问SageMaker - mini_batch_size，它是什么，为什么我不能得到它高于5？

EN

# The algorithm supports multiple network depth (number of layers). They are 18, 34, 50, 101, 152 and 200
# For this training, we will use 18 layers
num_layers = 18
# we need to specify the input image shape for the training data
image_shape = "3,640,640"
# specify the number of output classes
num_classes = 2
# we also need to specify the number of training samples in the training set
num_training_samples = num_classes * 500
# batch size for training
mini_batch_size = 8
# number of epochs
epochs = 1
# learning rate
learning_rate = 0.01
# report top_5 accuracy
top_k = 5
# resize image before training
resize = 640
# period to store model parameters (in number of epochs), in this case, we will save parameters from epoch 2, 4, and 6
checkpoint_frequency = 2
# Since we are using transfer learning, we set use_pretrained_model to 1 so that weights can be
# initialized with pre-trained weights
use_pretrained_model = 0

[07/24/2021 12:59:04 ERROR 140201375991616] [12:59:04]
/opt/brazil-pkg-cache/packages/AIAlgorithmsMXNet/AIAlgorithmsMXNet-1.3.x_ecl_Cuda_10.1.x.6753.0/AL2_x86_64/generic-flavor/src/src/io/iter_image_recordio_2.cc:318:
Check failed: !overflow number of input images must be bigger than the batch size