Fits the data generator to some sample data. This computes the internal data stats related to the data-dependent transformations, bas

Sets the values of `layer.weights` from a list of NumPy arrays.

Squeeze/expand last dim if ranks differ from expected by exactly 1.

Prints a string summary of the network. Args: line_length: Total length of printed lines (e.g. set this to adapt

Register a new serving endpoint. Args: name: `str`. The name of the endpoint. fn: A callable. It should only leverage

DEPRECATED.

Sets the default dtype policy globally. Example: >>> keras.config.set_dtype_policy("mixed_float16")

Write the corresponding SavedModel to disk. Arguments: filepath: `str` or `pathlib.Path` object. Path where to sa

Canonicalize an axis in [-num_dims, num_dims) to [0, num_dims).

Creates a generator to extract data from the queue. Skip the data if it is `None`. This method is called from the main thread.

Track the variables (of a layer or model) and other assets. By default, all variables used by an endpoint function are automatically

Converts bounding boxes between formats. Supported formats (case-insensitive): `"xyxy"`: [left, top, right, bottom] `"yxyx"`: [top, left,

Convert the non-`None` value to either a tuple or a list.

Exclude variables from weight decay. This method must be called before the optimizer's `build` method is called. You can set specific

Export the model as an artifact for inference. Args: filepath: `str` or `pathlib.Path` object. The path to save the

Get the H5 entry group. This method is only available in read mode. Args: path: `str`. The variable path.

Call the layer without any side effects. Args: trainable_variables: List of trainable variables of the model. non_tra

Backward pass computation specification. Args: ctx: Context object. grad_output: Gradient with respect to the output.

Sum of a tensor over the given axes. Args: x: Input tensor. axis: Axis or axes along which the sum is computed. The default is to

Add a value to a variable. This should be used in optimizers instead of `variable.assign_add(value)` to support backend specific opti

Slice a Tensor along the given axis.

Turns `logs` dict into a list as per key order of `metrics_names`.

Can be called inside of the `call()` method to add a scalar loss. Example: ```python class MyLayer(Layer): ...

Add optimizer variables from the list of trainable model variables. Create an optimizer variable based on the information of the supplied

Subtract a value from a variable. This should be used in optimizers instead of `variable.assign_sub(value)` to support backend specif

Returns the current default dtype policy object.

Convert a Keras model to dot format. Args: model: A Keras model instance. show_shapes: whether to display shape information.

Updates the running average of the Hessian matrix with a new batch. This method computes the Hessian matrix for a given batch of inp

DEPRECATED.

Clone a Functional or Sequential `Model` instance. Model cloning is similar to calling a model on new inputs, except that it creates new laye

Computes the scale and zero-point for quantization. This function calculates the scale and zero-point required for quantizing a given te

Return the serializable config of the metric.

Downloads a file from a URL if it not already in the cache. By default the file at the url `origin` is downloaded to the cache_dir `~/.keras`

Read all summaries under the logdir into a `_SummaryFile`. Args: logdir: A path to a directory that contains zero or more event fil