def METHOD_NAME():
    # float 64 transformer
    X_64 = Xdigits[:100].astype(np.float64)
    rbm_64 = BernoulliRBM(n_components=16, batch_size=5, n_iter=5, random_state=42)
    Xt_64 = rbm_64.fit_transform(X_64)
    # float 32 transformer
    X_32 = Xdigits[:100].astype(np.float32)
    rbm_32 = BernoulliRBM(n_components=16, batch_size=5, n_iter=5, random_state=42)
    Xt_32 = rbm_32.fit_transform(X_32)
    # results and attributes should be close enough in 32 bit and 64 bit
    assert_allclose(Xt_64, Xt_32, rtol=1e-06, atol=0)
    assert_allclose(
        rbm_64.intercept_hidden_, rbm_32.intercept_hidden_, rtol=1e-06, atol=0
    )
    assert_allclose(
        rbm_64.intercept_visible_, rbm_32.intercept_visible_, rtol=1e-05, atol=0
    )
    assert_allclose(rbm_64.components_, rbm_32.components_, rtol=1e-03, atol=0)
    assert_allclose(rbm_64.h_samples_, rbm_32.h_samples_)