docstr: Function to generate labels features y and X that corresponds
  to w, c
docstr_tok: ["Function","to","generate","labels","features","y","and","X","that","corresponds","to","w",",","c"]
code: def generate_logistic_data(
      n_features, n_samples, dtype, use_intercept=False
  ):
      """Function to generate labels features y and X that corresponds
      to w, c
      """
      if n_features <= 5:
          raise ValueError("``n_features`` must be larger than 5")
      np.random.seed(12)
      coeffs0 = weights_sparse_gauss(n_features, nnz=5, dtype=dtype)
      if use_intercept:
          interc0 = 2.0
      else:
          interc0 = None
      simu = SimuLogReg(
          coeffs0,
          interc0,
          n_samples=n_samples,
          verbose=False,
          dtype=dtype,
      )
      X, y = simu.simulate()
      return y, X, coeffs0, interc0
  
file_path: tick/tick/solver/tests/solver.py
imports: import unittest
  import itertools
  import numpy
  from scipy.linalg import norm
  from scipy.sparse import csr_matrix
  from tick.linear_model import ModelLogReg, ModelPoisReg, ModelLinReg, SimuLinReg, SimuLogReg, SimuPoisReg
  from tick.prox import ProxL2Sq, ProxZero, ProxL1
  from tick.solver import SVRG, AGD, SGD, SDCA, GD, BFGS, AdaGrad
  from tick.simulation import weights_sparse_gauss
label_desc: Use image node_id 2 for calling the TestSolver obj's underlying member method code with example usage: obj.generate_logistic_data(n_features, n_samples, dtype, use_intercept) and returns: y,  X,  coeffs0,  interc0