docstr: We keep the input dtype for the image input model to fp32, unless it is GRAYSCALE_FLOAT16
docstr_tok: ["We","keep","the","input","dtype","for","the","image","input","model","to","fp32",",","unless","it","is","GRAYSCALE_FLOAT16"]
code: def test_iO16_default_image_dtype_input(
      self,
      rank4_input_model,
      rank4_grayscale_input_model,
  ):
      """
      We keep the input dtype for the image input model to fp32, unless it is GRAYSCALE_FLOAT16
      """
      # Example 1
      mlmodel = ct.convert(
          rank4_input_model,
          inputs=[ct.ImageType(color_layout=ct.colorlayout.RGB)],
          minimum_deployment_target=ct.target.iOS16,
      )
      assert_spec_input_image_type(
          mlmodel._spec, expected_feature_type=ft.ImageFeatureType.RGB
      )
      assert_prog_input_type(
          mlmodel._mil_program, expected_dtype_str="fp32"
      )
      assert_prog_output_type(
          mlmodel._mil_program, expected_dtype_str="fp16"
      )
      verify_prediction(mlmodel)
  
      # Example 2
      mlmodel = ct.convert(
          rank4_input_model,
          inputs=[ct.ImageType(color_layout=ct.colorlayout.BGR)],
          minimum_deployment_target=ct.target.iOS16,
      )
      assert_spec_input_image_type(
          mlmodel._spec, expected_feature_type=ft.ImageFeatureType.BGR
      )
      assert_prog_input_type(
          mlmodel._mil_program, expected_dtype_str="fp32"
      )
      assert_prog_output_type(
          mlmodel._mil_program, expected_dtype_str="fp16"
      )
      verify_prediction(mlmodel)
  
      # Example 3
      mlmodel = ct.convert(
          rank4_grayscale_input_model,
          inputs=[ct.ImageType(color_layout=ct.colorlayout.GRAYSCALE)],
          minimum_deployment_target=ct.target.iOS16,
      )
      assert_spec_input_image_type(
          mlmodel._spec,
          expected_feature_type=ft.ImageFeatureType.GRAYSCALE,
      )
      assert_prog_input_type(
          mlmodel._mil_program, expected_dtype_str="fp32"
      )
      assert_prog_output_type(
          mlmodel._mil_program, expected_dtype_str="fp16"
      )
      verify_prediction(mlmodel)
  
      # Example 4
      mlmodel = ct.convert(
          rank4_grayscale_input_model,
          inputs=[
              ct.ImageType(
                  color_layout=ct.colorlayout.GRAYSCALE_FLOAT16
              )
          ],
          minimum_deployment_target=ct.target.iOS16,
      )
      assert_spec_input_image_type(
          mlmodel._spec,
          expected_feature_type=ft.ImageFeatureType.GRAYSCALE_FLOAT16,
      )
      assert_prog_input_type(
          mlmodel._mil_program, expected_dtype_str="fp16"
      )
      assert_prog_output_type(
          mlmodel._mil_program, expected_dtype_str="fp16"
      )
      verify_prediction(mlmodel)
  
imports: import itertools
  import os
  import tempfile
  import numpy
  import pytest
  import coremltools
  from coremltools._deps import _HAS_TF_1, _HAS_TF_2, MSG_TF1_NOT_FOUND
  from coremltools.converters.mil.testing_reqs import backends, compute_units
  from coremltools.converters.mil.testing_utils import assert_cast_ops_count, assert_input_dtype, assert_ops_in_mil_program, assert_output_dtype, assert_prog_input_type, assert_prog_output_type, assert_spec_input_image_type, assert_spec_output_image_type, get_op_types_in_program, verify_prediction
  from coremltools.proto import FeatureTypes_pb2
  from coremltools.test.api.test_api_examples import TestInputs
label_desc: Use image node_id 6 for calling the TestiOS16DefaultIODtype obj's underlying member method code with example usage: obj.test_iO16_default_image_dtype_input(rank4_input_model, rank4_grayscale_input_model) without return types