merlin.models.tf.RegressionTask
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class
merlin.models.tf.
RegressionTask
(*args, **kwargs)[source] Bases:
merlin.models.tf.prediction_tasks.base.PredictionTask
Prediction task for regression-task.
- Parameters
target (Union[str, Schema], optional) – The name of the target. If a Schema is provided, the target is inferred from the schema.
task_name (str, optional) – The name of the task.
task_block (Block, optional) – The block to use for the task.
metrics (MetricOrMetrics, optional) – The metrics to use for the task. Defaults to [root-mean-squared-error].
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__init__
(target: Optional[Union[str, merlin.schema.schema.Schema]] = None, task_name: Optional[str] = None, task_block: Optional[keras.engine.base_layer.Layer] = None, **kwargs)[source]
Methods
__init__
([target, task_name, task_block])add_loss
(losses, **kwargs)Add loss tensor(s), potentially dependent on layer inputs.
add_metric
(value[, name])Adds metric tensor to the layer.
add_update
(updates)Add update op(s), potentially dependent on layer inputs.
add_variable
(*args, **kwargs)Deprecated, do NOT use! Alias for add_weight.
add_weight
([name, shape, dtype, …])Adds a new variable to the layer.
build
(input_shape)Creates the variables of the layer (optional, for subclass implementers).
build_task
(input_shape, schema, body, **kwargs)call
(inputs[, training])child_name
(name)compute_mask
(inputs[, mask])Computes an output mask tensor.
compute_output_shape
(input_shape)Computes the output shape of the layer.
compute_output_signature
(input_signature)Compute the output tensor signature of the layer based on the inputs.
count_params
()Count the total number of scalars composing the weights.
finalize_state
()Finalizes the layers state after updating layer weights.
from_config
(config)get_input_at
(node_index)Retrieves the input tensor(s) of a layer at a given node.
get_input_mask_at
(node_index)Retrieves the input mask tensor(s) of a layer at a given node.
get_input_shape_at
(node_index)Retrieves the input shape(s) of a layer at a given node.
get_output_at
(node_index)Retrieves the output tensor(s) of a layer at a given node.
get_output_mask_at
(node_index)Retrieves the output mask tensor(s) of a layer at a given node.
get_output_shape_at
(node_index)Retrieves the output shape(s) of a layer at a given node.
get_weights
()Returns the current weights of the layer, as NumPy arrays.
pre_call
(inputs, **kwargs)Apply PredictionTask to inputs to get predictions scores
pre_loss
(outputs, **kwargs)Apply call_outputs method of pre block to transform predictions and targets before computing loss and metrics.
set_weights
(weights)Sets the weights of the layer, from NumPy arrays.
with_name_scope
(method)Decorator to automatically enter the module name scope.
Attributes
activity_regularizer
Optional regularizer function for the output of this layer.
compute_dtype
The dtype of the layer’s computations.
context
dtype
The dtype of the layer weights.
dtype_policy
The dtype policy associated with this layer.
dynamic
Whether the layer is dynamic (eager-only); set in the constructor.
inbound_nodes
Return Functional API nodes upstream of this layer.
input
Retrieves the input tensor(s) of a layer.
input_mask
Retrieves the input mask tensor(s) of a layer.
input_shape
Retrieves the input shape(s) of a layer.
input_spec
InputSpec instance(s) describing the input format for this layer.
losses
List of losses added using the add_loss() API.
metrics
List of metrics added using the add_metric() API.
name
Name of the layer (string), set in the constructor.
name_scope
Returns a tf.name_scope instance for this class.
non_trainable_variables
non_trainable_weights
List of all non-trainable weights tracked by this layer.
outbound_nodes
Return Functional API nodes downstream of this layer.
output
Retrieves the output tensor(s) of a layer.
output_mask
Retrieves the output mask tensor(s) of a layer.
output_shape
Retrieves the output shape(s) of a layer.
pre_eval_topk
stateful
submodules
Sequence of all sub-modules.
supports_masking
Whether this layer supports computing a mask using compute_mask.
task_name
trainable
trainable_variables
trainable_weights
List of all trainable weights tracked by this layer.
updates
variable_dtype
Alias of Layer.dtype, the dtype of the weights.
variables
Returns the list of all layer variables/weights.
weights
Returns the list of all layer variables/weights.
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DEFAULT_LOSS
= 'mse'
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DEFAULT_METRICS
= (<class 'keras.metrics.metrics.RootMeanSquaredError'>,)