inference_varseqlen Namespace Reference

Functions
def	parse_args ()
def	question_features (tokens, question)
def	inference (features, tokens)
def	print_single_query (eval_time_elapsed, prediction, nbest_json)

Variables
	TRT_LOGGER = trt.Logger(trt.Logger.INFO)
def	args = parse_args()
	paragraph_text = None
	squad_examples = None
	output_prediction_file = None
	f = open(args.passage_file, 'r')
	question_text = None
	tokenizer = tokenization.FullTokenizer(vocab_file=args.vocab_file, do_lower_case=True)
int	doc_stride = 128
def	max_seq_length = args.sequence_length
	handle = ctypes.CDLL("libnvinfer_plugin.so", mode=ctypes.RTLD_GLOBAL)
	active_optimization_profile
def	input_nbytes = max_seq_length * trt.int32.itemsize
	stream = cuda.Stream()
list	d_inputs = [cuda.mem_alloc(input_nbytes) for binding in range(4)]
	h_output = cuda.pagelocked_empty((2 * max_seq_length), dtype=np.float32)
	d_output = cuda.mem_alloc(h_output.nbytes)
	all_predictions = collections.OrderedDict()
def	features = question_features(example.doc_tokens, example.question_text)
	eval_time_elapsed
	prediction
	nbest_json
	doc_tokens = dp.convert_doc_tokens(paragraph_text)
list	EXIT_CMDS = ["exit", "quit"]

Function Documentation

parse_args()

def inference_varseqlen.parse_args

(

)

Parse command line arguments

question_features()

def inference_varseqlen.question_features	(		tokens,
			question
	)

inference()

def inference_varseqlen.inference	(		features,
			tokens
	)

print_single_query()

def inference_varseqlen.print_single_query	(		eval_time_elapsed,
			prediction,
			nbest_json
	)

Variable Documentation

TRT_LOGGER

inference_varseqlen.TRT_LOGGER = trt.Logger(trt.Logger.INFO)

args

def inference_varseqlen.args = parse_args()

paragraph_text

string inference_varseqlen.paragraph_text = None

squad_examples

inference_varseqlen.squad_examples = None

output_prediction_file

def inference_varseqlen.output_prediction_file = None

f

inference_varseqlen.f = open(args.passage_file, 'r')

question_text

string inference_varseqlen.question_text = None

tokenizer

inference_varseqlen.tokenizer = tokenization.FullTokenizer(vocab_file=args.vocab_file, do_lower_case=True)

doc_stride

int inference_varseqlen.doc_stride = 128

max_seq_length

def inference_varseqlen.max_seq_length = args.sequence_length

handle

inference_varseqlen.handle = ctypes.CDLL("libnvinfer_plugin.so", mode=ctypes.RTLD_GLOBAL)

active_optimization_profile

inference_varseqlen.active_optimization_profile

input_nbytes

def inference_varseqlen.input_nbytes = max_seq_length * trt.int32.itemsize

stream

inference_varseqlen.stream = cuda.Stream()

d_inputs

list inference_varseqlen.d_inputs = [cuda.mem_alloc(input_nbytes) for binding in range(4)]

h_output

inference_varseqlen.h_output = cuda.pagelocked_empty((2 * max_seq_length), dtype=np.float32)

d_output

inference_varseqlen.d_output = cuda.mem_alloc(h_output.nbytes)

all_predictions

inference_varseqlen.all_predictions = collections.OrderedDict()

features

def inference_varseqlen.features = question_features(example.doc_tokens, example.question_text)

eval_time_elapsed

inference_varseqlen.eval_time_elapsed

prediction

inference_varseqlen.prediction

nbest_json

inference_varseqlen.nbest_json

doc_tokens

inference_varseqlen.doc_tokens = dp.convert_doc_tokens(paragraph_text)

EXIT_CMDS

list inference_varseqlen.EXIT_CMDS = ["exit", "quit"]