garage.tf.baselines.continuous_mlp_baseline module¶
A value function (baseline) based on a MLP model.
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class
ContinuousMLPBaseline
(env_spec, num_seq_inputs=1, regressor_args=None, name='ContinuousMLPBaseline')[source]¶ Bases:
garage.np.baselines.baseline.Baseline
A value function using a MLP network.
It fits the input data by performing linear regression to the outputs.
Parameters: - env_spec (garage.envs.env_spec.EnvSpec) – Environment specification.
- num_seq_inputs (float) – Number of sequence per input. By default it is 1.0, which means only one single sequence.
- regressor_args (dict) – Arguments for regressor.
- name (str) – Name of baseline.
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fit
(paths)[source]¶ Fit regressor based on paths.
Parameters: paths (dict[numpy.ndarray]) – Sample paths.
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get_param_values
()[source]¶ Get parameter values.
Returns: A list of values of each parameter. Return type: List[np.ndarray]
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get_params_internal
()[source]¶ Get the params, which are the trainable variables.
Returns: A list of trainable variables in the current variable scope. Return type: List[tf.Variable]