初是用来...
Test name: test_cat_slice_cat_cuda_dynamic_shapes_cuda_wrapper (__main__.DynamicShapesCudaWrapperCudaTests) Platforms for which to skip the test: linux Disabled by desertfire Within ~15 minutes, test_cat_slice_cat_cuda_dynamic_shapes_cuda_wrapper (__main__.DynamicShapesCudaWrapperCudaTests) ...
attn_ckpt=catvton_path, attn_ckpt_version="mix", weight_dtype=mixed_precision, use_tf32=True, device='cuda' ) if mask.dim() == 2: mask = torch.unsqueeze(mask, 0) mask = mask[0] if mask_grow: mask = expand_mask(mask, mask_grow, 0) mask_image = mask.reshape((-1, 1, mas...
amp.autocast("cuda", dtype=torch.bfloat16): if not enable_vae_tiling: samples = vae(samples) else: batch_size, num_channels, num_frames, height, width = samples.shape overlap_height = int(self.tile_latent_min_height * (1 - self.tile_overlap_factor_height)) overlap_width = int(...
Nvidia driver version: No CUDA cuDNN version: No CUDA HIP runtime version: N/A MIOpen runtime version: N/A Is XNNPACK available: True CPU: Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Byte Order: Little Endian Address sizes: 52 bits physical, 57 bits virtual ...
@th.autocast("cuda") @th.autocast("cuda", enabled=False) @th.no_grad() def update(self, stream: ResidualStream): """Update the online stats in-place with a new stream.""" @@ -47,13 +47,13 @@ def update(self, stream: ResidualStream): self._mean_norm = stream.map(lambda x...
self.top_scores = torch.cuda.FloatTensor(self.num_classes,1).zero_()#self._aboxes = [[[] for _ in xrange(self.num_frames)] for _ in xrange(self.num_classes)]self._aboxes = np.ndarray(shape=(self.num_classes, self.num_frames), dtype=np.object)#self._box_inds = [[[] for ...
-1|=== 0 NONE 0 NOTE 0 WARNING 0 ERROR === webui-docker-auto-1|webui-docker-auto-1|ERROR:root:Exporting to ONNX failed. Expected all tensors to be on the same device, but found at least two devices, cpu and cuda:0!(when checking argumentforargu ment mat1inmethod wrapper_CUDA...
x = x.cuda() t1 = time.time() output = net(x) boxes, scores = detector.forward(output) t2 = time.time() max_conf, max_id = scores[0].topk(1,1,True,True) pos = max_id >0iflen(pos) ==0:returnnp.empty((0,6))