graphenv.examples.tsp.tsp_model.TSPQModelBellman

class TSPQModelBellman(*args, num_nodes, hidden_dim=32, embed_dim=32, **kwargs)[source]

Methods

`context`	Returns a contextmanager for the current TF graph.
`custom_loss`	Override to customize the loss function used to optimize this model.
`forward`	Tensorflow/Keras style forward method.
`forward_vertex`	Forward function returning a value and weight tensor for the vertices observed via input_dict (a dict of tensors for each vertex property)
`from_batch`
`get_initial_state`	Get the initial recurrent state values for the model.
`get_q_value_distributions`	Returns distributional values for Q(s, a) given a state embedding.
`get_state_value`	Returns the state value prediction for the given state embedding.
`import_from_h5`	Imports weights from an h5 file.
`is_time_major`	If True, data for calling this ModelV2 must be in time-major format.
`last_output`	Returns the last output returned from calling the model.
`metrics`	Override to return custom metrics from your model.
`register_variables`	Register the given list of variables with this model.
`trainable_variables`	Returns the list of trainable variables for this model.
`update_ops`	Return the list of update ops for this model.
`value_function`	returns A tensor of current state values.
`variables`	Returns the list (or a dict) of variables for this model.

Parameters