Export StringLookup and IntegerLookup layers.
PiperOrigin-RevId: 313801697
Change-Id: Ib159a0b7fe36e6d9d00a7e2d6bc6fbeb3c76af10
diff --git a/tensorflow/python/keras/layers/__init__.py b/tensorflow/python/keras/layers/__init__.py
index 36e58ef..8ce1c7d 100644
--- a/tensorflow/python/keras/layers/__init__.py
+++ b/tensorflow/python/keras/layers/__init__.py
@@ -47,19 +47,31 @@
from tensorflow.python.keras.layers.preprocessing.category_encoding import CategoryEncoding
from tensorflow.python.keras.layers.preprocessing.category_encoding_v1 import CategoryEncoding as CategoryEncodingV1
CategoryEncodingV2 = CategoryEncoding
+ from tensorflow.python.keras.layers.preprocessing.integer_lookup import IntegerLookup
+ from tensorflow.python.keras.layers.preprocessing.integer_lookup_v1 import IntegerLookup as IntegerLookupV1
+ IntegerLookupV2 = IntegerLookup
from tensorflow.python.keras.layers.preprocessing.normalization import Normalization
from tensorflow.python.keras.layers.preprocessing.normalization_v1 import Normalization as NormalizationV1
NormalizationV2 = Normalization
+ from tensorflow.python.keras.layers.preprocessing.string_lookup import StringLookup
+ from tensorflow.python.keras.layers.preprocessing.string_lookup_v1 import StringLookup as StringLookupV1
+ StringLookupV2 = StringLookup
from tensorflow.python.keras.layers.preprocessing.text_vectorization import TextVectorization
from tensorflow.python.keras.layers.preprocessing.text_vectorization_v1 import TextVectorization as TextVectorizationV1
TextVectorizationV2 = TextVectorization
else:
+ from tensorflow.python.keras.layers.preprocessing.integer_lookup_v1 import IntegerLookup
+ from tensorflow.python.keras.layers.preprocessing.integer_lookup import IntegerLookup as IntegerLookupV2
+ IntegerLookupV1 = IntegerLookup
from tensorflow.python.keras.layers.preprocessing.category_encoding_v1 import CategoryEncoding
from tensorflow.python.keras.layers.preprocessing.category_encoding import CategoryEncoding as CategoryEncodingV2
CategoryEncodingV1 = CategoryEncoding
from tensorflow.python.keras.layers.preprocessing.normalization_v1 import Normalization
from tensorflow.python.keras.layers.preprocessing.normalization import Normalization as NormalizationV2
NormalizationV1 = Normalization
+ from tensorflow.python.keras.layers.preprocessing.string_lookup_v1 import StringLookup
+ from tensorflow.python.keras.layers.preprocessing.string_lookup import StringLookup as StringLookupV2
+ StringLookupV1 = StringLookup
from tensorflow.python.keras.layers.preprocessing.text_vectorization_v1 import TextVectorization
from tensorflow.python.keras.layers.preprocessing.text_vectorization import TextVectorization as TextVectorizationV2
TextVectorizationV1 = TextVectorization
diff --git a/tensorflow/python/keras/layers/preprocessing/integer_lookup.py b/tensorflow/python/keras/layers/preprocessing/integer_lookup.py
index 6f49798..3512b99 100644
--- a/tensorflow/python/keras/layers/preprocessing/integer_lookup.py
+++ b/tensorflow/python/keras/layers/preprocessing/integer_lookup.py
@@ -20,8 +20,10 @@
from tensorflow.python.framework import dtypes
from tensorflow.python.keras.layers.preprocessing import index_lookup
from tensorflow.python.keras.layers.preprocessing import table_utils
+from tensorflow.python.util.tf_export import keras_export
+@keras_export("keras.layers.experimental.preprocessing.IntegerLookup", v1=[])
class IntegerLookup(index_lookup.IndexLookup):
"""Maps integers from a vocabulary to integer indices.
@@ -39,18 +41,18 @@
Attributes:
max_values: The maximum size of the vocabulary for this layer. If None,
there is no cap on the size of the vocabulary. Note that this vocabulary
- includes the OOV and mask tokens, so the effective number of tokens is
- (max_tokens - num_oov_tokens - (1 if mask_token else 0))
+ includes the OOV and mask values, so the effective number of values is
+ (max_values - num_oov_values - (1 if mask_token else 0))
num_oov_indices: The number of out-of-vocabulary values to use; defaults to
- 1. If this value is more than 1, OOV inputs are hashed to determine their
- OOV value; if this value is 0, passing an OOV input will result in a '-1'
- being returned for that value in the output tensor. (Note that, because
- the value is -1 and not 0, this will allow you to effectively drop OOV
- values from categorical encodings.)
+ 1. If this value is more than 1, OOV inputs are modulated to determine
+ their OOV value; if this value is 0, passing an OOV input will result in
+ a '-1' being returned for that value in the output tensor. (Note that,
+ because the value is -1 and not 0, this will allow you to effectively drop
+ OOV values from categorical encodings.)
mask_value: A value that represents masked inputs, and which is mapped to
index 0. Defaults to 0. If set to None, no mask term will be added and the
- OOV tokens, if any, will be indexed from (0...num_oov_tokens) instead of
- (1...num_oov_tokens+1).
+ OOV values, if any, will be indexed from (0...num_oov_values) instead of
+ (1...num_oov_values+1).
oov_value: The value representing an out-of-vocabulary value. Defaults to
-1.
vocabulary: An optional list of values, or a path to a text file containing
@@ -87,7 +89,7 @@
[0, -1, 42, 1138, 1000, 36, 12]
Note how the mask value 0 and the OOV value -1 have been added to the
- vocabulary. The remaining tokens are sorted by frequency (1138, which has
+ vocabulary. The remaining values are sorted by frequency (1138, which has
2 occurrences, is first) then by inverse sort order.
>>> data = tf.constant([[12, 1138, 42], [42, 1000, 36]])
@@ -99,6 +101,27 @@
[2, 4, 5]])>
+ Lookups with multiple OOV tokens.
+
+ This example demonstrates how to use a lookup layer with multiple OOV tokens.
+ When a layer is created with more than one OOV token, any OOV values are
+ hashed into the number of OOV buckets, distributing OOV values in a
+ deterministic fashion across the set.
+
+ >>> vocab = [12, 36, 1138, 42]
+ >>> data = tf.constant([[12, 1138, 42], [37, 1000, 36]])
+ >>> layer = IntegerLookup(vocabulary=vocab, num_oov_indices=2)
+ >>> layer(data)
+ <tf.Tensor: shape=(2, 3), dtype=int64, numpy=
+ array([[3, 5, 6],
+ [2, 1, 4]])>
+
+ Note that the output for OOV value 37 is 2, while the output for OOV value
+ 1000 is 1. The in-vocab terms have their output index increased by 1 from
+ earlier examples (12 maps to 3, etc) in order to make space for the extra OOV
+ value.
+
+
Inverse lookup
This example demonstrates how to map indices to values using this layer. (You
diff --git a/tensorflow/python/keras/layers/preprocessing/integer_lookup_v1.py b/tensorflow/python/keras/layers/preprocessing/integer_lookup_v1.py
index ec326f4..2a86e9d 100644
--- a/tensorflow/python/keras/layers/preprocessing/integer_lookup_v1.py
+++ b/tensorflow/python/keras/layers/preprocessing/integer_lookup_v1.py
@@ -19,7 +19,9 @@
from tensorflow.python.keras.layers.preprocessing import index_lookup_v1
from tensorflow.python.keras.layers.preprocessing import integer_lookup
+from tensorflow.python.util.tf_export import keras_export
+@keras_export(v1=["keras.layers.experimental.preprocessing.IntegerLookup"])
class IntegerLookup(integer_lookup.IntegerLookup, index_lookup_v1.IndexLookup):
pass
diff --git a/tensorflow/python/keras/layers/preprocessing/string_lookup.py b/tensorflow/python/keras/layers/preprocessing/string_lookup.py
index a420de8..d772f57 100644
--- a/tensorflow/python/keras/layers/preprocessing/string_lookup.py
+++ b/tensorflow/python/keras/layers/preprocessing/string_lookup.py
@@ -20,8 +20,10 @@
from tensorflow.python.framework import dtypes
from tensorflow.python.keras.layers.preprocessing import index_lookup
from tensorflow.python.keras.layers.preprocessing import table_utils
+from tensorflow.python.util.tf_export import keras_export
+@keras_export("keras.layers.experimental.preprocessing.StringLookup", v1=[])
class StringLookup(index_lookup.IndexLookup):
"""Maps strings from a vocabulary to integer indices.
@@ -52,7 +54,7 @@
will be added and the OOV tokens, if any, will be indexed from
(0...num_oov_indices) instead of (1...num_oov_indices+1).
oov_token: The token representing an out-of-vocabulary value. Defaults to
- "[OOV]".
+ "[UNK]".
vocabulary: An optional list of vocabulary terms, or a path to a text file
containing a vocabulary to load into this layer. The file should contain
one token per line. If the list or file contains the same token multiple
@@ -85,9 +87,9 @@
>>> layer = StringLookup()
>>> layer.adapt(data)
>>> layer.get_vocabulary()
- ['', '[OOV]', 'd', 'z', 'c', 'b', 'a']
+ ['', '[UNK]', 'd', 'z', 'c', 'b', 'a']
- Note how the mask token '' and the OOV token [OOV] have been added to the
+ Note how the mask token '' and the OOV token [UNK] have been added to the
vocabulary. The remaining tokens are sorted by frequency ('d', which has
2 occurrences, is first) then by inverse sort order.
@@ -99,6 +101,25 @@
array([[6, 4, 2],
[2, 3, 5]])>
+ Lookups with multiple OOV tokens.
+
+ This example demonstrates how to use a lookup layer with multiple OOV tokens.
+ When a layer is created with more than one OOV token, any OOV values are
+ hashed into the number of OOV buckets, distributing OOV values in a
+ deterministic fashion across the set.
+
+ >>> vocab = ["a", "b", "c", "d"]
+ >>> data = tf.constant([["a", "c", "d"], ["m", "z", "b"]])
+ >>> layer = StringLookup(vocabulary=vocab, num_oov_indices=2)
+ >>> layer(data)
+ <tf.Tensor: shape=(2, 3), dtype=int64, numpy=
+ array([[3, 5, 6],
+ [1, 2, 4]])>
+
+ Note that the output for OOV value 'm' is 1, while the output for OOV value
+ 'z' is 2. The in-vocab terms have their output index increased by 1 from
+ earlier examples (a maps to 3, etc) in order to make space for the extra OOV
+ value.
Inverse lookup
@@ -112,7 +133,7 @@
>>> layer(data)
<tf.Tensor: shape=(2, 3), dtype=string, numpy=
array([[b'a', b'c', b'd'],
- [b'd', b'[OOV]', b'b']], dtype=object)>
+ [b'd', b'[UNK]', b'b']], dtype=object)>
Note that the integer 5, which is out of the vocabulary space, returns an OOV
token.
@@ -131,9 +152,9 @@
>>> i_layer(int_data)
<tf.Tensor: shape=(2, 3), dtype=string, numpy=
array([[b'a', b'c', b'd'],
- [b'd', b'[OOV]', b'b']], dtype=object)>
+ [b'd', b'[UNK]', b'b']], dtype=object)>
- In this example, the input value 'z' resulted in an output of '[OOV]', since
+ In this example, the input value 'z' resulted in an output of '[UNK]', since
1000 was not in the vocabulary - it got represented as an OOV, and all OOV
values are returned as '[OOV}' in the inverse layer. Also, note that for the
inverse to work, you must have already set the forward layer vocabulary
@@ -144,9 +165,9 @@
max_tokens=None,
num_oov_indices=1,
mask_token="",
- oov_token="[OOV]",
+ oov_token="[UNK]",
vocabulary=None,
- encoding="utf-8",
+ encoding=None,
invert=False,
**kwargs):
allowed_dtypes = [dtypes.string]
@@ -158,6 +179,9 @@
if "dtype" not in kwargs:
kwargs["dtype"] = dtypes.string
+ if encoding is None:
+ encoding = "utf-8"
+
if vocabulary is not None:
if isinstance(vocabulary, str):
vocabulary = table_utils.get_vocabulary_from_file(vocabulary, encoding)
diff --git a/tensorflow/python/keras/layers/preprocessing/string_lookup_test.py b/tensorflow/python/keras/layers/preprocessing/string_lookup_test.py
index 0b9081d..2b45b59 100644
--- a/tensorflow/python/keras/layers/preprocessing/string_lookup_test.py
+++ b/tensorflow/python/keras/layers/preprocessing/string_lookup_test.py
@@ -36,6 +36,7 @@
from tensorflow.python.keras.layers.preprocessing import string_lookup_v1
from tensorflow.python.keras.saving import save
from tensorflow.python.keras.utils.generic_utils import CustomObjectScope
+from tensorflow.python.ops.ragged import ragged_factory_ops
from tensorflow.python.platform import gfile
from tensorflow.python.platform import test
@@ -155,7 +156,7 @@
def test_get_vocab_returns_str(self):
vocab_data = ["earth", "wind", "and", "fire"]
- expected_vocab = ["", "[OOV]", "earth", "wind", "and", "fire"]
+ expected_vocab = ["", "[UNK]", "earth", "wind", "and", "fire"]
layer = get_layer_class()(vocabulary=vocab_data)
layer_vocab = layer.get_vocabulary()
self.assertAllEqual(expected_vocab, layer_vocab)
@@ -205,7 +206,7 @@
input_array = np.array([["earth", "wind", "and", "fire"],
["fire", "and", "earth", "michigan"]])
expected_output = np.array([["earth", "wind", "and", "fire"],
- ["fire", "and", "earth", "[OOV]"]])
+ ["fire", "and", "earth", "[UNK]"]])
input_data = keras.Input(shape=(None,), dtype=dtypes.string)
layer = get_layer_class()(vocabulary=vocab_data)
@@ -217,6 +218,21 @@
output_dataset = model.predict(input_array)
self.assertAllEqual(expected_output, output_dataset)
+ def test_ragged_string_input_multi_bucket(self):
+ vocab_data = ["earth", "wind", "and", "fire"]
+ input_array = ragged_factory_ops.constant([["earth", "wind", "fire"],
+ ["fire", "and", "earth",
+ "ohio"]])
+ expected_output = [[3, 4, 6], [6, 5, 3, 2]]
+
+ input_data = keras.Input(shape=(None,), dtype=dtypes.string, ragged=True)
+ layer = get_layer_class()(num_oov_indices=2)
+ layer.set_vocabulary(vocab_data)
+ int_data = layer(input_data)
+ model = keras.Model(inputs=input_data, outputs=int_data)
+ output_dataset = model.predict(input_array)
+ self.assertAllEqual(expected_output, output_dataset)
+
@keras_parameterized.run_all_keras_modes(always_skip_eager=True)
class StringLookupSaveableTest(keras_parameterized.TestCase,
diff --git a/tensorflow/python/keras/layers/preprocessing/string_lookup_v1.py b/tensorflow/python/keras/layers/preprocessing/string_lookup_v1.py
index 0d4c70d..3b5d067 100644
--- a/tensorflow/python/keras/layers/preprocessing/string_lookup_v1.py
+++ b/tensorflow/python/keras/layers/preprocessing/string_lookup_v1.py
@@ -19,7 +19,9 @@
from tensorflow.python.keras.layers.preprocessing import index_lookup_v1
from tensorflow.python.keras.layers.preprocessing import string_lookup
+from tensorflow.python.util.tf_export import keras_export
+@keras_export(v1=["keras.layers.experimental.preprocessing.StringLookup"])
class StringLookup(string_lookup.StringLookup, index_lookup_v1.IndexLookup):
pass
diff --git a/tensorflow/python/keras/layers/serialization.py b/tensorflow/python/keras/layers/serialization.py
index 6b58a08..d990f20 100644
--- a/tensorflow/python/keras/layers/serialization.py
+++ b/tensorflow/python/keras/layers/serialization.py
@@ -51,8 +51,12 @@
from tensorflow.python.keras.layers.preprocessing import discretization
from tensorflow.python.keras.layers.preprocessing import hashing
from tensorflow.python.keras.layers.preprocessing import image_preprocessing
+from tensorflow.python.keras.layers.preprocessing import integer_lookup as preprocessing_integer_lookup
+from tensorflow.python.keras.layers.preprocessing import integer_lookup_v1 as preprocessing_integer_lookup_v1
from tensorflow.python.keras.layers.preprocessing import normalization as preprocessing_normalization
from tensorflow.python.keras.layers.preprocessing import normalization_v1 as preprocessing_normalization_v1
+from tensorflow.python.keras.layers.preprocessing import string_lookup as preprocessing_string_lookup
+from tensorflow.python.keras.layers.preprocessing import string_lookup_v1 as preprocessing_string_lookup_v1
from tensorflow.python.keras.layers.preprocessing import text_vectorization as preprocessing_text_vectorization
from tensorflow.python.keras.layers.preprocessing import text_vectorization_v1 as preprocessing_text_vectorization_v1
from tensorflow.python.keras.utils import generic_utils
@@ -63,11 +67,13 @@
ALL_MODULES = (base_layer, input_layer, advanced_activations, convolutional,
convolutional_recurrent, core, cudnn_recurrent, dense_attention,
embeddings, einsum_dense, local, merge, noise, normalization,
- pooling, image_preprocessing, preprocessing_normalization_v1,
+ pooling, image_preprocessing, preprocessing_integer_lookup_v1,
+ preprocessing_normalization_v1, preprocessing_string_lookup_v1,
preprocessing_text_vectorization_v1, recurrent, wrappers,
hashing, category_crossing, category_encoding_v1, discretization)
ALL_V2_MODULES = (rnn_cell_wrapper_v2, normalization_v2, recurrent_v2,
- preprocessing_normalization, preprocessing_text_vectorization,
+ preprocessing_integer_lookup, preprocessing_normalization,
+ preprocessing_string_lookup, preprocessing_text_vectorization,
category_encoding)
# ALL_OBJECTS is meant to be a global mutable. Hence we need to make it
# thread-local to avoid concurrent mutations.
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.keras.layers.experimental.preprocessing.-integer-lookup.__metaclass__.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.keras.layers.experimental.preprocessing.-integer-lookup.__metaclass__.pbtxt
new file mode 100644
index 0000000..409509c
--- /dev/null
+++ b/tensorflow/tools/api/golden/v1/tensorflow.keras.layers.experimental.preprocessing.-integer-lookup.__metaclass__.pbtxt
@@ -0,0 +1,14 @@
+path: "tensorflow.keras.layers.experimental.preprocessing.IntegerLookup.__metaclass__"
+tf_class {
+ is_instance: "<type \'type\'>"
+ member_method {
+ name: "__init__"
+ }
+ member_method {
+ name: "mro"
+ }
+ member_method {
+ name: "register"
+ argspec: "args=[\'cls\', \'subclass\'], varargs=None, keywords=None, defaults=None"
+ }
+}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.keras.layers.experimental.preprocessing.-integer-lookup.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.keras.layers.experimental.preprocessing.-integer-lookup.pbtxt
new file mode 100644
index 0000000..c005276
--- /dev/null
+++ b/tensorflow/tools/api/golden/v1/tensorflow.keras.layers.experimental.preprocessing.-integer-lookup.pbtxt
@@ -0,0 +1,240 @@
+path: "tensorflow.keras.layers.experimental.preprocessing.IntegerLookup"
+tf_class {
+ is_instance: "<class \'tensorflow.python.keras.layers.preprocessing.integer_lookup_v1.IntegerLookup\'>"
+ is_instance: "<class \'tensorflow.python.keras.layers.preprocessing.integer_lookup.IntegerLookup\'>"
+ is_instance: "<class \'tensorflow.python.keras.layers.preprocessing.index_lookup_v1.IndexLookup\'>"
+ is_instance: "<class \'tensorflow.python.keras.layers.preprocessing.index_lookup.IndexLookup\'>"
+ is_instance: "<class \'tensorflow.python.keras.engine.base_preprocessing_layer_v1.CombinerPreprocessingLayer\'>"
+ is_instance: "<class \'tensorflow.python.keras.engine.base_preprocessing_layer.CombinerPreprocessingLayer\'>"
+ is_instance: "<class \'tensorflow.python.keras.engine.base_preprocessing_layer.PreprocessingLayer\'>"
+ is_instance: "<class \'tensorflow.python.keras.engine.base_layer.Layer\'>"
+ is_instance: "<class \'tensorflow.python.module.module.Module\'>"
+ is_instance: "<class \'tensorflow.python.training.tracking.tracking.AutoTrackable\'>"
+ is_instance: "<class \'tensorflow.python.training.tracking.base.Trackable\'>"
+ is_instance: "<class \'tensorflow.python.keras.utils.version_utils.LayerVersionSelector\'>"
+ is_instance: "<type \'object\'>"
+ member {
+ name: "activity_regularizer"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "dtype"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "dynamic"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "inbound_nodes"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "input"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "input_mask"
+ mtype: "<type \'property\'>"
+ }
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+ name: "input_shape"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "input_spec"
+ mtype: "<type \'property\'>"
+ }
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+ name: "losses"
+ mtype: "<type \'property\'>"
+ }
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+ name: "metrics"
+ mtype: "<type \'property\'>"
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+ mtype: "<type \'property\'>"
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+ mtype: "<type \'property\'>"
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+ name: "stateful"
+ mtype: "<type \'property\'>"
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+ name: "submodules"
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+ mtype: "<type \'property\'>"
+ }
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+ mtype: "<type \'property\'>"
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+ mtype: "<type \'property\'>"
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+ mtype: "<type \'property\'>"
+ }
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+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "weights"
+ mtype: "<type \'property\'>"
+ }
+ member_method {
+ name: "__init__"
+ argspec: "args=[\'self\', \'max_values\', \'num_oov_indices\', \'mask_value\', \'oov_value\', \'vocabulary\', \'invert\'], varargs=None, keywords=kwargs, defaults=[\'None\', \'1\', \'0\', \'-1\', \'None\', \'False\'], "
+ }
+ member_method {
+ name: "adapt"
+ argspec: "args=[\'self\', \'data\', \'reset_state\'], varargs=None, keywords=None, defaults=[\'True\'], "
+ }
+ member_method {
+ name: "add_loss"
+ argspec: "args=[\'self\', \'losses\'], varargs=None, keywords=kwargs, defaults=None"
+ }
+ member_method {
+ name: "add_metric"
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+ }
+ member_method {
+ name: "add_update"
+ argspec: "args=[\'self\', \'updates\', \'inputs\'], varargs=None, keywords=None, defaults=[\'None\'], "
+ }
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+ name: "add_variable"
+ argspec: "args=[\'self\'], varargs=args, keywords=kwargs, defaults=None"
+ }
+ member_method {
+ name: "add_weight"
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+ argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_input_at"
+ argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_input_mask_at"
+ argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_input_shape_at"
+ argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_losses_for"
+ argspec: "args=[\'self\', \'inputs\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_output_at"
+ argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_output_mask_at"
+ argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_output_shape_at"
+ argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_updates_for"
+ argspec: "args=[\'self\', \'inputs\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_vocabulary"
+ argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_weights"
+ argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "set_vocabulary"
+ argspec: "args=[\'self\', \'vocab\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "set_weights"
+ argspec: "args=[\'self\', \'weights\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "vocab_size"
+ argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "with_name_scope"
+ argspec: "args=[\'cls\', \'method\'], varargs=None, keywords=None, defaults=None"
+ }
+}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.keras.layers.experimental.preprocessing.-string-lookup.__metaclass__.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.keras.layers.experimental.preprocessing.-string-lookup.__metaclass__.pbtxt
new file mode 100644
index 0000000..4cb5735
--- /dev/null
+++ b/tensorflow/tools/api/golden/v1/tensorflow.keras.layers.experimental.preprocessing.-string-lookup.__metaclass__.pbtxt
@@ -0,0 +1,14 @@
+path: "tensorflow.keras.layers.experimental.preprocessing.StringLookup.__metaclass__"
+tf_class {
+ is_instance: "<type \'type\'>"
+ member_method {
+ name: "__init__"
+ }
+ member_method {
+ name: "mro"
+ }
+ member_method {
+ name: "register"
+ argspec: "args=[\'cls\', \'subclass\'], varargs=None, keywords=None, defaults=None"
+ }
+}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.keras.layers.experimental.preprocessing.-string-lookup.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.keras.layers.experimental.preprocessing.-string-lookup.pbtxt
new file mode 100644
index 0000000..1deb932
--- /dev/null
+++ b/tensorflow/tools/api/golden/v1/tensorflow.keras.layers.experimental.preprocessing.-string-lookup.pbtxt
@@ -0,0 +1,240 @@
+path: "tensorflow.keras.layers.experimental.preprocessing.StringLookup"
+tf_class {
+ is_instance: "<class \'tensorflow.python.keras.layers.preprocessing.string_lookup_v1.StringLookup\'>"
+ is_instance: "<class \'tensorflow.python.keras.layers.preprocessing.string_lookup.StringLookup\'>"
+ is_instance: "<class \'tensorflow.python.keras.layers.preprocessing.index_lookup_v1.IndexLookup\'>"
+ is_instance: "<class \'tensorflow.python.keras.layers.preprocessing.index_lookup.IndexLookup\'>"
+ is_instance: "<class \'tensorflow.python.keras.engine.base_preprocessing_layer_v1.CombinerPreprocessingLayer\'>"
+ is_instance: "<class \'tensorflow.python.keras.engine.base_preprocessing_layer.CombinerPreprocessingLayer\'>"
+ is_instance: "<class \'tensorflow.python.keras.engine.base_preprocessing_layer.PreprocessingLayer\'>"
+ is_instance: "<class \'tensorflow.python.keras.engine.base_layer.Layer\'>"
+ is_instance: "<class \'tensorflow.python.module.module.Module\'>"
+ is_instance: "<class \'tensorflow.python.training.tracking.tracking.AutoTrackable\'>"
+ is_instance: "<class \'tensorflow.python.training.tracking.base.Trackable\'>"
+ is_instance: "<class \'tensorflow.python.keras.utils.version_utils.LayerVersionSelector\'>"
+ is_instance: "<type \'object\'>"
+ member {
+ name: "activity_regularizer"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "dtype"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "dynamic"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "inbound_nodes"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "input"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "input_mask"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "input_shape"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "input_spec"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "losses"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "metrics"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "name"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "name_scope"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "non_trainable_weights"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "outbound_nodes"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "output"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "output_mask"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "output_shape"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "stateful"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "submodules"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "trainable"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "trainable_weights"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "updates"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "weights"
+ mtype: "<type \'property\'>"
+ }
+ member_method {
+ name: "__init__"
+ argspec: "args=[\'self\', \'max_tokens\', \'num_oov_indices\', \'mask_token\', \'oov_token\', \'vocabulary\', \'encoding\', \'invert\'], varargs=None, keywords=kwargs, defaults=[\'None\', \'1\', \'\', \'[UNK]\', \'None\', \'None\', \'False\'], "
+ }
+ member_method {
+ name: "adapt"
+ argspec: "args=[\'self\', \'data\', \'reset_state\'], varargs=None, keywords=None, defaults=[\'True\'], "
+ }
+ member_method {
+ name: "add_loss"
+ argspec: "args=[\'self\', \'losses\'], varargs=None, keywords=kwargs, defaults=None"
+ }
+ member_method {
+ name: "add_metric"
+ argspec: "args=[\'self\', \'value\', \'name\'], varargs=None, keywords=kwargs, defaults=[\'None\'], "
+ }
+ member_method {
+ name: "add_update"
+ argspec: "args=[\'self\', \'updates\', \'inputs\'], varargs=None, keywords=None, defaults=[\'None\'], "
+ }
+ member_method {
+ name: "add_variable"
+ argspec: "args=[\'self\'], varargs=args, keywords=kwargs, defaults=None"
+ }
+ member_method {
+ name: "add_weight"
+ argspec: "args=[\'self\', \'name\', \'shape\', \'dtype\', \'initializer\', \'regularizer\', \'trainable\', \'constraint\', \'partitioner\', \'use_resource\', \'synchronization\', \'aggregation\'], varargs=None, keywords=kwargs, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'VariableSynchronization.AUTO\', \'VariableAggregation.NONE\'], "
+ }
+ member_method {
+ name: "apply"
+ argspec: "args=[\'self\', \'inputs\'], varargs=args, keywords=kwargs, defaults=None"
+ }
+ member_method {
+ name: "build"
+ argspec: "args=[\'self\', \'input_shape\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "call"
+ argspec: "args=[\'self\', \'inputs\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "compute_mask"
+ argspec: "args=[\'self\', \'inputs\', \'mask\'], varargs=None, keywords=None, defaults=[\'None\'], "
+ }
+ member_method {
+ name: "compute_output_shape"
+ argspec: "args=[\'self\', \'input_shape\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "compute_output_signature"
+ argspec: "args=[\'self\', \'input_spec\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "count_params"
+ argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "from_config"
+ argspec: "args=[\'cls\', \'config\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_config"
+ argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_input_at"
+ argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_input_mask_at"
+ argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_input_shape_at"
+ argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_losses_for"
+ argspec: "args=[\'self\', \'inputs\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_output_at"
+ argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_output_mask_at"
+ argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_output_shape_at"
+ argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_updates_for"
+ argspec: "args=[\'self\', \'inputs\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_vocabulary"
+ argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_weights"
+ argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "set_vocabulary"
+ argspec: "args=[\'self\', \'vocab\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "set_weights"
+ argspec: "args=[\'self\', \'weights\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "vocab_size"
+ argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "with_name_scope"
+ argspec: "args=[\'cls\', \'method\'], varargs=None, keywords=None, defaults=None"
+ }
+}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.keras.layers.experimental.preprocessing.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.keras.layers.experimental.preprocessing.pbtxt
index 4a0522d..94f6e3b 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.keras.layers.experimental.preprocessing.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.keras.layers.experimental.preprocessing.pbtxt
@@ -21,6 +21,10 @@
mtype: "<type \'type\'>"
}
member {
+ name: "IntegerLookup"
+ mtype: "<type \'type\'>"
+ }
+ member {
name: "Normalization"
mtype: "<type \'type\'>"
}
@@ -69,6 +73,10 @@
mtype: "<type \'type\'>"
}
member {
+ name: "StringLookup"
+ mtype: "<type \'type\'>"
+ }
+ member {
name: "TextVectorization"
mtype: "<type \'type\'>"
}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.keras.layers.experimental.preprocessing.-integer-lookup.__metaclass__.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.keras.layers.experimental.preprocessing.-integer-lookup.__metaclass__.pbtxt
new file mode 100644
index 0000000..409509c
--- /dev/null
+++ b/tensorflow/tools/api/golden/v2/tensorflow.keras.layers.experimental.preprocessing.-integer-lookup.__metaclass__.pbtxt
@@ -0,0 +1,14 @@
+path: "tensorflow.keras.layers.experimental.preprocessing.IntegerLookup.__metaclass__"
+tf_class {
+ is_instance: "<type \'type\'>"
+ member_method {
+ name: "__init__"
+ }
+ member_method {
+ name: "mro"
+ }
+ member_method {
+ name: "register"
+ argspec: "args=[\'cls\', \'subclass\'], varargs=None, keywords=None, defaults=None"
+ }
+}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.keras.layers.experimental.preprocessing.-integer-lookup.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.keras.layers.experimental.preprocessing.-integer-lookup.pbtxt
new file mode 100644
index 0000000..dedb0f3
--- /dev/null
+++ b/tensorflow/tools/api/golden/v2/tensorflow.keras.layers.experimental.preprocessing.-integer-lookup.pbtxt
@@ -0,0 +1,237 @@
+path: "tensorflow.keras.layers.experimental.preprocessing.IntegerLookup"
+tf_class {
+ is_instance: "<class \'tensorflow.python.keras.layers.preprocessing.integer_lookup.IntegerLookup\'>"
+ is_instance: "<class \'tensorflow.python.keras.layers.preprocessing.index_lookup.IndexLookup\'>"
+ is_instance: "<class \'tensorflow.python.keras.engine.base_preprocessing_layer.CombinerPreprocessingLayer\'>"
+ is_instance: "<class \'tensorflow.python.keras.engine.base_preprocessing_layer.PreprocessingLayer\'>"
+ is_instance: "<class \'tensorflow.python.keras.engine.base_layer.Layer\'>"
+ is_instance: "<class \'tensorflow.python.module.module.Module\'>"
+ is_instance: "<class \'tensorflow.python.training.tracking.tracking.AutoTrackable\'>"
+ is_instance: "<class \'tensorflow.python.training.tracking.base.Trackable\'>"
+ is_instance: "<class \'tensorflow.python.keras.utils.version_utils.LayerVersionSelector\'>"
+ is_instance: "<type \'object\'>"
+ member {
+ name: "activity_regularizer"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "dtype"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "dynamic"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "inbound_nodes"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "input"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "input_mask"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "input_shape"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "input_spec"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "losses"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "metrics"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "name"
+ mtype: "<type \'property\'>"
+ }
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+ name: "name_scope"
+ mtype: "<type \'property\'>"
+ }
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+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "non_trainable_weights"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "outbound_nodes"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "output"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "output_mask"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "output_shape"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "stateful"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "submodules"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "trainable"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "trainable_weights"
+ mtype: "<type \'property\'>"
+ }
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+ name: "updates"
+ mtype: "<type \'property\'>"
+ }
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+ name: "variables"
+ mtype: "<type \'property\'>"
+ }
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+ name: "weights"
+ mtype: "<type \'property\'>"
+ }
+ member_method {
+ name: "__init__"
+ argspec: "args=[\'self\', \'max_values\', \'num_oov_indices\', \'mask_value\', \'oov_value\', \'vocabulary\', \'invert\'], varargs=None, keywords=kwargs, defaults=[\'None\', \'1\', \'0\', \'-1\', \'None\', \'False\'], "
+ }
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+ name: "adapt"
+ argspec: "args=[\'self\', \'data\', \'reset_state\'], varargs=None, keywords=None, defaults=[\'True\'], "
+ }
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+ name: "add_loss"
+ argspec: "args=[\'self\', \'losses\'], varargs=None, keywords=kwargs, defaults=None"
+ }
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+ name: "add_metric"
+ argspec: "args=[\'self\', \'value\', \'name\'], varargs=None, keywords=kwargs, defaults=[\'None\'], "
+ }
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+ }
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+ argspec: "args=[\'self\', \'name\', \'shape\', \'dtype\', \'initializer\', \'regularizer\', \'trainable\', \'constraint\', \'partitioner\', \'use_resource\', \'synchronization\', \'aggregation\'], varargs=None, keywords=kwargs, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'VariableSynchronization.AUTO\', \'VariableAggregation.NONE\'], "
+ }
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+ }
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+ }
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+ }
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+ argspec: "args=[\'self\', \'inputs\', \'mask\'], varargs=None, keywords=None, defaults=[\'None\'], "
+ }
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+ name: "compute_output_shape"
+ argspec: "args=[\'self\', \'input_shape\'], varargs=None, keywords=None, defaults=None"
+ }
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+ argspec: "args=[\'self\', \'input_spec\'], varargs=None, keywords=None, defaults=None"
+ }
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+ name: "count_params"
+ argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+ }
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+ name: "from_config"
+ argspec: "args=[\'cls\', \'config\'], varargs=None, keywords=None, defaults=None"
+ }
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+ name: "get_config"
+ argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+ }
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+ name: "get_input_at"
+ argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
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+ name: "get_input_mask_at"
+ argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
+ }
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+ name: "get_input_shape_at"
+ argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
+ }
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+ name: "get_losses_for"
+ argspec: "args=[\'self\', \'inputs\'], varargs=None, keywords=None, defaults=None"
+ }
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+ name: "get_output_at"
+ argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
+ }
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+ name: "get_output_mask_at"
+ argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
+ }
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+ name: "get_output_shape_at"
+ argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
+ }
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+ name: "get_updates_for"
+ argspec: "args=[\'self\', \'inputs\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_vocabulary"
+ argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+ }
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+ name: "get_weights"
+ argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+ }
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+ name: "set_vocabulary"
+ argspec: "args=[\'self\', \'vocab\'], varargs=None, keywords=None, defaults=None"
+ }
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+ name: "set_weights"
+ argspec: "args=[\'self\', \'weights\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "vocab_size"
+ argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "with_name_scope"
+ argspec: "args=[\'cls\', \'method\'], varargs=None, keywords=None, defaults=None"
+ }
+}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.keras.layers.experimental.preprocessing.-string-lookup.__metaclass__.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.keras.layers.experimental.preprocessing.-string-lookup.__metaclass__.pbtxt
new file mode 100644
index 0000000..4cb5735
--- /dev/null
+++ b/tensorflow/tools/api/golden/v2/tensorflow.keras.layers.experimental.preprocessing.-string-lookup.__metaclass__.pbtxt
@@ -0,0 +1,14 @@
+path: "tensorflow.keras.layers.experimental.preprocessing.StringLookup.__metaclass__"
+tf_class {
+ is_instance: "<type \'type\'>"
+ member_method {
+ name: "__init__"
+ }
+ member_method {
+ name: "mro"
+ }
+ member_method {
+ name: "register"
+ argspec: "args=[\'cls\', \'subclass\'], varargs=None, keywords=None, defaults=None"
+ }
+}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.keras.layers.experimental.preprocessing.-string-lookup.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.keras.layers.experimental.preprocessing.-string-lookup.pbtxt
new file mode 100644
index 0000000..b419e77
--- /dev/null
+++ b/tensorflow/tools/api/golden/v2/tensorflow.keras.layers.experimental.preprocessing.-string-lookup.pbtxt
@@ -0,0 +1,237 @@
+path: "tensorflow.keras.layers.experimental.preprocessing.StringLookup"
+tf_class {
+ is_instance: "<class \'tensorflow.python.keras.layers.preprocessing.string_lookup.StringLookup\'>"
+ is_instance: "<class \'tensorflow.python.keras.layers.preprocessing.index_lookup.IndexLookup\'>"
+ is_instance: "<class \'tensorflow.python.keras.engine.base_preprocessing_layer.CombinerPreprocessingLayer\'>"
+ is_instance: "<class \'tensorflow.python.keras.engine.base_preprocessing_layer.PreprocessingLayer\'>"
+ is_instance: "<class \'tensorflow.python.keras.engine.base_layer.Layer\'>"
+ is_instance: "<class \'tensorflow.python.module.module.Module\'>"
+ is_instance: "<class \'tensorflow.python.training.tracking.tracking.AutoTrackable\'>"
+ is_instance: "<class \'tensorflow.python.training.tracking.base.Trackable\'>"
+ is_instance: "<class \'tensorflow.python.keras.utils.version_utils.LayerVersionSelector\'>"
+ is_instance: "<type \'object\'>"
+ member {
+ name: "activity_regularizer"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "dtype"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "dynamic"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "inbound_nodes"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "input"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "input_mask"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "input_shape"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "input_spec"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "losses"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "metrics"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "name"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "name_scope"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "non_trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "non_trainable_weights"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "outbound_nodes"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "output"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "output_mask"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "output_shape"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "stateful"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "submodules"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "trainable"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "trainable_variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "trainable_weights"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "updates"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "variables"
+ mtype: "<type \'property\'>"
+ }
+ member {
+ name: "weights"
+ mtype: "<type \'property\'>"
+ }
+ member_method {
+ name: "__init__"
+ argspec: "args=[\'self\', \'max_tokens\', \'num_oov_indices\', \'mask_token\', \'oov_token\', \'vocabulary\', \'encoding\', \'invert\'], varargs=None, keywords=kwargs, defaults=[\'None\', \'1\', \'\', \'[UNK]\', \'None\', \'None\', \'False\'], "
+ }
+ member_method {
+ name: "adapt"
+ argspec: "args=[\'self\', \'data\', \'reset_state\'], varargs=None, keywords=None, defaults=[\'True\'], "
+ }
+ member_method {
+ name: "add_loss"
+ argspec: "args=[\'self\', \'losses\'], varargs=None, keywords=kwargs, defaults=None"
+ }
+ member_method {
+ name: "add_metric"
+ argspec: "args=[\'self\', \'value\', \'name\'], varargs=None, keywords=kwargs, defaults=[\'None\'], "
+ }
+ member_method {
+ name: "add_update"
+ argspec: "args=[\'self\', \'updates\', \'inputs\'], varargs=None, keywords=None, defaults=[\'None\'], "
+ }
+ member_method {
+ name: "add_variable"
+ argspec: "args=[\'self\'], varargs=args, keywords=kwargs, defaults=None"
+ }
+ member_method {
+ name: "add_weight"
+ argspec: "args=[\'self\', \'name\', \'shape\', \'dtype\', \'initializer\', \'regularizer\', \'trainable\', \'constraint\', \'partitioner\', \'use_resource\', \'synchronization\', \'aggregation\'], varargs=None, keywords=kwargs, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'VariableSynchronization.AUTO\', \'VariableAggregation.NONE\'], "
+ }
+ member_method {
+ name: "apply"
+ argspec: "args=[\'self\', \'inputs\'], varargs=args, keywords=kwargs, defaults=None"
+ }
+ member_method {
+ name: "build"
+ argspec: "args=[\'self\', \'input_shape\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "call"
+ argspec: "args=[\'self\', \'inputs\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "compute_mask"
+ argspec: "args=[\'self\', \'inputs\', \'mask\'], varargs=None, keywords=None, defaults=[\'None\'], "
+ }
+ member_method {
+ name: "compute_output_shape"
+ argspec: "args=[\'self\', \'input_shape\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "compute_output_signature"
+ argspec: "args=[\'self\', \'input_spec\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "count_params"
+ argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "from_config"
+ argspec: "args=[\'cls\', \'config\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_config"
+ argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_input_at"
+ argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_input_mask_at"
+ argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_input_shape_at"
+ argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_losses_for"
+ argspec: "args=[\'self\', \'inputs\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_output_at"
+ argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_output_mask_at"
+ argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_output_shape_at"
+ argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_updates_for"
+ argspec: "args=[\'self\', \'inputs\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_vocabulary"
+ argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_weights"
+ argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "set_vocabulary"
+ argspec: "args=[\'self\', \'vocab\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "set_weights"
+ argspec: "args=[\'self\', \'weights\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "vocab_size"
+ argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "with_name_scope"
+ argspec: "args=[\'cls\', \'method\'], varargs=None, keywords=None, defaults=None"
+ }
+}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.keras.layers.experimental.preprocessing.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.keras.layers.experimental.preprocessing.pbtxt
index 4a0522d..94f6e3b 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.keras.layers.experimental.preprocessing.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.keras.layers.experimental.preprocessing.pbtxt
@@ -21,6 +21,10 @@
mtype: "<type \'type\'>"
}
member {
+ name: "IntegerLookup"
+ mtype: "<type \'type\'>"
+ }
+ member {
name: "Normalization"
mtype: "<type \'type\'>"
}
@@ -69,6 +73,10 @@
mtype: "<type \'type\'>"
}
member {
+ name: "StringLookup"
+ mtype: "<type \'type\'>"
+ }
+ member {
name: "TextVectorization"
mtype: "<type \'type\'>"
}
