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"]