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| from __future__ import absolute_import |
|
|
| import io |
| import json |
| import os |
|
|
| import numpy as np |
| import pytest |
| import scipy.sparse |
|
|
| from sagemaker.serializers import ( |
| CSVSerializer, |
| NumpySerializer, |
| JSONSerializer, |
| IdentitySerializer, |
| SparseMatrixSerializer, |
| JSONLinesSerializer, |
| LibSVMSerializer, |
| DataSerializer, |
| ) |
| from tests.unit import DATA_DIR |
|
|
|
|
| @pytest.fixture |
| def csv_serializer(): |
| return CSVSerializer() |
|
|
|
|
| def test_csv_serializer_str(csv_serializer): |
| original = "1,2,3" |
| result = csv_serializer.serialize("1,2,3") |
|
|
| assert result == original |
|
|
|
|
| def test_csv_serializer_python_array(csv_serializer): |
| result = csv_serializer.serialize([1, 2, 3]) |
|
|
| assert result == "1,2,3" |
|
|
|
|
| def test_csv_serializer_numpy_valid(csv_serializer): |
| result = csv_serializer.serialize(np.array([1, 2, 3])) |
|
|
| assert result == "1,2,3" |
|
|
|
|
| def test_csv_serializer_numpy_valid_2dimensional(csv_serializer): |
| result = csv_serializer.serialize(np.array([[1, 2, 3], [3, 4, 5]])) |
|
|
| assert result == "1,2,3\n3,4,5" |
|
|
|
|
| def test_csv_serializer_list_of_str(csv_serializer): |
| result = csv_serializer.serialize(["1,2,3", "4,5,6"]) |
|
|
| assert result == "1,2,3\n4,5,6" |
|
|
|
|
| def test_csv_serializer_list_of_list(csv_serializer): |
| result = csv_serializer.serialize([[1, 2, 3], [3, 4, 5]]) |
|
|
| assert result == "1,2,3\n3,4,5" |
|
|
|
|
| def test_csv_serializer_list_of_empty(csv_serializer): |
| with pytest.raises(ValueError) as invalid_input: |
| csv_serializer.serialize(np.array([[], []])) |
|
|
| assert "empty array" in str(invalid_input) |
|
|
|
|
| def test_csv_serializer_numpy_invalid_empty(csv_serializer): |
| with pytest.raises(ValueError) as invalid_input: |
| csv_serializer.serialize(np.array([])) |
|
|
| assert "empty array" in str(invalid_input) |
|
|
|
|
| def test_csv_serializer_python_invalid_empty(csv_serializer): |
| with pytest.raises(ValueError) as error: |
| csv_serializer.serialize([]) |
| assert "empty array" in str(error) |
|
|
|
|
| def test_csv_serializer_csv_reader(csv_serializer): |
| csv_file_path = os.path.join(DATA_DIR, "with_integers.csv") |
| with open(csv_file_path) as csv_file: |
| validation_data = csv_file.read() |
| csv_file.seek(0) |
| result = csv_serializer.serialize(csv_file) |
| assert result == validation_data |
|
|
|
|
| @pytest.fixture |
| def numpy_serializer(): |
| return NumpySerializer() |
|
|
|
|
| def test_numpy_serializer_python_array(numpy_serializer): |
| array = [1, 2, 3] |
| result = numpy_serializer.serialize(array) |
|
|
| assert np.array_equal(array, np.load(io.BytesIO(result))) |
|
|
|
|
| def test_numpy_serializer_python_array_with_dtype(): |
| numpy_serializer = NumpySerializer(dtype="float16") |
| array = [1, 2, 3] |
|
|
| result = numpy_serializer.serialize(array) |
|
|
| deserialized = np.load(io.BytesIO(result)) |
| assert np.array_equal(array, deserialized) |
| assert deserialized.dtype == "float16" |
|
|
|
|
| def test_numpy_serializer_numpy_valid_2_dimensional(numpy_serializer): |
| array = np.array([[1, 2, 3], [3, 4, 5]]) |
| result = numpy_serializer.serialize(array) |
|
|
| assert np.array_equal(array, np.load(io.BytesIO(result))) |
|
|
|
|
| def test_numpy_serializer_numpy_valid_multidimensional(numpy_serializer): |
| array = np.ones((10, 10, 10, 10)) |
| result = numpy_serializer.serialize(array) |
|
|
| assert np.array_equal(array, np.load(io.BytesIO(result))) |
|
|
|
|
| def test_numpy_serializer_numpy_valid_list_of_strings(numpy_serializer): |
| array = np.array(["one", "two", "three"]) |
| result = numpy_serializer.serialize(array) |
|
|
| assert np.array_equal(array, np.load(io.BytesIO(result))) |
|
|
|
|
| def test_numpy_serializer_from_buffer_or_file(numpy_serializer): |
| array = np.ones((2, 3)) |
| stream = io.BytesIO() |
| np.save(stream, array) |
| stream.seek(0) |
|
|
| result = numpy_serializer.serialize(stream) |
|
|
| assert np.array_equal(array, np.load(io.BytesIO(result))) |
|
|
|
|
| def test_numpy_serializer_object(numpy_serializer): |
| object = {1, 2, 3} |
|
|
| result = numpy_serializer.serialize(object) |
|
|
| assert np.array_equal(np.array(object), np.load(io.BytesIO(result), allow_pickle=True)) |
|
|
|
|
| def test_numpy_serializer_list_of_empty(numpy_serializer): |
| with pytest.raises(ValueError) as invalid_input: |
| numpy_serializer.serialize(np.array([[], []])) |
|
|
| assert "empty array" in str(invalid_input) |
|
|
|
|
| def test_numpy_serializer_numpy_invalid_empty(numpy_serializer): |
| with pytest.raises(ValueError) as invalid_input: |
| numpy_serializer.serialize(np.array([])) |
|
|
| assert "empty array" in str(invalid_input) |
|
|
|
|
| def test_numpy_serializer_python_invalid_empty(numpy_serializer): |
| with pytest.raises(ValueError) as error: |
| numpy_serializer.serialize([]) |
| assert "empty array" in str(error) |
|
|
|
|
| @pytest.fixture |
| def json_serializer(): |
| return JSONSerializer() |
|
|
|
|
| def test_json_serializer_numpy_valid(json_serializer): |
| result = json_serializer.serialize(np.array([1, 2, 3])) |
|
|
| assert result == "[1, 2, 3]" |
|
|
|
|
| def test_json_serializer_numpy_valid_2dimensional(json_serializer): |
| result = json_serializer.serialize(np.array([[1, 2, 3], [3, 4, 5]])) |
|
|
| assert result == "[[1, 2, 3], [3, 4, 5]]" |
|
|
|
|
| def test_json_serializer_empty(json_serializer): |
| assert json_serializer.serialize(np.array([])) == "[]" |
|
|
|
|
| def test_json_serializer_python_array(json_serializer): |
| result = json_serializer.serialize([1, 2, 3]) |
|
|
| assert result == "[1, 2, 3]" |
|
|
|
|
| def test_json_serializer_python_dictionary(json_serializer): |
| d = {"gender": "m", "age": 22, "city": "Paris"} |
|
|
| result = json_serializer.serialize(d) |
|
|
| assert json.loads(result) == d |
|
|
|
|
| def test_json_serializer_python_invalid_empty(json_serializer): |
| assert json_serializer.serialize([]) == "[]" |
|
|
|
|
| def test_json_serializer_python_dictionary_invalid_empty(json_serializer): |
| assert json_serializer.serialize({}) == "{}" |
|
|
|
|
| def test_json_serializer_csv_buffer(json_serializer): |
| 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.serialize(csv_file) |
| assert result == validation_value |
|
|
|
|
| def test_identity_serializer(): |
| identity_serializer = IdentitySerializer() |
| assert identity_serializer.serialize(b"{}") == b"{}" |
|
|
|
|
| def test_identity_serializer_with_custom_content_type(): |
| identity_serializer = IdentitySerializer(content_type="text/csv") |
| assert identity_serializer.serialize(b"a,b\n1,2") == b"a,b\n1,2" |
| assert identity_serializer.CONTENT_TYPE == "text/csv" |
|
|
|
|
| @pytest.fixture |
| def json_lines_serializer(): |
| return JSONLinesSerializer() |
|
|
|
|
| @pytest.mark.parametrize( |
| "input, expected", |
| [ |
| ('["Name", "Score"]\n["Gilbert", 24]', '["Name", "Score"]\n["Gilbert", 24]'), |
| ( |
| '{"Name": "Gilbert", "Score": 24}\n{"Name": "Alexa", "Score": 29}', |
| '{"Name": "Gilbert", "Score": 24}\n{"Name": "Alexa", "Score": 29}', |
| ), |
| ], |
| ) |
| def test_json_lines_serializer_string(json_lines_serializer, input, expected): |
| actual = json_lines_serializer.serialize(input) |
| assert actual == expected |
|
|
|
|
| @pytest.mark.parametrize( |
| "input, expected", |
| [ |
| ([["Name", "Score"], ["Gilbert", 24]], '["Name", "Score"]\n["Gilbert", 24]'), |
| ( |
| [{"Name": "Gilbert", "Score": 24}, {"Name": "Alexa", "Score": 29}], |
| '{"Name": "Gilbert", "Score": 24}\n{"Name": "Alexa", "Score": 29}', |
| ), |
| ], |
| ) |
| def test_json_lines_serializer_list(json_lines_serializer, input, expected): |
| actual = json_lines_serializer.serialize(input) |
| assert actual == expected |
|
|
|
|
| @pytest.mark.parametrize( |
| "source, expected", |
| [ |
| ('["Name", "Score"]\n["Gilbert", 24]', '["Name", "Score"]\n["Gilbert", 24]'), |
| ( |
| '{"Name": "Gilbert", "Score": 24}\n{"Name": "Alexa", "Score": 29}', |
| '{"Name": "Gilbert", "Score": 24}\n{"Name": "Alexa", "Score": 29}', |
| ), |
| ], |
| ) |
| def test_json_lines_serializer_file_like(json_lines_serializer, source, expected): |
| input = io.StringIO(source) |
| actual = json_lines_serializer.serialize(input) |
| assert actual == expected |
|
|
|
|
| @pytest.fixture |
| def sparse_matrix_serializer(): |
| return SparseMatrixSerializer() |
|
|
|
|
| def test_sparse_matrix_serializer(sparse_matrix_serializer): |
| data = scipy.sparse.csc_matrix(np.array([[0, 0, 3], [4, 0, 0]])) |
| stream = io.BytesIO(sparse_matrix_serializer.serialize(data)) |
| result = scipy.sparse.load_npz(stream).toarray() |
| expected = data.toarray() |
| assert np.array_equal(result, expected) |
|
|
|
|
| @pytest.fixture |
| def libsvm_serializer(): |
| return LibSVMSerializer() |
|
|
|
|
| def test_libsvm_serializer_str(libsvm_serializer): |
| original = "0 0:1 5:1" |
| result = libsvm_serializer.serialize("0 0:1 5:1") |
| assert result == original |
|
|
|
|
| def test_libsvm_serializer_file_like(libsvm_serializer): |
| libsvm_file_path = os.path.join(DATA_DIR, "xgboost_abalone", "abalone") |
| with open(libsvm_file_path) as libsvm_file: |
| validation_data = libsvm_file.read() |
| libsvm_file.seek(0) |
| result = libsvm_serializer.serialize(libsvm_file) |
| assert result == validation_data |
|
|
|
|
| @pytest.fixture |
| def data_serializer(): |
| return DataSerializer() |
|
|
|
|
| def test_data_serializer_raw(data_serializer): |
| input_image_file_path = os.path.join(DATA_DIR, "", "cuteCat.jpg") |
| with open(input_image_file_path, "rb") as image: |
| input_image = image.read() |
| input_image_data = data_serializer.serialize(input_image) |
| validation_image_file_path = os.path.join(DATA_DIR, "", "cuteCat.raw") |
| validation_image_data = open(validation_image_file_path, "rb").read() |
| assert input_image_data == validation_image_data |
|
|
|
|
| def test_data_serializer_file_like(data_serializer): |
| input_image_file_path = os.path.join(DATA_DIR, "", "cuteCat.jpg") |
| validation_image_file_path = os.path.join(DATA_DIR, "", "cuteCat.raw") |
| input_image_data = data_serializer.serialize(input_image_file_path) |
| validation_image_data = open(validation_image_file_path, "rb").read() |
| assert input_image_data == validation_image_data |
|
|