ResNet1DBlock
- class ketos.neural_networks.resnet.ResNet1DBlock(*args, **kwargs)[source]
Residual block for 1D (temporal) ResNet architectures.
- Args:
- filters: int
The number of filters in the block
- strides: int
Strides used in convolutional layers within the block
- kernel: int
Kernel size used in convolutional layers within the block
- residual_path: bool
Whether or not the block will contain a residual path
- batch_norm_momentum: float between 0 and 1
Momentum for the moving average of the batch normalization layers. The default value is 0.99. For an explanation of how the momentum affects the batch normalisation operation, see <https://www.tensorflow.org/api_docs/python/tf/keras/layers/BatchNormalization>
- dropout_rate: float between 0 and 1
Fraction of the input units to drop in the dropout layers. Set this parameter to 0 to disable dropout (default).
- Returns:
A ResNetBlock object. The block itself is a tensorflow model and can be used as such.
Methods
call
(inputs[, training])Calls the model on new inputs.
set_batch_norm_momentum
(momentum)Set the momentum for the moving average of the batch normalization layers in the block.
set_dropout_rate
(rate)Set the fraction of the input units to drop in the dropout layers in the block.
Attributes
activity_regularizer
Optional regularizer function for the output of this layer.
compute_dtype
The dtype of the layer's computations.
distribute_strategy
The tf.distribute.Strategy this model was created under.
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
Deprecated, do NOT use! Only for compatibility with external Keras.
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.
layers
losses
List of losses added using the add_loss() API.
metrics
Returns the model's metrics added using compile(), add_metric() APIs.
metrics_names
Returns the model's display labels for all outputs.
name
Name of the layer (string), set in the constructor.
name_scope
Returns a tf.name_scope instance for this class.
non_trainable_variables
Sequence of non-trainable variables owned by this module and its submodules.
non_trainable_weights
List of all non-trainable weights tracked by this layer.
outbound_nodes
Deprecated, do NOT use! Only for compatibility with external Keras.
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.
run_eagerly
Settable attribute indicating whether the model should run eagerly.
state_updates
Deprecated, do NOT use!
stateful
submodules
Sequence of all sub-modules.
supports_masking
Whether this layer supports computing a mask using compute_mask.
trainable
trainable_variables
Sequence of trainable variables owned by this module and its submodules.
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.
- call(inputs, training=None)[source]
Calls the model on new inputs.
In this case call just reapplies all ops in the graph to the new inputs (e.g. build a new computational graph from the provided inputs).
- Args:
- inputs: Tensor or list of tensors
A tensor or list of tensors
- training: Bool
Boolean or boolean scalar tensor, indicating whether to run the Network in training mode or inference mode.
- Returns:
A tensor if there is a single output, or a list of tensors if there are more than one outputs.
- set_batch_norm_momentum(momentum)[source]
Set the momentum for the moving average of the batch normalization layers in the block.
For an explanation of how the momentum affects the batch normalisation operation, see <https://www.tensorflow.org/api_docs/python/tf/keras/layers/BatchNormalization>
- Args:
- momentum: float between 0 and 1
Momentum for the moving average of the batch normalization layers.
- Returns:
None