update docs

docs/source/torchquantlib.calibration.model_calibrator.rst

@@ -1,20 +1,41 @@
-torchquantlib.calibration.model_calibrator
-==========================================
-
-.. automodule:: torchquantlib.calibration.model_calibrator
-   :members:
-   :undoc-members:
-   :show-inheritance:
-
 ModelCalibrator
----------------
+===============
 
-.. autoclass:: ModelCalibrator
+.. autoclass:: torchquantlib.calibration.model_calibrator.ModelCalibrator
    :members:
    :undoc-members:
    :show-inheritance:
 
    .. automethod:: __init__
-   .. automethod:: _setup_optimizer
-   .. automethod:: calibrate
-   .. automethod:: get_calibrated_params
+
+Class Description
+-----------------
+
+The ``ModelCalibrator`` class is designed to calibrate a stochastic model using the Sinkhorn divergence. It utilizes the geomloss library for calculating the loss.
+
+Parameters
+----------
+
+- ``model``: The stochastic model to be calibrated.
+- ``observed_data``: The observed market data used for calibration.
+- ``S0`` (optional): Initial value. Default is None.
+- ``T`` (float): Time horizon. Default is 1.0.
+- ``loss_type`` (str): Type of loss function. Default is "sinkhorn".
+- ``p`` (int): Power parameter for the loss function. Default is 2.
+- ``blur`` (float): Blur parameter for the loss function. Default is 0.05.
+- ``optimizer_cls``: Optimizer class. Default is ``torch.optim.Adam``.
+- ``lr`` (float): Learning rate for the optimizer. Default is 0.01.
+
+Methods
+-------
+
+__init__(self, model, observed_data, S0=None, T=1.0, loss_type="sinkhorn", p=2, blur=0.05, optimizer_cls=optim.Adam, lr=0.01)
+    Initialize the ModelCalibrator with the given parameters.
+
+calibrate(self, num_epochs=1000, batch_size=None, steps=100, verbose=True)
+    Perform the calibration process.
+
+get_calibrated_params(self)
+    Retrieve the calibrated parameters after calibration.
+
+