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Make new Model methods public.

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PiperOrigin-RevId: 297727907
Change-Id: I8734601149976bb46c5c37988d53208806ee76b7
This commit is contained in:
Thomas O'Malley 2020-02-27 17:20:14 -08:00 committed by TensorFlower Gardener
parent dbb1058655
commit 4a8f4803f6
17 changed files with 324 additions and 27 deletions
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43
tensorflow/python/keras/engine/training.py
View File

@ -173,6 +173,12 @@ class Model(network.Network, version_utils.ModelVersionSelector):
self._training_state = None
self.history = None
# These objects are used in the default `Model.compile`. They are not
# guaranteed to be set after `Model.compile` is called, as users can
# override compile with custom logic.
self.compiled_loss = None
self.compiled_metrics = None
def get_weights(self):
"""Retrieves the weights of the model.
@ -349,9 +355,12 @@ class Model(network.Network, version_utils.ModelVersionSelector):
"""Returns the model's metrics added using `compile`, `add_metric` APIs."""
metrics = []
if self._is_compiled:
# TODO(omalleyt): Track `CompiledLoss` and `CompiledMetrics` objects
# TODO(omalleyt): Track `LossesContainer` and `MetricsContainer` objects
# so that attr names are not load-bearing.
metrics = self.compiled_loss.metrics + self.compiled_metrics.metrics
if self.compiled_loss is not None:
metrics += self.compiled_loss.metrics
if self.compiled_metrics is not None:
metrics += self.compiled_metrics.metrics
all_layers = self._gather_unique_layers()
for l in all_layers:
@ -414,7 +423,7 @@ class Model(network.Network, version_utils.ModelVersionSelector):
def run_eagerly(self, value):
self._run_eagerly = value
def _train_step(self, data):
def train_step(self, data):
"""The logic for one training step.
This method can be overridden to support custom training logic.
@ -462,7 +471,7 @@ class Model(network.Network, version_utils.ModelVersionSelector):
self.compiled_metrics.update_state(y, y_pred, sample_weight)
return {m.name: m.result() for m in self.metrics}
def _make_train_function(self):
def make_train_function(self):
"""Creates a function that executes one step of training.
This method can be overridden to support custom training logic.
@ -488,7 +497,7 @@ class Model(network.Network, version_utils.ModelVersionSelector):
def train_function(iterator):
data = next(iterator)
outputs = self.distribute_strategy.experimental_run_v2(
self._train_step, args=(data,))
self.train_step, args=(data,))
outputs = reduce_per_replica(
outputs, self.distribute_strategy, reduction='first')
return outputs
@ -747,7 +756,7 @@ class Model(network.Network, version_utils.ModelVersionSelector):
steps=data_handler._steps) # pylint: disable=protected-access
self.stop_training = False
train_function = self._make_train_function()
train_function = self.make_train_function()
callbacks.on_train_begin()
# Handle fault-tolerance for multi-worker.
# TODO(omalleyt): Fix the ordering issues that mean this has to
@ -799,7 +808,7 @@ class Model(network.Network, version_utils.ModelVersionSelector):
callbacks.on_train_end()
return self.history
def _test_step(self, data):
def test_step(self, data):
"""The logic for one evaluation step.
This method can be overridden to support custom evaluation logic.
@ -833,7 +842,7 @@ class Model(network.Network, version_utils.ModelVersionSelector):
self.compiled_metrics.update_state(y, y_pred, sample_weight)
return {m.name: m.result() for m in self.metrics}
def _make_test_function(self):
def make_test_function(self):
"""Creates a function that executes one step of evaluation.
This method can be overridden to support custom evaluation logic.
@ -858,7 +867,7 @@ class Model(network.Network, version_utils.ModelVersionSelector):
def test_function(iterator):
data = next(iterator)
outputs = self.distribute_strategy.experimental_run_v2(
self._test_step, args=(data,))
self.test_step, args=(data,))
outputs = reduce_per_replica(
outputs, self.distribute_strategy, reduction='first')
return outputs
@ -986,7 +995,7 @@ class Model(network.Network, version_utils.ModelVersionSelector):
epochs=1,
steps=data_handler._steps) # pylint: disable=protected-access
test_function = self._make_test_function()
test_function = self.make_test_function()
callbacks.on_test_begin()
for _, iterator in data_handler.enumerate_epochs(): # Single epoch.
self.reset_metrics()
@ -1012,7 +1021,7 @@ class Model(network.Network, version_utils.ModelVersionSelector):
return results[0]
return results
def _predict_step(self, data):
def predict_step(self, data):
"""The logic for one inference step.
This method can be overridden to support custom inference logic.
@ -1036,7 +1045,7 @@ class Model(network.Network, version_utils.ModelVersionSelector):
x, _, _ = data_adapter.unpack_x_y_sample_weight(data)
return self(x, training=False)
def _make_predict_function(self):
def make_predict_function(self):
"""Creates a function that executes one step of inference.
This method can be overridden to support custom inference logic.
@ -1060,7 +1069,7 @@ class Model(network.Network, version_utils.ModelVersionSelector):
def predict_function(iterator):
data = next(iterator)
outputs = self.distribute_strategy.experimental_run_v2(
self._predict_step, args=(data,))
self.predict_step, args=(data,))
outputs = reduce_per_replica(
outputs, self.distribute_strategy, reduction='concat')
return outputs
@ -1173,7 +1182,7 @@ class Model(network.Network, version_utils.ModelVersionSelector):
epochs=1,
steps=data_handler._steps) # pylint: disable=protected-access
predict_function = self._make_predict_function()
predict_function = self.make_predict_function()
callbacks.on_predict_begin()
for _, iterator in data_handler.enumerate_epochs(): # Single epoch.
with data_handler.catch_stop_iteration():
@ -1254,7 +1263,7 @@ class Model(network.Network, version_utils.ModelVersionSelector):
iterator = data_adapter.single_batch_iterator(self.distribute_strategy, x,
y, sample_weight,
class_weight)
train_function = self._make_train_function()
train_function = self.make_train_function()
logs = train_function(iterator)
if reset_metrics:
@ -1312,7 +1321,7 @@ class Model(network.Network, version_utils.ModelVersionSelector):
with self.distribute_strategy.scope():
iterator = data_adapter.single_batch_iterator(self.distribute_strategy, x,
y, sample_weight)
test_function = self._make_test_function()
test_function = self.make_test_function()
logs = test_function(iterator)
if reset_metrics:
@ -1344,7 +1353,7 @@ class Model(network.Network, version_utils.ModelVersionSelector):
self._check_call_args('predict_on_batch')
with self.distribute_strategy.scope():
iterator = data_adapter.single_batch_iterator(self.distribute_strategy, x)
predict_function = self._make_predict_function()
predict_function = self.make_predict_function()
outputs = predict_function(iterator)
return to_numpy(outputs)

3
tensorflow/python/keras/optimizer_v2/optimizer_v2_test.py
View File

@ -689,7 +689,8 @@ class OptimizersCompatibilityTest(keras_parameterized.TestCase):
loss='categorical_crossentropy',
metrics=[],
run_eagerly=testing_utils.should_run_eagerly())
model_v2._make_train_function()
if not ops.executing_eagerly_outside_functions():
model_v2._make_train_function()
if test_weights:
opt_v2.set_weights(opt_v1.get_weights())

6
tensorflow/python/keras/premade/wide_deep.py
View File

@ -19,7 +19,6 @@ from __future__ import division
from __future__ import print_function
from tensorflow.python.eager import backprop
from tensorflow.python.framework import ops
from tensorflow.python.keras import activations
from tensorflow.python.keras import backend as K
from tensorflow.python.keras import layers as layer_module
@ -110,7 +109,7 @@ class WideDeepModel(keras_training.Model):
return output
# This does not support gradient scaling and LossScaleOptimizer.
def _train_step(self, data):
def train_step(self, data):
x, y, sample_weight = data_adapter.unpack_x_y_sample_weight(data)
x, y, sample_weight = data_adapter.expand_1d((x, y, sample_weight))
@ -137,9 +136,6 @@ class WideDeepModel(keras_training.Model):
return {m.name: m.result() for m in self.metrics}
def _make_train_function(self):
if ops.executing_eagerly_outside_functions():
return super(WideDeepModel, self)._make_train_function()
# Only needed for graph mode and model_to_estimator.
has_recompiled = self._recompile_weights_loss_and_weighted_metrics()
self._check_trainable_weights_consistency()

4
tensorflow/python/keras/saving/hdf5_format.py
View File

@ -25,6 +25,7 @@ import os
import numpy as np
from six.moves import zip # pylint: disable=redefined-builtin
from tensorflow.python.framework import ops
from tensorflow.python.keras import backend as K
from tensorflow.python.keras import optimizers
from tensorflow.python.keras.saving import model_config as model_config_lib
@ -191,7 +192,8 @@ def load_model_from_hdf5(filepath, custom_objects=None, compile=True): # pylint
# with data to _make_train_function() and so can't load optimizer
# weights.
if model._is_graph_network: # pylint: disable=protected-access
model._make_train_function()
if not ops.executing_eagerly_outside_functions():
model._make_train_function()
optimizer_weight_values = load_optimizer_weights_from_hdf5_group(f)
try:
model.optimizer.set_weights(optimizer_weight_values)

7
tensorflow/python/keras/saving/hdf5_format_test.py
View File

@ -577,8 +577,8 @@ class TestWholeModelSaving(test.TestCase, parameterized.TestCase):
model.add(keras.layers.Dense(2, input_shape=(3,)))
model.add(keras.layers.Dense(3))
model.compile(loss='mse', optimizer='sgd', metrics=['acc'])
model._make_train_function()
if not ops.executing_eagerly_outside_functions():
model._make_train_function()
keras.models.save_model(model, saved_model_dir, save_format=save_format)
model = keras.models.load_model(saved_model_dir)
@ -964,7 +964,8 @@ class TestWeightSavingAndLoadingTFFormat(test.TestCase):
model.add(keras.layers.Dense(2, input_shape=(3,)))
model.add(keras.layers.Dense(3))
model.compile(loss='mse', optimizer=optimizers.Adam(), metrics=['acc'])
model._make_train_function()
if not ops.executing_eagerly_outside_functions():
model._make_train_function()
temp_dir = self.get_temp_dir()
prefix = os.path.join(temp_dir, 'ckpt')
with test.mock.patch.object(logging, 'warning') as mock_log:

24
tensorflow/tools/api/golden/v1/tensorflow.keras.-model.pbtxt
View File

@ -257,6 +257,18 @@ tf_class {
name: "load_weights"
argspec: "args=[\'self\', \'filepath\', \'by_name\', \'skip_mismatch\'], varargs=None, keywords=None, defaults=[\'False\', \'False\'], "
}
member_method {
name: "make_predict_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "make_test_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "make_train_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "predict"
argspec: "args=[\'self\', \'x\', \'batch_size\', \'verbose\', \'steps\', \'callbacks\', \'max_queue_size\', \'workers\', \'use_multiprocessing\'], varargs=None, keywords=None, defaults=[\'None\', \'0\', \'None\', \'None\', \'10\', \'1\', \'False\'], "
@ -269,6 +281,10 @@ tf_class {
name: "predict_on_batch"
argspec: "args=[\'self\', \'x\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "predict_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "reset_metrics"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
@ -297,6 +313,10 @@ tf_class {
name: "test_on_batch"
argspec: "args=[\'self\', \'x\', \'y\', \'sample_weight\', \'reset_metrics\', \'return_dict\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'True\', \'False\'], "
}
member_method {
name: "test_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "to_json"
argspec: "args=[\'self\'], varargs=None, keywords=kwargs, defaults=None"
@ -309,6 +329,10 @@ tf_class {
name: "train_on_batch"
argspec: "args=[\'self\', \'x\', \'y\', \'sample_weight\', \'class_weight\', \'reset_metrics\', \'return_dict\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'True\', \'False\'], "
}
member_method {
name: "train_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "with_name_scope"
argspec: "args=[\'cls\', \'method\'], varargs=None, keywords=None, defaults=None"

24
tensorflow/tools/api/golden/v1/tensorflow.keras.-sequential.pbtxt
View File

@ -262,6 +262,18 @@ tf_class {
name: "load_weights"
argspec: "args=[\'self\', \'filepath\', \'by_name\', \'skip_mismatch\'], varargs=None, keywords=None, defaults=[\'False\', \'False\'], "
}
member_method {
name: "make_predict_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "make_test_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "make_train_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "pop"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
@ -286,6 +298,10 @@ tf_class {
name: "predict_proba"
argspec: "args=[\'self\', \'x\', \'batch_size\', \'verbose\'], varargs=None, keywords=None, defaults=[\'32\', \'0\'], "
}
member_method {
name: "predict_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "reset_metrics"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
@ -314,6 +330,10 @@ tf_class {
name: "test_on_batch"
argspec: "args=[\'self\', \'x\', \'y\', \'sample_weight\', \'reset_metrics\', \'return_dict\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'True\', \'False\'], "
}
member_method {
name: "test_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "to_json"
argspec: "args=[\'self\'], varargs=None, keywords=kwargs, defaults=None"
@ -326,6 +346,10 @@ tf_class {
name: "train_on_batch"
argspec: "args=[\'self\', \'x\', \'y\', \'sample_weight\', \'class_weight\', \'reset_metrics\', \'return_dict\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'True\', \'False\'], "
}
member_method {
name: "train_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "with_name_scope"
argspec: "args=[\'cls\', \'method\'], varargs=None, keywords=None, defaults=None"

24
tensorflow/tools/api/golden/v1/tensorflow.keras.experimental.-linear-model.pbtxt
View File

@ -258,6 +258,18 @@ tf_class {
name: "load_weights"
argspec: "args=[\'self\', \'filepath\', \'by_name\', \'skip_mismatch\'], varargs=None, keywords=None, defaults=[\'False\', \'False\'], "
}
member_method {
name: "make_predict_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "make_test_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "make_train_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "predict"
argspec: "args=[\'self\', \'x\', \'batch_size\', \'verbose\', \'steps\', \'callbacks\', \'max_queue_size\', \'workers\', \'use_multiprocessing\'], varargs=None, keywords=None, defaults=[\'None\', \'0\', \'None\', \'None\', \'10\', \'1\', \'False\'], "
@ -270,6 +282,10 @@ tf_class {
name: "predict_on_batch"
argspec: "args=[\'self\', \'x\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "predict_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "reset_metrics"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
@ -298,6 +314,10 @@ tf_class {
name: "test_on_batch"
argspec: "args=[\'self\', \'x\', \'y\', \'sample_weight\', \'reset_metrics\', \'return_dict\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'True\', \'False\'], "
}
member_method {
name: "test_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "to_json"
argspec: "args=[\'self\'], varargs=None, keywords=kwargs, defaults=None"
@ -310,6 +330,10 @@ tf_class {
name: "train_on_batch"
argspec: "args=[\'self\', \'x\', \'y\', \'sample_weight\', \'class_weight\', \'reset_metrics\', \'return_dict\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'True\', \'False\'], "
}
member_method {
name: "train_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "with_name_scope"
argspec: "args=[\'cls\', \'method\'], varargs=None, keywords=None, defaults=None"

24
tensorflow/tools/api/golden/v1/tensorflow.keras.experimental.-wide-deep-model.pbtxt
View File

@ -258,6 +258,18 @@ tf_class {
name: "load_weights"
argspec: "args=[\'self\', \'filepath\', \'by_name\', \'skip_mismatch\'], varargs=None, keywords=None, defaults=[\'False\', \'False\'], "
}
member_method {
name: "make_predict_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "make_test_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "make_train_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "predict"
argspec: "args=[\'self\', \'x\', \'batch_size\', \'verbose\', \'steps\', \'callbacks\', \'max_queue_size\', \'workers\', \'use_multiprocessing\'], varargs=None, keywords=None, defaults=[\'None\', \'0\', \'None\', \'None\', \'10\', \'1\', \'False\'], "
@ -270,6 +282,10 @@ tf_class {
name: "predict_on_batch"
argspec: "args=[\'self\', \'x\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "predict_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "reset_metrics"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
@ -298,6 +314,10 @@ tf_class {
name: "test_on_batch"
argspec: "args=[\'self\', \'x\', \'y\', \'sample_weight\', \'reset_metrics\', \'return_dict\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'True\', \'False\'], "
}
member_method {
name: "test_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "to_json"
argspec: "args=[\'self\'], varargs=None, keywords=kwargs, defaults=None"
@ -310,6 +330,10 @@ tf_class {
name: "train_on_batch"
argspec: "args=[\'self\', \'x\', \'y\', \'sample_weight\', \'class_weight\', \'reset_metrics\', \'return_dict\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'True\', \'False\'], "
}
member_method {
name: "train_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "with_name_scope"
argspec: "args=[\'cls\', \'method\'], varargs=None, keywords=None, defaults=None"

24
tensorflow/tools/api/golden/v1/tensorflow.keras.models.-model.pbtxt
View File

@ -257,6 +257,18 @@ tf_class {
name: "load_weights"
argspec: "args=[\'self\', \'filepath\', \'by_name\', \'skip_mismatch\'], varargs=None, keywords=None, defaults=[\'False\', \'False\'], "
}
member_method {
name: "make_predict_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "make_test_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "make_train_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "predict"
argspec: "args=[\'self\', \'x\', \'batch_size\', \'verbose\', \'steps\', \'callbacks\', \'max_queue_size\', \'workers\', \'use_multiprocessing\'], varargs=None, keywords=None, defaults=[\'None\', \'0\', \'None\', \'None\', \'10\', \'1\', \'False\'], "
@ -269,6 +281,10 @@ tf_class {
name: "predict_on_batch"
argspec: "args=[\'self\', \'x\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "predict_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "reset_metrics"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
@ -297,6 +313,10 @@ tf_class {
name: "test_on_batch"
argspec: "args=[\'self\', \'x\', \'y\', \'sample_weight\', \'reset_metrics\', \'return_dict\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'True\', \'False\'], "
}
member_method {
name: "test_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "to_json"
argspec: "args=[\'self\'], varargs=None, keywords=kwargs, defaults=None"
@ -309,6 +329,10 @@ tf_class {
name: "train_on_batch"
argspec: "args=[\'self\', \'x\', \'y\', \'sample_weight\', \'class_weight\', \'reset_metrics\', \'return_dict\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'True\', \'False\'], "
}
member_method {
name: "train_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "with_name_scope"
argspec: "args=[\'cls\', \'method\'], varargs=None, keywords=None, defaults=None"

24
tensorflow/tools/api/golden/v1/tensorflow.keras.models.-sequential.pbtxt
View File

@ -262,6 +262,18 @@ tf_class {
name: "load_weights"
argspec: "args=[\'self\', \'filepath\', \'by_name\', \'skip_mismatch\'], varargs=None, keywords=None, defaults=[\'False\', \'False\'], "
}
member_method {
name: "make_predict_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "make_test_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "make_train_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "pop"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
@ -286,6 +298,10 @@ tf_class {
name: "predict_proba"
argspec: "args=[\'self\', \'x\', \'batch_size\', \'verbose\'], varargs=None, keywords=None, defaults=[\'32\', \'0\'], "
}
member_method {
name: "predict_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "reset_metrics"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
@ -314,6 +330,10 @@ tf_class {
name: "test_on_batch"
argspec: "args=[\'self\', \'x\', \'y\', \'sample_weight\', \'reset_metrics\', \'return_dict\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'True\', \'False\'], "
}
member_method {
name: "test_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "to_json"
argspec: "args=[\'self\'], varargs=None, keywords=kwargs, defaults=None"
@ -326,6 +346,10 @@ tf_class {
name: "train_on_batch"
argspec: "args=[\'self\', \'x\', \'y\', \'sample_weight\', \'class_weight\', \'reset_metrics\', \'return_dict\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'True\', \'False\'], "
}
member_method {
name: "train_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "with_name_scope"
argspec: "args=[\'cls\', \'method\'], varargs=None, keywords=None, defaults=None"

24
tensorflow/tools/api/golden/v2/tensorflow.keras.-model.pbtxt
View File

@ -257,6 +257,18 @@ tf_class {
name: "load_weights"
argspec: "args=[\'self\', \'filepath\', \'by_name\', \'skip_mismatch\'], varargs=None, keywords=None, defaults=[\'False\', \'False\'], "
}
member_method {
name: "make_predict_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "make_test_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "make_train_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "predict"
argspec: "args=[\'self\', \'x\', \'batch_size\', \'verbose\', \'steps\', \'callbacks\', \'max_queue_size\', \'workers\', \'use_multiprocessing\'], varargs=None, keywords=None, defaults=[\'None\', \'0\', \'None\', \'None\', \'10\', \'1\', \'False\'], "
@ -269,6 +281,10 @@ tf_class {
name: "predict_on_batch"
argspec: "args=[\'self\', \'x\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "predict_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "reset_metrics"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
@ -297,6 +313,10 @@ tf_class {
name: "test_on_batch"
argspec: "args=[\'self\', \'x\', \'y\', \'sample_weight\', \'reset_metrics\', \'return_dict\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'True\', \'False\'], "
}
member_method {
name: "test_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "to_json"
argspec: "args=[\'self\'], varargs=None, keywords=kwargs, defaults=None"
@ -309,6 +329,10 @@ tf_class {
name: "train_on_batch"
argspec: "args=[\'self\', \'x\', \'y\', \'sample_weight\', \'class_weight\', \'reset_metrics\', \'return_dict\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'True\', \'False\'], "
}
member_method {
name: "train_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "with_name_scope"
argspec: "args=[\'cls\', \'method\'], varargs=None, keywords=None, defaults=None"

24
tensorflow/tools/api/golden/v2/tensorflow.keras.-sequential.pbtxt
View File

@ -262,6 +262,18 @@ tf_class {
name: "load_weights"
argspec: "args=[\'self\', \'filepath\', \'by_name\', \'skip_mismatch\'], varargs=None, keywords=None, defaults=[\'False\', \'False\'], "
}
member_method {
name: "make_predict_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "make_test_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "make_train_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "pop"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
@ -286,6 +298,10 @@ tf_class {
name: "predict_proba"
argspec: "args=[\'self\', \'x\', \'batch_size\', \'verbose\'], varargs=None, keywords=None, defaults=[\'32\', \'0\'], "
}
member_method {
name: "predict_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "reset_metrics"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
@ -314,6 +330,10 @@ tf_class {
name: "test_on_batch"
argspec: "args=[\'self\', \'x\', \'y\', \'sample_weight\', \'reset_metrics\', \'return_dict\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'True\', \'False\'], "
}
member_method {
name: "test_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "to_json"
argspec: "args=[\'self\'], varargs=None, keywords=kwargs, defaults=None"
@ -326,6 +346,10 @@ tf_class {
name: "train_on_batch"
argspec: "args=[\'self\', \'x\', \'y\', \'sample_weight\', \'class_weight\', \'reset_metrics\', \'return_dict\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'True\', \'False\'], "
}
member_method {
name: "train_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "with_name_scope"
argspec: "args=[\'cls\', \'method\'], varargs=None, keywords=None, defaults=None"

24
tensorflow/tools/api/golden/v2/tensorflow.keras.experimental.-linear-model.pbtxt
View File

@ -258,6 +258,18 @@ tf_class {
name: "load_weights"
argspec: "args=[\'self\', \'filepath\', \'by_name\', \'skip_mismatch\'], varargs=None, keywords=None, defaults=[\'False\', \'False\'], "
}
member_method {
name: "make_predict_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "make_test_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "make_train_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "predict"
argspec: "args=[\'self\', \'x\', \'batch_size\', \'verbose\', \'steps\', \'callbacks\', \'max_queue_size\', \'workers\', \'use_multiprocessing\'], varargs=None, keywords=None, defaults=[\'None\', \'0\', \'None\', \'None\', \'10\', \'1\', \'False\'], "
@ -270,6 +282,10 @@ tf_class {
name: "predict_on_batch"
argspec: "args=[\'self\', \'x\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "predict_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "reset_metrics"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
@ -298,6 +314,10 @@ tf_class {
name: "test_on_batch"
argspec: "args=[\'self\', \'x\', \'y\', \'sample_weight\', \'reset_metrics\', \'return_dict\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'True\', \'False\'], "
}
member_method {
name: "test_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "to_json"
argspec: "args=[\'self\'], varargs=None, keywords=kwargs, defaults=None"
@ -310,6 +330,10 @@ tf_class {
name: "train_on_batch"
argspec: "args=[\'self\', \'x\', \'y\', \'sample_weight\', \'class_weight\', \'reset_metrics\', \'return_dict\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'True\', \'False\'], "
}
member_method {
name: "train_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "with_name_scope"
argspec: "args=[\'cls\', \'method\'], varargs=None, keywords=None, defaults=None"

24
tensorflow/tools/api/golden/v2/tensorflow.keras.experimental.-wide-deep-model.pbtxt
View File

@ -258,6 +258,18 @@ tf_class {
name: "load_weights"
argspec: "args=[\'self\', \'filepath\', \'by_name\', \'skip_mismatch\'], varargs=None, keywords=None, defaults=[\'False\', \'False\'], "
}
member_method {
name: "make_predict_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "make_test_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "make_train_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "predict"
argspec: "args=[\'self\', \'x\', \'batch_size\', \'verbose\', \'steps\', \'callbacks\', \'max_queue_size\', \'workers\', \'use_multiprocessing\'], varargs=None, keywords=None, defaults=[\'None\', \'0\', \'None\', \'None\', \'10\', \'1\', \'False\'], "
@ -270,6 +282,10 @@ tf_class {
name: "predict_on_batch"
argspec: "args=[\'self\', \'x\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "predict_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "reset_metrics"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
@ -298,6 +314,10 @@ tf_class {
name: "test_on_batch"
argspec: "args=[\'self\', \'x\', \'y\', \'sample_weight\', \'reset_metrics\', \'return_dict\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'True\', \'False\'], "
}
member_method {
name: "test_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "to_json"
argspec: "args=[\'self\'], varargs=None, keywords=kwargs, defaults=None"
@ -310,6 +330,10 @@ tf_class {
name: "train_on_batch"
argspec: "args=[\'self\', \'x\', \'y\', \'sample_weight\', \'class_weight\', \'reset_metrics\', \'return_dict\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'True\', \'False\'], "
}
member_method {
name: "train_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "with_name_scope"
argspec: "args=[\'cls\', \'method\'], varargs=None, keywords=None, defaults=None"

24
tensorflow/tools/api/golden/v2/tensorflow.keras.models.-model.pbtxt
View File

@ -257,6 +257,18 @@ tf_class {
name: "load_weights"
argspec: "args=[\'self\', \'filepath\', \'by_name\', \'skip_mismatch\'], varargs=None, keywords=None, defaults=[\'False\', \'False\'], "
}
member_method {
name: "make_predict_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "make_test_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "make_train_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "predict"
argspec: "args=[\'self\', \'x\', \'batch_size\', \'verbose\', \'steps\', \'callbacks\', \'max_queue_size\', \'workers\', \'use_multiprocessing\'], varargs=None, keywords=None, defaults=[\'None\', \'0\', \'None\', \'None\', \'10\', \'1\', \'False\'], "
@ -269,6 +281,10 @@ tf_class {
name: "predict_on_batch"
argspec: "args=[\'self\', \'x\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "predict_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "reset_metrics"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
@ -297,6 +313,10 @@ tf_class {
name: "test_on_batch"
argspec: "args=[\'self\', \'x\', \'y\', \'sample_weight\', \'reset_metrics\', \'return_dict\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'True\', \'False\'], "
}
member_method {
name: "test_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "to_json"
argspec: "args=[\'self\'], varargs=None, keywords=kwargs, defaults=None"
@ -309,6 +329,10 @@ tf_class {
name: "train_on_batch"
argspec: "args=[\'self\', \'x\', \'y\', \'sample_weight\', \'class_weight\', \'reset_metrics\', \'return_dict\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'True\', \'False\'], "
}
member_method {
name: "train_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "with_name_scope"
argspec: "args=[\'cls\', \'method\'], varargs=None, keywords=None, defaults=None"

24
tensorflow/tools/api/golden/v2/tensorflow.keras.models.-sequential.pbtxt
View File

@ -262,6 +262,18 @@ tf_class {
name: "load_weights"
argspec: "args=[\'self\', \'filepath\', \'by_name\', \'skip_mismatch\'], varargs=None, keywords=None, defaults=[\'False\', \'False\'], "
}
member_method {
name: "make_predict_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "make_test_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "make_train_function"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "pop"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
@ -286,6 +298,10 @@ tf_class {
name: "predict_proba"
argspec: "args=[\'self\', \'x\', \'batch_size\', \'verbose\'], varargs=None, keywords=None, defaults=[\'32\', \'0\'], "
}
member_method {
name: "predict_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "reset_metrics"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
@ -314,6 +330,10 @@ tf_class {
name: "test_on_batch"
argspec: "args=[\'self\', \'x\', \'y\', \'sample_weight\', \'reset_metrics\', \'return_dict\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'True\', \'False\'], "
}
member_method {
name: "test_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "to_json"
argspec: "args=[\'self\'], varargs=None, keywords=kwargs, defaults=None"
@ -326,6 +346,10 @@ tf_class {
name: "train_on_batch"
argspec: "args=[\'self\', \'x\', \'y\', \'sample_weight\', \'class_weight\', \'reset_metrics\', \'return_dict\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'True\', \'False\'], "
}
member_method {
name: "train_step"
argspec: "args=[\'self\', \'data\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "with_name_scope"
argspec: "args=[\'cls\', \'method\'], varargs=None, keywords=None, defaults=None"