Standardizing device names to the newer /device:<type>:<index> format by making all the device factories produce the new device names.

The python API would still support the legacy /<type>:<index> format so the C++ layer would accept both legacy and standardized names but the C++ layer would produce only new device names now.

PiperOrigin-RevId: 170758313

1 files changed, 3 insertions, 3 deletions

diff --git a/tensorflow/python/profiler/model_analyzer_test.py b/tensorflow/python/profiler/model_analyzer_test.py
index 81c628289e..943ae0a3a1 100644
--- a/tensorflow/python/profiler/model_analyzer_test.py
+++ b/tensorflow/python/profiler/model_analyzer_test.py
@@ -62,7 +62,7 @@ class PrintModelAnalysisTest(test.TestCase):
 
   def testSelectEverthingDetail(self):
     ops.reset_default_graph()
-    dev = '/gpu:0' if test.is_gpu_available() else '/cpu:0'
+    dev = '/device:GPU:0' if test.is_gpu_available() else '/device:CPU:0'
     outfile = os.path.join(test.get_temp_dir(), 'dump')
     opts = (builder(builder.trainable_variables_parameter())
             .with_file_output(outfile)
@@ -143,7 +143,7 @@ class PrintModelAnalysisTest(test.TestCase):
         disable_model_pruning=True)
     graph_options = config_pb2.GraphOptions(rewrite_options=rewriter_config)
     config = config_pb2.ConfigProto(graph_options=graph_options)
-    with session.Session(config=config) as sess, ops.device('/cpu:0'):
+    with session.Session(config=config) as sess, ops.device('/device:CPU:0'):
       x = lib.BuildSmallModel()
 
       sess.run(variables.global_variables_initializer())
@@ -159,7 +159,7 @@ class PrintModelAnalysisTest(test.TestCase):
       with gfile.Open(outfile, 'r') as f:
         # pylint: disable=line-too-long
         self.assertEqual(
-            'node name | # parameters | # float_ops | assigned devices | op types | op count (run|defined) | input shapes\n_TFProfRoot (--/451 params, --/11.34k flops, _kTFScopeParent, --/8|--/36, )\n  Conv2D (0/0 params, 5.83k/5.83k flops, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|Conv2D, 1/1|1/1, 0:2x6x6x3|1:3x3x3x6)\n  Conv2D_1 (0/0 params, 4.61k/4.61k flops, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|Conv2D, 1/1|1/1, 0:2x3x3x6|1:2x2x6x12)\n  DW (3x3x3x6, 162/162 params, 0/324 flops, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|VariableV2|_trainable_variables, 1/2|1/10, )\n    DW/Assign (0/0 params, 0/0 flops, Assign, 0/0|1/1, 0:3x3x3x6|1:3x3x3x6)\n    DW/Initializer (0/0 params, 0/324 flops, _kTFScopeParent, 0/0|1/7, )\n      DW/Initializer/random_normal (0/0 params, 162/324 flops, Add, 0/0|1/6, 0:3x3x3x6|1:1)\n        DW/Initializer/random_normal/RandomStandardNormal (0/0 params, 0/0 flops, RandomStandardNormal, 0/0|1/1, 0:4)\n        DW/Initializer/random_normal/mean (0/0 params, 0/0 flops, Const, 0/0|1/1, )\n        DW/Initializer/random_normal/mul (0/0 params, 162/162 flops, Mul, 0/0|1/1, 0:3x3x3x6|1:1)\n        DW/Initializer/random_normal/shape (0/0 params, 0/0 flops, Const, 0/0|1/1, )\n        DW/Initializer/random_normal/stddev (0/0 params, 0/0 flops, Const, 0/0|1/1, )\n    DW/read (0/0 params, 0/0 flops, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|Identity, 1/1|1/1, 0:3x3x3x6)\n  DW2 (2x2x6x12, 288/288 params, 0/576 flops, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|VariableV2|_trainable_variables, 1/2|1/10, )\n    DW2/Assign (0/0 params, 0/0 flops, Assign, 0/0|1/1, 0:2x2x6x12|1:2x2x6x12)\n    DW2/Initializer (0/0 params, 0/576 flops, _kTFScopeParent, 0/0|1/7, )\n      DW2/Initializer/random_normal (0/0 params, 288/576 flops, Add, 0/0|1/6, 0:2x2x6x12|1:1)\n        DW2/Initializer/random_normal/RandomStandardNormal (0/0 params, 0/0 flops, RandomStandardNormal, 0/0|1/1, 0:4)\n        DW2/Initializer/random_normal/mean (0/0 params, 0/0 flops, Const, 0/0|1/1, )\n        DW2/Initializer/random_normal/mul (0/0 params, 288/288 flops, Mul, 0/0|1/1, 0:2x2x6x12|1:1)\n        DW2/Initializer/random_normal/shape (0/0 params, 0/0 flops, Const, 0/0|1/1, )\n        DW2/Initializer/random_normal/stddev (0/0 params, 0/0 flops, Const, 0/0|1/1, )\n    DW2/read (0/0 params, 0/0 flops, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|Identity, 1/1|1/1, 0:2x2x6x12)\n  ScalarW (1, 1/1 params, 0/2 flops, VariableV2|_trainable_variables, 0/0|1/10, )\n    ScalarW/Assign (0/0 params, 0/0 flops, Assign, 0/0|1/1, 0:1|1:1)\n    ScalarW/Initializer (0/0 params, 0/2 flops, _kTFScopeParent, 0/0|1/7, )\n      ScalarW/Initializer/random_normal (0/0 params, 1/2 flops, Add, 0/0|1/6, 0:1|1:1)\n        ScalarW/Initializer/random_normal/RandomStandardNormal (0/0 params, 0/0 flops, RandomStandardNormal, 0/0|1/1, 0:0)\n        ScalarW/Initializer/random_normal/mean (0/0 params, 0/0 flops, Const, 0/0|1/1, )\n        ScalarW/Initializer/random_normal/mul (0/0 params, 1/1 flops, Mul, 0/0|1/1, 0:1|1:1)\n        ScalarW/Initializer/random_normal/shape (0/0 params, 0/0 flops, Const, 0/0|1/1, )\n        ScalarW/Initializer/random_normal/stddev (0/0 params, 0/0 flops, Const, 0/0|1/1, )\n    ScalarW/read (0/0 params, 0/0 flops, Identity, 0/0|1/1, 0:1)\n  _retval_Conv2D_1_0_0 (0/0 params, 0/0 flops, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|RunTimeOp, 1/1|1/1, )\n  init (0/0 params, 0/0 flops, NoOp, 0/0|1/1, 0:1|1:3x3x3x6|2:2x2x6x12)\n  zeros (0/0 params, 0/0 flops, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|Const, 1/1|1/1, )\n',
+            'node name | # parameters | # float_ops | assigned devices | op types | op count (run|defined) | input shapes\n_TFProfRoot (--/451 params, --/11.34k flops, _kTFScopeParent, --/8|--/36, )\n  Conv2D (0/0 params, 5.83k/5.83k flops, /job:localhost/replica:0/task:0/device:cpu:0, /job:localhost/replica:0/task:0/device:cpu:0|Conv2D, 1/1|1/1, 0:2x6x6x3|1:3x3x3x6)\n  Conv2D_1 (0/0 params, 4.61k/4.61k flops, /job:localhost/replica:0/task:0/device:cpu:0, /job:localhost/replica:0/task:0/device:cpu:0|Conv2D, 1/1|1/1, 0:2x3x3x6|1:2x2x6x12)\n  DW (3x3x3x6, 162/162 params, 0/324 flops, /job:localhost/replica:0/task:0/device:cpu:0, /job:localhost/replica:0/task:0/device:cpu:0|VariableV2|_trainable_variables, 1/2|1/10, )\n    DW/Assign (0/0 params, 0/0 flops, Assign, 0/0|1/1, 0:3x3x3x6|1:3x3x3x6)\n    DW/Initializer (0/0 params, 0/324 flops, _kTFScopeParent, 0/0|1/7, )\n      DW/Initializer/random_normal (0/0 params, 162/324 flops, Add, 0/0|1/6, 0:3x3x3x6|1:1)\n        DW/Initializer/random_normal/RandomStandardNormal (0/0 params, 0/0 flops, RandomStandardNormal, 0/0|1/1, 0:4)\n        DW/Initializer/random_normal/mean (0/0 params, 0/0 flops, Const, 0/0|1/1, )\n        DW/Initializer/random_normal/mul (0/0 params, 162/162 flops, Mul, 0/0|1/1, 0:3x3x3x6|1:1)\n        DW/Initializer/random_normal/shape (0/0 params, 0/0 flops, Const, 0/0|1/1, )\n        DW/Initializer/random_normal/stddev (0/0 params, 0/0 flops, Const, 0/0|1/1, )\n    DW/read (0/0 params, 0/0 flops, /job:localhost/replica:0/task:0/device:cpu:0, /job:localhost/replica:0/task:0/device:cpu:0|Identity, 1/1|1/1, 0:3x3x3x6)\n  DW2 (2x2x6x12, 288/288 params, 0/576 flops, /job:localhost/replica:0/task:0/device:cpu:0, /job:localhost/replica:0/task:0/device:cpu:0|VariableV2|_trainable_variables, 1/2|1/10, )\n    DW2/Assign (0/0 params, 0/0 flops, Assign, 0/0|1/1, 0:2x2x6x12|1:2x2x6x12)\n    DW2/Initializer (0/0 params, 0/576 flops, _kTFScopeParent, 0/0|1/7, )\n      DW2/Initializer/random_normal (0/0 params, 288/576 flops, Add, 0/0|1/6, 0:2x2x6x12|1:1)\n        DW2/Initializer/random_normal/RandomStandardNormal (0/0 params, 0/0 flops, RandomStandardNormal, 0/0|1/1, 0:4)\n        DW2/Initializer/random_normal/mean (0/0 params, 0/0 flops, Const, 0/0|1/1, )\n        DW2/Initializer/random_normal/mul (0/0 params, 288/288 flops, Mul, 0/0|1/1, 0:2x2x6x12|1:1)\n        DW2/Initializer/random_normal/shape (0/0 params, 0/0 flops, Const, 0/0|1/1, )\n        DW2/Initializer/random_normal/stddev (0/0 params, 0/0 flops, Const, 0/0|1/1, )\n    DW2/read (0/0 params, 0/0 flops, /job:localhost/replica:0/task:0/device:cpu:0, /job:localhost/replica:0/task:0/device:cpu:0|Identity, 1/1|1/1, 0:2x2x6x12)\n  ScalarW (1, 1/1 params, 0/2 flops, VariableV2|_trainable_variables, 0/0|1/10, )\n    ScalarW/Assign (0/0 params, 0/0 flops, Assign, 0/0|1/1, 0:1|1:1)\n    ScalarW/Initializer (0/0 params, 0/2 flops, _kTFScopeParent, 0/0|1/7, )\n      ScalarW/Initializer/random_normal (0/0 params, 1/2 flops, Add, 0/0|1/6, 0:1|1:1)\n        ScalarW/Initializer/random_normal/RandomStandardNormal (0/0 params, 0/0 flops, RandomStandardNormal, 0/0|1/1, 0:0)\n        ScalarW/Initializer/random_normal/mean (0/0 params, 0/0 flops, Const, 0/0|1/1, )\n        ScalarW/Initializer/random_normal/mul (0/0 params, 1/1 flops, Mul, 0/0|1/1, 0:1|1:1)\n        ScalarW/Initializer/random_normal/shape (0/0 params, 0/0 flops, Const, 0/0|1/1, )\n        ScalarW/Initializer/random_normal/stddev (0/0 params, 0/0 flops, Const, 0/0|1/1, )\n    ScalarW/read (0/0 params, 0/0 flops, Identity, 0/0|1/1, 0:1)\n  _retval_Conv2D_1_0_0 (0/0 params, 0/0 flops, /job:localhost/replica:0/task:0/device:cpu:0, /job:localhost/replica:0/task:0/device:cpu:0|RunTimeOp, 1/1|1/1, )\n  init (0/0 params, 0/0 flops, NoOp, 0/0|1/1, 0:1|1:3x3x3x6|2:2x2x6x12)\n  zeros (0/0 params, 0/0 flops, /job:localhost/replica:0/task:0/device:cpu:0, /job:localhost/replica:0/task:0/device:cpu:0|Const, 1/1|1/1, )\n',
             f.read())
         # pylint: enable=line-too-long