class_docstr: A trivial classifier that classifies everything the same.
class_docstr_tok: ["A","trivial","classifier","that","classifies","everything","the","same","."]
code: def _compute(self, arrays, dates, assets, mask):
      return where(
          mask,
          zeros(shape=mask.shape, dtype=int64_dtype),
          self.missing_value,
      )
  
imports: from numbers import Number
  import operator
  import re
  from numpy import where, isnan, nan, zeros
  import pandas
  from catalyst.lib.labelarray import LabelArray
  from catalyst.lib.quantiles import quantiles
  from catalyst.pipeline.api_utils import restrict_to_dtype
  from catalyst.pipeline.sentinels import NotSpecified
  from catalyst.pipeline.term import ComputableTerm
  from catalyst.utils.compat import unicode
  from catalyst.utils.input_validation import expect_types, expect_dtypes
  from catalyst.utils.memoize import classlazyval
  from catalyst.utils.numpy_utils import categorical_dtype, int64_dtype, vectorized_is_element
  from ..filters import ArrayPredicate, NotNullFilter, NullFilter, NumExprFilter
  from ..mixins import AliasedMixin, CustomTermMixin, DownsampledMixin, LatestMixin, PositiveWindowLengthMixin, RestrictedDTypeMixin, SingleInputMixin, StandardOutputs
label_desc: Use image node_id 1 for calling the Everything obj's underlying member method code with example usage: obj._compute(arrays, dates, assets, mask) and returns: where