def test_json_serializer_csv_buffer(): csv_file_path = os.path.join(DATA_DIR, "with_integers.csv") with open(csv_file_path) as csv_file: validation_value = csv_file.read() csv_file.seek(0) result = json_serializer(csv_file) assert result == validation_value
def test_json_serializer_csv_buffer(): csv_file_path = os.path.join(DATA_DIR, "with_integers.csv") with open(csv_file_path) as csv_file: validation_value = csv_file.read() csv_file.seek(0) result = json_serializer(csv_file) assert result == validation_value
def __call__(self, data): """ Args: data: """ if isinstance(data, tensor_pb2.TensorProto): return json_format.MessageToJson(data) return json_serializer(data)
def __call__(self, data): """ Args: data: """ from tensorflow.core.framework import tensor_pb2 # pylint: disable=no-name-in-module if isinstance(data, tensor_pb2.TensorProto): return json_format.MessageToJson(data) return json_serializer(data)
def test_json_serializer_python_array(): result = json_serializer([1, 2, 3]) assert result == '[1, 2, 3]'
def test_json_serializer_numpy_invalid_empty(): with pytest.raises(ValueError) as invalid_input: json_serializer(np.array([])) assert "empty array" in str(invalid_input)
def test_json_serializer_numpy_valid_2dimensional(): result = json_serializer(np.array([[1, 2, 3], [3, 4, 5]])) assert result == '[[1, 2, 3], [3, 4, 5]]'
def test_json_serializer_numpy_valid(): result = json_serializer(np.array([1, 2, 3])) assert result == '[1, 2, 3]'
def test_json_serializer_python_dictionary_invalid_empty(): assert json_serializer({}) == "{}"
def test_json_serializer_python_array(): result = json_serializer([1, 2, 3]) assert result == '[1, 2, 3]'
def test_json_serializer_python_dictionary_invalid_empty(): with pytest.raises(ValueError) as error: json_serializer({}) assert "empty dictionary" in str(error)
def test_json_serializer_numpy_valid_2dimensional(): result = json_serializer(np.array([[1, 2, 3], [3, 4, 5]])) assert result == '[[1, 2, 3], [3, 4, 5]]'
ap = argparse.ArgumentParser() ap.add_argument("-i", "--image", required=True, help="path of the image") args = vars(ap.parse_args()) image_path = args['image'] # define function to read and transform image def transform_image(image_path): img = image.img_to_array(image.load_img(image_path, target_size=(250, 250))) / 255 img = np.expand_dims(img, axis=0) return img data = {'instances': transform_image(image_path)} payload = json_serializer(data) # sending post request and saving response as response object response = sage.invoke_endpoint(EndpointName=MODEL_ENDPOINT, ContentType='application/json', Body=payload) r = response.get('Body').read() r = json.loads(r) prob = r['predictions'][0][0] cat = "Chart" if prob > .5 else "Meme" # extracting the response print({"probability": prob, "class": cat})
def test_json_serializer_python_dictionary_invalid_empty(): with pytest.raises(ValueError) as error: json_serializer({}) assert "empty dictionary" in str(error)
def test_json_serializer_python_invalid_empty(): with pytest.raises(ValueError) as error: json_serializer([]) assert "empty array" in str(error)
def test_json_serializer_python_dictionary(): d = {"gender": "m", "age": 22, "city": "Paris"} result = json_serializer(d) assert json.loads(result) == d
def test_json_serializer_python_dictionary(): d = {"gender": "m", "age": 22, "city": "Paris"} result = json_serializer(d) assert json.loads(result) == d
def test_json_serializer_numpy_valid(): result = json_serializer(np.array([1, 2, 3])) assert result == '[1, 2, 3]'
def test_json_serializer_python_invalid_empty(): with pytest.raises(ValueError) as error: json_serializer([]) assert "empty array" in str(error)
def test_json_serializer_python_invalid_empty(): assert json_serializer([]) == "[]"
def test_json_serializer_empty(): assert json_serializer(np.array([])) == "[]"
def test_json_serializer_numpy_invalid_empty(): with pytest.raises(ValueError) as invalid_input: json_serializer(np.array([])) assert "empty array" in str(invalid_input)