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python - 默认 MaxPoolingOp 仅在设备类型 CPU 上支持 NHWC

转载 作者:行者123 更新时间:2023-12-05 00:58:11 56 4
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我尝试在 SegNet 模型上运行预测,但是当调用预测函数时收到错误。

我也尝试使用 with tf.device('/cpu:0'): 运行预测,但我收到了同样的错误

if __name__ == '__main__':
# path to the model
model = tf.keras.models.load_model('segnet_weightsONNXbackToKeras3.h5')

model.compile(loss='categorical_crossentropy', optimizer='RMSprop', metrics=['accuracy'])

model.summary()

input_shape = [None, 360, 480, 3]
output_shape = [None, 352, 480, 20]

img = cv2.imread('test4.jpg')
input_image = img
img = cv2.resize(img, (input_shape[2], input_shape[1]))
img = np.reshape(img, [1, input_shape[1], input_shape[2], input_shape[3]])

if normalize:
img = img.astype('float32') / 255

model.summary()
classes = model.predict(img)[0]
colors = []
for i in range(output_shape[3]):
colors.append(generate_color())

maxMatrix = np.amax(classes, axis=2)
prediction = np.zeros((output_shape[1], output_shape[2], 3), dtype=np.uint8)

2019-10-25 19:32:03.126831: E tensorflow/core/common_runtime/executor.cc:642] Executor failed to create kernel. Invalid argument: Default MaxPoolingOp only supports NHWC on device type CPU
[[{{node model/LAYER_7/MaxPool}}]]
Traceback (most recent call last):
File "../mold_segmentation_h5VM.py", line 62, in <module>
classes = model.predict(img)[0]
File "..\anaconda3\lib\site-packages\tensorflow_core\python\keras\engine\training.py", line 909, in predict
use_multiprocessing=use_multiprocessing)
File "..\anaconda3\lib\site-packages\tensorflow_core\python\eager\execute.py", line 67, in quick_execute
six.raise_from(core._status_to_exception(e.code, message), None)
File "<string>", line 3, in raise_from
tensorflow.python.framework.errors_impl.InvalidArgumentError: Default MaxPoolingOp only supports NHWC on device type CPU
[[node model/LAYER_7/MaxPool (defined at D:\EB-AI\tools\anaconda3\lib\site-packages\tensorflow_core\python\framework\ops.py:1751) ]] [Op:__inference_distributed_function_4421]

Function call stack:
distributed_function

最佳答案

没有 test4.jpg 很难测试解决方案。但是,错误 Default MaxPoolingOp only support NHWC on device type CPU意味着模型只能接受形式为 n_examples x height x width x channels 的输入。我认为您的 cv2.resize 和随后的 np.reshape 行没有以正确的格式输出图像。在调用 model.predict() 之前尝试打印出图像的形状,并确保其格式为 n_examples x height x width x channels。

关于python - 默认 MaxPoolingOp 仅在设备类型 CPU 上支持 NHWC,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/58562582/

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