wehub-resource-sync
55 lines
1.6 KiB
Python
55 lines
1.6 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. 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,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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"""TVM operator flatten compute."""
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import tvm
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from tvm import te
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from .. import tag
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@tvm.te.tag_scope(tag=tag.INJECTIVE)
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def flatten(data):
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"""Flattens the input array into a 2-D array by collapsing the higher dimensions.
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Parameters
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----------
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data : tvm.te.Tensor
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Input array.
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Returns
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-------
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output : tvm.te.Tensor
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2-D array with collapsed higher dimensions.
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"""
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ishape = data.shape
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dim = 1
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for i in range(1, len(ishape)):
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dim = dim * ishape[i]
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oshape = [ishape[0], dim]
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idxdiv = tvm.tirx.indexdiv
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idxmod = tvm.tirx.indexmod
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def unwrap(idx, shape):
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index = []
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for s in reversed(shape):
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index.append(idxmod(idx, s))
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idx = idxdiv(idx, s)
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return list(reversed(index))
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return te.compute(oshape, lambda i, j: data(i, *unwrap(j, ishape[1:])))
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