Add recent(-ish) top-level packages to pyproject.toml config

GitOrigin-RevId: f0cb727f9894f7a856ef78724536f453ba3af099

src/gretel_synthetics/actgan/actgan.py

@@ -6,6 +6,19 @@
 import pandas as pd
 import torch
 
+from packaging import version
+from torch import optim
+from torch.nn import (
+    BatchNorm1d,
+    Dropout,
+    functional,
+    LeakyReLU,
+    Linear,
+    Module,
+    ReLU,
+    Sequential,
+)
+
 from gretel_synthetics.actgan.base import BaseSynthesizer, random_state
 from gretel_synthetics.actgan.column_encodings import (
     BinaryColumnEncoding,
@@ -21,18 +34,6 @@
 )
 from gretel_synthetics.actgan.train_data import TrainData
 from gretel_synthetics.typing import DFLike
-from packaging import version
-from torch import optim
-from torch.nn import (
-    BatchNorm1d,
-    Dropout,
-    functional,
-    LeakyReLU,
-    Linear,
-    Module,
-    ReLU,
-    Sequential,
-)
 
 logging.basicConfig()
 logger = logging.getLogger(__name__)

src/gretel_synthetics/actgan/actgan_wrapper.py

@@ -10,21 +10,23 @@
 import numpy as np
 import pandas as pd
 
+from rdt.transformers import BaseTransformer
+from sdv.tabular.base import BaseTabularModel
+
 from gretel_synthetics.actgan.actgan import ACTGANSynthesizer
 from gretel_synthetics.actgan.columnar_df import ColumnarDF
 from gretel_synthetics.actgan.structures import ConditionalVectorType
 from gretel_synthetics.detectors.sdv import SDVTableMetadata
 from gretel_synthetics.utils import rdt_patches, torch_utils
-from rdt.transformers import BaseTransformer
-from sdv.tabular.base import BaseTabularModel
 
 if TYPE_CHECKING:
-    from gretel_synthetics.actgan.structures import EpochInfo
     from numpy.random import RandomState
     from sdv.constraints import Constraint
     from sdv.metadata import Metadata
     from torch import Generator
 
+    from gretel_synthetics.actgan.structures import EpochInfo
+
 EPOCH_CALLBACK = "epoch_callback"
 
 logging.basicConfig()

src/gretel_synthetics/actgan/data_transformer.py

@@ -6,6 +6,8 @@
 import numpy as np
 import pandas as pd
 
+from rdt.transformers import BinaryEncoder, OneHotEncoder
+
 from gretel_synthetics.actgan.column_encodings import (
     BinaryColumnEncoding,
     FloatColumnEncoding,
@@ -22,7 +24,6 @@
     ClusterBasedNormalizer,
 )
 from gretel_synthetics.typing import DFLike
-from rdt.transformers import BinaryEncoder, OneHotEncoder
 
 logging.basicConfig()
 logger = logging.getLogger(__name__)

src/gretel_synthetics/actgan/structures.py

@@ -11,9 +11,10 @@
 if TYPE_CHECKING:
     import numpy as np
 
-    from gretel_synthetics.actgan.column_encodings import ColumnEncoding
     from rdt.transformers.base import BaseTransformer
 
+    from gretel_synthetics.actgan.column_encodings import ColumnEncoding
+
 
 class ColumnType(str, Enum):
     CONTINUOUS = "continuous"

src/gretel_synthetics/actgan/transformers.py

@@ -10,11 +10,12 @@
 import pandas as pd
 
 from category_encoders import BaseNEncoder, BinaryEncoder
-from gretel_synthetics.typing import ListOrSeriesOrDF, SeriesOrDFLike
 from rdt.transformers import BaseTransformer
 from rdt.transformers import ClusterBasedNormalizer as RDTClusterBasedNormalizer
 from rdt.transformers import FloatFormatter
 
+from gretel_synthetics.typing import ListOrSeriesOrDF, SeriesOrDFLike
+
 MODE = "mode"
 VALID_ROUNDING_MODES = (MODE,)
 

src/gretel_synthetics/batch.py

@@ -30,10 +30,14 @@
 from typing import List, Optional, Tuple, Type, Union
 
 import cloudpickle
-import gretel_synthetics.const as const
 import numpy as np
 import pandas as pd
 
+from pandas.errors import EmptyDataError
+from tqdm.auto import tqdm
+
+import gretel_synthetics.const as const
+
 from gretel_synthetics.config import (
     BaseConfig,
     config_from_model_dir,
@@ -44,8 +48,6 @@
 from gretel_synthetics.generate import generate_text, GenText, SeedingGenerator
 from gretel_synthetics.tokenizers import BaseTokenizerTrainer
 from gretel_synthetics.train import train
-from pandas.errors import EmptyDataError
-from tqdm.auto import tqdm
 
 logging.basicConfig()
 logger = logging.getLogger(__name__)

src/gretel_synthetics/config.py

@@ -13,9 +13,10 @@
 from pathlib import Path
 from typing import Callable, Optional, TYPE_CHECKING
 
-import gretel_synthetics.const as const
 import tensorflow as tf
 
+import gretel_synthetics.const as const
+
 from gretel_synthetics.tensorflow.generator import TensorFlowGenerator
 from gretel_synthetics.tensorflow.train import train_rnn
 

src/gretel_synthetics/detectors/sdv.py

@@ -9,10 +9,11 @@
 import numpy as np
 import pandas as pd
 
-from gretel_synthetics.detectors.dates import detect_datetimes
 from rdt.transformers import BaseTransformer
 from rdt.transformers.datetime import UnixTimestampEncoder
 
+from gretel_synthetics.detectors.dates import detect_datetimes
+
 if TYPE_CHECKING:
     from gretel_synthetics.detectors.dates import DateTimeColumn
 

src/gretel_synthetics/generate_utils.py

@@ -11,11 +11,12 @@
 from tempfile import NamedTemporaryFile, TemporaryDirectory
 from typing import Callable, Optional, Union
 
+from smart_open import open as smart_open
+
 from gretel_synthetics.batch import DataFrameBatch, MAX_INVALID
 from gretel_synthetics.config import config_from_model_dir
 from gretel_synthetics.generate import generate_text
 from gretel_synthetics.utils.tar_util import safe_extractall
-from smart_open import open as smart_open
 
 logging.basicConfig()
 logger = logging.getLogger(__name__)

src/gretel_synthetics/tensorflow/train.py

@@ -17,6 +17,8 @@
 import pandas as pd
 import tensorflow as tf
 
+from tqdm import tqdm
+
 from gretel_synthetics.const import (
     METRIC_ACCURACY,
     METRIC_DELTA,
@@ -30,7 +32,6 @@
 from gretel_synthetics.tensorflow.model import build_model, load_model
 from gretel_synthetics.tokenizers import BaseTokenizer
 from gretel_synthetics.train import EpochState
-from tqdm import tqdm
 
 if TYPE_CHECKING:
     from gretel_synthetics.config import TensorFlowConfig

src/gretel_synthetics/timeseries_dgan/dgan.py

@@ -56,6 +56,8 @@
 import pandas as pd
 import torch
 
+from torch.utils.data import DataLoader, Dataset, TensorDataset
+
 from gretel_synthetics.errors import DataError, InternalError, ParameterError
 from gretel_synthetics.timeseries_dgan.config import DfStyle, DGANConfig, OutputType
 from gretel_synthetics.timeseries_dgan.structures import ProgressInfo
@@ -67,7 +69,6 @@
     Output,
     transform,
 )
-from torch.utils.data import DataLoader, Dataset, TensorDataset
 
 logger = logging.getLogger(__name__)
 

src/gretel_synthetics/timeseries_dgan/transformations.py

@@ -8,9 +8,10 @@
 import numpy as np
 
 from category_encoders import BinaryEncoder, OneHotEncoder
-from gretel_synthetics.timeseries_dgan.config import Normalization, OutputType
 from scipy.stats import mode
 
+from gretel_synthetics.timeseries_dgan.config import Normalization, OutputType
+
 
 def _new_uuid() -> str:
     """Return a random uuid prefixed with 'gretel-'."""

src/gretel_synthetics/tokenizers.py

@@ -47,13 +47,15 @@
 )
 
 import cloudpickle
-import gretel_synthetics.const as const
 import numpy as np
 import sentencepiece as spm
 
-from gretel_synthetics.errors import ParameterError
 from smart_open import open as smart_open
 
+import gretel_synthetics.const as const
+
+from gretel_synthetics.errors import ParameterError
+
 if TYPE_CHECKING:
     from gretel_synthetics.config import BaseConfig
 else:

tests-integration/test_generate.py

@@ -31,10 +31,11 @@
 import pandas as pd
 import pytest
 
+from smart_open import open as smart_open
+
 from gretel_synthetics.batch import DataFrameBatch, GenerationProgress
 from gretel_synthetics.generate_utils import DataFileGenerator
 from gretel_synthetics.utils.tar_util import safe_extractall
-from smart_open import open as smart_open
 
 BATCH_MODELS = [
     "https://gretel-public-website.s3-us-west-2.amazonaws.com/tests/synthetics/models/safecast-batch-sp-0-14.tar.gz",

tests-integration/test_train.py

@@ -7,10 +7,11 @@
 
 from pathlib import Path
 
-import gretel_synthetics.const as const
 import pandas as pd
 import pytest
 
+import gretel_synthetics.const as const
+
 from gretel_synthetics.batch import DataFrameBatch, PATH_HOLDER
 from gretel_synthetics.config import TensorFlowConfig
 from gretel_synthetics.errors import DataError

tests/actgan/test_actgan.py

@@ -7,10 +7,11 @@
 import pandas as pd
 import pytest
 
+from pandas.api.types import is_number
+
 from gretel_synthetics.actgan import ACTGAN
 from gretel_synthetics.actgan.data_transformer import BinaryEncodingTransformer
 from gretel_synthetics.actgan.structures import ConditionalVectorType
-from pandas.api.types import is_number
 
 
 @pytest.fixture

tests/detectors/test_sdv.py

@@ -7,12 +7,13 @@
 import pandas as pd
 import pytest
 
-from gretel_synthetics.detectors.dates import DateTimeColumn, DateTimeColumns
-from gretel_synthetics.detectors.sdv import EmptyFieldTransformer, SDVTableMetadata
 from rdt import HyperTransformer
 from rdt.transformers.datetime import UnixTimestampEncoder
 from sdv import Table
 
+from gretel_synthetics.detectors.dates import DateTimeColumn, DateTimeColumns
+from gretel_synthetics.detectors.sdv import EmptyFieldTransformer, SDVTableMetadata
+
 
 def _create_info() -> DateTimeColumns:
     return DateTimeColumns(columns={"footime": DateTimeColumn("footime", "%Y-%m-%d")})

tests/test_tokenizers.py

@@ -1,9 +1,10 @@
 from copy import deepcopy
 from pathlib import Path
 
-import gretel_synthetics.tokenizers as tok
 import pytest
 
+import gretel_synthetics.tokenizers as tok
+
 from gretel_synthetics.config import BaseConfig
 from gretel_synthetics.tokenizers import VocabSizeTooSmall
 

tests/timeseries_dgan/test_dgan.py

@@ -5,6 +5,9 @@
 import pandas as pd
 import pytest
 
+from pandas.api.types import is_numeric_dtype, is_object_dtype
+from pandas.testing import assert_frame_equal
+
 from gretel_synthetics.errors import DataError, ParameterError
 from gretel_synthetics.timeseries_dgan.config import (
     DfStyle,
@@ -27,8 +30,6 @@
     ContinuousOutput,
     OneHotEncodedOutput,
 )
-from pandas.api.types import is_numeric_dtype, is_object_dtype
-from pandas.testing import assert_frame_equal
 
 
 @pytest.fixture

tests/utils/test_rdt_float_formatter_orig.py

@@ -9,10 +9,11 @@
 import pandas as pd
 import pytest
 
-from gretel_synthetics.utils.rdt_patches import patch_float_formatter_rounding_bug
 from rdt.transformers.null import NullTransformer
 from rdt.transformers.numerical import FloatFormatter
 
+from gretel_synthetics.utils.rdt_patches import patch_float_formatter_rounding_bug
+
 with patch_float_formatter_rounding_bug():
     # This is the original suite of tests for the FloatFormatter from rdt.
     # Source code is copied from

tests/utils/test_rdt_patches.py

@@ -3,11 +3,12 @@
 import numpy as np
 import pandas as pd
 
+from rdt.transformers.numerical import FloatFormatter
+
 from gretel_synthetics.utils.rdt_patches import (
     _patched_float_formatter_reverse_transform,
     patch_float_formatter_rounding_bug,
 )
-from rdt.transformers.numerical import FloatFormatter
 
 
 def test_original_rounding_bug_upstream():