forked from mindspore-Ecosystem/mindspore
add fasterrcnn, mass, unet, psenet hub conf file.
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# Copyright 2020 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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"""hub config."""
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from src.FasterRcnn.faster_rcnn_r50 import Faster_Rcnn_Resnet50
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from src.config import config
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def create_network(name, *args, **kwargs):
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if name == "faster_rcnn":
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return Faster_Rcnn_Resnet50(config=config)
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raise NotImplementedError(f"{name} is not implemented in the repo")
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# Copyright 2020 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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"""hub config."""
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from src.ETSNET.etsnet import ETSNet
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from src.config import config
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def create_network(name, *args, **kwargs):
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if name == "psenet":
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infer_mode = kwargs.get("infer_mode", False)
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config.INFERENCE = infer_mode
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return ETSNet(config)
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raise NotImplementedError(f"{name} is not implemented in the repo")
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# Copyright 2020 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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"""hub config."""
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from src.unet import UNet
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def create_network(name, *args, **kwargs):
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if name == "unet2d":
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unet = UNet(*args, **kwargs)
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return unet
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raise NotImplementedError(f"{name} is not implemented in the repo")
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# Copyright 2020 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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"""hub config."""
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import mindspore.common.dtype as mstype
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from config import TransformerConfig
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from src.transformer import TransformerNetworkWithLoss, TransformerInferModel
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def get_config(config):
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config = TransformerConfig.from_json_file(config)
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config.compute_type = mstype.float16
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config.dtype = mstype.float32
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return config
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def create_network(name, *args, **kwargs):
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"""create mass network."""
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if name == "mass":
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if "config" in kwargs:
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config = get_config(kwargs["config"])
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else:
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raise NotImplementedError(f"Please make sure the configuration file path is correct")
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is_training = kwargs.get("is_training", False)
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if is_training:
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return TransformerNetworkWithLoss(config, is_training=is_training, *args)
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return TransformerInferModel(config, *args)
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raise NotImplementedError(f"{name} is not implemented in the repo")
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