def conv_set_params(conv_param, conv_type):
# Defaults
padding = [0, 0]
stride = [1, 1]
kernel = [0, 0]
dilate = [1, 1]
group = 1
kernel = get_spatial_attr(kernel, 'kernel_size', 'kernel', conv_param)
padding = get_spatial_attr(padding, 'pad', 'pad', conv_param)
stride = get_spatial_attr(stride, 'stride', 'stride', conv_param)
dilates = get_list_from_container(conv_param, 'dilation', int)
if len(dilates) > 0:
dilate[0] = dilate[1] = dilates[0]
groups = get_list_from_container(conv_param, 'group', int)
group = groups[0] if len(groups) > 0 and groups[0] != 1 else group
return {
'type_str': conv_type,
'padding': padding,
'dilate': dilate,
'stride': stride,
'kernel': kernel,
'group': group,
'output': conv_param.num_output,
'bias_term': conv_param.bias_term
}
def extract(cls, node):
proto_layer = node.pb
param = proto_layer.pooling_param
method = 'max'
exclude_pad = True
kernel = [0, 0]
stride = [1, 1]
padding = [0, 0]
global_pooling = False
if hasattr(param, 'global_pooling') and param.global_pooling:
global_pooling = param.global_pooling
else:
kernel = get_spatial_attr(kernel, 'kernel_size', 'kernel', param)
padding = get_spatial_attr(padding, 'pad', 'pad', param)
stride = get_spatial_attr(stride, 'stride', 'stride', param)
if param.pool == 0:
method = 'max'
exclude_pad = True
elif param.pool == 1:
method = 'avg'
exclude_pad = False
else:
raise ValueError('Unknown Pooling Method!')
pooling_convention = 'full' # for Caffe rounding type should be ceil
rt = 'ceil'
if hasattr(param, 'ceil_mode') and not param.ceil_mode:
# If pooling has ceil_mode and ceil_mode is False using floor for rounding shapes in partial_infer
pooling_convention = 'valid'
rt = 'floor'
attrs = {
'window':
np.array([1, 1, kernel[1], kernel[0]], dtype=np.int64),
'stride':
np.array([1, 1, stride[1], stride[0]], dtype=np.int64),
'pad':
np.array([[0, 0], [0, 0], [padding[1], padding[1]],
[padding[0], padding[0]]],
dtype=np.int64),
'pad_spatial_shape':
np.array([[padding[1], padding[1]], [padding[0], padding[0]]],
dtype=np.int64),
'pool_method':
method,
'exclude_pad':
exclude_pad,
'global_pool':
global_pooling,
'output_spatial_shape':
None,
'rounding_type':
rt
}
attrs.update(layout_attrs())
attrs['pooling_convention'] = pooling_convention
# update the attributes of the node
Pooling.update_node_stat(node, attrs)
return cls.enabled