From 5bbfa674398a6052e8ad8e1bbb144eb7e4bb8f95 Mon Sep 17 00:00:00 2001 From: chenzomi Date: Wed, 19 Aug 2020 10:17:12 +0800 Subject: [PATCH] bug fix for ME --- mindspore/nn/layer/conv.py | 30 ++++++++----------- model_zoo/official/cv/mobilenetv2/eval.py | 2 +- .../cv/mobilenetv2/scripts/run_train.sh | 3 +- model_zoo/official/cv/mobilenetv2/train.py | 20 ++++++------- model_zoo/official/cv/mobilenetv3/Readme.md | 8 ++--- 5 files changed, 28 insertions(+), 35 deletions(-) diff --git a/mindspore/nn/layer/conv.py b/mindspore/nn/layer/conv.py index 9a1d132447..96bcd966ef 100644 --- a/mindspore/nn/layer/conv.py +++ b/mindspore/nn/layer/conv.py @@ -51,6 +51,8 @@ class _Conv(Cell): self.kernel_size = kernel_size self.stride = stride self.pad_mode = pad_mode + self.weight_init = weight_init + self.bias_init = bias_init if isinstance(padding, int): Validator.check_integer('padding', padding, 0, Rel.GE, self.cls_name) self.padding = padding @@ -85,12 +87,12 @@ class _Conv(Cell): shape = [in_channels, out_channels // group, *kernel_size] else: shape = [out_channels, in_channels // group, *kernel_size] - self.weight = Parameter(initializer(weight_init, shape), name='weight') + self.weight = Parameter(initializer(self.weight_init, shape), name='weight') if check_bool(has_bias): - self.bias = Parameter(initializer(bias_init, [out_channels]), name='bias') + self.bias = Parameter(initializer(self.bias_init, [out_channels]), name='bias') else: - if bias_init != 'zeros': + if self.bias_init != 'zeros': logger.warning("Value of 'has_bias' is False, value of 'bias_init' will be ignored.") self.bias = None @@ -249,11 +251,8 @@ class Conv2d(_Conv): self.dilation, self.group, self.has_bias, - self.weight, - self.bias) - - if self.has_bias: - s += ', bias={}'.format(self.bias) + self.weight_init, + self.bias_init) return s @@ -431,11 +430,8 @@ class Conv1d(_Conv): self.dilation, self.group, self.has_bias, - self.weight, - self.bias) - - if self.has_bias: - s += ', bias={}'.format(self.bias) + self.weight_init, + self.bias_init) return s @@ -605,8 +601,8 @@ class Conv2dTranspose(_Conv): self.dilation, self.group, self.has_bias, - self.weight, - self.bias) + self.weight_init, + self.bias_init) return s @@ -788,8 +784,8 @@ class Conv1dTranspose(_Conv): self.dilation, self.group, self.has_bias, - self.weight, - self.bias) + self.weight_init, + self.bias_init) return s diff --git a/model_zoo/official/cv/mobilenetv2/eval.py b/model_zoo/official/cv/mobilenetv2/eval.py index b9c92bb19e..6431f6bfd3 100644 --- a/model_zoo/official/cv/mobilenetv2/eval.py +++ b/model_zoo/official/cv/mobilenetv2/eval.py @@ -30,7 +30,7 @@ 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('--device_targe', type=str, default=None, help='run device_targe') +parser.add_argument('--device_target', type=str, default=None, help='run device_target') args_opt = parser.parse_args() diff --git a/model_zoo/official/cv/mobilenetv2/scripts/run_train.sh b/model_zoo/official/cv/mobilenetv2/scripts/run_train.sh index efd203f3ad..0cd24a0f2f 100644 --- a/model_zoo/official/cv/mobilenetv2/scripts/run_train.sh +++ b/model_zoo/official/cv/mobilenetv2/scripts/run_train.sh @@ -73,6 +73,7 @@ run_gpu() mpirun -n $2 --allow-run-as-root \ python ${BASEPATH}/../train.py \ --dataset_path=$4 \ + --pre_trained=$5 \ --device_target=$1 \ &> ../train.log & # dataset train folder } @@ -81,7 +82,7 @@ if [ $# -gt 6 ] || [ $# -lt 4 ] then echo "Usage:\n \ Ascend: sh run_train.sh Ascend [DEVICE_NUM] [VISIABLE_DEVICES(0,1,2,3,4,5,6,7)] [RANK_TABLE_FILE] [DATASET_PATH] [CKPT_PATH]\n \ - GPU: sh run_train.sh GPU [DEVICE_NUM] [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] [CKPT_PATH]\n \ " exit 1 fi diff --git a/model_zoo/official/cv/mobilenetv2/train.py b/model_zoo/official/cv/mobilenetv2/train.py index 65cbbac6e3..5ea5e6d2c3 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('--device_targe', type=str, default=None, help='run device_targe') +parser.add_argument('--device_target', type=str, default=None, help='run device_target') args_opt = parser.parse_args() -if args_opt.device_targe == "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 +61,7 @@ if args_opt.device_targe == "Ascend": context.set_context(mode=context.GRAPH_MODE, device_target="Ascend", device_id=device_id, save_graphs=False) -elif args_opt.device_targe == "GPU": +elif args_opt.device_target == "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.device_targe == "GPU": + if args_opt.device_target == "GPU": # train on gpu print("train args: ", args_opt) print("cfg: ", config_gpu) # define network - net = mobilenet_v2(num_classes=config_gpu.num_classes, device_targe="GPU") + net = mobilenet_v2(num_classes=config_gpu.num_classes, device_target="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, - device_targe=args_opt.device_targe, + device_target=args_opt.device_target, 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.device_targe == "Ascend": + elif args_opt.device_target == "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, device_targe="Ascend") + net = mobilenet_v2(num_classes=config_ascend.num_classes, device_target="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, - device_targe=args_opt.device_targe, + device_target=args_opt.device_target, 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("Unsupported device_targe.") + raise ValueError("Unsupported device_target.") diff --git a/model_zoo/official/cv/mobilenetv3/Readme.md b/model_zoo/official/cv/mobilenetv3/Readme.md index fa5ca1ae77..7031faa9e4 100644 --- a/model_zoo/official/cv/mobilenetv3/Readme.md +++ b/model_zoo/official/cv/mobilenetv3/Readme.md @@ -27,8 +27,8 @@ Dataset used: [imagenet](http://www.image-net.org/) # Environment Requirements -- Hardware（Ascend/GPU） - - Prepare hardware environment with Ascend or GPU processor. If you want to try Ascend , please send the [application form](https://obs-9be7.obs.cn-east-2.myhuaweicloud.com/file/other/Ascend%20Model%20Zoo%E4%BD%93%E9%AA%8C%E8%B5%84%E6%BA%90%E7%94%B3%E8%AF%B7%E8%A1%A8.docx) to ascend@huawei.com. Once approved, you can get the resources. +- Hardware（GPU） + - Prepare hardware environment with GPU processor. - Framework - [MindSpore](http://10.90.67.50/mindspore/archive/20200506/OpenSource/me_vm_x86/) - For more information, please check the resources below： @@ -60,14 +60,12 @@ Dataset used: [imagenet](http://www.image-net.org/) ### Usage -- 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] - GPU: sh run_trian.sh GPU [DEVICE_NUM] [VISIABLE_DEVICES(0,1,2,3,4,5,6,7)] [DATASET_PATH] ### Launch ``` # training example - Ascend: sh run_train.sh Ascend 8 192.168.0.1 0,1,2,3,4,5,6,7 ~/imagenet/train/ GPU: sh run_train.sh GPU 8 0,1,2,3,4,5,6,7 ~/imagenet/train/ ``` @@ -86,14 +84,12 @@ epoch time: 138331.250, per step time: 221.330, avg loss: 3.917 ### Usage -- Ascend: sh run_infer.sh Ascend [DATASET_PATH] [CHECKPOINT_PATH] - GPU: sh run_infer.sh GPU [DATASET_PATH] [CHECKPOINT_PATH] ### Launch ``` # infer example - Ascend: sh run_infer.sh Ascend ~/imagenet/val/ ~/train/mobilenet-200_625.ckpt GPU: sh run_infer.sh GPU ~/imagenet/val/ ~/train/mobilenet-200_625.ckpt ```