forked from huawei/mindspore2022
51 lines
1.5 KiB
Python
51 lines
1.5 KiB
Python
# Copyright 2019 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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"""squeeze"""
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import _akg.topi as topi
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import _akg.tvm as tvm
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def Squeeze(x, axis=None):
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"""
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Remove the dimensions which have shape size 1.
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Args:
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x (tvm.tensor.Tensor): Tensor, input whose shape is to be squeeze.
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axis (Union[list, tuple, int, None]): specify which size 1 dimension to be removed.
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Returns:
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tvm.tensor.Tensor, has the same type and element as x, but some size 1 dimensions are removed.
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"""
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return topi.squeeze(x, axis)
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def gpu_schedule_Squeeze(outs):
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"""
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gpu schedule Squeeze.
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Args:
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outs (tvm.tensor.Tensor): outputs of compute.
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Returns:
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sch (schedule.Schedule): The created schedule.
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"""
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device = 'cuda'
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ctx = tvm.context(device, 0)
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if not ctx.exist:
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raise SystemError("Skip because %s is not enabled" % device)
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with tvm.target.create(device):
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sch = topi.cuda.schedule_injective(outs)
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return sch
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