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[英]How to fix MatMul Op has type float64 that does not match type float32 TypeError?
[英]How to fix 'AssertionError: The input images should be float64(32) and in the range of [-1.0, 1.0]!'
我正在學校的HPC上的Tensorflow上運行CycleGAN的代碼。 上周我運行的代碼正常運行,但本周停止運行。 我相信這可能是由於其中一個模塊的更新引起的,但我不確定。
Traceback (most recent call last):
File "test.py", line 55, in <module>
im.imwrite(im.immerge(a_img_opt, 1, 3), a_save_dir + '/' + img_name)
File "/home/kseelma/PleaseWork/image_utils.py", line 46, in imwrite
return scipy.misc.imsave(path, _to_range(image, 0, 255, np.uint8))
File "/home/kseelma/PleaseWork/image_utils.py", line 14, in _to_range
'The input images should be float64(32) and in the range of [-1.0, 1.0]!'
AssertionError: The input images should be float64(32) and in the range of [-1.0, 1.0]!
這就是問題所在,下面顯示了寫入和浸入的方法
def imwrite(image, path):
# save an [-1.0, 1.0] image
return scipy.misc.imsave(path, _to_range(image, 0, 255, np.uint8))
def immerge(images, row, col):
"""Merge images.
merge images into an image with (row * h) * (col * w)
`images` is in shape of N * H * W(* C=1 or 3)
"""
if images.ndim == 4:
c = images.shape[3]
elif images.ndim == 3:
c = 1
h, w = images.shape[1], images.shape[2]
if c > 1:
img = np.zeros((h * row, w * col, c))
else:
img = np.zeros((h * row, w * col))
for idx, image in enumerate(images):
i = idx % col
j = idx // col
img[j * h:j * h + h, i * w:i * w + w, ...] = image
return img
您的CycleGAN正在保存的圖像,即模型返回的圖像的值小於-1或大於1。CycleGAN在生成器中的最后一層是tanh,其范圍介於-1到1之間。因此,請確保生成器的最后一層是tanh,或范圍在-1到+1之間的函數。
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