code: def test_jumpstart_validate_provided_hyperparameters(
      patched_get_model_specs,
  ):
      def add_options_to_hyperparameter(*largs, **kwargs):
          spec = get_spec_from_base_spec(*largs, **kwargs)
          spec.hyperparameters.extend(
              [
                  JumpStartHyperparameter(
                      {
                          "name": "penalty",
                          "type": "text",
                          "default": "l2",
                          "options": ["l1", "l2", "elasticnet", "none"],
                          "scope": "algorithm",
                      }
                  ),
                  JumpStartHyperparameter(
                      {
                          "name": "test_bool_param",
                          "type": "bool",
                          "default": True,
                          "scope": "algorithm",
                      }
                  ),
                  JumpStartHyperparameter(
                      {
                          "name": "test_exclusive_min_param",
                          "type": "float",
                          "default": 4,
                          "scope": "algorithm",
                          "exclusive_min": 1,
                      }
                  ),
                  JumpStartHyperparameter(
                      {
                          "name": "test_exclusive_max_param",
                          "type": "int",
                          "default": -4,
                          "scope": "algorithm",
                          "exclusive_max": 4,
                      }
                  ),
                  JumpStartHyperparameter(
                      {
                          "name": "test_exclusive_min_param_text",
                          "type": "text",
                          "default": "hello",
                          "scope": "algorithm",
                          "exclusive_min": 1,
                      }
                  ),
                  JumpStartHyperparameter(
                      {
                          "name": "test_exclusive_max_param_text",
                          "type": "text",
                          "default": "hello",
                          "scope": "algorithm",
                          "exclusive_max": 6,
                      }
                  ),
                  JumpStartHyperparameter(
                      {
                          "name": "test_min_param_text",
                          "type": "text",
                          "default": "hello",
                          "scope": "algorithm",
                          "min": 1,
                      }
                  ),
                  JumpStartHyperparameter(
                      {
                          "name": "test_max_param_text",
                          "type": "text",
                          "default": "hello",
                          "scope": "algorithm",
                          "max": 6,
                      }
                  ),
              ]
          )
          return spec
  
      patched_get_model_specs.side_effect = (
          add_options_to_hyperparameter
      )
  
      model_id, model_version = "pytorch-eqa-bert-base-cased", "*"
      region = "us-west-2"
  
      hyperparameter_to_test = {
          "adam-learning-rate": "0.05",
          "batch-size": "4",
          "epochs": "3",
          "penalty": "l2",
          "test_bool_param": False,
          "test_exclusive_min_param": 4,
          "test_exclusive_max_param": -4,
          "test_exclusive_min_param_text": "hello",
          "test_exclusive_max_param_text": "hello",
          "test_min_param_text": "hello",
          "test_max_param_text": "hello",
      }
  
      hyperparameters.validate(
          region=region,
          model_id=model_id,
          model_version=model_version,
          hyperparameters=hyperparameter_to_test,
          sagemaker_session=mock_session,
      )
  
      patched_get_model_specs.assert_called_once_with(
          region=region,
          model_id=model_id,
          version=model_version,
          s3_client=mock_client,
      )
  
      patched_get_model_specs.reset_mock()
  
      del hyperparameter_to_test["adam-learning-rate"]
  
      hyperparameters.validate(
          region=region,
          model_id=model_id,
          model_version=model_version,
          hyperparameters=hyperparameter_to_test,
          sagemaker_session=mock_session,
      )
  
      hyperparameter_to_test["batch-size"] = "0"
      with pytest.raises(JumpStartHyperparametersError) as e:
          hyperparameters.validate(
              region=region,
              model_id=model_id,
              model_version=model_version,
              hyperparameters=hyperparameter_to_test,
          )
      assert str(e.value) == (
          "Hyperparameter 'batch-size' " "can be no less than 1."
      )
  
      hyperparameter_to_test["batch-size"] = "-1"
      with pytest.raises(JumpStartHyperparametersError) as e:
          hyperparameters.validate(
              region=region,
              model_id=model_id,
              model_version=model_version,
              hyperparameters=hyperparameter_to_test,
          )
      assert str(e.value) == (
          "Hyperparameter 'batch-size' can be no " "less than 1."
      )
  
      hyperparameter_to_test["batch-size"] = "-1.5"
      with pytest.raises(JumpStartHyperparametersError) as e:
          hyperparameters.validate(
              region=region,
              model_id=model_id,
              model_version=model_version,
              hyperparameters=hyperparameter_to_test,
          )
      assert str(e.value) == (
          "Hyperparameter 'batch-size' must be "
          "integer type ('-1.5')."
      )
  
      hyperparameter_to_test["batch-size"] = "1.5"
      with pytest.raises(JumpStartHyperparametersError) as e:
          hyperparameters.validate(
              region=region,
              model_id=model_id,
              model_version=model_version,
              hyperparameters=hyperparameter_to_test,
          )
      assert str(e.value) == (
          "Hyperparameter 'batch-size' must be integer " "type ('1.5')."
      )
  
      hyperparameter_to_test["batch-size"] = "99999"
      with pytest.raises(JumpStartHyperparametersError) as e:
          hyperparameters.validate(
              region=region,
              model_id=model_id,
              model_version=model_version,
              hyperparameters=hyperparameter_to_test,
          )
      assert str(e.value) == (
          "Hyperparameter 'batch-size' can be no greater " "than 1024."
      )
  
      hyperparameter_to_test["batch-size"] = 5
      hyperparameters.validate(
          region=region,
          model_id=model_id,
          model_version=model_version,
          hyperparameters=hyperparameter_to_test,
      )
  
      original_bool_val = hyperparameter_to_test["test_bool_param"]
      for val in [
          "False",
          "fAlSe",
          "false",
          "True",
          "TrUe",
          "true",
          True,
          False,
      ]:
          hyperparameter_to_test["test_bool_param"] = val
          hyperparameters.validate(
              region=region,
              model_id=model_id,
              model_version=model_version,
              hyperparameters=hyperparameter_to_test,
          )
      for val in [None, "", 5, "Truesday", "Falsehood"]:
          hyperparameter_to_test["test_bool_param"] = val
          with pytest.raises(JumpStartHyperparametersError) as e:
              hyperparameters.validate(
                  region=region,
                  model_id=model_id,
                  model_version=model_version,
                  hyperparameters=hyperparameter_to_test,
              )
          assert str(e.value) == (
              "Expecting boolean valued hyperparameter, "
              f"but got '{str(val)}'."
          )
  
      hyperparameter_to_test["test_bool_param"] = original_bool_val
  
      original_exclusive_min_val = hyperparameter_to_test[
          "test_exclusive_min_param"
      ]
      for val in [2, 1 + 1e-9]:
          hyperparameter_to_test["test_exclusive_min_param"] = val
          hyperparameters.validate(
              region=region,
              model_id=model_id,
              model_version=model_version,
              hyperparameters=hyperparameter_to_test,
          )
      for val in [1, 1 - 1e-99, -99]:
          hyperparameter_to_test["test_exclusive_min_param"] = val
          with pytest.raises(JumpStartHyperparametersError) as e:
              hyperparameters.validate(
                  region=region,
                  model_id=model_id,
                  model_version=model_version,
                  hyperparameters=hyperparameter_to_test,
              )
          assert str(e.value) == (
              "Hyperparameter 'test_exclusive_min_param' must "
              "be greater than 1."
          )
      hyperparameter_to_test[
          "test_exclusive_min_param"
      ] = original_exclusive_min_val
  
      original_exclusive_max_val = hyperparameter_to_test[
          "test_exclusive_max_param"
      ]
      for val in [-2, 2, 3]:
          hyperparameter_to_test["test_exclusive_max_param"] = val
          hyperparameters.validate(
              region=region,
              model_id=model_id,
              model_version=model_version,
              hyperparameters=hyperparameter_to_test,
          )
      for val in [4, 5, 99]:
          hyperparameter_to_test["test_exclusive_max_param"] = val
          with pytest.raises(JumpStartHyperparametersError) as e:
              hyperparameters.validate(
                  region=region,
                  model_id=model_id,
                  model_version=model_version,
                  hyperparameters=hyperparameter_to_test,
              )
          assert (
              str(e.value)
              == "Hyperparameter 'test_exclusive_max_param' must be less than 4."
          )
  
      hyperparameter_to_test[
          "test_exclusive_max_param"
      ] = original_exclusive_max_val
  
      original_exclusive_max_text_val = hyperparameter_to_test[
          "test_exclusive_max_param_text"
      ]
      for val in ["", "sd", "12345"]:
          hyperparameter_to_test["test_exclusive_max_param_text"] = val
          hyperparameters.validate(
              region=region,
              model_id=model_id,
              model_version=model_version,
              hyperparameters=hyperparameter_to_test,
          )
      for val in ["123456", "123456789"]:
          hyperparameter_to_test["test_exclusive_max_param_text"] = val
          with pytest.raises(JumpStartHyperparametersError) as e:
              hyperparameters.validate(
                  region=region,
                  model_id=model_id,
                  model_version=model_version,
                  hyperparameters=hyperparameter_to_test,
              )
          assert (
              str(e.value)
              == "Hyperparameter 'test_exclusive_max_param_text' must have length less than 6."
          )
      hyperparameter_to_test[
          "test_exclusive_max_param_text"
      ] = original_exclusive_max_text_val
  
      original_max_text_val = hyperparameter_to_test[
          "test_max_param_text"
      ]
      for val in ["", "sd", "12345", "123456"]:
          hyperparameter_to_test["test_max_param_text"] = val
          hyperparameters.validate(
              region=region,
              model_id=model_id,
              model_version=model_version,
              hyperparameters=hyperparameter_to_test,
          )
      for val in ["1234567", "123456789"]:
          hyperparameter_to_test["test_max_param_text"] = val
          with pytest.raises(JumpStartHyperparametersError) as e:
              hyperparameters.validate(
                  region=region,
                  model_id=model_id,
                  model_version=model_version,
                  hyperparameters=hyperparameter_to_test,
              )
          assert (
              str(e.value)
              == "Hyperparameter 'test_max_param_text' must have length no greater than 6."
          )
      hyperparameter_to_test[
          "test_max_param_text"
      ] = original_max_text_val
  
      original_exclusive_min_text_val = hyperparameter_to_test[
          "test_exclusive_min_param_text"
      ]
      for val in ["12", "sdfs", "12345dsfs"]:
          hyperparameter_to_test["test_exclusive_min_param_text"] = val
          hyperparameters.validate(
              region=region,
              model_id=model_id,
              model_version=model_version,
              hyperparameters=hyperparameter_to_test,
          )
      for val in ["1", "d", ""]:
          hyperparameter_to_test["test_exclusive_min_param_text"] = val
          with pytest.raises(JumpStartHyperparametersError) as e:
              hyperparameters.validate(
                  region=region,
                  model_id=model_id,
                  model_version=model_version,
                  hyperparameters=hyperparameter_to_test,
              )
          assert str(e.value) == (
              "Hyperparameter 'test_exclusive_min_param_text' must have length greater "
              "than 1."
          )
      hyperparameter_to_test[
          "test_exclusive_min_param_text"
      ] = original_exclusive_min_text_val
  
      original_min_text_val = hyperparameter_to_test[
          "test_min_param_text"
      ]
      for val in ["1", "s", "12", "sdfs", "12345dsfs"]:
          hyperparameter_to_test["test_min_param_text"] = val
          hyperparameters.validate(
              region=region,
              model_id=model_id,
              model_version=model_version,
              hyperparameters=hyperparameter_to_test,
          )
      for val in [""]:
          hyperparameter_to_test["test_min_param_text"] = val
          with pytest.raises(JumpStartHyperparametersError) as e:
              hyperparameters.validate(
                  region=region,
                  model_id=model_id,
                  model_version=model_version,
                  hyperparameters=hyperparameter_to_test,
              )
          assert str(e.value) == (
              "Hyperparameter 'test_min_param_text' "
              "must have length no less than 1."
          )
      hyperparameter_to_test[
          "test_min_param_text"
      ] = original_min_text_val
  
      del hyperparameter_to_test["batch-size"]
      hyperparameter_to_test["penalty"] = "blah"
      with pytest.raises(JumpStartHyperparametersError) as e:
          hyperparameters.validate(
              region=region,
              model_id=model_id,
              model_version=model_version,
              hyperparameters=hyperparameter_to_test,
          )
      assert str(e.value) == (
          "Hyperparameter 'penalty' must have one of the following values: l1, l2, elasticnet,"
          " none."
      )
  
      hyperparameter_to_test["penalty"] = "elasticnet"
      hyperparameters.validate(
          region=region,
          model_id=model_id,
          model_version=model_version,
          hyperparameters=hyperparameter_to_test,
      )
  
file_path: sagemaker-python-sdk/tests/unit/sagemaker/hyperparameters/jumpstart/test_validate.py
imports: from __future__ import absolute_import
  from mock.mock import patch, Mock
  import pytest
  import boto3
  from sagemaker import hyperparameters
  from sagemaker.jumpstart.enums import HyperparameterValidationMode
  from sagemaker.jumpstart.exceptions import JumpStartHyperparametersError
  from sagemaker.jumpstart.types import JumpStartHyperparameter
  from tests.unit.sagemaker.jumpstart.utils import get_spec_from_base_spec
label_desc: Use image node_id 1 for calling a global function with example usage: test_jumpstart_validate_provided_hyperparameters(patched_get_model_specs) and returns: spec