forked from huawei/mindspore2022
53 lines
1.8 KiB
Python
53 lines
1.8 KiB
Python
# 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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"""Weight loader."""
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import numpy as np
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from mindspore.train.serialization import load_checkpoint
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def load_infer_weights(config):
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"""
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Load weights from ckpt or npz.
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Args:
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config (TransformerConfig): Config.
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Returns:
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dict, weights.
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"""
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model_path = config.existed_ckpt
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if model_path.endswith(".npz"):
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ms_ckpt = np.load(model_path)
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is_npz = True
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else:
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ms_ckpt = load_checkpoint(model_path)
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is_npz = False
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weights = {}
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with open("variable_after_deal.txt", "a") as f:
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for param_name in ms_ckpt:
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infer_name = param_name.replace("transformer.transformer.", "")
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if not infer_name.startswith("encoder"):
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if infer_name.startswith("decoder.layers."):
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infer_name = infer_name.replace("decoder.layers.", "decoder.layer")
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infer_name = "decoder.decoder." + infer_name
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if is_npz:
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weights[infer_name] = ms_ckpt[param_name]
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else:
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weights[infer_name] = ms_ckpt[param_name].data.asnumpy()
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f.write(infer_name)
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f.write("\n")
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f.close()
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return weights
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