import tensorflow as tf
from kblocks.keras import wrap
loc = locals()
for k, v in wrap.wrapped_items(tf.keras.initializers, "tf.keras.initializers"):
loc[k] = v
del loc, wrap
import tensorflow as tf
from kblocks.keras import wrap
loc = locals()
for k, v in wrap.wrapped_items(tf.keras.optimizers, "tf.keras.optimizers"):
loc[k] = v
del loc, wrap
import tensorflow as tf
from kblocks.keras import wrap
loc = locals()
for k, v in wrap.wrapped_items(tf.keras.losses, "tf.keras.losses"):
loc[k] = v
del loc, wrap
import tensorflow as tf
from kblocks.keras import wrap
loc = locals()
for k, v in wrap.wrapped_items(tf.keras.optimizers.schedules,
"tf.keras.optimizers.schedules"):
loc[k] = v
del loc, wrap
import tensorflow as tf
from kblocks.keras import wrap
loc = locals()
for k, v in wrap.wrapped_items(tf.keras.constraints, "tf.keras.constraints"):
loc[k] = v
del loc, wrap
import tensorflow as tf
from kblocks.keras import wrap
loc = locals()
for k, v in wrap.wrapped_items(tf.keras.layers, "tf.keras.layers"):
loc[k] = v
# make linters shut up
BatchNormalization = loc["BatchNormalization"]
Dense = loc["Dense"]
Convolution1D = loc["Convolution1D"]
Conv1D = loc["Conv1D"]
Convolution2D = loc["Convolution2D"]
Conv2D = loc["Conv2D"]
Convolution3D = loc["Convolution3D"]
Conv3D = loc["Conv3D"]
Dropout = loc["Dropout"]
AlphaDropout = loc["AlphaDropout"]
del loc, wrap
import tensorflow as tf
from kblocks.keras import wrap
loc = locals()
for k, v in wrap.wrapped_items(tf.keras.regularizers, "tf.keras.regularizers"):
loc[k] = v
del loc, wrap
import tensorflow as tf
from kblocks.keras import wrap
loc = locals()
for k, v in wrap.wrapped_items(tf.keras.metrics, "tf.keras.metrics"):
loc[k] = v
del loc, wrap
import gin
import tensorflow as tf
from kblocks.keras import wrap
from kblocks.utils import super_signature
loc = locals()
for k, v in wrap.wrapped_items(
tf.keras.callbacks,
"tf.keras.callbacks",
blacklist=wrap.BLACKLIST +
("LearningRateScheduler", "ReduceLROnPlateau"),
):
loc[k] = v
# make linter shut up
TensorBoard = loc["TensorBoard"]
CSVLogger = loc["CSVLogger"]
EarlyStopping = loc["EarlyStopping"]
BackupAndRestore = gin.external_configurable(
tf.keras.callbacks.experimental.BackupAndRestore,
module="tf.keras.callbacks")
del loc, wrap
# add _supports_tf_logs = True
# Github issue: https://github.com/tensorflow/tensorflow/issues/45895
@gin.configurable(module="tf.keras.callbacks")
@super_signature