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)