TensorFlow:可以使用 tf.convert_to_tensor 函数将任意形状和类型的数据转换为张量。 PyTorch:可以使用 torch.tensor 或torch.as_tensor 函数进行转换。 4. 实施类型转换 以下是根据TensorFlow和PyTorch分别提供的代码示例: TensorFlow python import tensorflow as tf # 假设 data 是一个包含 float32 类型元素的列表或...
torch.Tensor as inputs.# need trt_network to enter tensorrt mode, otherwise pytorch modewithtorch2trt.trt_network(trt_net):# must use this to enter trt modeimg=trt_net.add_input(name="image",shape=[3,299,299],dtype=trt.float32)trt_mode_out=graph_pth(img,verbose=True)# call graph_...
"vae": "torch.float32", "unet": "torch.float16" }, } What browsers do you use to access the UI ? Google Chrome Console logs Loading weights [0b9e46a0b0] from /Users/alyears/stable-diffusion-webui/models/Stable-diffusion/人物/墨幽人造人_v1040.safetensors Traceback (most recent call...
你得设定FLOAT import torchimport numpy as np arr1 = np.array([1,2,3], dtype=np.float32) ...
MPS Tensor to float64 dtype as the MPS framework doesn't support float64. Please use float32 ...
_lora_B: Tensor # (col_size, n_rank) _rank: int def __init__(self, A: Tensor, B: Tensor): assert len(A.shape) == len(B.shape) assert A.shape[-2] == B.shape[-1] if A.dtype != B.dtype: A = A.to(torch.float32) ...
# Convert weight to float32 for calculations weight = weight.to(torch.float32) # Expand scale to match the weight tensor's shape scale_expanded = scale.repeat_interleave(block_size, dim=0).repeat_interleave(block_size, dim=1) # Trim scale_expanded to match weight's shape if necessa...
<Output: names[detection_classes:0, add:0] shape[?,100] type: f32>, <Output: names[detection_scores:0, Postprocessor/BatchMultiClassNonMaxSuppression/map/TensorArrayStack_1/TensorArrayGatherV3:0] shape[?,100] type: f32>, <Output: names[num_detections:0, Post...
importtorch.onnx#Function to Convert to ONNXdefConvert_ONNX():# set the model to inference modemodel.eval()# Let's create a dummy input tensordummy_input = torch.randn(1, input_size, requires_grad=True)# Export the modeltorch.onnx.export(model,# model being rundummy_input,# model in...
data_loader=DataLoader(dataset)forx,yindata_loader:print(x.dtype,y.dtype)# returns torch.float32 torch.uint8 Isn'tToTensorV2supposed to change the formats? By inspecting the source code (see the two links below), I noticed that the functionsimg_to_tensorandmask_to_tensorare not being calle...