I have to train a model from where I dont have access to Internet.
base_cnn = resnet.ResNet50( weights="imagenet", input_shape=target_shape + (3,), include_top=False )
Subsequently, training is failing with:
Traceback (most recent call last): base_cnn = resnet.ResNet50( return ResNet(stack_fn, False, True, 'resnet50', include_top, weights, weights_path = data_utils.get_file( raise Exception(error_msg.format(origin, e.errno, e.reason)) Exception: URL fetch failure on https://storage.googleapis.com/tensorflow/keras-applications/resnet/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5: None -- [Errno 101] Network is unreachable
Is there a way I can load the weights from drive instead of fetching an URL?
Weights could be downloaded as:
from tensorflow.keras.applications import resnet base_cnn = resnet.ResNet50( weights="imagenet", input_shape=target_shape + (3,), include_top=False ) base_cnn.save("weights.h5")
Then load the saved weights:
from tensorflow.keras.models import load_model base_cnn=load_model('weights.h5')
Answered By – Exploring