UpSampling2D
类tf_keras.layers.UpSampling2D(
size=(2, 2), data_format=None, interpolation="nearest", **kwargs
)
用于 2D 输入的上采样层。
通过分别复制数据行和列 size[0]
次和 size[1]
次来实现。
示例
>>> input_shape = (2, 2, 1, 3)
>>> x = np.arange(np.prod(input_shape)).reshape(input_shape)
>>> print(x)
[[[[ 0 1 2]]
[[ 3 4 5]]]
[[[ 6 7 8]]
[[ 9 10 11]]]]
>>> y = tf.keras.layers.UpSampling2D(size=(1, 2))(x)
>>> print(y)
tf.Tensor(
[[[[ 0 1 2]
[ 0 1 2]]
[[ 3 4 5]
[ 3 4 5]]]
[[[ 6 7 8]
[ 6 7 8]]
[[ 9 10 11]
[ 9 10 11]]]], shape=(2, 2, 2, 3), dtype=int64)
参数
channels_last
(默认) 或 channels_first
。输入中维度的顺序。channels_last
对应于形状为 (batch_size, height, width, channels)
的输入,而 channels_first
对应于形状为 (batch_size, channels, height, width)
的输入。未指定时,使用 TF-Keras 配置文件 ~/.keras/keras.json
中找到的 image_data_format
值(如果存在),否则使用 'channels_last'。默认为 'channels_last'。"area"
, "bicubic"
, "bilinear"
, "gaussian"
, "lanczos3"
, "lanczos5"
, "mitchellcubic"
, "nearest"
。输入形状
形状为 4D 张量: - 如果 data_format
为 "channels_last"
:(batch_size, rows, cols, channels)
- 如果 data_format
为 "channels_first"
:(batch_size, channels, rows, cols)
输出形状
形状为 4D 张量: - 如果 data_format
为 "channels_last"
:(batch_size, upsampled_rows, upsampled_cols, channels)
- 如果 data_format
为 "channels_first"
:(batch_size, channels, upsampled_rows, upsampled_cols)