b1bfd16945a658d02847209e46a2ba8d72b456e1,autokeras/hypermodel/hyper_block.py,ImageBlock,build,#ImageBlock#Any#Any#,123
Before Change
input_node = layer_utils.format_inputs(inputs, self.name, num=1)[0]
output_node = input_node
for i in range(hp.Choice("num_layers", [1, 2, 3], default=2)):
output_node = tf.keras.layers.Conv2D(
hp.Choice("units_{i}".format(i=i),
[16, 32, 64],
default=32),
hp.Choice("kernel_size_{i}".format(i=i),
[3, 5, 7],
default=3))(output_node)
return output_node
def shape_compatible(shape1, shape2):
After Change
["resnet", "xception", "vanilla"],
default="resnet")
if block_type == "resnet":
output_node = ResNetBlock().build(hp, output_node)
elif block_type == "xception":
output_node = XceptionBlock().build(hp, output_node)
elif block_type == "vanilla":
output_node = ConvBlock().build(hp, output_node)
return output_node
class ConvBlock(HyperBlock):
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 6
Instances
Project Name: keras-team/autokeras
Commit Name: b1bfd16945a658d02847209e46a2ba8d72b456e1
Time: 2019-07-01
Author: jhfjhfj1@gmail.com
File Name: autokeras/hypermodel/hyper_block.py
Class Name: ImageBlock
Method Name: build
Project Name: keras-team/keras
Commit Name: 36ac91f0576b2295df1f3f8b23c305d69698a0ff
Time: 2017-02-15
Author: francois.chollet@gmail.com
File Name: keras/models.py
Class Name: Sequential
Method Name: set_weights