def ShouldRunTest(self, run_params):
"""Whether to run the test."""
# Disable the test in fp16 mode since multiple matmul and add ops together
# can cause overflow.
return ((run_params.precision_mode != "FP16") and
not (trt_test.IsQuantizationMode(run_params.precision_mode) and
not run_params.use_calibration))
def ShouldRunTest(self, run_params):
if trt_convert.get_linked_tensorrt_version()[0] < 5:
return False
# Only test static engine mode, with or without calibration.
return (trt_test.IsQuantizationMode(run_params.precision_mode)
and not run_params.use_optimizer
and not run_params.dynamic_engine)
def ExpectedEnginesToBuild(self, run_params):
"""Return the expected engines to build."""
# In dynamic engine mode the engines are built in execution time, not in
# conversion time, so build errors occurs later. Here three of the engines
# will be failed to built but the corresponding engine op are still created.
# TODO(aaroey, jjsjann123): fix this.
if (run_params.dynamic_engine and
not trt_test.IsQuantizationMode(run_params.precision_mode)):
return self._ValidEngines() + self._InvalidEngines()
return self._ValidEngines()
def ShouldRunTest(self, run_params):
"""Whether to run the test."""
# TODO(aaroey): Trt library will fail like:
#
# ../builder/cudnnBuilder2.cpp:685:
# virtual std::vector<nvinfer1::query::Ports<
# nvinfer1::query::TensorRequirements>>
# nvinfer1::builder::Node::getSupportedFormats(
# const nvinfer1::query::Ports<nvinfer1::query::AbstractTensor>&,
# const nvinfer1::cudnn::HardwareContext&,
# nvinfer1::builder::Format::Type,
# const nvinfer1::builder::FormatTypeHack&) const:
# Assertion `sf' failed.
#
# To reproduce, run:
# bazel test -c opt --copt=-mavx \
# --test_arg=BatchMatMulTest.testTfTrt_ToolConversion_INT8_DynamicEngine \
# tensorflow/contrib/tensorrt:batch_matmul_test
#
# Investigate and fix it.
return not trt_test.IsQuantizationMode(run_params.precision_mode)
def ShouldRunTest(self, run_params):
# Only test FP32/FP16 mode.
return not trt_test.IsQuantizationMode(run_params.precision_mode)
def ShouldRunTest(self, run_params):
"""Whether to run the test."""
# TODO(aaroey): Trt 4.0 forbids conversion for tensors with rank <3 in int8
# mode, which is a bug. Re-enable this when trt library is fixed.
return not trt_test.IsQuantizationMode(run_params.precision_mode)
def ShouldRunTest(self, run_params):
return (run_params.dynamic_engine
and not trt_test.IsQuantizationMode(run_params.precision_mode))
def ShouldRunTest(self, run_params):
"""Whether to run the test."""
return (not trt_test.IsQuantizationMode(run_params.precision_mode)
and not run_params.dynamic_engine)
def ExpectedEnginesToBuild(self, run_params):
"""Return the expected engines to build."""
if (run_params.dynamic_engine and
not trt_test.IsQuantizationMode(run_params.precision_mode)):
return ["TRTEngineOp_0", "TRTEngineOp_1"]
return ["TRTEngineOp_1"]
