code: def parse_layer(layer_data):
      # Get the first row, excluding the first column
      x = layer_data[0, 1:]
      # Get the first column, excluding the first row
      # .ascontiguousarray is support important here!!!!
      b = np.ascontiguousarray(layer_data[1:, 0], dtype="float64")
      # Slice out the row and the column used for the X and the bias
      W = layer_data[1:, 1:]
      assert x.ndim == 1
      assert b.ndim == 1
      assert b.shape[0] == W.shape[0]
      assert x.shape[0] == W.shape[1]
      assume(not np.isnan(W.sum()))
      assume(not np.isnan(x.sum()))
      assume(not np.isnan(b.sum()))
      assume(not any(np.isinf(val) for val in W.flatten()))
      assume(not any(np.isinf(val) for val in x))
      assume(not any(np.isinf(val) for val in b))
      return x, b, W
  
file_path: cython-blis/tests/blis_tests_common.py
imports: from __future__ import print_function
  import numpy
  from numpy.testing import assert_allclose
  from hypothesis import given, assume
  from hypothesis.strategies import tuples, lists, integers, floats
  from hypothesis.extra.numpy import arrays
label_desc: Use image node_id 8 for calling a global function with example usage: parse_layer(layer_data) and returns: x,  b,  W