Update Assert Statements For New TF 2.2.0 DLC

tests/tensorflow2/test_keras.py

@@ -14,7 +14,7 @@
 import tensorflow.compat.v2 as tf
 import tensorflow_datasets as tfds
 from tests.constants import TEST_DATASET_S3_PATH
-from tests.tensorflow2.utils import is_tf_2_2
+from tests.tensorflow2.utils import is_tf_2_2, is_tf_2_3
 from tests.tensorflow.utils import create_trial_fast_refresh
 from tests.utils import use_s3_datasets
 
@@ -195,7 +195,7 @@ def test_keras_gradtape(out_dir, saveall):
 
     trial = smd.create_trial(path=out_dir)
     if saveall:  # save losses, metrics, weights, biases
-        assert len(trial.tensor_names()) == 15
+        assert len(trial.tensor_names()) == (25 if is_tf_2_2() else 15)
         assert len(trial.tensor_names(collection=CollectionKeys.BIASES)) == 2
         assert len(trial.tensor_names(collection=CollectionKeys.WEIGHTS)) == 2
         assert len(trial.tensor_names(collection=CollectionKeys.OPTIMIZER_VARIABLES)) == 5
@@ -275,7 +275,7 @@ def test_gradtape_include_regex(out_dir):
     tr = create_trial_fast_refresh(out_dir)
     tnames = tr.tensor_names(collection="custom_coll")
 
-    assert len(tnames) == 8
+    assert len(tnames) == (12 if is_tf_2_2() else 8)
     for tname in tnames:
         assert tr.tensor(tname).value(0) is not None
 
@@ -343,7 +343,7 @@ def test_gradtape_include_collections(out_dir):
 
     trial = smd.create_trial(path=out_dir)
     # can't save gradients in TF 2.x
-    assert len(trial.tensor_names()) == 15
+    assert len(trial.tensor_names()) == (16 if is_tf_2_2() else 15)
     assert len(trial.tensor_names(collection=CollectionKeys.GRADIENTS)) == 4
     assert len(trial.tensor_names(collection=CollectionKeys.OPTIMIZER_VARIABLES)) == 5
     assert len(trial.tensor_names(collection=CollectionKeys.BIASES)) == 2
@@ -388,7 +388,7 @@ def test_gradtape_persistent(out_dir, saveall):
 
     trial = smd.create_trial(path=out_dir)
     if saveall:  # save losses, metrics, weights, biases
-        assert len(trial.tensor_names()) == 15
+        assert len(trial.tensor_names()) == (25 if is_tf_2_2() else 15)
         assert len(trial.tensor_names(collection=CollectionKeys.BIASES)) == 2
         assert len(trial.tensor_names(collection=CollectionKeys.WEIGHTS)) == 2
         assert len(trial.tensor_names(collection=CollectionKeys.OPTIMIZER_VARIABLES)) == 5
@@ -409,17 +409,24 @@ def test_keras_fit(out_dir, tf_eager_mode, saveall):
     helper_keras_fit(
         trial_dir=out_dir,
         hook=hook,
-        eager=tf_eager_mode,
+        run_eagerly=tf_eager_mode,
         steps=["train", "eval", "predict", "train"],
     )
 
     trial = smd.create_trial(path=out_dir)
     # can't save gradients in TF 2.x eager mode
     if saveall:  # save losses, metrics, weights, biases, scalar
         if tf_eager_mode:
-            assert len(trial.tensor_names()) == (13 if is_tf_2_2() else 14)
-            assert len(trial.tensor_names(collection=CollectionKeys.INPUTS)) == 0
-            assert len(trial.tensor_names(collection=CollectionKeys.OUTPUTS)) == 0
+            if is_tf_2_2():
+                assert len(trial.tensor_names()) == 28
+            else:
+                assert len(trial.tensor_names()) == (21 if is_tf_2_3() else 14)
+            assert len(trial.tensor_names(collection=CollectionKeys.INPUTS)) == (
+                1 if is_tf_2_2() else 0
+            )
+            assert len(trial.tensor_names(collection=CollectionKeys.OUTPUTS)) == (
+                2 if is_tf_2_2() else 0
+            )
         else:
             assert len(trial.tensor_names()) == 21
         assert len(trial.tensor_names(collection=CollectionKeys.BIASES)) == 2
@@ -435,10 +442,12 @@ def test_keras_fit(out_dir, tf_eager_mode, saveall):
             "No Optimizer Variables Should be Saved in EVAL Mode",
         )
     else:  # save the default losses and metrics
-        assert len(trial.tensor_names()) == (4 if is_tf_2_2() and tf_eager_mode else 5)
+        assert len(trial.tensor_names()) == (
+            4 if (is_tf_2_2() or is_tf_2_3()) and tf_eager_mode else 5
+        )
     assert len(trial.tensor_names(collection=CollectionKeys.LOSSES)) == 1
     assert len(trial.tensor_names(collection=CollectionKeys.METRICS)) == (
-        2 if is_tf_2_2() and tf_eager_mode else 3
+        2 if (is_tf_2_2() or is_tf_2_3()) and tf_eager_mode else 3
     )
     for tname in trial.tensor_names():
         assert trial.tensor(tname).value(0) is not None
@@ -510,7 +519,7 @@ def test_include_regex(out_dir, tf_eager_mode):
     tnames = tr.tensor_names(collection="custom_coll")
 
     if tf_eager_mode:
-        assert len(tnames) == 8
+        assert len(tnames) == (12 if is_tf_2_2() else 8)
     else:
         assert len(tnames) == 8
     for tname in tnames:
@@ -534,7 +543,7 @@ def test_clash_with_tb_callback(out_dir):
         add_callbacks=["tensorboard"],
     )
     tr = create_trial_fast_refresh(out_dir)
-    assert len(tr.tensor_names()) == (7 if is_tf_2_2() else 8)
+    assert len(tr.tensor_names()) == (7 if (is_tf_2_2() or is_tf_2_3()) else 8)
 
 
 @pytest.mark.slow
@@ -560,12 +569,12 @@ def test_weights_collections(out_dir, tf_eager_mode):
 
     trial = smd.create_trial(path=out_dir)
     # can't save gradients in TF 2.x
-    assert len(trial.tensor_names()) == (5 if is_tf_2_2() and tf_eager_mode else 6)
+    assert len(trial.tensor_names()) == (5 if (is_tf_2_2() or is_tf_2_3()) and tf_eager_mode else 6)
     assert len(trial.tensor_names(collection=CollectionKeys.BIASES)) == 0
     assert len(trial.tensor_names(collection=CollectionKeys.WEIGHTS)) == 2
     assert len(trial.tensor_names(collection=CollectionKeys.LOSSES)) == 1
     assert len(trial.tensor_names(collection=CollectionKeys.METRICS)) == (
-        2 if is_tf_2_2() and tf_eager_mode else 3
+        2 if (is_tf_2_2() or is_tf_2_3()) and tf_eager_mode else 3
     )
 
 
@@ -595,7 +604,10 @@ def test_include_collections(out_dir, tf_eager_mode):
     trial = smd.create_trial(path=out_dir)
     # can't save gradients in TF 2.x
     if tf_eager_mode:
-        assert len(trial.tensor_names()) == (12 if is_tf_2_2() else 13)
+        if is_tf_2_2():
+            assert len(trial.tensor_names()) == 16
+        else:
+            assert len(trial.tensor_names()) == (12 if is_tf_2_3() else 13)
     else:
         assert len(trial.tensor_names()) == 18
         assert len(trial.tensor_names(collection=CollectionKeys.GRADIENTS)) == 4
@@ -605,7 +617,7 @@ def test_include_collections(out_dir, tf_eager_mode):
     assert len(trial.tensor_names(collection=CollectionKeys.WEIGHTS)) == 2
     assert len(trial.tensor_names(collection=CollectionKeys.LOSSES)) == 1
     assert len(trial.tensor_names(collection=CollectionKeys.METRICS)) == (
-        2 if is_tf_2_2() and tf_eager_mode else 3
+        2 if (is_tf_2_2() or is_tf_2_3()) and tf_eager_mode else 3
     )
 
 
@@ -625,7 +637,7 @@ def test_include_only_custom_collection(out_dir, tf_eager_mode):
     )
 
     trial = smd.create_trial(path=out_dir)
-    assert len(trial.tensor_names()) == (8 if is_tf_2_2() and tf_eager_mode else 9)
+    assert len(trial.tensor_names()) == (8 if (is_tf_2_2() or is_tf_2_3()) and tf_eager_mode else 9)
     assert len(trial.tensor_names(collection="custom_optimizer_variables")) == 5
 
 
@@ -640,12 +652,12 @@ def test_hook_from_json(out_dir, tf_eager_mode, monkeypatch):
 
     trial = smd.create_trial(path=out_dir)
     # can't save gradients in TF 2.x
-    assert len(trial.tensor_names()) == (5 if is_tf_2_2() and tf_eager_mode else 6)
+    assert len(trial.tensor_names()) == (5 if (is_tf_2_2() or is_tf_2_3()) and tf_eager_mode else 6)
     assert len(trial.tensor_names(collection=CollectionKeys.BIASES)) == 0
     assert len(trial.tensor_names(collection=CollectionKeys.WEIGHTS)) == 2
     assert len(trial.tensor_names(collection=CollectionKeys.LOSSES)) == 1
     assert len(trial.tensor_names(collection=CollectionKeys.METRICS)) == (
-        2 if is_tf_2_2() and tf_eager_mode else 3
+        2 if (is_tf_2_2() or is_tf_2_3()) and tf_eager_mode else 3
     )
 
 
@@ -658,12 +670,15 @@ def test_keras_fit_pure_eager(out_dir, tf_eager_mode):
     helper_keras_fit(trial_dir=out_dir, hook=hook, eager=tf_eager_mode, run_eagerly=True)
 
     trial = smd.create_trial(path=out_dir)
-    assert len(trial.tensor_names()) == (20 if is_tf_2_2() else 21)
+    if is_tf_2_2():
+        assert len(trial.tensor_names()) == 27
+    else:
+        assert len(trial.tensor_names()) == (20 if is_tf_2_3() else 21)
     assert len(trial.tensor_names(collection=CollectionKeys.BIASES)) == 2
     assert len(trial.tensor_names(collection=CollectionKeys.WEIGHTS)) == 2
     assert len(trial.tensor_names(collection=CollectionKeys.OPTIMIZER_VARIABLES)) == 5
-    assert len(trial.tensor_names(collection=CollectionKeys.INPUTS)) == 0
-    assert len(trial.tensor_names(collection=CollectionKeys.OUTPUTS)) == 0
+    assert len(trial.tensor_names(collection=CollectionKeys.INPUTS)) == (1 if is_tf_2_2() else 0)
+    assert len(trial.tensor_names(collection=CollectionKeys.OUTPUTS)) == (2 if is_tf_2_2() else 0)
 
 
 @pytest.mark.skip  # skip until aws tf update

tests/tensorflow2/test_keras_mirrored.py

@@ -11,7 +11,7 @@
 import tensorflow_datasets as tfds
 from tensorflow.python.client import device_lib
 from tests.core.utils import verify_files
-from tests.tensorflow2.utils import is_tf_2_2
+from tests.tensorflow2.utils import is_tf_2_2, is_tf_2_3
 from tests.tensorflow.utils import create_trial_fast_refresh
 
 # First Party
@@ -164,11 +164,16 @@ def exhaustive_check(trial_dir, include_workers="one", eager=True):
     if include_workers == "all":
         assert len(tr.workers()) == strategy.num_replicas_in_sync
         if eager:
-            assert len(tr.tensor_names()) == (
-                6 + 1 + 2 + 5 + 1 if is_tf_2_2() else 6 + 1 + 3 + 5 + 1
-            )
-            # 6 weights, 1 loss, 3 metrics, 5 optimizer variables for Tf 2.1, 1 scalar
-            # 6 weights, 1 loss, 2 metrics, 5 optimizer variables for Tf 2.2, 1 scalar
+            if is_tf_2_2():
+                assert len(tr.tensor_names()) == (6 + 1 + 2 + 5 + 1 + 6 + 2)
+                # 6 weights, 1 loss, 2 metrics, 5 optimizer variables, 6 gradients, 2 outputs for Tf 2.2, 1 scalar
+            else:
+                assert len(tr.tensor_names()) == (
+                    6 + 1 + 2 + 5 + 1 if (is_tf_2_2() or is_tf_2_3()) else 6 + 1 + 3 + 5 + 1
+                )
+                # 6 weights, 1 loss, 2 metrics, 5 optimizer variables for Tf 2.3, 1 scalar
+                # 6 weights, 1 loss, 3 metrics, 5 optimizer variables for Tf 2.1, 1 scalar
+
         else:
             assert len(tr.tensor_names()) == (6 + 6 + 1 + 3 + strategy.num_replicas_in_sync * 3 + 5)
     else:
@@ -232,7 +237,7 @@ def exhaustive_check(trial_dir, include_workers="one", eager=True):
     assert len(tr.tensor(loss_name).steps()) == 12
 
     metricnames = tr.tensor_names(collection=CollectionKeys.METRICS)
-    assert len(metricnames) == (2 if is_tf_2_2() else 3)
+    assert len(metricnames) == (2 if (is_tf_2_2() or is_tf_2_3()) else 3)
 
 
 @pytest.mark.slow
@@ -256,8 +261,15 @@ def test_save_all(out_dir, tf_eager_mode, workers):
     tr = create_trial_fast_refresh(out_dir)
     print(tr.tensor_names())
     if tf_eager_mode:
-        assert len(tr.tensor_names()) == (6 + 2 + 1 + 5 + 1 if is_tf_2_2() else 6 + 3 + 1 + 5 + 1)
-        # weights, metrics, losses, optimizer variables, scalar
+        if is_tf_2_2():
+            assert len(tr.tensor_names()) == (
+                6 + 2 + 1 + 5 + 1 + 1 + 2 + 8 + 8 if is_tf_2_2() else 6 + 3 + 1 + 5 + 1
+            )
+            # weights, metrics, losses, optimizer variables, scalar, inputs, outputs, gradients, layers
+        else:
+            assert len(tr.tensor_names()) == (
+                6 + 2 + 1 + 5 + 1 if is_tf_2_3() else 6 + 3 + 1 + 5 + 1
+            )
     else:
         assert (
             len(tr.tensor_names())
@@ -366,7 +378,7 @@ def test_include_regex(out_dir, tf_eager_mode, workers):
     tnames = tr.tensor_names(collection="custom_coll")
 
     if tf_eager_mode:
-        assert len(tnames) == 4
+        assert len(tnames) == (12 if is_tf_2_2() else 4)
     else:
         assert len(tnames) == 4 + 3 * strategy.num_replicas_in_sync
     for tname in tnames:
@@ -421,7 +433,10 @@ def test_clash_with_tb_callback(out_dir):
         add_callbacks=["tensorboard"],
     )
     tr = create_trial_fast_refresh(out_dir)
-    assert len(tr.tensor_names()) == (10 if is_tf_2_2() else 11)
+    if is_tf_2_2():
+        assert len(tr.tensor_names()) == 16
+    else:
+        assert len(tr.tensor_names()) == (10 if is_tf_2_3() else 11)
 
 
 @pytest.mark.skip

tests/tensorflow2/utils.py

@@ -12,7 +12,7 @@ def is_tf_2_2():
     number of tensor_names emitted by 1.
     :return: bool
     """
-    if version.parse(tf.__version__) >= version.parse("2.2.0"):
+    if version.parse(tf.__version__) == version.parse("2.2.0"):
         return True
     return False
 

tests/zero_code_change/test_tensorflow2_gradtape_integration.py

@@ -12,7 +12,7 @@
 # Third Party
 import pytest
 import tensorflow.compat.v2 as tf
-from tests.tensorflow2.utils import is_tf_2_2
+from tests.tensorflow2.utils import is_tf_2_2, is_tf_2_3
 
 # First Party
 import smdebug.tensorflow as smd
@@ -26,7 +26,9 @@ def get_keras_data():
     return (x_train, y_train), (x_test, y_test)
 
 
-def helper_test_keras_v2_gradienttape(script_mode: bool = False, json_file_contents="{}"):
+def helper_test_keras_v2_gradienttape(
+    script_mode: bool = False, json_file_contents="{}", default=False
+):
     """ Test the default ZCC behavior of saving losses and metrics in eager and non-eager modes."""
     smd.del_hook()
     tf.keras.backend.clear_session()
@@ -49,7 +51,7 @@ def helper_test_keras_v2_gradienttape(script_mode: bool = False, json_file_conte
         opt = tf.keras.optimizers.RMSprop()
         cce = tf.keras.losses.CategoricalCrossentropy(from_logits=True)
         train_acc_metric = tf.keras.metrics.SparseCategoricalAccuracy()
-        n_epochs = 2
+        n_epochs = 1
         if script_mode:
             if json_file_contents == "{}":
                 hook = smd.KerasHook(out_dir=sim.out_dir, export_tensorboard=True)
@@ -100,7 +102,7 @@ def helper_test_keras_v2_gradienttape(script_mode: bool = False, json_file_conte
                 print(log)
                 train_acc_metric.reset_states()
             hook = smd.get_hook()
-            if not is_tf_2_2():
+            if not (is_tf_2_2() or is_tf_2_3()):
                 assert not hook  # only supported on TF 2.2 and greater
                 return
             assert hook
@@ -110,12 +112,23 @@ def helper_test_keras_v2_gradienttape(script_mode: bool = False, json_file_conte
             assert len(trial.steps()) > 0, "Nothing saved at any step."
             assert len(trial.tensor_names()) > 0, "Tensors were not saved."
             assert len(trial.tensor_names(collection="losses")) > 0
+            if is_tf_2_2() and default is False:
+                # Inputs and Outputs are not saved with the default collection configurations.
+                assert len(trial.tensor_names(collection="inputs")) > 0
+                assert len(trial.tensor_names(collection="outputs")) > 0
+                assert trial.tensor_names(collection="outputs") == ["predictions"]
+                if "dense_layers" in json_file_contents:
+                    # Only assert for test_keras_v2_multi_collections
+                    # which defines this custom collection
+                    assert len(trial.tensor_names(collection="dense_layers")) > 0
+                else:
+                    assert len(trial.tensor_names(collection="dense_layers")) == 0
 
 
 @pytest.mark.parametrize("script_mode", [False])
 def test_keras_v2_default(script_mode):
     # Test default ZCC behavior
-    helper_test_keras_v2_gradienttape(script_mode=script_mode)
+    helper_test_keras_v2_gradienttape(script_mode=script_mode, default=True)
 
 
 @pytest.mark.parametrize("script_mode", [False])
@@ -144,6 +157,18 @@ def test_keras_v2_multi_collections(script_mode):
                     },
                     {
                         "CollectionName": "optimizer_variables"
+                    },
+                    {
+                        "CollectionName": "outputs"
+                    },
+                    {
+                        "CollectionName": "inputs"
+                    },
+                    {
+                        "CollectionName": "dense_layers",
+                        "CollectionParameters": {
+                            "include_regex": ".*dense.*"
+                        }
                     }
                 ]
             }
@@ -161,7 +186,7 @@ def test_keras_v2_save_all(script_mode):
                 "S3OutputPath": "s3://sagemaker-test",
                 "LocalPath": "/opt/ml/output/tensors",
                 "HookParameters" : {
-                    "save_steps": "0,1,2,3",
+                    "save_steps": "0",
                     "save_all": true
                 }
             }