Fix typos in "Profile Model Float Operations" documentation.

PiperOrigin-RevId: 191751175

diff --git a/tensorflow/core/profiler/g3doc/profile_model_architecture.md b/tensorflow/core/profiler/g3doc/profile_model_architecture.md
index 61bb66b..4ccd43c 100644 (file)
--- a/tensorflow/core/profiler/g3doc/profile_model_architecture.md
+++ b/tensorflow/core/profiler/g3doc/profile_model_architecture.md
@@ -45,22 +45,22 @@ sys.stdout.write('total_params: %d\n' % param_stats.total_parameters)
 
 For an operation to have float operation statistics:
 
-* It must have `RegisterStatistics('flops')` defined in TensorFlow. tfprof
-use the definition to calculate float operations. Contributes are welcome.
-
-* It must have known "shape" information for RegisterStatistics('flops')
-to calculate the statistics. It is suggested to pass in `-run_meta_path` if
-shape is only known during runtime. tfprof can fill in the missing shape with
-the runtime shape information from RunMetadata.
-Hence, it is suggested to use `-account_displayed_op_only`
-option so that you know the statistics are only for the operations printed out.
-
-* If no RunMetadata provided, tfprof count float_ops of each graph node once,
-even if it is defined in tf.while_loop. This is because tfprof doesn't know
-how many times are run statically. If RunMetadata provided, tfprof calculate
-float_ops as float_ops * run_count.
-
-
+*   It must have `RegisterStatistics('flops')` defined in TensorFlow. tfprof
+    uses the definition to calculate float operations. Contributions are
+    welcomed.
+
+*   It must have known "shape" information for RegisterStatistics('flops') to
+    calculate the statistics. It is suggested to pass in `-run_meta_path` if
+    shape is only known during runtime. tfprof can fill in the missing shape
+    with the runtime shape information from RunMetadata. Hence, it is suggested
+    to use `-account_displayed_op_only` option so that you know the statistics
+    are only for the operations printed out.
+
+*   If no RunMetadata is provided, tfprof counts float_ops of each graph node
+    once, even if it is defined in a tf.while_loop. This is because tfprof
+    doesn't know statically how many times each graph node is run. If
+    RunMetadata is provided, tfprof calculates float_ops as float_ops *
+    run_count.
 
 ```python
 # To profile float opertions in commandline, you need to pass --graph_path