pool

torch_to_nnef.op.aten.pool

adaptive_avg_poolnd

adaptive_avg_poolnd(g, node, op_helper, **kwargs)

Map PyTorch: 'aten:adaptive_avg_pool{1,2,3}d' to NNEF.

adaptive_max_poolnd

adaptive_max_poolnd(node, op_helper, **kwargs)

Map PyTorch: adaptive_max_pool{1,2,3}d to NNEF.

avg_pool1d

avg_pool1d(node, op_helper, **kwargs)

Map PyTorch: 'aten:avg_pool1d' to NNEF.

avg_pool_nd

avg_pool_nd(node, op_helper, **kwargs)

Map PyTorch: 'aten:avg_pool(2|3)d', 'aten:max_pool3d' to NNEF.

Cpp func parameters:. (const Tensor& input, IntArrayRef kernel_size, IntArrayRef stride, IntArrayRef padding, bool ceil_mode, bool count_include_pad, c10::optional divisor_override

_pooling_op expect:

(input_node, kernel_size_node, stride_node, padding_node, dilation_node, ceil_mode_node)

max_pool1d

max_pool1d(g, node, op_helper, **kwargs)

Map PyTorch: 'aten:max_pool1d' to NNEF.

max_pool_nd

max_pool_nd(node, op_helper, **kwargs)

Map PyTorch: 'aten:max_pool2d', 'aten:max_pool3d' to NNEF.

upsample_nearest2d

upsample_nearest2d(node, op_helper, **kwargs)

Operator mapping PyTorch: 'aten:upsample_nearest2d' to NNEF.