wehub-resource-sync
53 lines
1.8 KiB
Python
53 lines
1.8 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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# pylint: disable=invalid-name
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"""TVM operator space_to_batch_nd compute."""
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from . import cpp
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def space_to_batch_nd(data, block_shape, pad_before, pad_after, pad_value=0.0):
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"""Perform batch to space transformation on the data
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Parameters
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----------
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data : tvm.te.Tensor
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N-D Tensor with shape [batch, spatial_shape, remaining_shapes],
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where spatial_shape has M dimensions.
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block_shape : list of ints
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list of size [M] where M is number of spatial dims, specifies block
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size for each spatial dimension.
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pad_before : list of ints
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list of shape [M] where M is number of spatial dims, specifies
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zero-padding size before each spatial dimension.
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pad_after : list of ints
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list of shape [M] where M is number of spatial dims, specifies
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zero-padding size after each spatial dimension.
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pad_value : float, optional
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The value used for padding.
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Returns
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-------
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output : tvm.te.Tensor
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"""
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return cpp.nn.space_to_batch_nd(data, block_shape, pad_before, pad_after, pad_value)
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