From bb125cb309d3bf58c99cbdeaac17adf44c2c7b5f Mon Sep 17 00:00:00 2001 From: chenzomi Date: Mon, 17 Aug 2020 20:26:54 +0800 Subject: [PATCH] change unsupport to unsupported --- .../backend/session/ascend_control_parser.cc | 2 +- .../runtime/device/cpu/mpi/mpi_adapter.cc | 2 +- mindspore/ccsrc/utils/tensorprint_utils.cc | 2 +- mindspore/lite/c_ops/cast.cc | 2 +- .../src/runtime/kernel/arm/fp16/cast_fp16.cc | 2 +- .../_custom_op/matmul_cube_dense_left_impl.py | 2 +- .../matmul_cube_fracz_left_cast_impl.py | 2 +- .../_op_impl/_custom_op/matmul_cube_impl.py | 2 +- mindspore/profiler/profiling.py | 2 +- mindspore/train/model.py | 2 +- model_zoo/official/cv/googlenet/train.py | 2 +- model_zoo/official/cv/maskrcnn/src/dataset.py | 2 +- model_zoo/official/cv/mobilenetv2/eval.py | 26 +++---- .../cv/mobilenetv2/scripts/run_infer.sh | 6 +- .../cv/mobilenetv2/scripts/run_train.sh | 6 +- .../official/cv/mobilenetv2/src/dataset.py | 8 +- .../cv/mobilenetv2/src/mobilenetV2.py | 20 ++--- model_zoo/official/cv/mobilenetv2/train.py | 20 ++--- .../cv/mobilenetv2_quant/src/dataset.py | 2 +- .../official/cv/mobilenetv2_quant/train.py | 2 + model_zoo/official/cv/mobilenetv3/eval.py | 24 +++--- .../cv/mobilenetv3/scripts/run_infer.sh | 5 +- .../cv/mobilenetv3/scripts/run_train.sh | 39 +--------- .../official/cv/mobilenetv3/src/config.py | 18 ----- .../official/cv/mobilenetv3/src/dataset.py | 15 +--- model_zoo/official/cv/mobilenetv3/train.py | 76 ++----------------- .../official/nlp/bert_thor/src/model_thor.py | 2 +- serving/acl/dvpp_process.cc | 2 +- .../models/resnet50/src_thor/model_thor.py | 2 +- 29 files changed, 88 insertions(+), 209 deletions(-) diff --git a/mindspore/ccsrc/backend/session/ascend_control_parser.cc b/mindspore/ccsrc/backend/session/ascend_control_parser.cc index e1d0a02a8..94a89ff32 100644 --- a/mindspore/ccsrc/backend/session/ascend_control_parser.cc +++ b/mindspore/ccsrc/backend/session/ascend_control_parser.cc @@ -384,7 +384,7 @@ std::vector>> AscendControlPar ret.emplace_back(target_graph, args); } } else { - MS_LOG(EXCEPTION) << "Unsupport call node: " << cnode->DebugString(5); + MS_LOG(EXCEPTION) << "Unsupported call node: " << cnode->DebugString(5); } return ret; } diff --git a/mindspore/ccsrc/runtime/device/cpu/mpi/mpi_adapter.cc b/mindspore/ccsrc/runtime/device/cpu/mpi/mpi_adapter.cc index 05ca85260..023fb0fb0 100644 --- a/mindspore/ccsrc/runtime/device/cpu/mpi/mpi_adapter.cc +++ b/mindspore/ccsrc/runtime/device/cpu/mpi/mpi_adapter.cc @@ -59,7 +59,7 @@ MPI_Op GetMpiOp(const std::string &op_type) { return MPI_PROD; } - RAISE_EXCEPTION_WITH_PARAM("unsupport op_type: ", op_type); + RAISE_EXCEPTION_WITH_PARAM("Unsupported op_type: ", op_type); return MPI_SUM; } diff --git a/mindspore/ccsrc/utils/tensorprint_utils.cc b/mindspore/ccsrc/utils/tensorprint_utils.cc index b716931b3..a9a2c83d0 100644 --- a/mindspore/ccsrc/utils/tensorprint_utils.cc +++ b/mindspore/ccsrc/utils/tensorprint_utils.cc @@ -159,7 +159,7 @@ void convertDataItem2Scalar(const char *str_data_ptr, const string &tensor_type, } else if (type_id == TypeId::kNumberTypeFloat64) { PrintScalarToString(str_data_ptr, tensor_type, buf); } else { - MS_LOG(EXCEPTION) << "Cannot print scalar because of unsupport data type: " << tensor_type << "."; + MS_LOG(EXCEPTION) << "Cannot print scalar because of unsupported data type: " << tensor_type << "."; } } diff --git a/mindspore/lite/c_ops/cast.cc b/mindspore/lite/c_ops/cast.cc index 1c3df5b44..feebe75a5 100644 --- a/mindspore/lite/c_ops/cast.cc +++ b/mindspore/lite/c_ops/cast.cc @@ -49,7 +49,7 @@ int Cast::InferShape(std::vector inputs_, std::vector
  • data_type()) == kSupportDataType.end()) { - MS_LOG(ERROR) << "Unsupport input data type " << input->data_type(); + MS_LOG(ERROR) << "Unsupported input data type " << input->data_type(); return 1; } if (GetDstT() != kNumberTypeFloat && GetDstT() != kNumberTypeFloat32) { diff --git a/mindspore/lite/src/runtime/kernel/arm/fp16/cast_fp16.cc b/mindspore/lite/src/runtime/kernel/arm/fp16/cast_fp16.cc index 97e3149ea..04125aa12 100644 --- a/mindspore/lite/src/runtime/kernel/arm/fp16/cast_fp16.cc +++ b/mindspore/lite/src/runtime/kernel/arm/fp16/cast_fp16.cc @@ -76,7 +76,7 @@ int CastFp16CPUKernel::DoCast(int thread_id) { reinterpret_cast(output_data) + offset, data_num); break; default: - MS_LOG(ERROR) << "Unsupport input data type " << input->data_type(); + MS_LOG(ERROR) << "Unsupported input data type " << input->data_type(); return RET_ERROR; } return RET_OK; diff --git a/mindspore/ops/_op_impl/_custom_op/matmul_cube_dense_left_impl.py b/mindspore/ops/_op_impl/_custom_op/matmul_cube_dense_left_impl.py index c626778b5..9455fcaa0 100644 --- a/mindspore/ops/_op_impl/_custom_op/matmul_cube_dense_left_impl.py +++ b/mindspore/ops/_op_impl/_custom_op/matmul_cube_dense_left_impl.py @@ -139,7 +139,7 @@ def _shape_check(shape_a, shape_b, shape_bias, src_dtype, trans_a, trans_b): if [i for i in shape_bias[-2:]] != [m_shape, n_shape]: raise RuntimeError("non broadcast bias shape must be same as output shape") else: - raise RuntimeError("unsupport input shape now for batch bias case") + raise RuntimeError("Unsupported input shape now for batch bias case") def _get_bias(shape_bias): diff --git a/mindspore/ops/_op_impl/_custom_op/matmul_cube_fracz_left_cast_impl.py b/mindspore/ops/_op_impl/_custom_op/matmul_cube_fracz_left_cast_impl.py index d6c0d850b..b43efc1b9 100644 --- a/mindspore/ops/_op_impl/_custom_op/matmul_cube_fracz_left_cast_impl.py +++ b/mindspore/ops/_op_impl/_custom_op/matmul_cube_fracz_left_cast_impl.py @@ -136,7 +136,7 @@ src_dtype: str if [i for i in shape_bias[-2:]] != [m_shape, n_shape]: raise RuntimeError("non broadcast bias shape must be same as output shape") else: - raise RuntimeError("unsupport input shape now for batch bias case") + raise RuntimeError("Unsupported input shape now for batch bias case") def _get_bias(shape_bias): diff --git a/mindspore/ops/_op_impl/_custom_op/matmul_cube_impl.py b/mindspore/ops/_op_impl/_custom_op/matmul_cube_impl.py index d14cb0d3c..93c328379 100644 --- a/mindspore/ops/_op_impl/_custom_op/matmul_cube_impl.py +++ b/mindspore/ops/_op_impl/_custom_op/matmul_cube_impl.py @@ -141,7 +141,7 @@ def _shape_check(shape_a, shape_b, shape_bias, src_dtype, trans_a, trans_b): if [i for i in shape_bias[-2:]] != [m_shape, n_shape]: raise RuntimeError("non broadcast bias shape must be same as output shape") else: - raise RuntimeError("unsupport input shape now for batch bias case") + raise RuntimeError("unsupported input shape now for batch bias case") def _get_bias(shape_bias): diff --git a/mindspore/profiler/profiling.py b/mindspore/profiler/profiling.py index bfea46276..f0716945d 100644 --- a/mindspore/profiler/profiling.py +++ b/mindspore/profiler/profiling.py @@ -427,7 +427,7 @@ class Profiler: logger.error("Fail to get DEVICE_ID, use 0 instead.") if device_target and device_target not in ["Davinci", "Ascend", "GPU"]: - msg = "Profiling: unsupport backend: %s" % device_target + msg = "Profiling: unsupported backend: %s" % device_target raise RuntimeError(msg) self._dev_id = dev_id diff --git a/mindspore/train/model.py b/mindspore/train/model.py index bea9f3395..c02ee713e 100755 --- a/mindspore/train/model.py +++ b/mindspore/train/model.py @@ -131,7 +131,7 @@ class Model: def _check_kwargs(self, kwargs): for arg in kwargs: if arg not in ['loss_scale_manager', 'keep_batchnorm_fp32']: - raise ValueError(f"Unsupport arg '{arg}'") + raise ValueError(f"Unsupported arg '{arg}'") def _build_train_network(self): """Build train network""" diff --git a/model_zoo/official/cv/googlenet/train.py b/model_zoo/official/cv/googlenet/train.py index 50e3ec7bc..5181f9c48 100644 --- a/model_zoo/official/cv/googlenet/train.py +++ b/model_zoo/official/cv/googlenet/train.py @@ -88,7 +88,7 @@ if __name__ == '__main__': context.set_auto_parallel_context(device_num=device_num, parallel_mode=ParallelMode.DATA_PARALLEL, mirror_mean=True) else: - raise ValueError("Unsupport platform.") + raise ValueError("Unsupported platform.") dataset = create_dataset(cfg.data_path, 1) batch_num = dataset.get_dataset_size() diff --git a/model_zoo/official/cv/maskrcnn/src/dataset.py b/model_zoo/official/cv/maskrcnn/src/dataset.py index e0bbbba70..15d20f1e4 100644 --- a/model_zoo/official/cv/maskrcnn/src/dataset.py +++ b/model_zoo/official/cv/maskrcnn/src/dataset.py @@ -467,7 +467,7 @@ def data_to_mindrecord_byte_image(dataset="coco", is_training=True, prefix="mask if dataset == "coco": image_files, image_anno_dict, masks, masks_shape = create_coco_label(is_training) else: - print("Error unsupport other dataset") + print("Error unsupported other dataset") return maskrcnn_json = { diff --git a/model_zoo/official/cv/mobilenetv2/eval.py b/model_zoo/official/cv/mobilenetv2/eval.py index 61e9c5ecd..b9c92bb19 100644 --- a/model_zoo/official/cv/mobilenetv2/eval.py +++ b/model_zoo/official/cv/mobilenetv2/eval.py @@ -30,31 +30,31 @@ from src.mobilenetV2 import mobilenet_v2 parser = argparse.ArgumentParser(description='Image classification') parser.add_argument('--checkpoint_path', type=str, default=None, help='Checkpoint file path') parser.add_argument('--dataset_path', type=str, default=None, help='Dataset path') -parser.add_argument('--platform', type=str, default=None, help='run platform') +parser.add_argument('--device_targe', type=str, default=None, help='run device_targe') args_opt = parser.parse_args() if __name__ == '__main__': - config_platform = None + config = None net = None - if args_opt.platform == "Ascend": - config_platform = config_ascend + if args_opt.device_target == "Ascend": + config = config_ascend device_id = int(os.getenv('DEVICE_ID')) context.set_context(mode=context.GRAPH_MODE, device_target="Ascend", device_id=device_id, save_graphs=False) - net = mobilenet_v2(num_classes=config_platform.num_classes, platform="Ascend") - elif args_opt.platform == "GPU": - config_platform = config_gpu + net = mobilenet_v2(num_classes=config.num_classes, device_target="Ascend") + elif args_opt.device_target == "GPU": + config = config_gpu context.set_context(mode=context.GRAPH_MODE, device_target="GPU", save_graphs=False) - net = mobilenet_v2(num_classes=config_platform.num_classes, platform="GPU") + net = mobilenet_v2(num_classes=config.num_classes, device_target="GPU") else: - raise ValueError("Unsupport platform.") + raise ValueError("Unsupported device_target.") loss = nn.SoftmaxCrossEntropyWithLogits( is_grad=False, sparse=True, reduction='mean') - if args_opt.platform == "Ascend": + if args_opt.device_target == "Ascend": net.to_float(mstype.float16) for _, cell in net.cells_and_names(): if isinstance(cell, nn.Dense): @@ -62,9 +62,9 @@ if __name__ == '__main__': dataset = create_dataset(dataset_path=args_opt.dataset_path, do_train=False, - config=config_platform, - platform=args_opt.platform, - batch_size=config_platform.batch_size) + config=config, + device_target=args_opt.device_target, + batch_size=config.batch_size) step_size = dataset.get_dataset_size() if args_opt.checkpoint_path: diff --git a/model_zoo/official/cv/mobilenetv2/scripts/run_infer.sh b/model_zoo/official/cv/mobilenetv2/scripts/run_infer.sh index 7385a221d..e13aa981e 100644 --- a/model_zoo/official/cv/mobilenetv2/scripts/run_infer.sh +++ b/model_zoo/official/cv/mobilenetv2/scripts/run_infer.sh @@ -15,8 +15,8 @@ # ============================================================================ if [ $# != 3 ] then - echo "Ascend: sh run_infer.sh [PLATFORM] [DATASET_PATH] [CHECKPOINT_PATH] \ - GPU: sh run_infer.sh [PLATFORM] [DATASET_PATH] [CHECKPOINT_PATH]" + echo "Ascend: sh run_infer.sh [DEVICE_TARGET] [DATASET_PATH] [CHECKPOINT_PATH] \ + GPU: sh run_infer.sh [DEVICE_TARGET] [DATASET_PATH] [CHECKPOINT_PATH]" exit 1 fi @@ -49,7 +49,7 @@ cd ../eval || exit # luanch python ${BASEPATH}/../eval.py \ - --platform=$1 \ + --device_target=$1 \ --dataset_path=$2 \ --checkpoint_path=$3 \ &> ../infer.log & # dataset val folder path diff --git a/model_zoo/official/cv/mobilenetv2/scripts/run_train.sh b/model_zoo/official/cv/mobilenetv2/scripts/run_train.sh index c260aac78..efd203f3a 100644 --- a/model_zoo/official/cv/mobilenetv2/scripts/run_train.sh +++ b/model_zoo/official/cv/mobilenetv2/scripts/run_train.sh @@ -43,7 +43,7 @@ run_ascend() --training_script=${BASEPATH}/../train.py \ --dataset_path=$5 \ --pre_trained=$6 \ - --platform=$1 &> ../train.log & # dataset train folder + --device_target=$1 &> ../train.log & # dataset train folder } run_gpu() @@ -73,7 +73,7 @@ run_gpu() mpirun -n $2 --allow-run-as-root \ python ${BASEPATH}/../train.py \ --dataset_path=$4 \ - --platform=$1 \ + --device_target=$1 \ &> ../train.log & # dataset train folder } @@ -91,6 +91,6 @@ if [ $1 = "Ascend" ] ; then elif [ $1 = "GPU" ] ; then run_gpu "$@" else - echo "Unsupported platform." + echo "Unsupported device_target." fi; diff --git a/model_zoo/official/cv/mobilenetv2/src/dataset.py b/model_zoo/official/cv/mobilenetv2/src/dataset.py index 1edfcabfa..887d86a5e 100644 --- a/model_zoo/official/cv/mobilenetv2/src/dataset.py +++ b/model_zoo/official/cv/mobilenetv2/src/dataset.py @@ -21,7 +21,7 @@ import mindspore.dataset.engine as de import mindspore.dataset.transforms.vision.c_transforms as C import mindspore.dataset.transforms.c_transforms as C2 -def create_dataset(dataset_path, do_train, config, platform, repeat_num=1, batch_size=32): +def create_dataset(dataset_path, do_train, config, device_target, repeat_num=1, batch_size=32): """ create a train or eval dataset @@ -34,7 +34,7 @@ def create_dataset(dataset_path, do_train, config, platform, repeat_num=1, batch Returns: dataset """ - if platform == "Ascend": + if device_target == "Ascend": rank_size = int(os.getenv("RANK_SIZE")) rank_id = int(os.getenv("RANK_ID")) if rank_size == 1: @@ -42,7 +42,7 @@ def create_dataset(dataset_path, do_train, config, platform, repeat_num=1, batch else: ds = de.ImageFolderDatasetV2(dataset_path, num_parallel_workers=8, shuffle=True, num_shards=rank_size, shard_id=rank_id) - elif platform == "GPU": + elif device_target == "GPU": if do_train: from mindspore.communication.management import get_rank, get_group_size ds = de.ImageFolderDatasetV2(dataset_path, num_parallel_workers=8, shuffle=True, @@ -50,7 +50,7 @@ def create_dataset(dataset_path, do_train, config, platform, repeat_num=1, batch else: ds = de.ImageFolderDatasetV2(dataset_path, num_parallel_workers=8, shuffle=True) else: - raise ValueError("Unsupport platform.") + raise ValueError("Unsupported device_target.") resize_height = config.image_height resize_width = config.image_width diff --git a/model_zoo/official/cv/mobilenetv2/src/mobilenetV2.py b/model_zoo/official/cv/mobilenetv2/src/mobilenetV2.py index 76fa21acd..6d0b6f38e 100644 --- a/model_zoo/official/cv/mobilenetv2/src/mobilenetV2.py +++ b/model_zoo/official/cv/mobilenetv2/src/mobilenetV2.py @@ -119,15 +119,15 @@ class ConvBNReLU(nn.Cell): >>> ConvBNReLU(16, 256, kernel_size=1, stride=1, groups=1) """ - def __init__(self, platform, in_planes, out_planes, kernel_size=3, stride=1, groups=1): + def __init__(self, device_target, in_planes, out_planes, kernel_size=3, stride=1, groups=1): super(ConvBNReLU, self).__init__() padding = (kernel_size - 1) // 2 if groups == 1: conv = nn.Conv2d(in_planes, out_planes, kernel_size, stride, pad_mode='pad', padding=padding) else: - if platform == "Ascend": + if device_target == "Ascend": conv = DepthwiseConv(in_planes, kernel_size, stride, pad_mode='pad', pad=padding) - elif platform == "GPU": + elif device_target == "GPU": conv = nn.Conv2d(in_planes, out_planes, kernel_size, stride, group=in_planes, pad_mode='pad', padding=padding) @@ -156,7 +156,7 @@ class InvertedResidual(nn.Cell): >>> ResidualBlock(3, 256, 1, 1) """ - def __init__(self, platform, inp, oup, stride, expand_ratio): + def __init__(self, device_target, inp, oup, stride, expand_ratio): super(InvertedResidual, self).__init__() assert stride in [1, 2] @@ -165,10 +165,10 @@ class InvertedResidual(nn.Cell): layers = [] if expand_ratio != 1: - layers.append(ConvBNReLU(platform, inp, hidden_dim, kernel_size=1)) + layers.append(ConvBNReLU(device_target, inp, hidden_dim, kernel_size=1)) layers.extend([ # dw - ConvBNReLU(platform, hidden_dim, hidden_dim, + ConvBNReLU(device_target, hidden_dim, hidden_dim, stride=stride, groups=hidden_dim), # pw-linear nn.Conv2d(hidden_dim, oup, kernel_size=1, @@ -204,7 +204,7 @@ class MobileNetV2(nn.Cell): >>> MobileNetV2(num_classes=1000) """ - def __init__(self, platform, num_classes=1000, width_mult=1., + def __init__(self, device_target, num_classes=1000, width_mult=1., has_dropout=False, inverted_residual_setting=None, round_nearest=8): super(MobileNetV2, self).__init__() block = InvertedResidual @@ -227,16 +227,16 @@ class MobileNetV2(nn.Cell): # building first layer input_channel = _make_divisible(input_channel * width_mult, round_nearest) self.out_channels = _make_divisible(last_channel * max(1.0, width_mult), round_nearest) - features = [ConvBNReLU(platform, 3, input_channel, stride=2)] + features = [ConvBNReLU(device_target, 3, input_channel, stride=2)] # building inverted residual blocks for t, c, n, s in self.cfgs: output_channel = _make_divisible(c * width_mult, round_nearest) for i in range(n): stride = s if i == 0 else 1 - features.append(block(platform, input_channel, output_channel, stride, expand_ratio=t)) + features.append(block(device_target, input_channel, output_channel, stride, expand_ratio=t)) input_channel = output_channel # building last several layers - features.append(ConvBNReLU(platform, input_channel, self.out_channels, kernel_size=1)) + features.append(ConvBNReLU(device_target, input_channel, self.out_channels, kernel_size=1)) # make it nn.CellList self.features = nn.SequentialCell(features) # mobilenet head diff --git a/model_zoo/official/cv/mobilenetv2/train.py b/model_zoo/official/cv/mobilenetv2/train.py index 8862937a8..65cbbac6e 100644 --- a/model_zoo/official/cv/mobilenetv2/train.py +++ b/model_zoo/official/cv/mobilenetv2/train.py @@ -49,10 +49,10 @@ de.config.set_seed(1) parser = argparse.ArgumentParser(description='Image classification') parser.add_argument('--dataset_path', type=str, default=None, help='Dataset path') parser.add_argument('--pre_trained', type=str, default=None, help='Pretrained checkpoint path') -parser.add_argument('--platform', type=str, default=None, help='run platform') +parser.add_argument('--device_targe', type=str, default=None, help='run device_targe') args_opt = parser.parse_args() -if args_opt.platform == "Ascend": +if args_opt.device_targe == "Ascend": device_id = int(os.getenv('DEVICE_ID')) rank_id = int(os.getenv('RANK_ID')) rank_size = int(os.getenv('RANK_SIZE')) @@ -61,7 +61,7 @@ if args_opt.platform == "Ascend": context.set_context(mode=context.GRAPH_MODE, device_target="Ascend", device_id=device_id, save_graphs=False) -elif args_opt.platform == "GPU": +elif args_opt.device_targe == "GPU": context.set_context(mode=context.GRAPH_MODE, device_target="GPU", save_graphs=False) @@ -161,13 +161,13 @@ class Monitor(Callback): if __name__ == '__main__': - if args_opt.platform == "GPU": + if args_opt.device_targe == "GPU": # train on gpu print("train args: ", args_opt) print("cfg: ", config_gpu) # define network - net = mobilenet_v2(num_classes=config_gpu.num_classes, platform="GPU") + net = mobilenet_v2(num_classes=config_gpu.num_classes, device_targe="GPU") # define loss if config_gpu.label_smooth > 0: loss = CrossEntropyWithLabelSmooth(smooth_factor=config_gpu.label_smooth, @@ -179,7 +179,7 @@ if __name__ == '__main__': dataset = create_dataset(dataset_path=args_opt.dataset_path, do_train=True, config=config_gpu, - platform=args_opt.platform, + device_targe=args_opt.device_targe, repeat_num=1, batch_size=config_gpu.batch_size) step_size = dataset.get_dataset_size() @@ -216,7 +216,7 @@ if __name__ == '__main__': # begin train model.train(epoch_size, dataset, callbacks=cb) print("============== End Training ==============") - elif args_opt.platform == "Ascend": + elif args_opt.device_targe == "Ascend": # train on ascend print("train args: ", args_opt, "\ncfg: ", config_ascend, "\nparallel args: rank_id {}, device_id {}, rank_size {}".format(rank_id, device_id, rank_size)) @@ -228,7 +228,7 @@ if __name__ == '__main__': init() epoch_size = config_ascend.epoch_size - net = mobilenet_v2(num_classes=config_ascend.num_classes, platform="Ascend") + net = mobilenet_v2(num_classes=config_ascend.num_classes, device_targe="Ascend") net.to_float(mstype.float16) for _, cell in net.cells_and_names(): if isinstance(cell, nn.Dense): @@ -242,7 +242,7 @@ if __name__ == '__main__': dataset = create_dataset(dataset_path=args_opt.dataset_path, do_train=True, config=config_ascend, - platform=args_opt.platform, + device_targe=args_opt.device_targe, repeat_num=1, batch_size=config_ascend.batch_size) step_size = dataset.get_dataset_size() @@ -276,4 +276,4 @@ if __name__ == '__main__': cb += [ckpt_cb] model.train(epoch_size, dataset, callbacks=cb) else: - raise ValueError("Unsupport platform.") + raise ValueError("Unsupported device_targe.") diff --git a/model_zoo/official/cv/mobilenetv2_quant/src/dataset.py b/model_zoo/official/cv/mobilenetv2_quant/src/dataset.py index ce9f2d8fa..81f49682c 100644 --- a/model_zoo/official/cv/mobilenetv2_quant/src/dataset.py +++ b/model_zoo/official/cv/mobilenetv2_quant/src/dataset.py @@ -61,7 +61,7 @@ def create_dataset(dataset_path, do_train, config, device_target, repeat_num=1, else: ds = de.ImageFolderDatasetV2(dataset_path, num_parallel_workers=8, shuffle=True) else: - raise ValueError("Unsupport device_target.") + raise ValueError("Unsupported device_target.") resize_height = config.image_height diff --git a/model_zoo/official/cv/mobilenetv2_quant/train.py b/model_zoo/official/cv/mobilenetv2_quant/train.py index bd8051ccc..ba7fe4791 100644 --- a/model_zoo/official/cv/mobilenetv2_quant/train.py +++ b/model_zoo/official/cv/mobilenetv2_quant/train.py @@ -207,3 +207,5 @@ if __name__ == '__main__': train_on_ascend() elif args_opt.device_target == "GPU": train_on_gpu() + else: + raise ValueError("Unsupported device target.") diff --git a/model_zoo/official/cv/mobilenetv3/eval.py b/model_zoo/official/cv/mobilenetv3/eval.py index e82ed496d..a44756dfe 100644 --- a/model_zoo/official/cv/mobilenetv3/eval.py +++ b/model_zoo/official/cv/mobilenetv3/eval.py @@ -30,29 +30,29 @@ from src.mobilenetV3 import mobilenet_v3_large parser = argparse.ArgumentParser(description='Image classification') parser.add_argument('--checkpoint_path', type=str, default=None, help='Checkpoint file path') parser.add_argument('--dataset_path', type=str, default=None, help='Dataset path') -parser.add_argument('--platform', type=str, default=None, help='run platform') +parser.add_argument('--device_target', type=str, default=None, help='run device_target') args_opt = parser.parse_args() if __name__ == '__main__': - config_platform = None - if args_opt.platform == "Ascend": - config_platform = config_ascend + config = None + if args_opt.device_target == "Ascend": + config = config_ascend device_id = int(os.getenv('DEVICE_ID')) context.set_context(mode=context.GRAPH_MODE, device_target="Ascend", device_id=device_id, save_graphs=False) - elif args_opt.platform == "GPU": - config_platform = config_gpu + elif args_opt.device_target == "GPU": + config = config_gpu context.set_context(mode=context.GRAPH_MODE, device_target="GPU", save_graphs=False) else: - raise ValueError("Unsupport platform.") + raise ValueError("Unsupported device_target.") loss = nn.SoftmaxCrossEntropyWithLogits( is_grad=False, sparse=True, reduction='mean') - net = mobilenet_v3_large(num_classes=config_platform.num_classes) + net = mobilenet_v3_large(num_classes=config.num_classes) - if args_opt.platform == "Ascend": + if args_opt.device_target == "Ascend": net.to_float(mstype.float16) for _, cell in net.cells_and_names(): if isinstance(cell, nn.Dense): @@ -60,9 +60,9 @@ if __name__ == '__main__': dataset = create_dataset(dataset_path=args_opt.dataset_path, do_train=False, - config=config_platform, - platform=args_opt.platform, - batch_size=config_platform.batch_size) + config=config, + device_target=args_opt.device_target, + batch_size=config.batch_size) step_size = dataset.get_dataset_size() if args_opt.checkpoint_path: diff --git a/model_zoo/official/cv/mobilenetv3/scripts/run_infer.sh b/model_zoo/official/cv/mobilenetv3/scripts/run_infer.sh index 7385a221d..529e8b10b 100644 --- a/model_zoo/official/cv/mobilenetv3/scripts/run_infer.sh +++ b/model_zoo/official/cv/mobilenetv3/scripts/run_infer.sh @@ -15,8 +15,7 @@ # ============================================================================ if [ $# != 3 ] then - echo "Ascend: sh run_infer.sh [PLATFORM] [DATASET_PATH] [CHECKPOINT_PATH] \ - GPU: sh run_infer.sh [PLATFORM] [DATASET_PATH] [CHECKPOINT_PATH]" + echo "GPU: sh run_infer.sh [DEVICE_TARGET] [DATASET_PATH] [CHECKPOINT_PATH]" exit 1 fi @@ -49,7 +48,7 @@ cd ../eval || exit # luanch python ${BASEPATH}/../eval.py \ - --platform=$1 \ + --device_target=$1 \ --dataset_path=$2 \ --checkpoint_path=$3 \ &> ../infer.log & # dataset val folder path diff --git a/model_zoo/official/cv/mobilenetv3/scripts/run_train.sh b/model_zoo/official/cv/mobilenetv3/scripts/run_train.sh index 7ac12c226..25c0667a5 100644 --- a/model_zoo/official/cv/mobilenetv3/scripts/run_train.sh +++ b/model_zoo/official/cv/mobilenetv3/scripts/run_train.sh @@ -13,36 +13,6 @@ # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================ -run_ascend() -{ - if [ $2 -lt 1 ] && [ $2 -gt 8 ] - then - echo "error: DEVICE_NUM=$2 is not in (1-8)" - exit 1 - fi - - if [ ! -d $5 ] - then - echo "error: DATASET_PATH=$5 is not a directory" - exit 1 - fi - - BASEPATH=$(cd "`dirname $0`" || exit; pwd) - export PYTHONPATH=${BASEPATH}:$PYTHONPATH - if [ -d "../train" ]; - then - rm -rf ../train - fi - mkdir ../train - cd ../train || exit - python ${BASEPATH}/../src/launch.py \ - --nproc_per_node=$2 \ - --visible_devices=$4 \ - --server_id=$3 \ - --training_script=${BASEPATH}/../train.py \ - --dataset_path=$5 \ - --platform=$1 &> ../train.log & # dataset train folder -} run_gpu() { @@ -71,24 +41,21 @@ run_gpu() mpirun -n $2 --allow-run-as-root \ python ${BASEPATH}/../train.py \ --dataset_path=$4 \ - --platform=$1 \ + --device_target=$1 \ &> ../train.log & # dataset train folder } if [ $# -gt 5 ] || [ $# -lt 4 ] then echo "Usage:\n \ - Ascend: sh run_train.sh Ascend [DEVICE_NUM] [SERVER_IP(x.x.x.x)] [VISIABLE_DEVICES(0,1,2,3,4,5,6,7)] [DATASET_PATH]\n \ GPU: sh run_train.sh GPU [DEVICE_NUM] [VISIABLE_DEVICES(0,1,2,3,4,5,6,7)] [DATASET_PATH]\n \ " exit 1 fi -if [ $1 = "Ascend" ] ; then - run_ascend "$@" -elif [ $1 = "GPU" ] ; then +if [ $1 = "GPU" ] ; then run_gpu "$@" else - echo "not support platform" + echo "Unsupported device_target" fi; diff --git a/model_zoo/official/cv/mobilenetv3/src/config.py b/model_zoo/official/cv/mobilenetv3/src/config.py index 279a55c34..586b93a78 100644 --- a/model_zoo/official/cv/mobilenetv3/src/config.py +++ b/model_zoo/official/cv/mobilenetv3/src/config.py @@ -17,24 +17,6 @@ network config setting, will be used in train.py and eval.py """ from easydict import EasyDict as ed -config_ascend = ed({ - "num_classes": 1000, - "image_height": 224, - "image_width": 224, - "batch_size": 256, - "epoch_size": 200, - "warmup_epochs": 4, - "lr": 0.4, - "momentum": 0.9, - "weight_decay": 4e-5, - "label_smooth": 0.1, - "loss_scale": 1024, - "save_checkpoint": True, - "save_checkpoint_epochs": 1, - "keep_checkpoint_max": 200, - "save_checkpoint_path": "./checkpoint", -}) - config_gpu = ed({ "num_classes": 1000, "image_height": 224, diff --git a/model_zoo/official/cv/mobilenetv3/src/dataset.py b/model_zoo/official/cv/mobilenetv3/src/dataset.py index d2fa12f79..869c6ab3e 100644 --- a/model_zoo/official/cv/mobilenetv3/src/dataset.py +++ b/model_zoo/official/cv/mobilenetv3/src/dataset.py @@ -15,14 +15,13 @@ """ create train or eval dataset. """ -import os import mindspore.common.dtype as mstype import mindspore.dataset.engine as de import mindspore.dataset.transforms.vision.c_transforms as C import mindspore.dataset.transforms.c_transforms as C2 -def create_dataset(dataset_path, do_train, config, platform, repeat_num=1, batch_size=32): +def create_dataset(dataset_path, do_train, config, device_target, repeat_num=1, batch_size=32): """ create a train or eval dataset @@ -35,15 +34,7 @@ def create_dataset(dataset_path, do_train, config, platform, repeat_num=1, batch Returns: dataset """ - if platform == "Ascend": - rank_size = int(os.getenv("RANK_SIZE")) - rank_id = int(os.getenv("RANK_ID")) - if rank_size == 1: - ds = de.ImageFolderDatasetV2(dataset_path, num_parallel_workers=8, shuffle=True) - else: - ds = de.ImageFolderDatasetV2(dataset_path, num_parallel_workers=8, shuffle=True, - num_shards=rank_size, shard_id=rank_id) - elif platform == "GPU": + if device_target == "GPU": if do_train: from mindspore.communication.management import get_rank, get_group_size ds = de.ImageFolderDatasetV2(dataset_path, num_parallel_workers=8, shuffle=True, @@ -51,7 +42,7 @@ def create_dataset(dataset_path, do_train, config, platform, repeat_num=1, batch else: ds = de.ImageFolderDatasetV2(dataset_path, num_parallel_workers=8, shuffle=True) else: - raise ValueError("Unsupport platform.") + raise ValueError("Unsupported device_target.") resize_height = config.image_height resize_width = config.image_width diff --git a/model_zoo/official/cv/mobilenetv3/train.py b/model_zoo/official/cv/mobilenetv3/train.py index 5f2a3502a..b103bfa36 100644 --- a/model_zoo/official/cv/mobilenetv3/train.py +++ b/model_zoo/official/cv/mobilenetv3/train.py @@ -22,7 +22,6 @@ import numpy as np from mindspore import context from mindspore import Tensor from mindspore import nn -from mindspore.parallel._auto_parallel_context import auto_parallel_context from mindspore.nn.optim.momentum import Momentum from mindspore.nn.loss import SoftmaxCrossEntropyWithLogits from mindspore.nn.loss.loss import _Loss @@ -38,7 +37,7 @@ from mindspore.communication.management import init, get_group_size, get_rank from src.dataset import create_dataset from src.lr_generator import get_lr -from src.config import config_gpu, config_ascend +from src.config import config_gpu from src.mobilenetV3 import mobilenet_v3_large random.seed(1) @@ -48,10 +47,10 @@ de.config.set_seed(1) parser = argparse.ArgumentParser(description='Image classification') parser.add_argument('--dataset_path', type=str, default=None, help='Dataset path') parser.add_argument('--pre_trained', type=str, default=None, help='Pretrained checkpoint path') -parser.add_argument('--platform', type=str, default=None, help='run platform') +parser.add_argument('--device_target', type=str, default=None, help='run device_target') args_opt = parser.parse_args() -if args_opt.platform == "Ascend": +if args_opt.device_target == "Ascend": device_id = int(os.getenv('DEVICE_ID')) rank_id = int(os.getenv('RANK_ID')) rank_size = int(os.getenv('RANK_SIZE')) @@ -61,7 +60,7 @@ if args_opt.platform == "Ascend": device_target="Ascend", device_id=device_id, save_graphs=False) -elif args_opt.platform == "GPU": +elif args_opt.device_target == "GPU": context.set_context(mode=context.GRAPH_MODE, device_target="GPU", save_graphs=False) @@ -70,7 +69,7 @@ elif args_opt.platform == "GPU": parallel_mode=ParallelMode.DATA_PARALLEL, mirror_mean=True) else: - raise ValueError("Unsupport platform.") + raise ValueError("Unsupported device_target.") class CrossEntropyWithLabelSmooth(_Loss): @@ -161,7 +160,7 @@ class Monitor(Callback): if __name__ == '__main__': - if args_opt.platform == "GPU": + if args_opt.device_target == "GPU": # train on gpu print("train args: ", args_opt) print("cfg: ", config_gpu) @@ -180,7 +179,7 @@ if __name__ == '__main__': dataset = create_dataset(dataset_path=args_opt.dataset_path, do_train=True, config=config_gpu, - platform=args_opt.platform, + device_target=args_opt.device_target, repeat_num=1, batch_size=config_gpu.batch_size) step_size = dataset.get_dataset_size() @@ -213,64 +212,3 @@ if __name__ == '__main__': cb += [ckpt_cb] # begine train model.train(epoch_size, dataset, callbacks=cb) - elif args_opt.platform == "Ascend": - # train on ascend - print("train args: ", args_opt, "\ncfg: ", config_ascend, - "\nparallel args: rank_id {}, device_id {}, rank_size {}".format(rank_id, device_id, rank_size)) - - if run_distribute: - context.set_auto_parallel_context(device_num=rank_size, parallel_mode=ParallelMode.DATA_PARALLEL, - parameter_broadcast=True, mirror_mean=True) - auto_parallel_context().set_all_reduce_fusion_split_indices([140]) - init() - - epoch_size = config_ascend.epoch_size - net = mobilenet_v3_large(num_classes=config_ascend.num_classes) - net.to_float(mstype.float16) - for _, cell in net.cells_and_names(): - if isinstance(cell, nn.Dense): - cell.to_float(mstype.float32) - if config_ascend.label_smooth > 0: - loss = CrossEntropyWithLabelSmooth( - smooth_factor=config_ascend.label_smooth, num_classes=config.num_classes) - else: - loss = SoftmaxCrossEntropyWithLogits( - is_grad=False, sparse=True, reduction='mean') - dataset = create_dataset(dataset_path=args_opt.dataset_path, - do_train=True, - config=config_ascend, - platform=args_opt.platform, - repeat_num=1, - batch_size=config_ascend.batch_size) - step_size = dataset.get_dataset_size() - if args_opt.pre_trained: - param_dict = load_checkpoint(args_opt.pre_trained) - load_param_into_net(net, param_dict) - - loss_scale = FixedLossScaleManager( - config_ascend.loss_scale, drop_overflow_update=False) - lr = Tensor(get_lr(global_step=0, - lr_init=0, - lr_end=0, - lr_max=config_ascend.lr, - warmup_epochs=config_ascend.warmup_epochs, - total_epochs=epoch_size, - steps_per_epoch=step_size)) - opt = Momentum(filter(lambda x: x.requires_grad, net.get_parameters()), lr, config_ascend.momentum, - config_ascend.weight_decay, config_ascend.loss_scale) - - model = Model(net, loss_fn=loss, optimizer=opt, - loss_scale_manager=loss_scale) - - cb = None - if rank_id == 0: - cb = [Monitor(lr_init=lr.asnumpy())] - if config_ascend.save_checkpoint: - config_ck = CheckpointConfig(save_checkpoint_steps=config_ascend.save_checkpoint_epochs * step_size, - keep_checkpoint_max=config_ascend.keep_checkpoint_max) - ckpt_cb = ModelCheckpoint( - prefix="mobilenetV3", directory=config_ascend.save_checkpoint_path, config=config_ck) - cb += [ckpt_cb] - model.train(epoch_size, dataset, callbacks=cb) - else: - raise Exception diff --git a/model_zoo/official/nlp/bert_thor/src/model_thor.py b/model_zoo/official/nlp/bert_thor/src/model_thor.py index ea35f0dab..2ccb8b6ec 100644 --- a/model_zoo/official/nlp/bert_thor/src/model_thor.py +++ b/model_zoo/official/nlp/bert_thor/src/model_thor.py @@ -176,7 +176,7 @@ class Model: def _check_kwargs(self, kwargs): for arg in kwargs: if arg not in ['loss_scale_manager', 'keep_batchnorm_fp32']: - raise ValueError(f"Unsupport arg '{arg}'") + raise ValueError(f"Unsupported arg '{arg}'") def _build_train_network(self): """Build train network""" diff --git a/serving/acl/dvpp_process.cc b/serving/acl/dvpp_process.cc index 1fedaf640..8a65d94b1 100644 --- a/serving/acl/dvpp_process.cc +++ b/serving/acl/dvpp_process.cc @@ -1085,7 +1085,7 @@ Status DvppJsonConfigParser::InitWithJsonConfigImp(const std::string &json_confi return FAILED; } } else { - MSI_LOG_ERROR << "Unsupport op name " << op_name << ", expect resize, crop or crop_and_paste"; + MSI_LOG_ERROR << "Unsupported op name " << op_name << ", expect resize, crop or crop_and_paste"; return FAILED; } return SUCCESS; diff --git a/tests/st/networks/models/resnet50/src_thor/model_thor.py b/tests/st/networks/models/resnet50/src_thor/model_thor.py index 07b9e60be..2399c4a01 100644 --- a/tests/st/networks/models/resnet50/src_thor/model_thor.py +++ b/tests/st/networks/models/resnet50/src_thor/model_thor.py @@ -169,7 +169,7 @@ class Model: def _check_kwargs(self, kwargs): for arg in kwargs: if arg not in ['loss_scale_manager', 'keep_batchnorm_fp32']: - raise ValueError(f"Unsupport arg '{arg}'") + raise ValueError(f"Unsupported arg '{arg}'") def _build_train_network(self): """Build train network""" -- GitLab