Assign bug numbers to TODOs

PiperOrigin-RevId: 369773833

Author: fredrec

ci/kokoro/gcp_ubuntu/Dockerfile

@@ -15,7 +15,7 @@
 # An image for building prerequisites for testing TensorFlow Model Optimization
 # on ubuntu.
 #
-# TODO(tfmot): generalize to different versions of TensorFlow to
+# TODO(b/185727356): generalize to different versions of TensorFlow to
 # run CI against.
 #
 #  Build as follows:

ci/kokoro/gcp_ubuntu/build.sh

@@ -18,7 +18,7 @@
 # be used to reproduce errors locally by modifying WORKDIR to be
 # the top-level directory of the checked out TFMOT Github repository.
 
-# TODO(tfmot): switch to prebuilt Docker image to speed this up.
+# TODO(b/185727163): switch to prebuilt Docker image to speed this up.
 
 # Fail on any error.
 set -e

tensorflow_model_optimization/python/core/common/keras/compression/BUILD

@@ -7,7 +7,7 @@ py_library(
     visibility = ["//visibility:public"],
     deps = [
         "//tensorflow_model_optimization/python/core/common/keras/compression/internal:optimize",
-        #TODO(tfmot): remove when we stick to Python 3.7, which includes this by default.
+        #TODO(b/185726660): remove when we stick to Python 3.7, which includes this by default.
         # dataclasses dep1,
         # tensorflow dep1,
     ],

tensorflow_model_optimization/python/core/common/keras/compression/internal/BUILD

@@ -9,7 +9,7 @@ py_library(
     srcs = ["optimize.py"],
     srcs_version = "PY3",
     deps = [
-        #TODO(tfmot): remove when we stick to Python 3.7, which includes this by default.
+        #TODO(b/185726660): remove when we stick to Python 3.7, which includes this by default.
         # dataclasses dep1,
         # tensorflow dep1,
     ],

tensorflow_model_optimization/python/core/quantization/keras/default_8bit/default_8bit_transforms_test.py

@@ -379,7 +379,7 @@ def testAddReLUQuantize(self, activation_type, transform_type):
       ('relu', default_8bit_transforms.LayerReLUQuantize),
       ('act_relu', default_8bit_transforms.LayerReluActivationQuantize))
   def testLayerReLUQuantize(self, activation_type, transform_type):
-    # TODO(tfmot): Add tests for DepthConv and Dense
+    # TODO(b/185727342): Add tests for DepthConv and Dense
     input_shape = (1, 3, 3, 3)
     conv_layer = tf.keras.layers.Conv2D(5, 2, input_shape=input_shape)
     if activation_type == 'relu':

tensorflow_model_optimization/python/core/quantization/keras/quantize_wrapper_test.py

@@ -68,7 +68,7 @@ def testQuantizesWeightsInLayer(self):
   #  1. Only layers with 'kernel' attribute work. Need to extend to others.
   #  2. Activations are not tested currently.
   #  3. RNN layers need to be added
-  # TODO(tfmot): reenable some of these once added back to allowlist
+  # TODO(b/185968347): reenable some of these once added back to allowlist
   # after testing in quantize_functional_test.py.
   @parameterized.parameters(
       # (layers.Conv1D, (3, 6), {

tensorflow_model_optimization/python/core/sparsity/keras/prune_integration_test.py

@@ -121,7 +121,7 @@ def setUp(self):
     }
 
   # TODO(pulkitb): Also assert correct weights are pruned.
-  # TODO(tfmot): this should not be verified in all the unit tests.
+  # TODO(b/185968817): this should not be verified in all the unit tests.
   # As long as there are a few unit tests for strip_pruning,
   # these checks are redundant.
   def _check_strip_pruning_matches_original(

tensorflow_model_optimization/python/core/sparsity/keras/prune_test.py

@@ -397,7 +397,7 @@ def testPruneScope_NotNeededForTFCheckpoint(self):
     same_architecture_model.load_weights(tf_weights)
 
   def testPruneScope_NotNeededForTF2SavedModel(self):
-    # TODO(tfmot): replace with shared v1 test_util.
+    # TODO(b/185726968): replace with shared v1 test_util.
     is_v1_apis = hasattr(tf, 'assign')
     if is_v1_apis:
       return
@@ -413,7 +413,7 @@ def testPruneScope_NotNeededForTF2SavedModel(self):
     tf.saved_model.load(saved_model_dir)
 
   def testPruneScope_NeededForTF1SavedModel(self):
-    # TODO(tfmot): replace with shared v1 test_util.
+    # TODO(b/185726968): replace with shared v1 test_util.
     is_v1_apis = hasattr(tf, 'assign')
     if not is_v1_apis:
       return