def _compute_multibox_prior(attrs, inputs, _):
"""Compute definition of multibox_prior"""
sizes = get_float_tuple(attrs.sizes)
ratios = get_float_tuple(attrs.ratios)
steps = get_float_tuple(attrs.steps)
offsets = get_float_tuple(attrs.offsets)
clip = bool(get_const_int(attrs.clip))
return [topi_compute(inputs[0], sizes, ratios, steps, offsets, clip)]
def compute_decode_BBox(attrs, inputs, _, target):
"""Compute definition of proposal"""
bbox_mean = get_float_tuple(attrs.bbox_mean)
bbox_std = get_float_tuple(attrs.bbox_std)
class_agnostic = bool(get_const_int(attrs.class_agnostic))
with target:
return [
topi.vision.rcnn.decode_BBox(inputs[0], inputs[1], inputs[2],
bbox_mean, bbox_std, class_agnostic)
]
def compute_multibox_prior(attrs, inputs, _, target):
"""Compute definition of multibox_prior"""
sizes = get_float_tuple(attrs.sizes)
ratios = get_float_tuple(attrs.ratios)
steps = get_float_tuple(attrs.steps)
offsets = get_float_tuple(attrs.offsets)
clip = bool(get_const_int(attrs.clip))
return [
topi.vision.ssd.multibox_prior(inputs[0], sizes, ratios, steps,
offsets, clip)
]
def _compute_proposal(attrs, inputs, out_type):
scales = get_float_tuple(attrs.scales)
ratios = get_float_tuple(attrs.ratios)
feature_stride = attrs.feature_stride
threshold = attrs.threshold
rpn_pre_nms_top_n = attrs.rpn_pre_nms_top_n
rpn_post_nms_top_n = attrs.rpn_post_nms_top_n
rpn_min_size = attrs.rpn_min_size
iou_loss = bool(get_const_int(attrs.iou_loss))
return [topi_compute(inputs[0], inputs[1], inputs[2], scales, ratios,
feature_stride, threshold, rpn_pre_nms_top_n,
rpn_post_nms_top_n, rpn_min_size, iou_loss)]
def compute_multibox_transform_loc(attrs, inputs, _, target):
"""Compute definition of multibox_detection"""
clip = bool(get_const_int(attrs.clip))
threshold = get_const_float(attrs.threshold)
variances = get_float_tuple(attrs.variances)
return topi.vision.ssd.multibox_transform_loc(
inputs[0], inputs[1], inputs[2], clip, threshold, variances)
def compute_multibox_transform_loc(attrs, inputs, _, target):
"""Compute definition of multibox_detection"""
clip = bool(get_const_int(attrs.clip))
threshold = get_const_float(attrs.threshold)
variances = get_float_tuple(attrs.variances)
return topi.vision.ssd.multibox_transform_loc(
inputs[0], inputs[1], inputs[2], clip, threshold, variances)
def compute_proposal(attrs, inputs, _, target):
"""Compute definition of proposal"""
scales = get_float_tuple(attrs.scales)
ratios = get_float_tuple(attrs.ratios)
feature_stride = attrs.feature_stride
threshold = attrs.threshold
rpn_pre_nms_top_n = attrs.rpn_pre_nms_top_n
rpn_post_nms_top_n = attrs.rpn_post_nms_top_n
rpn_min_size = attrs.rpn_min_size
iou_loss = bool(get_const_int(attrs.iou_loss))
with target:
return [
topi.vision.rcnn.proposal(inputs[0], inputs[1], inputs[2], scales, ratios,
feature_stride, threshold, rpn_pre_nms_top_n,
rpn_post_nms_top_n, rpn_min_size, iou_loss)
]
def compute_proposal(attrs, inputs, _, target):
"""Compute definition of proposal"""
scales = get_float_tuple(attrs.scales)
ratios = get_float_tuple(attrs.ratios)
feature_stride = attrs.feature_stride
threshold = attrs.threshold
rpn_pre_nms_top_n = attrs.rpn_pre_nms_top_n
rpn_post_nms_top_n = attrs.rpn_post_nms_top_n
rpn_min_size = attrs.rpn_min_size
iou_loss = bool(get_const_int(attrs.iou_loss))
with target:
return [
topi.vision.rcnn.proposal(inputs[0], inputs[1], inputs[2], scales,
ratios, feature_stride, threshold,
rpn_pre_nms_top_n, rpn_post_nms_top_n,
rpn_min_size, iou_loss)
]
