save_model_weights_tf
Save model weights in the SavedModel format
Description
Save model weights in the SavedModel format
Usage
save_model_weights_tf(object, filepath, overwrite = TRUE)
load_model_weights_tf(
object,
filepath, by_name = FALSE,
skip_mismatch = FALSE,
reshape = FALSE
)
Arguments
Arguments | Description |
---|---|
object | Model object to save/load |
filepath | Path to the file |
overwrite | Whether to silently overwrite any existing file at the target location |
by_name | Whether to load weights by name or by topological order. |
skip_mismatch | Logical, whether to skip loading of layers where there is a mismatch in the number of weights, or a mismatch in the shape of the weight (only valid when by_name = FALSE ). |
reshape | Reshape weights to fit the layer when the correct number of values are present but the shape does not match. |
Details
When saving in TensorFlow format, all objects referenced by the network are saved in the same format as tf.train.Checkpoint
, including any Layer instances or Optimizer instances assigned to object attributes. For networks constructed from inputs and outputs using tf.keras.Model(inputs, outputs)
, Layer instances used by the network are tracked/saved automatically. For user-defined classes which inherit from tf.keras.Model
, Layer instances must be assigned to object attributes, typically in the constructor. See the documentation of tf.train.Checkpoint
and tf.keras.Model
for details.