test_loss, acc = model.evaluate(test_x, test_y)print('loss: {}, acc: {}'.format(test_loss, acc))#---## unbox#以下代码来自tensorflow微信公众号classMNISTLoader():def__init__(self): mnist = tf.keras.datasets.mnist (self.train_data, self.train_label), (self.test_data, self.test...
print("#===epoch: {}, train loss is: {}, train acc is: {:2.2f}%===#".format(epoch, total_train_loss.numpy(), train_acc*100)) # --- Validation --- model.eval() for batch_id, data in enumerate(val_loader): x_data, y_data = data labels = paddle.unsqueeze(y_data, axis...
]/dso_loader.cc:108] successfully opened CUDA library libcurand.so locally 代码语言:javascript 代码运行次数:0 运行 AI代码解释 >>> sess = tf.Session() [...] I [...]/gpu_init.cc:102] Found device 0 with properties: name: GRID K520 major: 3 minor: 0 memoryClockRate (GHz) 0.797 ...
随后，我们可以初始化 Bagua 的进程组:torch.cuda.set_device(bagua.get_local_rank())bagua.init_process_group()对于数据集的初始化，Bagua 完全兼容 PyTorch 的实现：train_dataset = ...test_dataset = ...train_sampler = torch.utils.data.distributed.DistributedSampler(train_dataset, num_replicas=bag...
方式了,那我们就用docker 方式试试。而且网上的安装教程也是docker 的居多【官方给出了一个教程】,我们也要与时俱进。 下面是我机器wslkernel的版本:可见是没有最新,只有更新哈! season@season:~$ uname-r5.10.16.3-microsoft-standard-WSL2 官方文档: ...
() data_loader = MNISTLoader() optimizer = tf.keras.optimizers.Adam(learning_rate=learning_rate) num_batches = int(data_loader.num_train_data // batch_size * num_epochs) for batch_index in range(num_batches): X, y = data_loader.get_batch(batch_size) with tf.GradientTape() as tape...
def train(args, model, device, train_loader, optimizer, epoch): model.train() for batch_idx, (data, target) in enumerate(train_loader): if (args['batch_num'] is not None) and batch_idx >= args['batch_num']: break data, target = data.to(device), (device) ...
I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:01:00.0 name: GeForce GTX 1060 computeCapability: 6.1 ...
MatMulOp<CPUDevice, T, false /* cublas, ignored for CPU */>); \ REGISTER_CPU_EIGEN(T); #define REGISTER_GPU(T) /*gpu对应实现(cublas与非cublas)*/ \ REGISTER_KERNEL_BUILDER( \ Name("MatMul").Device(DEVICE_GPU).TypeConstraint<T>("T"), \ ...
2019-10-01 12:25:37.691337: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll 2019-10-01 12:25:38.107940: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties: ...