Clarify comments around Dynamic ops.
PiperOrigin-RevId: 282394368
Change-Id: I4b470338ab9201db1f31880f02d3ccad580e40a7
diff --git a/tensorflow/python/compiler/tensorrt/trt_convert.py b/tensorflow/python/compiler/tensorrt/trt_convert.py
index 7815749..5d4ab19 100644
--- a/tensorflow/python/compiler/tensorrt/trt_convert.py
+++ b/tensorflow/python/compiler/tensorrt/trt_convert.py
@@ -135,13 +135,18 @@
# Whether to generate dynamic TRT ops which will build the TRT network
# and engine at run time.
- # This option should be set to True in TF 2.0.
+ # i.e. Since TensorRT version < 6.0 does not support dynamic dimensions
+ # other than the batch dimension, when the TensorFlow graph has a
+ # non-batch dimension of dynamic size, we would need to enable this
+ # option. This option should be set to True in TF 2.0.
"is_dynamic_op",
- # Max number of cached TRT engines in dynamic TRT ops. If the number of
- # cached engines is already at max but none of them can serve the input,
- # the TRTEngineOp will fall back to run the TF function based on which
- # the TRTEngineOp is created.
+ # Max number of cached TRT engines for dynamic TRT ops.
+ # Created TRT engines for a dynamic dimension are cached.
+ # This is the maximum number of engines that can be cached.
+ # If the number of cached engines is already at max but none of them
+ # supports the input shapes, the TRTEngineOp will fall back to run the
+ # original TF subgraph that corresponds to the TRTEngineOp.
"maximum_cached_engines",
# This argument is ignored if precision_mode is not INT8. If set to
