docstr: Fit truncated SVD on training data X
  
  Parameters
  ----------
  X : array-like, shape (n_samples, n_features)
      Training data.
  
  y : Ignored
  
  Returns
  -------
  self : object
      Returns the transformer object.
docstr_tok: ["Fit","truncated","SVD","on","training","data","X","Parameters","--","--","--","--","--","X",":","array-like",",","shape","(","n_samples",",","n_features",")","Training","data",".","y",":","Ignored","Returns","--","--","--","-","self",":","object","Returns","the","transformer","object","."]
code: def fit(self, X, y=None):
      """Fit truncated SVD on training data X
  
      Parameters
      ----------
      X : array-like, shape (n_samples, n_features)
          Training data.
  
      y : Ignored
  
      Returns
      -------
      self : object
          Returns the transformer object.
      """
      self.fit_transform(X)
      return self
  
file_path: dask-ml/dask_ml/decomposition/truncated_svd.py
imports: import dask.array
  from dask import compute
  from sklearn.base import BaseEstimator, TransformerMixin
  from .._compat import DASK_2_26_0
  from ..utils import svd_flip
label_desc: Use image node_id 2 for calling the TruncatedSVD obj's underlying member method code with example usage: obj.fit(X, y) and returns: self