【发布时间】：2018-07-04 15:07:22
【问题描述】：
我正在尝试将 SqueezeDet model 的 Keras 实现适应新数据集。在对我的配置文件进行适当的更改后，我尝试运行 train 脚本，但它似乎在调用 fit_generator() 后挂起。当我得到以下输出时：
/anaconda/envs/py35/lib/python3.5/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
from ._conv import register_converters as _register_converters
Using TensorFlow backend.
Number of images: 536
Number of epochs: 100
Number of batches: 53
Batch size: 10
2018-07-04 14:18:49.711606: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-07-04 14:18:54.080912: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1356] Found device 0 with properties:
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 52a9:00:00.0
totalMemory: 11.17GiB freeMemory: 11.10GiB
2018-07-04 14:18:54.080958: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1435] Adding visible gpu devices: 0
2018-07-04 14:18:54.333214: I tensorflow/core/common_runtime/gpu/gpu_device.cc:923] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-07-04 14:18:54.333270: I tensorflow/core/common_runtime/gpu/gpu_device.cc:929] 0
2018-07-04 14:18:54.333290: I tensorflow/core/common_runtime/gpu/gpu_device.cc:942] 0: N
2018-07-04 14:18:54.333559: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1053] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10764 MB memory) -> physical GPU (device: 0, name: Tesla K80, pci bus id: 52a9:00:00.0, compute capability: 3.7)
Learning rate: 0.01
Weights initialized by name from ../main/model/imagenet.h5
Using single GPU
Backend Qt5Agg is interactive backend. Turning interactive mode on.
Epoch 1/100
然后，即使将其搁置一天，也不会发生任何事情。它似乎冻结的电话是：
squeeze.model.fit_generator(train_generator, epochs=EPOCHS, verbose=1,
steps_per_epoch=nbatches_train, callbacks=cb)
参数在哪里：
train_generator = generator_from_data_path(img_names, gt_names, config=cfg)
EPOCHS = 100
nbatches_train = 53
callbacks = [# TensorBoard object, ReduceLROnPlateau object, ModelCheckpoint object #]
我的版本：
Python 3.5.4 :: Anaconda custom (64-bit)
tensorflow-gpu : 1.8.0
tensorflow : 1.8.0
Keras : 2.2.0
【问题讨论】：
-
移除 TensorBoard 回调并重试。
-
train_generator[0]return 什么？len(train_generator)会返回什么吗？ -
@wl2776 不起作用，因为 train_generator 是
threadsafe_iter对象train_generator[0] > TypeError("'threadsafe_iter' object does not support indexing",)和len(train_generator) > TypeError("object of type 'threadsafe_iter' has no len()",)。但是，我认为您正在做某事，如果我尝试使用next(train_generator)访问第一个元素，它会挂在该行上。 -
@MatiasValdenegro 删除回调没有任何区别。
-
好的，那么你应该添加更多信息（代码），比如什么是 train_generator。
标签： python python-3.x tensorflow keras