def test_decode(content_type):
decoder = Mock()
with patch.dict(_encoders._decoders_map, {content_type: decoder},
clear=True):
_encoders.decode(42, content_type)
decoder.assert_called_once_with(42)
def test_request(content_type_header):
headers = {
content_type_header: _content_types.JSON,
"Accept": _content_types.CSV
}
request = _worker.Request(test.environ(data="42", headers=headers))
assert request.content_type == _content_types.JSON
assert request.accept == _content_types.CSV
assert request.content == "42"
headers = {
content_type_header: _content_types.NPY,
"Accept": _content_types.CSV
}
request = _worker.Request(
test.environ(data=_encoders.encode([6, 9.3], _content_types.NPY),
headers=headers))
assert request.content_type == _content_types.NPY
assert request.accept == _content_types.CSV
result = _encoders.decode(request.data, _content_types.NPY)
np.testing.assert_array_equal(result, np.array([6, 9.3]))
def test_request():
request = test.request(data='42')
assert request.content_type == _content_types.JSON
assert request.accept == _content_types.JSON
assert request.content == '42'
request = test.request(data=_encoders.encode([6, 9.3], _content_types.NPY),
content_type=_content_types.NPY,
accept=_content_types.CSV)
assert request.content_type == _content_types.NPY
assert request.accept == _content_types.CSV
result = _encoders.decode(request.data, _content_types.NPY)
np.testing.assert_array_equal(result, np.array([6, 9.3]))
def default_input_fn(input_data, content_type):
"""Takes request data and de-serializes the data into an object for prediction.
When an InvokeEndpoint operation is made against an Endpoint running SageMaker model server,
the model server receives two pieces of information:
- The request Content-Type, for example "application/json"
- The request data, which is at most 5 MB (5 * 1024 * 1024 bytes) in size.
The input_fn is responsible to take the request data and pre-process it before prediction.
Args:
input_data (obj): the request data.
content_type (str): the request Content-Type.
Returns:
(obj): data ready for prediction.
"""
return _encoders.decode(input_data, content_type)
def test_decode_error():
with pytest.raises(_errors.UnsupportedFormatError):
_encoders.decode(42, _content_types.OCTET_STREAM)