class_docstr: Test that the boolean flag `use_float_arraytype` correctly changes the datatype of the
  network's inputs and outputs and produces a spec that the `MLModel` class can call `predict`
  with.
class_docstr_tok: ["Test","that","the","boolean","flag","`","use_float_arraytype","`","correctly","changes","the","datatype","of","the","network","'s","inputs","and","outputs","and","produces","a","spec","that","the","`","MLModel","`","class","can","call","`","predict","`","with","."]
code: def test_true_use_float_array(self):
      # Instruct the builder to use the Float32 datatype for inputs and outputs
      self._test_use_float_array_helper(True)
  
imports: import numpy
  import pytest
  import unittest
  import coremltools
  from coremltools import ComputeUnit
  from coremltools.converters.mil.mil.types.type_mapping import np_val_to_py_type
  from coremltools.models import MLModel, datatypes
  from coremltools.models.neural_network import NeuralNetworkBuilder
  from coremltools.models.neural_network.quantization_utils import _convert_array_to_nbit_quantized_bytes, quantize_weights
  from coremltools.models.utils import _is_macos, _macos_version
label_desc: Use image node_id 2 for calling the UseFloatArraytypeTest obj's underlying member method code with example usage: obj.test_true_use_float_array() without return types