82 lines
2.9 KiB
Python
82 lines
2.9 KiB
Python
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# Copyright 2019 Yan Yan
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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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from . import functional as Fsp
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from . import ops
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from .modules import SparseModule
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from .structure import SparseConvTensor
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class SparseMaxPool(SparseModule):
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def __init__(self, ndim, kernel_size, stride=1, padding=0, dilation=1, subm=False):
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super(SparseMaxPool, self).__init__()
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if not isinstance(kernel_size, (list, tuple)):
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kernel_size = [kernel_size] * ndim
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if not isinstance(stride, (list, tuple)):
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stride = [stride] * ndim
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if not isinstance(padding, (list, tuple)):
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padding = [padding] * ndim
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if not isinstance(dilation, (list, tuple)):
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dilation = [dilation] * ndim
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self.ndim = ndim
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self.kernel_size = kernel_size
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self.stride = stride
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self.padding = padding
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self.subm = subm
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self.dilation = dilation
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def forward(self, input):
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assert isinstance(input, SparseConvTensor)
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features = input.features
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device = features.device
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indices = input.indices
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spatial_shape = input.spatial_shape
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batch_size = input.batch_size
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if not self.subm:
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out_spatial_shape = ops.get_conv_output_size(
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spatial_shape, self.kernel_size, self.stride, self.padding, self.dilation
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)
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else:
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out_spatial_shape = spatial_shape
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outids, indice_pairs, indice_pairs_num = ops.get_indice_pairs(
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indices,
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batch_size,
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spatial_shape,
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self.kernel_size,
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self.stride,
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self.padding,
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self.dilation,
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0,
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self.subm,
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)
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out_features = Fsp.indice_maxpool(
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features, indice_pairs.to(device), indice_pairs_num.to(device), outids.shape[0]
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)
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out_tensor = SparseConvTensor(out_features, outids, out_spatial_shape, batch_size)
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out_tensor.indice_dict = input.indice_dict
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out_tensor.grid = input.grid
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return out_tensor
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class SparseMaxPool2d(SparseMaxPool):
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def __init__(self, kernel_size, stride=1, padding=0, dilation=1):
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super(SparseMaxPool2d, self).__init__(2, kernel_size, stride, padding, dilation)
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class SparseMaxPool3d(SparseMaxPool):
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def __init__(self, kernel_size, stride=1, padding=0, dilation=1):
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super(SparseMaxPool3d, self).__init__(3, kernel_size, stride, padding, dilation)
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