From a09bcf5c210355baf1156acb0091557041fcf70e Mon Sep 17 00:00:00 2001 From: LDOUBLEV Date: Thu, 25 Nov 2021 09:56:59 +0800 Subject: [PATCH] fix get gpu id --- tools/infer/utility.py | 100 +++-------------------------------------- 1 file changed, 6 insertions(+), 94 deletions(-) mode change 100755 => 100644 tools/infer/utility.py diff --git a/tools/infer/utility.py b/tools/infer/utility.py old mode 100755 new mode 100644 index db2ec9c8..af6c54bb --- a/tools/infer/utility.py +++ b/tools/infer/utility.py @@ -159,93 +159,7 @@ def create_predictor(args, mode, logger): sess = ort.InferenceSession(model_file_path) return sess, sess.get_inputs()[0], None, None - if args.use_gpu: - gpu_id = get_infer_gpuid() - if gpu_id is None: - raise ValueError( - "Not found GPU in current device. Please check your device or set args.use_gpu as False" - ) - config.enable_use_gpu(args.gpu_mem, 0) - if args.use_tensorrt: - config.enable_tensorrt_engine( - workspace_size=1 << 30, - precision_mode=precision, - max_batch_size=args.max_batch_size, - min_subgraph_size=args.min_subgraph_size) - # skip the minmum trt subgraph - if mode == "det": - min_input_shape = { - "x": [1, 3, 50, 50], - "conv2d_92.tmp_0": [1, 120, 20, 20], - "conv2d_91.tmp_0": [1, 24, 10, 10], - "conv2d_59.tmp_0": [1, 96, 20, 20], - "nearest_interp_v2_1.tmp_0": [1, 256, 10, 10], - "nearest_interp_v2_2.tmp_0": [1, 256, 20, 20], - "conv2d_124.tmp_0": [1, 256, 20, 20], - "nearest_interp_v2_3.tmp_0": [1, 64, 20, 20], - "nearest_interp_v2_4.tmp_0": [1, 64, 20, 20], - "nearest_interp_v2_5.tmp_0": [1, 64, 20, 20], - "elementwise_add_7": [1, 56, 2, 2], - "nearest_interp_v2_0.tmp_0": [1, 256, 2, 2] - } - max_input_shape = { - "x": [1, 3, 2000, 2000], - "conv2d_92.tmp_0": [1, 120, 400, 400], - "conv2d_91.tmp_0": [1, 24, 200, 200], - "conv2d_59.tmp_0": [1, 96, 400, 400], - "nearest_interp_v2_1.tmp_0": [1, 256, 200, 200], - "conv2d_124.tmp_0": [1, 256, 400, 400], - "nearest_interp_v2_2.tmp_0": [1, 256, 400, 400], - "nearest_interp_v2_3.tmp_0": [1, 64, 400, 400], - "nearest_interp_v2_4.tmp_0": [1, 64, 400, 400], - "nearest_interp_v2_5.tmp_0": [1, 64, 400, 400], - "elementwise_add_7": [1, 56, 400, 400], - "nearest_interp_v2_0.tmp_0": [1, 256, 400, 400] - } - opt_input_shape = { - "x": [1, 3, 640, 640], - "conv2d_92.tmp_0": [1, 120, 160, 160], - "conv2d_91.tmp_0": [1, 24, 80, 80], - "conv2d_59.tmp_0": [1, 96, 160, 160], - "nearest_interp_v2_1.tmp_0": [1, 256, 80, 80], - "nearest_interp_v2_2.tmp_0": [1, 256, 160, 160], - "conv2d_124.tmp_0": [1, 256, 160, 160], - "nearest_interp_v2_3.tmp_0": [1, 64, 160, 160], - "nearest_interp_v2_4.tmp_0": [1, 64, 160, 160], - "nearest_interp_v2_5.tmp_0": [1, 64, 160, 160], - "elementwise_add_7": [1, 56, 40, 40], - "nearest_interp_v2_0.tmp_0": [1, 256, 40, 40] - } - min_pact_shape = { - "nearest_interp_v2_26.tmp_0": [1, 256, 20, 20], - "nearest_interp_v2_27.tmp_0": [1, 64, 20, 20], - "nearest_interp_v2_28.tmp_0": [1, 64, 20, 20], - "nearest_interp_v2_29.tmp_0": [1, 64, 20, 20] - } - max_pact_shape = { - "nearest_interp_v2_26.tmp_0": [1, 256, 400, 400], - "nearest_interp_v2_27.tmp_0": [1, 64, 400, 400], - "nearest_interp_v2_28.tmp_0": [1, 64, 400, 400], - "nearest_interp_v2_29.tmp_0": [1, 64, 400, 400] - } - opt_pact_shape = { - "nearest_interp_v2_26.tmp_0": [1, 256, 160, 160], - "nearest_interp_v2_27.tmp_0": [1, 64, 160, 160], - "nearest_interp_v2_28.tmp_0": [1, 64, 160, 160], - "nearest_interp_v2_29.tmp_0": [1, 64, 160, 160] - } - min_input_shape.update(min_pact_shape) - max_input_shape.update(max_pact_shape) - opt_input_shape.update(opt_pact_shape) - elif mode == "rec": - min_input_shape = {"x": [1, 3, 32, 10]} - max_input_shape = {"x": [args.rec_batch_num, 3, 32, 2000]} - opt_input_shape = {"x": [args.rec_batch_num, 3, 32, 320]} - elif mode == "cls": - min_input_shape = {"x": [1, 3, 48, 10]} - max_input_shape = {"x": [args.rec_batch_num, 3, 48, 2000]} - opt_input_shape = {"x": [args.rec_batch_num, 3, 48, 320]} - + else: model_file_path = model_dir + "/inference.pdmodel" params_file_path = model_dir + "/inference.pdiparams" if not os.path.exists(model_file_path): @@ -276,6 +190,7 @@ def create_predictor(args, mode, logger): config.enable_use_gpu(args.gpu_mem, 0) if args.use_tensorrt: config.enable_tensorrt_engine( + workspace_size=1 << 30, precision_mode=precision, max_batch_size=args.max_batch_size, min_subgraph_size=args.min_subgraph_size) @@ -396,13 +311,10 @@ def create_predictor(args, mode, logger): def get_infer_gpuid(): - cmd = "nvidia-smi" - try: - res = os.popen(cmd).readlines() - except: - res = None - if len(res) == 0: - return None + #cmd = "nvidia-smi" + #res = os.popen(cmd).readlines() + #if len(res) == 0: + # return None cmd = "env | grep CUDA_VISIBLE_DEVICES" env_cuda = os.popen(cmd).readlines() if len(env_cuda) == 0: -- GitLab