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Overview
In this activity, you'll use Fairness Indicators for TensorBoard. With the plugin, you can visualize fairness evaluations for your runs and easily compare performance across groups.
Importing
Run the following code to install the required libraries.
pip install -q -U pip==20.2pip install fairness_indicators 'absl-py<0.9,>=0.7'pip install google-api-python-client==1.8.3pip install tensorboard-plugin-fairness-indicatorspip install tensorflow-serving-api==2.4.1
Restart the runtime. After the runtime is restarted, continue with following cells without running previous cell again.
# %tf.disable_v2_behavior() # Uncomment this line if running in Google Colab.
import datetime
import os
import tempfile
from tensorboard_plugin_fairness_indicators import summary_v2
import tensorflow.compat.v1 as tf
# example_model.py is provided in fairness_indicators package to train and
# evaluate an example model.
from fairness_indicators import example_model
tf.compat.v1.enable_eager_execution()
Data and Constants
# To know about dataset, check Fairness Indicators Example Colab at:
# https://github.com/tensorflow/fairness-indicators/blob/master/g3doc/tutorials/Fairness_Indicators_Example_Colab.ipynb
train_tf_file = tf.keras.utils.get_file('train.tf', 'https://storage.googleapis.com/civil_comments_dataset/train_tf_processed.tfrecord')
validate_tf_file = tf.keras.utils.get_file('validate.tf', 'https://storage.googleapis.com/civil_comments_dataset/validate_tf_processed.tfrecord')
BASE_DIR = tempfile.gettempdir()
TEXT_FEATURE = 'comment_text'
LABEL = 'toxicity'
FEATURE_MAP = {
# Label:
LABEL: tf.io.FixedLenFeature([], tf.float32),
# Text:
TEXT_FEATURE: tf.io.FixedLenFeature([], tf.string),
# Identities:
'sexual_orientation': tf.io.VarLenFeature(tf.string),
'gender': tf.io.VarLenFeature(tf.string),
'religion': tf.io.VarLenFeature(tf.string),
'race': tf.io.VarLenFeature(tf.string),
'disability': tf.io.VarLenFeature(tf.string),
}
Downloading data from https://storage.googleapis.com/civil_comments_dataset/train_tf_processed.tfrecord 488161280/488153424 [==============================] - 3s 0us/step Downloading data from https://storage.googleapis.com/civil_comments_dataset/validate_tf_processed.tfrecord 324943872/324941336 [==============================] - 1s 0us/step
Train the Model
model_dir = os.path.join(BASE_DIR, 'train',
datetime.datetime.now().strftime('%Y%m%d-%H%M%S'))
classifier = example_model.train_model(model_dir,
train_tf_file,
LABEL,
TEXT_FEATURE,
FEATURE_MAP)
INFO:tensorflow:Using default config.
INFO:tensorflow:Using default config.
INFO:tensorflow:Using config: {'_model_dir': '/tmp/train/20210310-102620', '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_steps': None, '_save_checkpoints_secs': 600, '_session_config': allow_soft_placement: true
graph_options {
rewrite_options {
meta_optimizer_iterations: ONE
}
}
, '_keep_checkpoint_max': 5, '_keep_checkpoint_every_n_hours': 10000, '_log_step_count_steps': 100, '_train_distribute': None, '_device_fn': None, '_protocol': None, '_eval_distribute': None, '_experimental_distribute': None, '_experimental_max_worker_delay_secs': None, '_session_creation_timeout_secs': 7200, '_checkpoint_save_graph_def': True, '_service': None, '_cluster_spec': ClusterSpec({}), '_task_type': 'worker', '_task_id': 0, '_global_id_in_cluster': 0, '_master': '', '_evaluation_master': '', '_is_chief': True, '_num_ps_replicas': 0, '_num_worker_replicas': 1}
INFO:tensorflow:Using config: {'_model_dir': '/tmp/train/20210310-102620', '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_steps': None, '_save_checkpoints_secs': 600, '_session_config': allow_soft_placement: true
graph_options {
rewrite_options {
meta_optimizer_iterations: ONE
}
}
, '_keep_checkpoint_max': 5, '_keep_checkpoint_every_n_hours': 10000, '_log_step_count_steps': 100, '_train_distribute': None, '_device_fn': None, '_protocol': None, '_eval_distribute': None, '_experimental_distribute': None, '_experimental_max_worker_delay_secs': None, '_session_creation_timeout_secs': 7200, '_checkpoint_save_graph_def': True, '_service': None, '_cluster_spec': ClusterSpec({}), '_task_type': 'worker', '_task_id': 0, '_global_id_in_cluster': 0, '_master': '', '_evaluation_master': '', '_is_chief': True, '_num_ps_replicas': 0, '_num_worker_replicas': 1}
WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.6/site-packages/tensorflow/python/training/training_util.py:236: Variable.initialized_value (from tensorflow.python.ops.variables) is deprecated and will be removed in a future version.
Instructions for updating:
Use Variable.read_value. Variables in 2.X are initialized automatically both in eager and graph (inside tf.defun) contexts.
WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.6/site-packages/tensorflow/python/training/training_util.py:236: Variable.initialized_value (from tensorflow.python.ops.variables) is deprecated and will be removed in a future version.
Instructions for updating:
Use Variable.read_value. Variables in 2.X are initialized automatically both in eager and graph (inside tf.defun) contexts.
INFO:tensorflow:Calling model_fn.
INFO:tensorflow:Calling model_fn.
INFO:tensorflow:Saver not created because there are no variables in the graph to restore
INFO:tensorflow:Saver not created because there are no variables in the graph to restore
INFO:tensorflow:Saver not created because there are no variables in the graph to restore
INFO:tensorflow:Saver not created because there are no variables in the graph to restore
WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.6/site-packages/tensorflow_estimator/python/estimator/canned/head.py:402: NumericColumn._get_dense_tensor (from tensorflow.python.feature_column.feature_column_v2) is deprecated and will be removed in a future version.
Instructions for updating:
The old _FeatureColumn APIs are being deprecated. Please use the new FeatureColumn APIs instead.
WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.6/site-packages/tensorflow_estimator/python/estimator/canned/head.py:402: NumericColumn._get_dense_tensor (from tensorflow.python.feature_column.feature_column_v2) is deprecated and will be removed in a future version.
Instructions for updating:
The old _FeatureColumn APIs are being deprecated. Please use the new FeatureColumn APIs instead.
WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.6/site-packages/tensorflow/python/feature_column/feature_column.py:2192: NumericColumn._transform_feature (from tensorflow.python.feature_column.feature_column_v2) is deprecated and will be removed in a future version.
Instructions for updating:
The old _FeatureColumn APIs are being deprecated. Please use the new FeatureColumn APIs instead.
WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.6/site-packages/tensorflow/python/feature_column/feature_column.py:2192: NumericColumn._transform_feature (from tensorflow.python.feature_column.feature_column_v2) is deprecated and will be removed in a future version.
Instructions for updating:
The old _FeatureColumn APIs are being deprecated. Please use the new FeatureColumn APIs instead.
WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.6/site-packages/tensorflow/python/training/adagrad.py:77: calling Constant.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.
Instructions for updating:
Call initializer instance with the dtype argument instead of passing it to the constructor
WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.6/site-packages/tensorflow/python/training/adagrad.py:77: calling Constant.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.
Instructions for updating:
Call initializer instance with the dtype argument instead of passing it to the constructor
INFO:tensorflow:Done calling model_fn.
INFO:tensorflow:Done calling model_fn.
INFO:tensorflow:Create CheckpointSaverHook.
INFO:tensorflow:Create CheckpointSaverHook.
INFO:tensorflow:Graph was finalized.
INFO:tensorflow:Graph was finalized.
INFO:tensorflow:Running local_init_op.
INFO:tensorflow:Running local_init_op.
INFO:tensorflow:Done running local_init_op.
INFO:tensorflow:Done running local_init_op.
INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 0...
INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 0...
INFO:tensorflow:Saving checkpoints for 0 into /tmp/train/20210310-102620/model.ckpt.
INFO:tensorflow:Saving checkpoints for 0 into /tmp/train/20210310-102620/model.ckpt.
INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 0...
INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 0...
INFO:tensorflow:loss = 59.46598, step = 0
INFO:tensorflow:loss = 59.46598, step = 0
INFO:tensorflow:global_step/sec: 23.6921
INFO:tensorflow:global_step/sec: 23.6921
INFO:tensorflow:loss = 55.49635, step = 100 (4.222 sec)
INFO:tensorflow:loss = 55.49635, step = 100 (4.222 sec)
INFO:tensorflow:global_step/sec: 25.7192
INFO:tensorflow:global_step/sec: 25.7192
INFO:tensorflow:loss = 47.124454, step = 200 (3.890 sec)
INFO:tensorflow:loss = 47.124454, step = 200 (3.890 sec)
INFO:tensorflow:global_step/sec: 25.8421
INFO:tensorflow:global_step/sec: 25.8421
INFO:tensorflow:loss = 55.988045, step = 300 (3.868 sec)
INFO:tensorflow:loss = 55.988045, step = 300 (3.868 sec)
INFO:tensorflow:global_step/sec: 25.9443
INFO:tensorflow:global_step/sec: 25.9443
INFO:tensorflow:loss = 56.25461, step = 400 (3.854 sec)
INFO:tensorflow:loss = 56.25461, step = 400 (3.854 sec)
INFO:tensorflow:global_step/sec: 25.4406
INFO:tensorflow:global_step/sec: 25.4406
INFO:tensorflow:loss = 42.057167, step = 500 (3.931 sec)
INFO:tensorflow:loss = 42.057167, step = 500 (3.931 sec)
INFO:tensorflow:global_step/sec: 25.8574
INFO:tensorflow:global_step/sec: 25.8574
INFO:tensorflow:loss = 45.63904, step = 600 (3.869 sec)
INFO:tensorflow:loss = 45.63904, step = 600 (3.869 sec)
INFO:tensorflow:global_step/sec: 25.0793
INFO:tensorflow:global_step/sec: 25.0793
INFO:tensorflow:loss = 50.938217, step = 700 (3.986 sec)
INFO:tensorflow:loss = 50.938217, step = 700 (3.986 sec)
INFO:tensorflow:global_step/sec: 24.6693
INFO:tensorflow:global_step/sec: 24.6693
INFO:tensorflow:loss = 47.633305, step = 800 (4.053 sec)
INFO:tensorflow:loss = 47.633305, step = 800 (4.053 sec)
INFO:tensorflow:global_step/sec: 25.2945
INFO:tensorflow:global_step/sec: 25.2945
INFO:tensorflow:loss = 47.770172, step = 900 (3.954 sec)
INFO:tensorflow:loss = 47.770172, step = 900 (3.954 sec)
INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 1000...
INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 1000...
INFO:tensorflow:Saving checkpoints for 1000 into /tmp/train/20210310-102620/model.ckpt.
INFO:tensorflow:Saving checkpoints for 1000 into /tmp/train/20210310-102620/model.ckpt.
INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 1000...
INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 1000...
INFO:tensorflow:Loss for final step: 51.219826.
INFO:tensorflow:Loss for final step: 51.219826.
Run TensorFlow Model Analysis with Fairness Indicators
This step might take 2 to 5 minutes.
tfma_eval_result_path = os.path.join(BASE_DIR, 'tfma_eval_result')
example_model.evaluate_model(classifier,
validate_tf_file,
tfma_eval_result_path,
'gender',
LABEL,
FEATURE_MAP)
WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.6/site-packages/tensorflow_model_analysis/eval_saved_model/encoding.py:141: build_tensor_info (from tensorflow.python.saved_model.utils_impl) is deprecated and will be removed in a future version. Instructions for updating: This function will only be available through the v1 compatibility library as tf.compat.v1.saved_model.utils.build_tensor_info or tf.compat.v1.saved_model.build_tensor_info. WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.6/site-packages/tensorflow_model_analysis/eval_saved_model/encoding.py:141: build_tensor_info (from tensorflow.python.saved_model.utils_impl) is deprecated and will be removed in a future version. Instructions for updating: This function will only be available through the v1 compatibility library as tf.compat.v1.saved_model.utils.build_tensor_info or tf.compat.v1.saved_model.build_tensor_info. INFO:tensorflow:Calling model_fn. INFO:tensorflow:Calling model_fn. INFO:tensorflow:Saver not created because there are no variables in the graph to restore INFO:tensorflow:Saver not created because there are no variables in the graph to restore INFO:tensorflow:Saver not created because there are no variables in the graph to restore INFO:tensorflow:Saver not created because there are no variables in the graph to restore WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.6/site-packages/tensorflow_estimator/python/estimator/canned/head.py:642: auc (from tensorflow.python.ops.metrics_impl) is deprecated and will be removed in a future version. Instructions for updating: The value of AUC returned by this may race with the update so this is deprecated. Please use tf.keras.metrics.AUC instead. WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.6/site-packages/tensorflow_estimator/python/estimator/canned/head.py:642: auc (from tensorflow.python.ops.metrics_impl) is deprecated and will be removed in a future version. Instructions for updating: The value of AUC returned by this may race with the update so this is deprecated. Please use tf.keras.metrics.AUC instead. WARNING:tensorflow:Trapezoidal rule is known to produce incorrect PR-AUCs; please switch to "careful_interpolation" instead. WARNING:tensorflow:Trapezoidal rule is known to produce incorrect PR-AUCs; please switch to "careful_interpolation" instead. WARNING:tensorflow:Trapezoidal rule is known to produce incorrect PR-AUCs; please switch to "careful_interpolation" instead. WARNING:tensorflow:Trapezoidal rule is known to produce incorrect PR-AUCs; please switch to "careful_interpolation" instead. INFO:tensorflow:Done calling model_fn. INFO:tensorflow:Done calling model_fn. INFO:tensorflow:Signatures INCLUDED in export for Classify: None INFO:tensorflow:Signatures INCLUDED in export for Classify: None INFO:tensorflow:Signatures INCLUDED in export for Regress: None INFO:tensorflow:Signatures INCLUDED in export for Regress: None INFO:tensorflow:Signatures INCLUDED in export for Predict: None INFO:tensorflow:Signatures INCLUDED in export for Predict: None INFO:tensorflow:Signatures INCLUDED in export for Train: None INFO:tensorflow:Signatures INCLUDED in export for Train: None INFO:tensorflow:Signatures INCLUDED in export for Eval: ['eval'] INFO:tensorflow:Signatures INCLUDED in export for Eval: ['eval'] WARNING:tensorflow:Export includes no default signature! WARNING:tensorflow:Export includes no default signature! INFO:tensorflow:Restoring parameters from /tmp/train/20210310-102620/model.ckpt-1000 INFO:tensorflow:Restoring parameters from /tmp/train/20210310-102620/model.ckpt-1000 INFO:tensorflow:Assets added to graph. INFO:tensorflow:Assets added to graph. INFO:tensorflow:Assets written to: /tmp/tfma_eval_model/temp-1615372025/assets INFO:tensorflow:Assets written to: /tmp/tfma_eval_model/temp-1615372025/assets INFO:tensorflow:SavedModel written to: /tmp/tfma_eval_model/temp-1615372025/saved_model.pb INFO:tensorflow:SavedModel written to: /tmp/tfma_eval_model/temp-1615372025/saved_model.pb WARNING:absl:Tensorflow version (2.4.1) found. Note that TFMA support for TF 2.0 is currently in beta WARNING:apache_beam.runners.interactive.interactive_environment:Dependencies required for Interactive Beam PCollection visualization are not available, please use: `pip install apache-beam[interactive]` to install necessary dependencies to enable all data visualization features. WARNING:apache_beam.typehints.typehints:Ignoring send_type hint: <class 'NoneType'> WARNING:apache_beam.typehints.typehints:Ignoring return_type hint: <class 'NoneType'> WARNING:apache_beam.typehints.typehints:Ignoring send_type hint: <class 'NoneType'> WARNING:apache_beam.typehints.typehints:Ignoring return_type hint: <class 'NoneType'> WARNING:apache_beam.typehints.typehints:Ignoring send_type hint: <class 'NoneType'> WARNING:apache_beam.typehints.typehints:Ignoring return_type hint: <class 'NoneType'> WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.6/site-packages/tensorflow_model_analysis/eval_saved_model/load.py:169: load (from tensorflow.python.saved_model.loader_impl) is deprecated and will be removed in a future version. Instructions for updating: This function will only be available through the v1 compatibility library as tf.compat.v1.saved_model.loader.load or tf.compat.v1.saved_model.load. There will be a new function for importing SavedModels in Tensorflow 2.0. WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.6/site-packages/tensorflow_model_analysis/eval_saved_model/load.py:169: load (from tensorflow.python.saved_model.loader_impl) is deprecated and will be removed in a future version. Instructions for updating: This function will only be available through the v1 compatibility library as tf.compat.v1.saved_model.loader.load or tf.compat.v1.saved_model.load. There will be a new function for importing SavedModels in Tensorflow 2.0. INFO:tensorflow:Restoring parameters from /tmp/tfma_eval_model/1615372025/variables/variables INFO:tensorflow:Restoring parameters from /tmp/tfma_eval_model/1615372025/variables/variables WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.6/site-packages/tensorflow_model_analysis/eval_saved_model/graph_ref.py:189: get_tensor_from_tensor_info (from tensorflow.python.saved_model.utils_impl) is deprecated and will be removed in a future version. Instructions for updating: This function will only be available through the v1 compatibility library as tf.compat.v1.saved_model.utils.get_tensor_from_tensor_info or tf.compat.v1.saved_model.get_tensor_from_tensor_info. WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.6/site-packages/tensorflow_model_analysis/eval_saved_model/graph_ref.py:189: get_tensor_from_tensor_info (from tensorflow.python.saved_model.utils_impl) is deprecated and will be removed in a future version. Instructions for updating: This function will only be available through the v1 compatibility library as tf.compat.v1.saved_model.utils.get_tensor_from_tensor_info or tf.compat.v1.saved_model.get_tensor_from_tensor_info. WARNING:apache_beam.io.tfrecordio:Couldn't find python-snappy so the implementation of _TFRecordUtil._masked_crc32c is not as fast as it could be. WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.6/site-packages/tensorflow_model_analysis/writers/metrics_plots_and_validations_writer.py:113: tf_record_iterator (from tensorflow.python.lib.io.tf_record) is deprecated and will be removed in a future version. Instructions for updating: Use eager execution and: `tf.data.TFRecordDataset(path)` WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.6/site-packages/tensorflow_model_analysis/writers/metrics_plots_and_validations_writer.py:113: tf_record_iterator (from tensorflow.python.lib.io.tf_record) is deprecated and will be removed in a future version. Instructions for updating: Use eager execution and: `tf.data.TFRecordDataset(path)`
Visualize Fairness Indicators in TensorBoard
Below you will visualize Fairness Indicators in Tensorboard and compare performance of each slice of the data on selected metrics. You can adjust the baseline comparison slice as well as the displayed threshold(s) using the drop down menus at the top of the visualization. You can also select different evaluation runs using the drop down menu at the top-left corner.
Write Fairness Indicators Summary
Write summary file containing all required information to visualize Fairness Indicators in TensorBoard.
import tensorflow.compat.v2 as tf2
writer = tf2.summary.create_file_writer(
os.path.join(model_dir, 'fairness_indicators'))
with writer.as_default():
summary_v2.FairnessIndicators(tfma_eval_result_path, step=1)
writer.close()
Launch TensorBoard
Navigate to "Fairness Indicators" tab to visualize Fairness Indicators.
%load_ext tensorboard
%tensorboard --logdir=$model_dir
ERROR: Failed to launch TensorBoard (exited with 1).
Contents of stderr:
2021-03-10 10:29:09.598370: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
Traceback (most recent call last):
File "/tmpfs/src/tf_docs_env/bin/tensorboard", line 8, in <module>
sys.exit(run_main())
File "/tmpfs/src/tf_docs_env/lib/python3.6/site-packages/tensorboard/main.py", line 65, in run_main
default.get_plugins(),
File "/tmpfs/src/tf_docs_env/lib/python3.6/site-packages/tensorboard/default.py", line 108, in get_plugins
return get_static_plugins() + get_dynamic_plugins()
File "/tmpfs/src/tf_docs_env/lib/python3.6/site-packages/tensorboard/default.py", line 146, in get_dynamic_plugins
"tensorboard_plugins"
File "/tmpfs/src/tf_docs_env/lib/python3.6/site-packages/tensorboard/default.py", line 145, in <listcomp>
for entry_point in pkg_resources.iter_entry_points(
File "/tmpfs/src/tf_docs_env/lib/python3.6/site-packages/pkg_resources/__init__.py", line 2449, in load
self.require(*args, **kwargs)
File "/tmpfs/src/tf_docs_env/lib/python3.6/site-packages/pkg_resources/__init__.py", line 2472, in require
items = working_set.resolve(reqs, env, installer, extras=self.extras)
File "/tmpfs/src/tf_docs_env/lib/python3.6/site-packages/pkg_resources/__init__.py", line 777, in resolve
raise VersionConflict(dist, req).with_context(dependent_req)
pkg_resources.ContextualVersionConflict: (absl-py 0.12.0 (/tmpfs/src/tf_docs_env/lib/python3.6/site-packages), Requirement.parse('absl-py<0.11,>=0.9'), {'tensorflow-model-analysis'})