Update references from variables.VariableV1 to its new location in …

…`ops/variable_v1.py`. PiperOrigin-RevId: 520732231
tensorflow · Sep 19, 2023 · 559f08f · 559f08f
1 parent c8e97df
commit 559f08f
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Showing 3 changed files with 17 additions and 11 deletions.
diff --git a/scripts/tf_cnn_benchmarks/models/experimental/deepspeech.py b/scripts/tf_cnn_benchmarks/models/experimental/deepspeech.py
@@ -26,7 +26,7 @@
 import constants
 from cnn_util import log_fn
 from models import model as model_lib
-from tensorflow.python.ops import variables  # pylint: disable=g-direct-tensorflow-import
+from tensorflow.python.ops import variable_v1  # pylint: disable=g-direct-tensorflow-import
 
 
 class DeepSpeechDecoder(object):
@@ -287,9 +287,11 @@ def get_input_shapes(self, subset):
   def get_synthetic_inputs(self, input_name, nclass):
     inputs = tf.random_uniform(self.get_input_shapes('train')[0],
                                dtype=self.get_input_data_types('train')[0])
-    inputs = variables.VariableV1(inputs, trainable=False,
-                                  collections=[tf.GraphKeys.LOCAL_VARIABLES],
-                                  name=input_name)
+    inputs = variable_v1.VariableV1(
+        inputs,
+        trainable=False,
+        collections=[tf.GraphKeys.LOCAL_VARIABLES],
+        name=input_name)
     labels = tf.convert_to_tensor(
         np.random.randint(28, size=[self.batch_size, self.max_label_length]))
     input_lengths = tf.convert_to_tensor(

diff --git a/scripts/tf_cnn_benchmarks/models/model.py b/scripts/tf_cnn_benchmarks/models/model.py
@@ -20,7 +20,7 @@
 
 import convnet_builder
 import mlperf
-from tensorflow.python.ops import variables as variables_module  # pylint: disable=g-direct-tensorflow-import
+from tensorflow.python.ops import variable_v1  # pylint: disable=g-direct-tensorflow-import
 
 # BuildNetworkResult encapsulate the result (e.g. logits) of a
 # Model.build_network() call.
@@ -245,8 +245,10 @@ def get_synthetic_inputs(self, input_name, nclass):
         mean=127,
         stddev=60,
         name=self.model_name + '_synthetic_inputs')
-    inputs = variables_module.VariableV1(
-        inputs, trainable=False, collections=[tf.GraphKeys.LOCAL_VARIABLES],
+    inputs = variable_v1.VariableV1(
+        inputs,
+        trainable=False,
+        collections=[tf.GraphKeys.LOCAL_VARIABLES],
         name=input_name)
     labels = tf.random_uniform(
         label_shape,

diff --git a/scripts/tf_cnn_benchmarks/models/tf1_only/ssd_model.py b/scripts/tf_cnn_benchmarks/models/tf1_only/ssd_model.py
@@ -41,7 +41,7 @@
 from models import model as model_lib
 from models import resnet_model
 from tensorflow.contrib import layers as contrib_layers
-from tensorflow.python.ops import variables
+from tensorflow.python.ops import variable_v1
 
 BACKBONE_MODEL_SCOPE_NAME = 'resnet34_backbone'
 
@@ -663,9 +663,11 @@ def get_synthetic_inputs(self, input_name, nclass):
     """Generating synthetic data matching real data shape and type."""
     inputs = tf.random_uniform(
         self.get_input_shapes('train')[0], dtype=self.data_type)
-    inputs = variables.VariableV1(inputs, trainable=False,
-                                  collections=[tf.GraphKeys.LOCAL_VARIABLES],
-                                  name=input_name)
+    inputs = variable_v1.VariableV1(
+        inputs,
+        trainable=False,
+        collections=[tf.GraphKeys.LOCAL_VARIABLES],
+        name=input_name)
     boxes = tf.random_uniform(
         [self.batch_size, ssd_constants.NUM_SSD_BOXES, 4], dtype=tf.float32)
     classes = tf.random_uniform(