grad_input3 = input.grad; input.grad = None assert torch.allclose(output1, output2) assert torch.allclose(output1, output3) assert torch.allclose(grad_input1, grad_input2) assert torch.allclose(grad_input1, grad_input3) 以下计算图显示了朴素实现的细节: 以下计算图显示了转换后实现的细节: 我...
torch.allclose() 比较两个元素是否接近,比较A和B是否接近的公式为 |A-B| <= atol+rtol*|B| torch.allclose(input, other, rtol=1e-05, atol=1e-08, equal_nan=False) torch.norm() 求模/求范数 模就是二范数 torch.norm(input, p='fro', dim=None, keepdim=False, out=None, dtype=None) ...
allclose(torch_output, numpy_output) 其中,单元测试函数的定义如下: @pytest.mark.parametrize('c_i, c_o', [(3, 6), (2, 2)]) @pytest.mark.parametrize('kernel_size', [3, 5]) @pytest.mark.parametrize('stride', [1, 2]) @pytest.mark.parametrize('padding', [0, 1]) @pytest.mark....
运行 AI代码解释 ifx.numel()>0:output=self.layers(x)else:output=torch.zeros((0,C,H,W))# Create empty outputs
allclose(other, rtol=1e-05, atol=1e-08, equal_nan=False)→ Tensor See torch.allclose() apply_(callable)→ Tensor Applies the function callable to each element in the tensor, replacing each element with the value returned by callable. Note This function only works with CPU tensors and sh...
(tensor_data, 'tensor_data.pt') # 验证tensor是否成功保存并可以加载 loaded_tensor_data = torch.load('tensor_data.pt') print(" Loaded Tensor:") print(loaded_tensor_data) # 检查加载的数据是否与原始数据一致 assert torch.allclose(tensor_data, loaded_tensor_data), "Loaded tensor data does not...
allclose(other, rtol=1e-05, atol=1e-08, equal_nan=False) → Tensor apply_(callable) → Tensor argmax(dim=None, keepdim=False) → LongTensor argmin(dim=None, keepdim=False) → LongTensor argsort(dim=-1, descending=False) → LongTensor ...
(dim,), keepdim=True) return (x - mean) / torch.sqrt(var + eps) custom_layer_norm_output = custom_layer_norm(embedding) print("y_custom: ", custom_layer_norm_output) print(custom_layer_norm_output.shape) assert torch.allclose(layer_norm_output, custom_layer_norm_output), 'Tensors ...
Torch脚本是一种从PyTorch代码创建可序列化和可优化模型的方法。用Torch脚本编写的代码可以从Python进程中保存,并在没有Python依赖的进程中加载。 我们提供了一些工具帮助我们将模型从纯Python程序逐步转换为可以独立于Python运行的Torch脚本程序。Torch脚本程序可以在其他语言的程序中运行(例如,在独立的C ++程序中)。这使...