在Colab上托管的Tensorflow团队尝试运行任意图像样式化的示例代码时，我一直收到这个错误。
这就是代码。(如本笔记本所示，方框5给出了错误(。
from __future__ import absolute_import, division, print_function
import functools
import os
from matplotlib import gridspec
import matplotlib.pylab as plt
import numpy as np
import tensorflow as tf
import tensorflow_hub as hub
print("TF Version: ", tf.__version__)
print("TF-Hub version: ", hub.__version__)
print("Eager mode enabled: ", tf.executing_eagerly())
print("GPU available: ", tf.test.is_gpu_available())
# @title Define image loading and visualization functions { display-mode: "form" }
def crop_center(image):
"""Returns a cropped square image."""
shape = image.shape
new_shape = min(shape[1], shape[2])
offset_y = max(shape[1] - shape[2], 0) // 2
offset_x = max(shape[2] - shape[1], 0) // 2
image = tf.image.crop_to_bounding_box(
image, offset_y, offset_x, new_shape, new_shape)
return image
@functools.lru_cache(maxsize=None)
def load_image(image_url, image_size=(256, 256), preserve_aspect_ratio=True):
"""Loads and preprocesses images."""
# Cache image file locally.
image_path = tf.keras.utils.get_file(os.path.basename(image_url)[-128:], image_url)
# Load and convert to float32 numpy array, add batch dimension, and normalize to range [0, 1].
img = plt.imread(image_path).astype(np.float32)[np.newaxis, ...]
if img.max() > 1.0:
img = img / 255.
if len(img.shape) == 3:
img = tf.stack([img, img, img], axis=-1)
img = crop_center(img)
img = tf.image.resize(img, image_size, preserve_aspect_ratio=True)
return img
def show_n(images, titles=('',)):
n = len(images)
image_sizes = [image.shape[1] for image in images]
w = (image_sizes[0] * 6) // 320
plt.figure(figsize=(w * n, w))
gs = gridspec.GridSpec(1, n, width_ratios=image_sizes)
for i in range(n):
plt.subplot(gs[i])
plt.imshow(images[i][0], aspect='equal')
plt.axis('off')
plt.title(titles[i] if len(titles) > i else '')
plt.show()
# @title Load example images { display-mode: "form" }
content_image_url = 'https://upload.wikimedia.org/wikipedia/commons/thumb/f/fd/Golden_Gate_Bridge_from_Battery_Spencer.jpg/640px-Golden_Gate_Bridge_from_Battery_Spencer.jpg' # @param {type:"string"}
style_image_url = 'https://upload.wikimedia.org/wikipedia/commons/0/0a/The_Great_Wave_off_Kanagawa.jpg' # @param {type:"string"}
output_image_size = 384 # @param {type:"integer"}
# The content image size can be arbitrary.
content_img_size = (output_image_size, output_image_size)
# The style prediction model was trained with image size 256 and it's the
# recommended image size for the style image (though, other sizes work as
# well but will lead to different results).
style_img_size = (256, 256) # Recommended to keep it at 256.
content_image = load_image(content_image_url, content_img_size)
style_image = load_image(style_image_url, style_img_size)
style_image = tf.nn.avg_pool(style_image, ksize=[3,3], strides=[1,1], padding='SAME')
show_n([content_image, style_image], ['Content image', 'Style image'])
这是错误消息：
TypeError Traceback (most recent call last)
<ipython-input-8-b21290c301e4> in <module>()
14 style_image = load_image(style_image_url, style_img_size)
15 style_image = tf.nn.avg_pool(style_image, ksize=[3,3], strides=[1,1], padding='SAME')
---> 16 show_n([content_image, style_image], ['Content image', 'Style image'])
3 frames
<ipython-input-3-a1ddf5894992> in show_n(images, titles)
29 image_sizes = [image.shape[1] for image in images]
30 w = (image_sizes[0] * 6) // 320
---> 31 plt.figure(figsize=(w * n, w))
32 gs = gridspec.GridSpec(1, n, width_ratios=image_sizes)
33 for i in range(n):
/usr/local/lib/python3.6/dist-packages/matplotlib/pyplot.py in figure(num, figsize, dpi, facecolor, edgecolor, frameon, FigureClass, clear, **kwargs)
544 frameon=frameon,
545 FigureClass=FigureClass,
--> 546 **kwargs)
547
548 if figLabel:
/usr/local/lib/python3.6/dist-packages/matplotlib/backend_bases.py in new_figure_manager(cls, num, *args, **kwargs)
3322 from matplotlib.figure import Figure
3323 fig_cls = kwargs.pop('FigureClass', Figure)
-> 3324 fig = fig_cls(*args, **kwargs)
3325 return cls.new_figure_manager_given_figure(num, fig)
3326
/usr/local/lib/python3.6/dist-packages/matplotlib/figure.py in __init__(self, figsize, dpi, facecolor, edgecolor, linewidth, frameon, subplotpars, tight_layout, constrained_layout)
346 frameon = rcParams['figure.frameon']
347
--> 348 if not np.isfinite(figsize).all() or (np.array(figsize) <= 0).any():
349 raise ValueError('figure size must be positive finite not '
350 f'{figsize}')
TypeError: ufunc 'isfinite' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
有人能解释一下问题是什么以及解决方法吗？提前谢谢。
使用您在Google托管的Colab中提供的代码，您也链接了
我刚刚在笔记本的开头添加了一行代码，选择Tensorflow 2.x.
%tensorflow_version 2.x
版本2.x意味着Google Colab将选择最新稳定的Tensorflow版本。