train_sample = train_sample.transpose((0, 3, 1, 2))
时间: 2023-10-06 17:13:29 浏览: 58
This line of code transposes the dimensions of the NumPy array called `train_sample`. Specifically, it reorders the dimensions of the array so that the elements in the second dimension (originally representing width) become the third dimension, and the elements in the third dimension (originally representing height) become the second dimension.
The new order of dimensions is `(0, 3, 1, 2)`, where:
- `0`: represents the samples (i.e., individual images) in the array
- `3`: represents the channels (i.e., color channels) in the array
- `1`: represents the new width dimension
- `2`: represents the new height dimension
This operation is commonly used in deep learning frameworks like TensorFlow and PyTorch to ensure that the data is in the correct format for training models. By transposing the dimensions in this way, the data is ready to be passed to a convolutional neural network (CNN) for feature extraction and classification.