ignore params key in schema_decorators (#79)

* ignore params key in schema_decorators

Signed-off-by: Walter Martin <[email protected]>

* change input data fixture name

Signed-off-by: Walter Martin <[email protected]>

* nested parameter type saves the day

Signed-off-by: Walter Martin <[email protected]>

* nested schema for params, handle requests without params

Signed-off-by: Walter Martin <[email protected]>

* linting

Signed-off-by: Walter Martin <[email protected]>

* linting 2.0

Signed-off-by: Walter Martin <[email protected]>

---------

Signed-off-by: Walter Martin <[email protected]>

Author: wamartin-aml

inference_schema/schema_decorators.py

@@ -327,7 +327,7 @@ def _deserialize_input_argument(input_data, param_type, param_name):
         # parameters other than subclass of AbstractParameterType will not be handled
         for k, v in sample_data_type_map.items():
             if k not in input_data.keys():
-                raise Exception('Invalid input. Expected: key "{0}" in "{1}"'.format(k, param_name))
+                continue
             input_data[k] = _deserialize_input_argument(input_data[k], v, k)
     elif sample_data_type in (list, tuple):
         sample_data_type_list = param_type.sample_data_type_list

tests/conftest.py

@@ -69,6 +69,26 @@ def pandas_sample_input_with_url():
     return pd.DataFrame(data=pandas_input_data)
 
 
+@pytest.fixture(scope="session")
+def pandas_sample_input_for_params():
+    import json
+    pandas_input_data = {
+        "columns": [
+            "sentence1"
+        ],
+        "data": [
+            ["this is a string starting with"]
+        ],
+        "index": [0]
+    }
+    return pd.read_json(json.dumps(pandas_input_data), orient='split')
+
+
+@pytest.fixture(scope="session")
+def sample_param_dict():
+    return {"num_beams": 1, "max_length": 2}
+
+
 @pytest.fixture(scope="session")
 def decorated_pandas_func(pandas_sample_input, pandas_sample_output):
     @input_schema('param', PandasParameterType(pandas_sample_input))
@@ -164,6 +184,23 @@ def pandas_url_func(param):
     return pandas_url_func
 
 
+@pytest.fixture(scope="session")
+def decorated_pandas_func_parameters(pandas_sample_input_for_params, sample_param_dict):
+    @input_schema('input_data', StandardPythonParameterType({
+        'split_df': PandasParameterType(pandas_sample_input_for_params, orient='split'),
+        'parameters': StandardPythonParameterType(sample_param_dict)
+    }))
+    def pandas_params_func(input_data):
+        assert type(input_data) is dict
+        assert type(input_data["split_df"]) is pd.DataFrame
+        if 'parameters' in input_data:
+            assert type(input_data["parameters"]) is dict
+        beams = input_data['parameters']['num_beams'] if 'parameters' in input_data else 0
+        return input_data["split_df"]["sentence1"], beams
+
+    return pandas_params_func
+
+
 @pytest.fixture(scope="session")
 def pandas_sample_input_with_categorical():
     pandas_input_data = {'state': ['characters'], 'cat': ['000']}

tests/test_pandas_parameter_type.py

@@ -78,6 +78,42 @@ def test_pandas_categorical_handling(self, decorated_pandas_categorical_func):
         result = decorated_pandas_categorical_func(pandas_input)
         assert categorical == result
 
+    def test_pandas_params_handling(self, decorated_pandas_func_parameters):
+        pandas_input_data = {"input_data": {
+            "split_df": {
+                "columns": [
+                    "sentence1"
+                ],
+                "data": [
+                    ["this is a string starting with"]
+                ],
+                "index": [0]
+            },
+            "parameters": {
+                "num_beams": 2,
+                "max_length": 512
+            }
+        }}
+        result = decorated_pandas_func_parameters(**pandas_input_data)
+        assert result[0][0] == "this is a string starting with"
+        assert result[1] == 2
+
+    def test_pandas_params_handling_without_params(self, decorated_pandas_func_parameters):
+        pandas_input_data = {"input_data": {
+            "split_df": {
+                "columns": [
+                    "sentence1"
+                ],
+                "data": [
+                    ["this is a string starting with"]
+                ],
+                "index": [0]
+            }
+        }}
+        result = decorated_pandas_func_parameters(**pandas_input_data)
+        assert result[0][0] == "this is a string starting with"
+        assert result[1] == 0
+
 
 class TestNestedType(object):