diff --git a/tensorflow/python/keras/engine/base_layer.py b/tensorflow/python/keras/engine/base_layer.py
index 4b732c07bec..da6099aa186 100644
--- a/tensorflow/python/keras/engine/base_layer.py
+++ b/tensorflow/python/keras/engine/base_layer.py
@@ -96,9 +96,11 @@ _AUTOCAST_TYPES = (ops.Tensor, sparse_tensor.SparseTensor,
keras_layers_gauge = monitoring.BoolGauge('/tensorflow/api/keras/layers',
'keras layers usage', 'method')
+keras_models_gauge = monitoring.BoolGauge(
+ '/tensorflow/api/keras/models', 'keras model usage', 'method')
keras_api_gauge = monitoring.BoolGauge('/tensorflow/api/keras',
'keras api usage', 'method')
-keras_model_gauge = monitoring.BoolGauge(
+keras_premade_model_gauge = monitoring.BoolGauge(
'/tensorflow/api/keras/premade_models', 'premade keras model usage', 'type')
@@ -304,7 +306,10 @@ class Layer(module.Module, version_utils.LayerVersionSelector):
dynamic=False,
**kwargs):
keras_api_gauge.get_cell('layer').set(True)
- keras_layers_gauge.get_cell(self.__class__.__name__).set(True)
+ if getattr(self, '_is_model_for_instrumentation', False):
+ keras_models_gauge.get_cell(self.__class__.__name__).set(True)
+ else:
+ keras_layers_gauge.get_cell(self.__class__.__name__).set(True)
# These properties should be set by the user via keyword arguments.
# note that 'dtype', 'input_shape' and 'batch_input_shape'
# are only applicable to input layers: do not pass these keywords
diff --git a/tensorflow/python/keras/engine/data_adapter.py b/tensorflow/python/keras/engine/data_adapter.py
index f4c80feddc8..2cc6f69403e 100644
--- a/tensorflow/python/keras/engine/data_adapter.py
+++ b/tensorflow/python/keras/engine/data_adapter.py
@@ -34,6 +34,7 @@ from tensorflow.python.data.ops import dataset_ops
from tensorflow.python.distribute import distribution_strategy_context as ds_context
from tensorflow.python.distribute import input_lib
from tensorflow.python.eager import context
+from tensorflow.python.eager import monitoring
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
from tensorflow.python.framework import ops
@@ -52,6 +53,9 @@ from tensorflow.python.platform import tf_logging as logging
from tensorflow.python.util import nest
from tensorflow.python.util.tf_export import keras_export
+keras_data_adapter_gauge = monitoring.BoolGauge(
+ "/tensorflow/api/keras/data_adapters", "keras data adapter usage", "method")
+
try:
from scipy import sparse as scipy_sparse # pylint: disable=g-import-not-at-top
except ImportError:
@@ -961,6 +965,8 @@ def select_data_adapter(x, y):
"handling inputs. Found multiple adapters {} to handle "
"input: {}, {}".format(
adapter_cls, _type_name(x), _type_name(y)))
+ # Instrument the data adapter usage before returning it
+ keras_data_adapter_gauge.get_cell(adapter_cls[0].__name__).set(True)
return adapter_cls[0]
diff --git a/tensorflow/python/keras/engine/training.py b/tensorflow/python/keras/engine/training.py
index 1109c0d5ed8..2c228583a1d 100644
--- a/tensorflow/python/keras/engine/training.py
+++ b/tensorflow/python/keras/engine/training.py
@@ -218,6 +218,7 @@ class Model(base_layer.Layer, version_utils.ModelVersionSelector):
@trackable.no_automatic_dependency_tracking
def __init__(self, *args, **kwargs):
+ self._is_model_for_instrumentation = True
base_layer.keras_api_gauge.get_cell('model').set(True)
# Special case for Subclassed Functional Model, which we couldn't detect
diff --git a/tensorflow/python/keras/layers/core.py b/tensorflow/python/keras/layers/core.py
index c0932e7297b..ad3a881a794 100644
--- a/tensorflow/python/keras/layers/core.py
+++ b/tensorflow/python/keras/layers/core.py
@@ -30,6 +30,7 @@ import numpy as np
from tensorflow.python.eager import backprop
from tensorflow.python.eager import context
+from tensorflow.python.eager import monitoring
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
@@ -62,6 +63,13 @@ from tensorflow.python.util.tf_export import get_canonical_name_for_symbol
from tensorflow.python.util.tf_export import get_symbol_from_name
from tensorflow.python.util.tf_export import keras_export
+# TODO(b/168039935): track dropout rate to decide whether/how to make a
+# dropout rate fastpath.
+keras_temporary_dropout_rate = monitoring.BoolGauge(
+ '/tensorflow/api/keras/dropout/temp_rate_is_zero',
+ 'Temporarily record if Keras dropout layer was created w/'
+ 'constant rate = 0')
+
# pylint: disable=g-classes-have-attributes
@keras_export('keras.layers.Masking')
@@ -186,6 +194,10 @@ class Dropout(Layer):
def __init__(self, rate, noise_shape=None, seed=None, **kwargs):
super(Dropout, self).__init__(**kwargs)
self.rate = rate
+ if isinstance(rate, (int, float)) and not rate:
+ keras_temporary_dropout_rate.get_cell().set(True)
+ else:
+ keras_temporary_dropout_rate.get_cell().set(False)
self.noise_shape = noise_shape
self.seed = seed
self.supports_masking = True
diff --git a/tensorflow/python/keras/optimizer_v2/optimizer_v2.py b/tensorflow/python/keras/optimizer_v2/optimizer_v2.py
index 0da75edf0c5..ca3f1a3a9b1 100644
--- a/tensorflow/python/keras/optimizer_v2/optimizer_v2.py
+++ b/tensorflow/python/keras/optimizer_v2/optimizer_v2.py
@@ -30,6 +30,7 @@ from tensorflow.python.distribute import parameter_server_strategy
from tensorflow.python.distribute import values as ds_values
from tensorflow.python.eager import backprop
from tensorflow.python.eager import context
+from tensorflow.python.eager import monitoring
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.framework import tensor_util
@@ -54,6 +55,9 @@ from tensorflow.python.util import nest
from tensorflow.python.util.tf_export import keras_export
+keras_optimizers_gauge = monitoring.BoolGauge(
+ "/tensorflow/api/keras/optimizers", "keras optimizer usage", "method")
+
_DEFAULT_VALID_DTYPES = frozenset([
dtypes.float16, dtypes.bfloat16, dtypes.float32, dtypes.float64,
dtypes.complex64, dtypes.complex128
@@ -326,6 +330,9 @@ class OptimizerV2(trackable.Trackable):
Raises:
ValueError: in case of any invalid argument.
"""
+ # Instrument optimizer usages
+ keras_optimizers_gauge.get_cell(self.__class__.__name__).set(True)
+
allowed_kwargs = {"clipnorm", "clipvalue", "lr", "decay", "global_clipnorm"}
for k in kwargs:
if k not in allowed_kwargs:
diff --git a/tensorflow/python/keras/premade/linear.py b/tensorflow/python/keras/premade/linear.py
index 438e3270021..f8ea38fa5f6 100644
--- a/tensorflow/python/keras/premade/linear.py
+++ b/tensorflow/python/keras/premade/linear.py
@@ -95,7 +95,7 @@ class LinearModel(training.Model):
self.kernel_regularizer = regularizers.get(kernel_regularizer)
self.bias_regularizer = regularizers.get(bias_regularizer)
super(LinearModel, self).__init__(**kwargs)
- base_layer.keras_model_gauge.get_cell('Linear').set(True)
+ base_layer.keras_premade_model_gauge.get_cell('Linear').set(True)
def build(self, input_shape):
if isinstance(input_shape, dict):
diff --git a/tensorflow/python/keras/premade/wide_deep.py b/tensorflow/python/keras/premade/wide_deep.py
index edb0124276f..1f70a38cc93 100644
--- a/tensorflow/python/keras/premade/wide_deep.py
+++ b/tensorflow/python/keras/premade/wide_deep.py
@@ -85,7 +85,7 @@ class WideDeepModel(keras_training.Model):
Allowed keyword arguments include `name`.
"""
super(WideDeepModel, self).__init__(**kwargs)
- base_layer.keras_model_gauge.get_cell('WideDeep').set(True)
+ base_layer.keras_premade_model_gauge.get_cell('WideDeep').set(True)
self.linear_model = linear_model
self.dnn_model = dnn_model
self.activation = activations.get(activation)