我正在尝试从TensorFlow 1.10 中的Keras 应用程序获取 ResNet101 或 ResNeXt,由于某种原因,它们仅在 Keras 的存储库中可用:
import tensorflow as tf
from keras import applications
tf.enable_eager_execution()
resnext = applications.resnext.ResNeXt101(include_top=False, weights='imagenet', input_shape=(SCALED_HEIGHT, SCALED_WIDTH, 3), pooling=None)
但是,这会导致:
Traceback (most recent call last):
File "myscript.py", line 519, in get_fpn
resnet = applications.resnet50.ResNet50(include_top=False, weights='imagenet', input_shape=(SCALED_HEIGHT, SCALED_WIDTH, 3), pooling=None)
File "Keras-2.2.4-py3.5.egg/keras/applications/__init__.py", line 28, in wrapper
return base_fun(*args, **kwargs)
File "Keras-2.2.4-py3.5.egg/keras/applications/resnet50.py", line 11, in ResNet50
return resnet50.ResNet50(*args, **kwargs)
File "Keras_Applications-1.0.8-py3.5.egg/keras_applications/resnet50.py", line 214, in ResNet50
img_input = layers.Input(shape=input_shape)
File "Keras-2.2.4-py3.5.egg/keras/engine/input_layer.py", line 178, in Input
input_tensor=tensor)
File "Keras-2.2.4-py3.5.egg/keras/legacy/interfaces.py", line 91, in wrapper
return func(*args, **kwargs)
File "Keras-2.2.4-py3.5.egg/keras/engine/input_layer.py", line 87, in __init__
name=self.name)
File "Keras-2.2.4-py3.5.egg/keras/backend/tensorflow_backend.py", line 529, in placeholder
x = tf.placeholder(dtype, shape=shape, name=name)
File "tensorflow/python/ops/array_ops.py", line 1732, in placeholder
raise RuntimeError("tf.placeholder() is not compatible with "
RuntimeError: tf.placeholder() is not compatible with eager execution.
我从它的 GitHub 主分支安装了 Keras,因为出于某种奇怪的原因,Keras 和 TensorFlow 的 Keras API 的 pip 安装不包括 ResNet101、ResNetv2、ResNeXt 等。有谁知道我如何在 TensorFlow 的热切中运行这些模型(最好是 ResNeXt)执行?