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alibi-detect
alibi-detect-master/alibi_detect/cd/pytorch/tests/test_classifier_pt.py
from itertools import product import numpy as np import pytest import torch import torch.nn as nn from typing import Union from alibi_detect.cd.pytorch.classifier import ClassifierDriftTorch n = 100 class MyModel(nn.Module): def __init__(self, n_features: int, softmax: bool = False): super().__init__() ...
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alibi-detect
alibi-detect-master/alibi_detect/cd/pytorch/tests/conftest.py
import pytest @pytest.fixture def seed(pytestconfig): """ Returns the random seed set by pytest-randomly. """ return pytestconfig.getoption("randomly_seed")
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alibi-detect
alibi-detect-master/alibi_detect/cd/pytorch/tests/test_spot_the_diff_pt.py
from itertools import product import numpy as np import pytest import torch import torch.nn as nn from typing import Union from alibi_detect.cd.pytorch.spot_the_diff import SpotTheDiffDriftTorch n = 100 class MyKernel(nn.Module): def __init__(self, n_features: int): super().__init__() self.dense ...
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alibi-detect
alibi-detect-master/alibi_detect/cd/pytorch/tests/test_lsdd_online_pt.py
from functools import partial from itertools import product import numpy as np import pytest import torch import torch.nn as nn from typing import Callable, List from alibi_detect.cd.pytorch.lsdd_online import LSDDDriftOnlineTorch from alibi_detect.cd.pytorch.preprocess import HiddenOutput, preprocess_drift from alibi_...
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alibi-detect
alibi-detect-master/alibi_detect/cd/pytorch/tests/test_preprocess_pt.py
from itertools import product import numpy as np import pytest import torch import torch.nn as nn from alibi_detect.cd.pytorch import HiddenOutput n, dim1, dim2, n_classes, latent_dim, n_hidden = 100, 2, 3, 5, 2, 7 n_features = dim1 * dim2 shape = (n, dim1, dim2) X = np.random.rand(n * n_features).reshape(shape).astyp...
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alibi-detect
alibi-detect-master/alibi_detect/cd/pytorch/tests/test_contextmmd_pt.py
from functools import partial from itertools import product import numpy as np import pytest import torch import torch.nn as nn from typing import Callable, List from alibi_detect.cd.pytorch.context_aware import ContextMMDDriftTorch from alibi_detect.cd.pytorch.preprocess import HiddenOutput, preprocess_drift class M...
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alibi-detect
alibi-detect-master/alibi_detect/cd/pytorch/tests/test_lsdd_pt.py
from functools import partial from itertools import product import numpy as np import pytest import torch import torch.nn as nn from typing import Callable, List from alibi_detect.cd.pytorch.lsdd import LSDDDriftTorch from alibi_detect.cd.pytorch.preprocess import HiddenOutput, preprocess_drift n, n_hidden, n_classes ...
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alibi-detect
alibi-detect-master/alibi_detect/cd/pytorch/tests/test_mmd_online_pt.py
from functools import partial from itertools import product import numpy as np import pytest import torch import torch.nn as nn from typing import Callable, List from alibi_detect.cd.pytorch.mmd_online import MMDDriftOnlineTorch from alibi_detect.cd.pytorch.preprocess import HiddenOutput, preprocess_drift from alibi_de...
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alibi-detect
alibi-detect-master/alibi_detect/cd/tensorflow/learned_kernel.py
from functools import partial import numpy as np import tensorflow as tf from typing import Callable, Dict, Optional, Tuple, Union from alibi_detect.cd.base import BaseLearnedKernelDrift from alibi_detect.utils.tensorflow.data import TFDataset from alibi_detect.utils.tensorflow.misc import clone_model from alibi_detect...
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alibi-detect
alibi-detect-master/alibi_detect/cd/tensorflow/mmd.py
import logging import numpy as np import tensorflow as tf from typing import Callable, Dict, Optional, Tuple, Union from alibi_detect.cd.base import BaseMMDDrift from alibi_detect.utils.tensorflow.distance import mmd2_from_kernel_matrix from alibi_detect.utils.tensorflow.kernels import GaussianRBF from alibi_detect.uti...
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alibi-detect
alibi-detect-master/alibi_detect/cd/tensorflow/utils.py
from typing import Callable from functools import partial def activate_train_mode_for_all_layers(model: Callable) -> Callable: model.trainable = False # type: ignore model = partial(model, training=True) # Note this affects batchnorm etc also return model
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alibi-detect-master/alibi_detect/cd/tensorflow/classifier.py
from functools import partial import numpy as np import tensorflow as tf from tensorflow.keras.losses import BinaryCrossentropy from scipy.special import softmax from typing import Callable, Dict, Optional, Tuple, Union from alibi_detect.cd.base import BaseClassifierDrift from alibi_detect.models.tensorflow.trainer imp...
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alibi-detect
alibi-detect-master/alibi_detect/cd/tensorflow/lsdd_online.py
from tqdm import tqdm import numpy as np import tensorflow as tf from typing import Any, Callable, Optional, Union from alibi_detect.cd.base_online import BaseMultiDriftOnline from alibi_detect.utils.tensorflow import GaussianRBF, quantile, permed_lsdds from alibi_detect.utils.frameworks import Framework class LSDDDr...
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alibi-detect
alibi-detect-master/alibi_detect/cd/tensorflow/spot_the_diff.py
import logging import numpy as np import tensorflow as tf from typing import Callable, Dict, Optional, Union from alibi_detect.cd.tensorflow.classifier import ClassifierDriftTF from alibi_detect.utils.tensorflow.data import TFDataset from alibi_detect.utils.tensorflow import GaussianRBF from alibi_detect.utils.tensorfl...
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alibi-detect
alibi-detect-master/alibi_detect/cd/tensorflow/mmd_online.py
from tqdm import tqdm import numpy as np import tensorflow as tf from typing import Any, Callable, Optional, Union from alibi_detect.cd.base_online import BaseMultiDriftOnline from alibi_detect.utils.tensorflow.kernels import GaussianRBF from alibi_detect.utils.tensorflow import zero_diag, quantile, subset_matrix from ...
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alibi-detect
alibi-detect-master/alibi_detect/cd/tensorflow/context_aware.py
import logging import numpy as np import tensorflow as tf import tensorflow_probability as tfp from typing import Callable, Dict, Optional, Tuple, Union, List from alibi_detect.cd.base import BaseContextMMDDrift from alibi_detect.utils.tensorflow.kernels import GaussianRBF from alibi_detect.utils.warnings import deprec...
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alibi-detect
alibi-detect-master/alibi_detect/cd/tensorflow/__init__.py
from alibi_detect.utils.missing_optional_dependency import import_optional HiddenOutput, UAE, preprocess_drift = import_optional( 'alibi_detect.cd.tensorflow.preprocess', names=['HiddenOutput', 'UAE', 'preprocess_drift'] ) __all__ = [ "HiddenOutput", "UAE", "preprocess_drift" ]
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alibi-detect-master/alibi_detect/cd/tensorflow/lsdd.py
import numpy as np import tensorflow as tf from typing import Callable, Dict, Optional, Tuple, Union from alibi_detect.cd.base import BaseLSDDDrift from alibi_detect.utils.tensorflow.kernels import GaussianRBF from alibi_detect.utils.tensorflow.distance import permed_lsdds from alibi_detect.utils.warnings import deprec...
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alibi-detect
alibi-detect-master/alibi_detect/cd/tensorflow/preprocess.py
from typing import Callable, Dict, Optional, Type, Union import numpy as np import tensorflow as tf from alibi_detect.utils.tensorflow.prediction import ( predict_batch, predict_batch_transformer) from tensorflow.keras.layers import Dense, Flatten, Input, InputLayer from tensorflow.keras.models import Model clas...
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alibi-detect
alibi-detect-master/alibi_detect/cd/tensorflow/tests/test_contextmmd_tf.py
from functools import partial from itertools import product import numpy as np import pytest import tensorflow as tf from tensorflow.keras.layers import Dense, Input, InputLayer from typing import Callable, List from alibi_detect.cd.tensorflow.context_aware import ContextMMDDriftTF from alibi_detect.cd.tensorflow.prepr...
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alibi-detect
alibi-detect-master/alibi_detect/cd/tensorflow/tests/test_classifier_tf.py
from itertools import product import numpy as np import pytest import tensorflow as tf from tensorflow.keras.layers import Dense, Input from typing import Union from alibi_detect.cd.tensorflow.classifier import ClassifierDriftTF n = 100 def mymodel(shape, softmax: bool = True): x_in = Input(shape=shape) x = ...
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alibi-detect
alibi-detect-master/alibi_detect/cd/tensorflow/tests/conftest.py
import pytest @pytest.fixture def seed(pytestconfig): """ Returns the random seed set by pytest-randomly. """ return pytestconfig.getoption("randomly_seed")
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alibi-detect-master/alibi_detect/cd/tensorflow/tests/test_lsdd_tf.py
from functools import partial from itertools import product import numpy as np import pytest import tensorflow as tf from tensorflow.keras.layers import Dense, Input, InputLayer from typing import Callable, List from alibi_detect.cd.tensorflow.lsdd import LSDDDriftTF from alibi_detect.cd.tensorflow.preprocess import Hi...
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alibi-detect
alibi-detect-master/alibi_detect/cd/tensorflow/tests/test_lsdd_online_tf.py
from functools import partial from itertools import product import numpy as np import pytest import tensorflow as tf from tensorflow.keras.layers import Dense, Input, InputLayer from typing import Callable, List from alibi_detect.cd.tensorflow.lsdd_online import LSDDDriftOnlineTF from alibi_detect.cd.tensorflow.preproc...
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alibi-detect
alibi-detect-master/alibi_detect/cd/tensorflow/tests/test_spot_the_diff_tf.py
from itertools import product import numpy as np import pytest import tensorflow as tf from tensorflow.keras.layers import Dense from typing import Union from alibi_detect.cd.tensorflow.spot_the_diff import SpotTheDiffDriftTF n = 100 class MyKernel(tf.keras.Model): # TODO: Support then test models using keras funct...
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alibi-detect
alibi-detect-master/alibi_detect/cd/tensorflow/tests/test_mmd_tf.py
from functools import partial from itertools import product import numpy as np import pytest import tensorflow as tf from tensorflow.keras.layers import Dense, Input, InputLayer from typing import Callable, List from alibi_detect.cd.tensorflow.mmd import MMDDriftTF from alibi_detect.cd.tensorflow.preprocess import Hidd...
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alibi-detect
alibi-detect-master/alibi_detect/cd/tensorflow/tests/test_mmd_online_tf.py
from functools import partial from itertools import product import numpy as np import pytest import tensorflow as tf from tensorflow.keras.layers import Dense, Input, InputLayer from typing import Callable, List from alibi_detect.cd.tensorflow.mmd_online import MMDDriftOnlineTF from alibi_detect.cd.tensorflow.preproces...
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alibi-detect
alibi-detect-master/alibi_detect/cd/tensorflow/tests/test_preprocess_tf.py
import numpy as np import pytest import tensorflow as tf from tensorflow.keras.layers import Dense, Input, InputLayer from alibi_detect.cd.tensorflow import UAE, HiddenOutput n, n_features, n_classes, latent_dim = 100, 10, 5, 2 X_uae = np.random.rand(n * n_features).reshape(n, n_features).astype('float32') encoder_ne...
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alibi-detect
alibi-detect-master/alibi_detect/cd/tensorflow/tests/test_learned_kernel_tf.py
from itertools import product import numpy as np import pytest import tensorflow as tf from tensorflow.keras.layers import Dense from typing import Union from alibi_detect.cd.tensorflow.learned_kernel import LearnedKernelDriftTF n = 100 class MyKernel(tf.keras.Model): # TODO: Support then test models using keras fu...
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alibi-detect
alibi-detect-master/alibi_detect/utils/missing_optional_dependency.py
"""Functionality for optional importing This module provides a way to import optional dependencies. In the case that the user imports some functionality from alibi-detect that is not usable due to missing optional dependencies this code is used to allow the import but replace it with an object that throws an error on u...
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alibi-detect
alibi-detect-master/alibi_detect/utils/url.py
from typing import Union, List from urllib.parse import urljoin, quote_plus def _join_url(base: str, parts: Union[str, List[str]]) -> str: """ Constructs a full (“absolute”) URL by combining a “base URL” (base) with additional relative URL parts. The behaviour is similar to os.path.join() on linux, but al...
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alibi-detect
alibi-detect-master/alibi_detect/utils/_types.py
""" Defining types compatible with different Python versions and defining custom types. """ import sys from sklearn.base import BaseEstimator # import here (instead of later) since sklearn currently a core dep from alibi_detect.utils.frameworks import has_tensorflow, has_pytorch from typing import Union, Type # Liter...
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alibi-detect-master/alibi_detect/utils/warnings.py
""" This module defines custom warnings and exceptions used across the Alibi Detect library. """ import functools import warnings from typing import Dict, Any, Callable def deprecated_alias(**aliases: str) -> Callable: """ Function decorator to warn about deprecated kwargs (and replace them). """ def ...
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alibi-detect-master/alibi_detect/utils/prediction.py
import numpy as np from typing import Callable, Union def tokenize_transformer(x: Union[list, np.ndarray], tokenizer: Callable, max_len: int, backend: str) -> dict: """ Batch tokenizer for transformer models. Parameters ---------- x Batch of instances. tokenizer Tokenizer for ...
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alibi-detect
alibi-detect-master/alibi_detect/utils/perturbation.py
import random from io import BytesIO from typing import List, Tuple, Union import cv2 import numpy as np import skimage as sk from alibi_detect.utils.data import Bunch from alibi_detect.utils.discretizer import Discretizer from alibi_detect.utils.distance import abdm, multidim_scaling from alibi_detect.utils.mapping i...
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alibi-detect-master/alibi_detect/utils/misc.py
import numpy as np def quantile(sample: np.ndarray, p: float, type: int = 7, sorted: bool = False, interpolate: bool = True) -> float: """ Estimate a desired quantile of a univariate distribution from a vector of samples Parameters ---------- sample A 1D vector of values ...
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alibi-detect
alibi-detect-master/alibi_detect/utils/data.py
import numpy as np import pandas as pd from typing import Tuple, Union class Bunch(dict): """ Container object for internal datasets Dictionary-like object that exposes its keys as attributes. """ def __init__(self, **kwargs): super().__init__(kwargs) def __setattr__(self, key, value...
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alibi-detect
alibi-detect-master/alibi_detect/utils/sampling.py
import numpy as np import random def reservoir_sampling(X_ref: np.ndarray, X: np.ndarray, reservoir_size: int, n: int) -> np.ndarray: """ Apply reservoir sampling. Parameters ---------- X_ref Current instances in reservo...
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alibi-detect-master/alibi_detect/utils/statstest.py
import numpy as np from typing import Callable, Tuple, Union def permutation_test(x: np.ndarray, y: np.ndarray, metric: Callable, n_permutations: int = 100, **kwargs) -> Tuple[float, float, np.ndarray]: """ Apply a permutation test to samples x and y. Parameters ---------- x ...
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alibi-detect-master/alibi_detect/utils/_random.py
""" This submodule contains utility functions to manage random number generator (RNG) seeds. It may change depending on how we decide to handle randomisation in tests (and elsewhere) going forwards. See https://github.com/SeldonIO/alibi-detect/issues/250. """ from contextlib import contextmanager import random import n...
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alibi-detect
alibi-detect-master/alibi_detect/utils/frameworks.py
from .missing_optional_dependency import ERROR_TYPES from typing import Optional, List, Dict, Iterable from enum import Enum class Framework(str, Enum): PYTORCH = 'pytorch' TENSORFLOW = 'tensorflow' KEOPS = 'keops' SKLEARN = 'sklearn' try: import tensorflow as tf # noqa import tensorflow_pr...
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alibi-detect-master/alibi_detect/utils/discretizer.py
import numpy as np from typing import Dict, Callable, List class Discretizer(object): def __init__(self, data: np.ndarray, categorical_features: List[int], feature_names: List[str], percentiles: List[int] = [25, 50, 75]) -> None: """ Initialize the discretizer. Parameter...
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alibi-detect-master/alibi_detect/utils/metrics.py
import numpy as np def accuracy(y_true: np.ndarray, y_pred: np.ndarray) -> float: y_true_class = np.argmax(y_true, axis=1) if len(y_true.shape) > 1 else np.round(y_true) y_pred_class = np.argmax(y_pred, axis=1) if len(y_pred.shape) > 1 else np.round(y_pred) return (y_true_class == y_pred_class).mean()
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alibi-detect-master/alibi_detect/utils/__init__.py
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alibi-detect-master/alibi_detect/utils/visualize.py
import matplotlib.pyplot as plt import numpy as np import pandas as pd from sklearn.metrics import roc_curve, auc from typing import Dict, Union import warnings def plot_instance_score(preds: Dict, target: np.ndarray, labels: np.ndarray, threshol...
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alibi-detect-master/alibi_detect/utils/distance.py
import numpy as np from sklearn.manifold import MDS from typing import Any, Dict, Tuple def norm(x: np.ndarray, p: int) -> np.ndarray: """ Compute p-norm across the features of a batch of instances. Parameters ---------- x Batch of instances of shape [N, features]. p Power of ...
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alibi-detect-master/alibi_detect/utils/mapping.py
import numpy as np from typing import Tuple, List def ohe2ord_shape(shape: tuple, cat_vars: dict = None, is_ohe: bool = False) -> tuple: """ Infer shape of instance if the categorical variables have ordinal instead of on-hot encoding. Parameters ---------- shape Instance shape, starting w...
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alibi-detect-master/alibi_detect/utils/saving/saving.py
# This submodule provides a link for the legacy alibi_detect.utils.saving location of load_detector and save_detector. # TODO: Remove in future from alibi_detect.saving import load_detector as _load_detector, save_detector as _save_detector from alibi_detect.base import ConfigurableDetector, Detector from typing impor...
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alibi-detect-master/alibi_detect/utils/saving/__init__.py
from alibi_detect.utils.saving.saving import save_detector, load_detector # noqa
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alibi-detect-master/alibi_detect/utils/tests/test_data.py
from itertools import product import numpy as np import pytest from alibi_detect.utils.data import create_outlier_batch, Bunch N, F = 1000, 4 X = np.random.rand(N, F) y = np.zeros(N,) y[:int(.5 * N)] = 1 n_samples = [50, 100] perc_outlier = [10, 50] tests = list(product(n_samples, perc_outlier)) n_tests = len(tests)...
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alibi-detect-master/alibi_detect/utils/tests/test_distance.py
import numpy as np from scipy.spatial.distance import cityblock from itertools import product import pytest from alibi_detect.utils.distance import pairwise_distance, abdm, cityblock_batch, mvdm, multidim_scaling n_features = [2, 5] n_instances = [(100, 100), (100, 75)] tests_pairwise = list(product(n_features, n_inst...
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alibi-detect-master/alibi_detect/utils/tests/test_saving_legacy.py
""" Tests for saving/loading of detectors with legacy .dill state_dict. As legacy save/load functionality becomes deprecated, these tests will be removed, and more tests will be added to test_saving.py. """ from alibi_detect.utils.missing_optional_dependency import MissingDependency from functools import partial import...
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alibi-detect-master/alibi_detect/utils/tests/conftest.py
import pytest @pytest.fixture def seed(pytestconfig): """ Returns the random seed set by pytest-randomly. """ return pytestconfig.getoption("randomly_seed")
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alibi-detect-master/alibi_detect/utils/tests/test_mapping.py
import numpy as np import alibi_detect.utils.mapping as mp X_ohe = np.array([[0, 1, 0.1, 1, 0, 0.2]]).astype(np.float32) shape_ohe = X_ohe.shape cat_vars_ohe = {0: 2, 3: 2} is_ohe = True X_ord = np.array([[1., 0.1, 0., 0.2]]).astype(np.float32) shape_ord = X_ord.shape cat_vars_ord = {0: 2, 2: 2} dist = {0: np.array(...
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alibi-detect-master/alibi_detect/utils/tests/test_sampling.py
from itertools import product import numpy as np import pytest from alibi_detect.utils.sampling import reservoir_sampling n_X_ref = [5, 10, 100] n_X = [2, 5, 100] reservoir_size = [10, 500] n = [100, 1000] n_features = 5 tests_sampling = list(product(n_X_ref, n_X, reservoir_size, n)) n_tests = len(tests_sampling) @p...
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alibi-detect-master/alibi_detect/utils/tests/test_discretize.py
from itertools import product import numpy as np import pytest from alibi_detect.utils.discretizer import Discretizer x = np.random.rand(10, 4) n_features = x.shape[1] feature_names = [str(_) for _ in range(n_features)] categorical_features = [[], [1, 3]] percentiles = [list(np.arange(25, 100, 25)), list(np.arange(10...
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alibi-detect-master/alibi_detect/utils/tests/test_random.py
from alibi_detect.utils._random import set_seed, get_seed, fixed_seed import numpy as np import tensorflow as tf import torch def test_set_get_seed(seed): """ Tests the set_seed and get_seed fuctions. """ # Check initial seed within test is the one set by pytest-randomly current_seed = get_seed() ...
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alibi-detect-master/alibi_detect/utils/tests/test_backend_verify.py
import pytest from alibi_detect.utils.missing_optional_dependency import ERROR_TYPES from alibi_detect.utils.frameworks import BackendValidator, HAS_BACKEND class TestBackendValidator: """Test the BackendValidator class.""" def setup_method(self): # mock missing dependency error for non existent modu...
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alibi-detect-master/alibi_detect/utils/tests/mocked_opt_dep.py
import non_existent_module # noqa: F401 class MockedClassMissingRequiredDeps: def __init__(self): self.opt_dep = "opt_dep" def mocked_function_missing_required_deps(): pass class MockedClassMissingMultipleRequiredDeps: def __init__(self): pass
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alibi-detect-master/alibi_detect/utils/tests/test_import_optional.py
import pytest from alibi_detect.utils.missing_optional_dependency import import_optional, MissingDependency, ERROR_TYPES class TestImportOptional: """Test the import_optional function.""" def setup_method(self): # mock missing dependency error for non existent module ERROR_TYPES['non_existen...
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alibi-detect-master/alibi_detect/utils/tests/test_perturbation.py
from functools import reduce from itertools import product from operator import mul import numpy as np import pytest from alibi_detect.utils.data import Bunch from alibi_detect.utils.perturbation import apply_mask, inject_outlier_ts from alibi_detect.utils.tensorflow.perturbation import mutate_categorical x = np.rando...
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alibi-detect-master/alibi_detect/utils/tests/test_statstest.py
from itertools import product import numpy as np import pytest import tensorflow as tf from alibi_detect.utils.tensorflow import GaussianRBF, mmd2 from alibi_detect.utils.statstest import fdr, permutation_test q_val = [.05, .1, .25] n_p = 1000 p_vals = [ {'is_below': True, 'p_val': np.zeros(n_p)}, {'is_below':...
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alibi-detect
alibi-detect-master/alibi_detect/utils/state/state.py
import os from pathlib import Path import logging from abc import ABC from typing import Union, Tuple import numpy as np from alibi_detect.utils.frameworks import Framework from alibi_detect.utils.state._pytorch import save_state_dict as _save_state_dict_pt,\ load_state_dict as _load_state_dict_pt logger = logging...
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alibi-detect-master/alibi_detect/utils/state/__init__.py
from alibi_detect.utils.state.state import StateMixin, _save_state_dict, _load_state_dict __all__ = [ "StateMixin", "_save_state_dict", "_load_state_dict", ]
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alibi-detect-master/alibi_detect/utils/state/_pytorch/state.py
""" Submodule to handle saving and loading of detector state dictionaries when the dictionaries contain `torch.Tensor`'s. """ from pathlib import Path import torch def save_state_dict(state_dict: dict, filepath: Path): """ Utility function to save a detector's state dictionary to a filepath using `torch.save`...
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alibi-detect
alibi-detect-master/alibi_detect/utils/state/_pytorch/__init__.py
from alibi_detect.utils.missing_optional_dependency import import_optional save_state_dict, load_state_dict = import_optional( 'alibi_detect.utils.state._pytorch.state', names=['save_state_dict', 'load_state_dict'] ) __all__ = [ "save_state_dict", "load_state_dict", ]
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alibi-detect-master/alibi_detect/utils/keops/kernels.py
from pykeops.torch import LazyTensor import torch import torch.nn as nn from typing import Callable, Optional, Union from alibi_detect.utils.frameworks import Framework from alibi_detect.utils._types import Literal from copy import deepcopy def sigma_mean(x: LazyTensor, y: LazyTensor, dist: LazyTensor, n_min: int = 1...
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alibi-detect
alibi-detect-master/alibi_detect/utils/keops/__init__.py
from alibi_detect.utils.missing_optional_dependency import import_optional GaussianRBF, DeepKernel = import_optional( 'alibi_detect.utils.keops.kernels', names=['GaussianRBF', 'DeepKernel'] ) __all__ = [ "GaussianRBF", "DeepKernel" ]
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alibi-detect-master/alibi_detect/utils/keops/tests/test_kernels_keops.py
from itertools import product import numpy as np from alibi_detect.utils.frameworks import has_keops import pytest import torch import torch.nn as nn if has_keops: from pykeops.torch import LazyTensor from alibi_detect.utils.keops import DeepKernel, GaussianRBF sigma = [None, np.array([1.]), np.array([1., 2.])...
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alibi-detect
alibi-detect-master/alibi_detect/utils/fetching/fetching.py
import logging import os from io import BytesIO from pathlib import Path from typing import Union, TYPE_CHECKING, Tuple import dill import requests from requests import RequestException import tensorflow as tf from tensorflow.python.keras import backend from alibi_detect.models.tensorflow import PixelCNN from alibi_...
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alibi-detect
alibi-detect-master/alibi_detect/utils/fetching/__init__.py
from alibi_detect.utils.missing_optional_dependency import import_optional fetch_detector, fetch_tf_model = import_optional('alibi_detect.utils.fetching.fetching', names=['fetch_detector', 'fetch_tf_model']) __all__ = ['fetch_tf_model', 'fetch_detector']
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alibi-detect-master/alibi_detect/utils/pytorch/losses.py
import torch def hinge_loss(preds: torch.Tensor) -> torch.Tensor: "L(pred) = max(0, 1-pred) averaged over multiple preds" linear_inds = preds < 1 return (((1 - preds)*linear_inds).sum(0))/len(preds)
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alibi-detect
alibi-detect-master/alibi_detect/utils/pytorch/kernels.py
import numpy as np import torch from torch import nn from . import distance from typing import Optional, Union, Callable from alibi_detect.utils.frameworks import Framework def sigma_median(x: torch.Tensor, y: torch.Tensor, dist: torch.Tensor) -> torch.Tensor: """ Bandwidth estimation using the median heurist...
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alibi-detect
alibi-detect-master/alibi_detect/utils/pytorch/prediction.py
from functools import partial from typing import Callable, Optional, Type, Union import numpy as np import torch import torch.nn as nn from alibi_detect.utils.pytorch.misc import get_device from alibi_detect.utils.prediction import tokenize_transformer def predict_batch(x: Union[list, np.ndarray, torch.Tensor], mode...
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alibi-detect
alibi-detect-master/alibi_detect/utils/pytorch/misc.py
import logging from typing import Optional, Union, Type import torch logger = logging.getLogger(__name__) def zero_diag(mat: torch.Tensor) -> torch.Tensor: """ Set the diagonal of a matrix to 0 Parameters ---------- mat A 2D square matrix Returns ------- A 2D square matrix ...
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alibi-detect
alibi-detect-master/alibi_detect/utils/pytorch/data.py
import numpy as np import torch from typing import Tuple, Union Indexable = Union[np.ndarray, torch.Tensor, list] class TorchDataset(torch.utils.data.Dataset): def __init__(self, *indexables: Union[Tuple[Indexable, ...], Indexable]) -> None: self.indexables = indexables def __getitem__(self, idx: in...
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alibi-detect
alibi-detect-master/alibi_detect/utils/pytorch/__init__.py
from alibi_detect.utils.missing_optional_dependency import import_optional TorchDataset = import_optional( 'alibi_detect.utils.pytorch.data', names=['TorchDataset'] ) mmd2, mmd2_from_kernel_matrix, squared_pairwise_distance, permed_lsdds, batch_compute_kernel_matrix = import_optional( 'alibi_detect.utils...
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alibi-detect
alibi-detect-master/alibi_detect/utils/pytorch/distance.py
import logging import torch from torch import nn import numpy as np from typing import Callable, List, Tuple, Optional, Union logger = logging.getLogger(__name__) @torch.jit.script def squared_pairwise_distance(x: torch.Tensor, y: torch.Tensor, a_min: float = 1e-30) -> torch.Tensor: """ PyTorch pairwise squa...
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alibi-detect-master/alibi_detect/utils/pytorch/tests/test_data_pt.py
import numpy as np import pytest from alibi_detect.utils.pytorch.data import TorchDataset # test on numpy array and list n, f = 100, 5 shape = (n, f) tests_ds = [list, np.ndarray] n_tests_ds = len(tests_ds) @pytest.fixture def ds_params(request): return tests_ds[request.param] @pytest.mark.parametrize('ds_para...
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alibi-detect
alibi-detect-master/alibi_detect/utils/pytorch/tests/test_distance_pt.py
import numpy as np from itertools import product import pytest import torch from alibi_detect.utils.pytorch import GaussianRBF, mmd2, mmd2_from_kernel_matrix, permed_lsdds from alibi_detect.utils.pytorch import squared_pairwise_distance, batch_compute_kernel_matrix n_features = [2, 5] n_instances = [(100, 100), (100, ...
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alibi-detect-master/alibi_detect/utils/pytorch/tests/test_misc_pt.py
from itertools import product import pytest import torch import numpy as np from alibi_detect.utils.pytorch import zero_diag, quantile def test_zero_diag(): ones = torch.ones(10, 10) ones_zd = zero_diag(ones) assert ones_zd.shape == (10, 10) assert float(ones_zd.trace()) == 0 assert float(ones_zd....
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alibi-detect-master/alibi_detect/utils/pytorch/tests/test_prediction_pt.py
import numpy as np import pytest import torch import torch.nn as nn from typing import Tuple, Union from alibi_detect.utils.pytorch import predict_batch n, n_features, n_classes, latent_dim = 100, 10, 5, 2 x = np.zeros((n, n_features), dtype=np.float32) class MyModel(nn.Module): def __init__(self, multi_out: boo...
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alibi-detect
alibi-detect-master/alibi_detect/utils/pytorch/tests/test_kernels_pt.py
from itertools import product import numpy as np import pytest import torch from torch import nn from alibi_detect.utils.pytorch import GaussianRBF, DeepKernel sigma = [None, np.array([1.]), np.array([1., 2.])] n_features = [5, 10] n_instances = [(100, 100), (100, 75)] trainable = [True, False] tests_gk = list(product...
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alibi-detect
alibi-detect-master/alibi_detect/utils/tensorflow/kernels.py
import tensorflow as tf import numpy as np from . import distance from typing import Optional, Union, Callable from scipy.special import logit from alibi_detect.utils.frameworks import Framework def sigma_median(x: tf.Tensor, y: tf.Tensor, dist: tf.Tensor) -> tf.Tensor: """ Bandwidth estimation using the medi...
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alibi-detect
alibi-detect-master/alibi_detect/utils/tensorflow/prediction.py
from functools import partial from typing import Callable, Type, Union import numpy as np import tensorflow as tf from alibi_detect.utils.prediction import tokenize_transformer def predict_batch(x: Union[list, np.ndarray, tf.Tensor], model: Union[Callable, tf.keras.Model], batch_size: int = int(1e1...
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alibi-detect
alibi-detect-master/alibi_detect/utils/tensorflow/perturbation.py
import numpy as np import tensorflow as tf def mutate_categorical(X: np.ndarray, rate: float = None, seed: int = 0, feature_range: tuple = (0, 255)) -> tf.Tensor: """ Randomly change integer feature values to values within a set range wi...
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alibi-detect
alibi-detect-master/alibi_detect/utils/tensorflow/misc.py
import tensorflow as tf def zero_diag(mat: tf.Tensor) -> tf.Tensor: """ Set the diagonal of a matrix to 0 Parameters ---------- mat A 2D square matrix Returns ------- A 2D square matrix with zeros along the diagonal """ return mat - tf.linalg.diag(tf.linalg.diag_part(...
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alibi-detect
alibi-detect-master/alibi_detect/utils/tensorflow/data.py
import numpy as np import tensorflow as tf from typing import Tuple, Union Indexable = Union[np.ndarray, tf.Tensor, list] class TFDataset(tf.keras.utils.Sequence): def __init__( self, *indexables: Indexable, batch_size: int = int(1e10), shuffle: bool = True, ) -> None: self.indexables = i...
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alibi-detect
alibi-detect-master/alibi_detect/utils/tensorflow/__init__.py
from alibi_detect.utils.missing_optional_dependency import import_optional mmd2, mmd2_from_kernel_matrix, batch_compute_kernel_matrix, relative_euclidean_distance, squared_pairwise_distance, \ permed_lsdds = import_optional( 'alibi_detect.utils.tensorflow.distance', names=['mmd2', 'mmd2_from_kernel...
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alibi-detect
alibi-detect-master/alibi_detect/utils/tensorflow/distance.py
import logging import numpy as np import tensorflow as tf from typing import Callable, Tuple, List, Optional, Union logger = logging.getLogger(__name__) def squared_pairwise_distance(x: tf.Tensor, y: tf.Tensor, a_min: float = 1e-30, a_max: float = 1e30) -> tf.Tensor: """ TensorFlow pairwise squared Euclidean...
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alibi-detect
alibi-detect-master/alibi_detect/utils/tensorflow/tests/test_data_tf.py
from itertools import product import numpy as np import pytest from alibi_detect.utils.tensorflow.data import TFDataset # test on numpy array and list n, f = 100, 5 shape = (n, f) xtype = [list, np.ndarray] shuffle = [True, False] batch_size = [2, 10] tests_ds = list(product(xtype, batch_size, shuffle)) n_tests_ds = l...
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alibi-detect
alibi-detect-master/alibi_detect/utils/tensorflow/tests/test_prediction_tf.py
import numpy as np import pytest import tensorflow as tf from tensorflow.keras.layers import Dense, InputLayer from typing import Tuple, Union from alibi_detect.utils.tensorflow import predict_batch n, n_features, n_classes, latent_dim = 100, 10, 5, 2 x = np.zeros((n, n_features), dtype=np.float32) class MyModel(tf....
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alibi-detect
alibi-detect-master/alibi_detect/utils/tensorflow/tests/test_misc_tf.py
from itertools import product import pytest import tensorflow as tf from tensorflow.keras.layers import Dense, Input, InputLayer import numpy as np from alibi_detect.utils.tensorflow import zero_diag, quantile, subset_matrix from alibi_detect.utils.tensorflow.misc import clone_model def test_zero_diag(): ones = t...
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alibi-detect
alibi-detect-master/alibi_detect/utils/tensorflow/tests/test_kernels_tf.py
from itertools import product import numpy as np import pytest import tensorflow as tf from tensorflow.keras.layers import Dense, Input from alibi_detect.utils.tensorflow import GaussianRBF, DeepKernel sigma = [None, np.array([1.]), np.array([1., 2.])] n_features = [5, 10] n_instances = [(100, 100), (100, 75)] trainab...
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alibi-detect
alibi-detect-master/alibi_detect/utils/tensorflow/tests/test_distance_tf.py
import numpy as np from itertools import product import pytest import tensorflow as tf from alibi_detect.utils.tensorflow import GaussianRBF, mmd2, mmd2_from_kernel_matrix, permed_lsdds from alibi_detect.utils.tensorflow import relative_euclidean_distance, squared_pairwise_distance from alibi_detect.utils.tensorflow im...
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alibi-detect
alibi-detect-master/alibi_detect/ad/model_distillation.py
import logging from typing import Callable, Dict, Tuple, Union, cast import numpy as np import tensorflow as tf from alibi_detect.base import (BaseDetector, FitMixin, ThresholdMixin, adversarial_prediction_dict) from alibi_detect.models.tensorflow.losses import loss_distillation from ali...
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alibi-detect-master/alibi_detect/ad/adversarialae.py
import logging from typing import Callable, Dict, List, Tuple, Union, cast import numpy as np import tensorflow as tf from alibi_detect.base import (BaseDetector, FitMixin, ThresholdMixin, adversarial_correction_dict, adversarial_prediction_dict) from alibi...
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alibi-detect-master/alibi_detect/ad/__init__.py
from alibi_detect.utils.missing_optional_dependency import import_optional AdversarialAE = import_optional('alibi_detect.ad.adversarialae', names=['AdversarialAE']) ModelDistillation = import_optional('alibi_detect.ad.model_distillation', names=['ModelDistillation']) __all__ = [ "AdversarialAE", "ModelDistill...
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alibi-detect-master/alibi_detect/ad/tests/test_admd.py
from itertools import product import numpy as np import pytest from sklearn.datasets import load_iris import tensorflow as tf from tensorflow.keras.utils import to_categorical from alibi_detect.ad import ModelDistillation from alibi_detect.version import __version__ threshold = [None, 5.] loss_type = ['kld', 'xent'] t...
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alibi-detect-master/alibi_detect/ad/tests/test_adae.py
from itertools import product import numpy as np import pytest from sklearn.datasets import load_iris import tensorflow as tf from tensorflow.keras.layers import Dense, InputLayer from tensorflow.keras.utils import to_categorical from alibi_detect.ad import AdversarialAE from alibi_detect.version import __version__ th...
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