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__init__.py
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# Copyright 2018 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Init module for TensorFlow Model Analysis."""
################################################################################
# This file acts as the public API for root-level interfaces. It should only
# include imports that are either in the root directory itself or under the api/
# or proto/ subdirectories. All other directories should have a single import
# for the entire directory in this file and have their own __init__.py for
# exposing their own public interfaces.
################################################################################
# pylint: disable=unused-import
# pylint: disable=g-bad-import-order
# pylint: disable=g-import-not-at-top
# pylint: disable=g-statement-before-imports
# See b/148667210 for why the ImportError is ignored.
try:
from tensorflow_model_analysis.sdk import *
# Allow api module types to be imported at the top-level since they are the
# main public interface to using TFMA.
from tensorflow_model_analysis.api import tfma_unit as test
from tensorflow_model_analysis.api.model_eval_lib import AttributionsForSlice
from tensorflow_model_analysis.api.model_eval_lib import analyze_raw_data
from tensorflow_model_analysis.api.model_eval_lib import BatchedInputsToExtracts
from tensorflow_model_analysis.api.model_eval_lib import default_eval_shared_model
from tensorflow_model_analysis.api.model_eval_lib import default_evaluators
from tensorflow_model_analysis.api.model_eval_lib import default_extractors
from tensorflow_model_analysis.api.model_eval_lib import default_writers
from tensorflow_model_analysis.api.model_eval_lib import ExtractAndEvaluate
from tensorflow_model_analysis.api.model_eval_lib import ExtractEvaluateAndWriteResults
from tensorflow_model_analysis.api.model_eval_lib import InputsToExtracts
from tensorflow_model_analysis.api.model_eval_lib import is_batched_input
from tensorflow_model_analysis.api.model_eval_lib import is_legacy_estimator
from tensorflow_model_analysis.api.model_eval_lib import load_attributions
from tensorflow_model_analysis.api.model_eval_lib import load_eval_result
from tensorflow_model_analysis.api.model_eval_lib import load_eval_results
from tensorflow_model_analysis.api.model_eval_lib import load_metrics
from tensorflow_model_analysis.api.model_eval_lib import load_plots
from tensorflow_model_analysis.api.model_eval_lib import load_validation_result
from tensorflow_model_analysis.api.model_eval_lib import make_eval_results
from tensorflow_model_analysis.api.model_eval_lib import MetricsForSlice
from tensorflow_model_analysis.api.model_eval_lib import multiple_data_analysis
from tensorflow_model_analysis.api.model_eval_lib import multiple_model_analysis
from tensorflow_model_analysis.api.model_eval_lib import PlotsForSlice
from tensorflow_model_analysis.api.model_eval_lib import run_model_analysis
from tensorflow_model_analysis.api.model_eval_lib import WriteResults
from tensorflow_model_analysis.api.model_eval_lib import ValidationResult
from tensorflow_model_analysis.api.verifier_lib import Validate
# TODO(b/171992041): Remove these imports in the future.
# For backwards compatibility allow eval_metrics_graph and exporter to be
# accessed from top-level model. These will be deprecated in the future.
from tensorflow_model_analysis.eval_metrics_graph import eval_metrics_graph
from tensorflow_model_analysis.eval_saved_model import export
from tensorflow_model_analysis.eval_saved_model import exporter
from tensorflow_model_analysis.post_export_metrics import post_export_metrics
# TODO(b/73882264): The orders should be kept in order to make benchmark on
# DataFlow work. We need to look into why the import orders matters for the
# DataFlow benchmark.
from tensorflow_model_analysis import addons
from tensorflow_model_analysis import extractors
from tensorflow_model_analysis import slicer
from tensorflow_model_analysis import validators
from tensorflow_model_analysis import evaluators
from tensorflow_model_analysis import metrics
from tensorflow_model_analysis import utils
from tensorflow_model_analysis import writers
from tensorflow_model_analysis import view
from tensorflow_model_analysis import model_agnostic_eval
# TODO(b/228406044): Stop exposing tfma.types and migrate all internal users
# to use the top-level symbols exported below (e.g. tfma.Extracts).
from tensorflow_model_analysis.api import types
# TODO(b/171992041): Deprecate use of EvalResult in the future.
from tensorflow_model_analysis.view.view_types import EvalResult
# Allow types to be imported at the top-level since they live in root dir.
from tensorflow_model_analysis.api.types import AddMetricsCallbackType
from tensorflow_model_analysis.api.types import EvalSharedModel
from tensorflow_model_analysis.api.types import Extracts
# TODO(b/120222218): Remove after passing of native FPL supported.
from tensorflow_model_analysis.api.types import FeaturesPredictionsLabels
# TODO(b/120222218): Remove after passing of native FPL supported.
from tensorflow_model_analysis.api.types import MaterializedColumn
from tensorflow_model_analysis.api.types import MaybeMultipleEvalSharedModels
from tensorflow_model_analysis.api.types import ModelLoader
from tensorflow_model_analysis.api.types import RaggedTensorValue
from tensorflow_model_analysis.api.types import SparseTensorValue
from tensorflow_model_analysis.api.types import TensorType
from tensorflow_model_analysis.api.types import TensorTypeMaybeDict
from tensorflow_model_analysis.api.types import TensorValue
from tensorflow_model_analysis.api.types import VarLenTensorValue
# Import VERSION as __version__ for compatibility with other TFX components.
from tensorflow_model_analysis.version import VERSION as __version__
except ImportError as err:
import sys
sys.stderr.write('Error importing: {}'.format(err))
# pylint: enable=g-statement-before-imports
# pylint: enable=g-import-not-at-top
def _jupyter_nbextension_paths():
return [{
'section': 'notebook',
'src': 'static',
'dest': 'tensorflow_model_analysis',
'require': 'tensorflow_model_analysis/extension'
}]