本文整理汇总了Python中maskrcnn_benchmark._C.modulated_deform_conv_backward方法的典型用法代码示例。如果您正苦于以下问题：Python _C.modulated_deform_conv_backward方法的具体用法？Python _C.modulated_deform_conv_backward怎么用？Python _C.modulated_deform_conv_backward使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类maskrcnn_benchmark._C的用法示例。
在下文中一共展示了_C.modulated_deform_conv_backward方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: backward
# 需要导入模块: from maskrcnn_benchmark import _C [as 别名]
# 或者: from maskrcnn_benchmark._C import modulated_deform_conv_backward [as 别名]
def backward(ctx, grad_output):
if not grad_output.is_cuda:
raise NotImplementedError
input, offset, mask, weight, bias = ctx.saved_tensors
grad_input = torch.zeros_like(input)
grad_offset = torch.zeros_like(offset)
grad_mask = torch.zeros_like(mask)
grad_weight = torch.zeros_like(weight)
grad_bias = torch.zeros_like(bias)
_C.modulated_deform_conv_backward(
input,
weight,
bias,
ctx._bufs[0],
offset,
mask,
ctx._bufs[1],
grad_input,
grad_weight,
grad_bias,
grad_offset,
grad_mask,
grad_output,
weight.shape[2],
weight.shape[3],
ctx.stride,
ctx.stride,
ctx.padding,
ctx.padding,
ctx.dilation,
ctx.dilation,
ctx.groups,
ctx.deformable_groups,
ctx.with_bias
)
if not ctx.with_bias:
grad_bias = None
return (grad_input, grad_offset, grad_mask, grad_weight, grad_bias,
None, None, None, None, None) 示例2: backward
# 需要导入模块: from maskrcnn_benchmark import _C [as 别名]
# 或者: from maskrcnn_benchmark._C import modulated_deform_conv_backward [as 别名]
def backward(ctx, grad_output):
if not grad_output.is_cuda:
raise NotImplementedError
input, offset, mask, weight, bias = ctx.saved_tensors
grad_input = torch.zeros_like(input)
grad_offset = torch.zeros_like(offset)
grad_mask = torch.zeros_like(mask)
grad_weight = torch.zeros_like(weight)
grad_bias = torch.zeros_like(bias)
_C.modulated_deform_conv_backward(
input,
weight,
bias,
ctx._bufs[0],
offset,
mask,
ctx._bufs[1],
grad_input,
grad_weight,
grad_bias,
grad_offset,
grad_mask,
grad_output,
weight.shape[2],
weight.shape[3],
ctx.stride,
ctx.stride,
ctx.padding,
ctx.padding,
ctx.dilation,
ctx.dilation,
ctx.groups,
ctx.deformable_groups,
ctx.with_bias
)
if not ctx.with_bias:
grad_bias = None
return (grad_input, grad_offset, grad_mask, grad_weight, grad_bias,
None, None, None, None, None)