wehub-resource-sync
64 lines
1.8 KiB
Python
64 lines
1.8 KiB
Python
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
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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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import paddle
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def rand_int_tensor(low, high, shape):
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return paddle.randint(
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low,
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high,
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shape=shape,
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dtype=paddle.int64,
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)
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def clone_tensor(x):
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y = x.clone()
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return y
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def clone_input(x):
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def paddle_clone(x):
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y = paddle.clone(x)
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if x.is_leaf:
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y.stop_gradient = x.stop_gradient
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if x.is_leaf and x.grad is not None:
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y.grad = clone_input(x.grad)
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return y
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with paddle.no_grad():
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result = paddle.empty(x.shape, dtype=x.dtype)
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result.copy_(x.clone(), True)
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if x.is_leaf:
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result.stop_gradient = x.stop_gradient
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if x.is_leaf and x.grad is not None:
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result.grad = clone_input(x.grad)
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return result
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def clone_inputs(example_inputs):
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if isinstance(example_inputs, dict):
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res = dict(example_inputs)
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for key, value in res.items():
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assert isinstance(value, paddle.Tensor)
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res[key] = clone_input(value)
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return res
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res = list(example_inputs)
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for i in range(len(res)):
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if isinstance(res[i], paddle.Tensor):
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res[i] = clone_input(res[i])
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return res
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