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35a3c2d
Format code with black
Browse files- pysr/sr.py +3 -3
pysr/sr.py
CHANGED
@@ -670,7 +670,7 @@ class PySRRegressor(BaseEstimator, RegressorMixin):
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def __repr__(self):
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"""Prints all current equations fitted by the model.
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-
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The string `>>>>` denotes which equation is selected by the
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`model_selection`.
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"""
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@@ -819,7 +819,7 @@ class PySRRegressor(BaseEstimator, RegressorMixin):
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def jax(self):
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"""Return jax representation of the equation(s) chosen by `model_selection`.
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-
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Each equation (multiple given if there are multiple outputs) is a dictionary
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containing {"callable": func, "parameters": params}. To call `func`, pass
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func(X, params). This function is differentiable using `jax.grad`.
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@@ -839,7 +839,7 @@ class PySRRegressor(BaseEstimator, RegressorMixin):
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def pytorch(self):
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"""Return pytorch representation of the equation(s) chosen by `model_selection`.
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-
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Each equation (multiple given if there are multiple outputs) is a PyTorch module
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containing the parameters as trainable attributes. You can use the module like
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any other PyTorch module: `module(X)`, where `X` is a tensor with the same
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def __repr__(self):
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"""Prints all current equations fitted by the model.
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+
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The string `>>>>` denotes which equation is selected by the
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`model_selection`.
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"""
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def jax(self):
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"""Return jax representation of the equation(s) chosen by `model_selection`.
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+
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Each equation (multiple given if there are multiple outputs) is a dictionary
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containing {"callable": func, "parameters": params}. To call `func`, pass
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func(X, params). This function is differentiable using `jax.grad`.
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def pytorch(self):
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"""Return pytorch representation of the equation(s) chosen by `model_selection`.
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+
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Each equation (multiple given if there are multiple outputs) is a PyTorch module
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containing the parameters as trainable attributes. You can use the module like
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845 |
any other PyTorch module: `module(X)`, where `X` is a tensor with the same
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