更加便捷的调试功能:直接使用python的打印方法即时打印所需要的结果,从而检查正在运行的模型结果便于测试更改 和静态执行图通用的模型代码:同样的模型代码可以使用更加便捷的DyGraph调试,执行,同时也支持使用原有的静态图模式执行 fluid.dygraph下包括 Conv2D,Conv3D,Conv2DTranspose,Conv3DTranspose,FC,Pool2D load_dygraph...
load_dygraph,save_graph Layer对象用于存储一个动态图层 import paddle.fluid as fluid import numpy as np with fluid.dygraph.guard(): value = np.arange(26).reshape(2, 13).astype("float32") a = fluid.dygraph.to_variable(value) linear = fluid.Linear(13, 5, dtype="float32") adam = fluid...
with fluid.dygraph.guard(): accs=[] model_dict, _= fluid.load_dygraph('MyDNN.pdparams') model=GR.MyDNN() model.load_dict(model_dict)#加载模型model.eval()#模型评估forbatch_id, datainenumerate(test_reader()): images= np.array([x[0].reshape(3, 100, 100)forxindata], np.float32) ...
with fluid.dygraph.guard(): model = MNIST() params_file_path = 'mnist' img_path = './work/example_0.png' # 加载模型参数 model_dict, _ = fluid.load_dygraph("mnist") model.load_dict(model_dict) # 灌入数据 model.eval() tensor_img = load_image(img_path) result = model(fluid.dyg...
''' # 导入 Paddle import paddle # 导入模型代码 from u2net import U2NET # 实例化模型 model = U2NET() # 加载预训练模型参数 params_state = paddle.load(path='u2net_dygraph/model.pdparams') model.set_dict(params_state) # 将模型设置为评估状态 model.eval() # 定义输入数据 input_spec = pa...
(data_loader): 1780 # data might come from different types of data_loader and have 1781 # different format, as following: /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/dataloader/dataloader_iter.py in __next__(self) 349 try: 350 if in_dygraph_mode()...
with fluid.dygraph.guard(): model=MyCNN()#模型实例化 model_dict,_=fluid.load_dygraph(model_save_dir) model.load_dict(model_dict)#加载模型参数 model.eval()#评估模式 infer_img = load_image(infer_path) infer_img=np.array(infer_img).astype('float32') ...
framework._dygraph_tracer(), retain_graph) paddle.fluid.core_avx.EnforceNotMet: C++ Call Stacks (More useful to developers): 0 std::string paddle::platform::GetTraceBackString<char const*>(char const*&&, char const*, int) 1 paddle::platform::EnforceNotMet::EnforceNotMet(std::__exception...
with fluid.dygraph.guard(): # 加载状态推断引擎 self.model = ResNet('resnet', 50) #加载模型参数 model_state_dict, _ = fluid.load_dygraph("arknights") self.model.load_dict(model_state_dict) self.model.eval() 在执行上面语句中的self.model.load_dict(model_state_dict)语句时,出现报错 ...
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py:1245: UserWarning: Skip loading for classifier.weight. classifier.weight is not found in the provided dict. warnings.warn(("Skip loading for {}. ".format(key) + str(err))) ...