2

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？

4

1 回答 1

3

如错误所示，tf.placeholder() 用作占位符，用于使用 feed_dict 将数据提供给 tf 会话，与急切模式不兼容。

这个链接用一个例子很好地解释了它：https ://github.com/tensorflow/tensorflow/issues/18165#issuecomment-377841925

为此，您可以使用 tf.keras.applications 中的模型。我已经尝试过使用 TF2.0 Beta 版本。

https://www.tensorflow.org/beta/tutorials/images/transfer_learning#create_the_base_model_from_the_pre-trained_convnets

import tensorflow as tf
resnext = tf.keras.applications.ResNeXt50(weights=None)
print(tf.executing_eagerly())

真的

ResNeXt 模型不可用（我必须进行一些更改，例如将 resnext.py 从 keras/applications 复制到 tensorflow/python/keras/applications 并更改为 __init__.py 等）但是您可以尝试使用现有模型，例如 ResNet50，如果他们工作然后你可以尝试移植ResNeXt。

于 2019-06-23T08:24:42.620 回答