Skip to content

Commit

Permalink
Update PyTorch script
Browse files Browse the repository at this point in the history
  • Loading branch information
@lutzroeder
lutzroeder committed Dec 8, 2024
1 parent a44954e commit 28ab781
Show file tree
Hide file tree
Showing 2 changed files with 20 additions and 20 deletions.
20 changes: 10 additions & 10 deletions source/pytorch-metadata.json
View file
Original file line number Diff line number Diff line change
Expand Up @@ -32,34 +32,34 @@
]
},
{
"name": "_caffe2::BBoxTransform(Tensor rois, Tensor deltas, Tensor im_info, float[] weights, bool apply_scale, bool rotated, bool angle_bound_on, int angle_bound_lo, int angle_bound_hi, float clip_angle_thresh, bool legacy_plus_one) -> (Tensor output_0, Tensor output_1)"
"name": "_caffe2::BBoxTransform(Tensor rois, Tensor deltas, Tensor im_info, float[] weights, bool apply_scale, bool rotated, bool angle_bound_on, int angle_bound_lo, int angle_bound_hi, float clip_angle_thresh, bool legacy_plus_one, Tensor[]? _caffe2_preallocated_outputs=None) -> (Tensor output_0, Tensor output_1)"
},
{
"name": "_caffe2::BatchPermutation(Tensor X, Tensor indices) -> Tensor"
"name": "_caffe2::BatchPermutation(Tensor X, Tensor indices, Tensor[]? _caffe2_preallocated_outputs=None) -> Tensor"
},
{
"name": "_caffe2::BoxWithNMSLimit(Tensor scores, Tensor boxes, Tensor batch_splits, float score_thresh, float nms, int detections_per_im, bool soft_nms_enabled, str soft_nms_method, float soft_nms_sigma, float soft_nms_min_score_thres, bool rotated, bool cls_agnostic_bbox_reg, bool input_boxes_include_bg_cls, bool output_classes_include_bg_cls, bool legacy_plus_one) -> (Tensor scores, Tensor boxes, Tensor classes, Tensor batch_splits, Tensor keeps, Tensor keeps_size)"
"name": "_caffe2::BoxWithNMSLimit(Tensor scores, Tensor boxes, Tensor batch_splits, float score_thresh, float nms, int detections_per_im, bool soft_nms_enabled, str soft_nms_method, float soft_nms_sigma, float soft_nms_min_score_thres, bool rotated, bool cls_agnostic_bbox_reg, bool input_boxes_include_bg_cls, bool output_classes_include_bg_cls, bool legacy_plus_one, Tensor[]? _caffe2_preallocated_outputs=None) -> (Tensor scores, Tensor boxes, Tensor classes, Tensor batch_splits, Tensor keeps, Tensor keeps_size)"
},
{
"name": "_caffe2::CollectAndDistributeFpnRpnProposals(Tensor[] input_list, int roi_canonical_scale, int roi_canonical_level, int roi_max_level, int roi_min_level, int rpn_max_level, int rpn_min_level, int rpn_post_nms_topN, bool legacy_plus_one) -> (Tensor rois, Tensor rois_fpn2, Tensor rois_fpn3, Tensor rois_fpn4, Tensor rois_fpn5, Tensor rois_idx_restore_int32)"
"name": "_caffe2::CollectAndDistributeFpnRpnProposals(Tensor[] input_list, int roi_canonical_scale, int roi_canonical_level, int roi_max_level, int roi_min_level, int rpn_max_level, int rpn_min_level, int rpn_post_nms_topN, bool legacy_plus_one, Tensor[]? _caffe2_preallocated_outputs=None) -> (Tensor rois, Tensor rois_fpn2, Tensor rois_fpn3, Tensor rois_fpn4, Tensor rois_fpn5, Tensor rois_idx_restore_int32)"
},
{
"name": "_caffe2::CollectRpnProposals(Tensor[] input_list, int rpn_max_level, int rpn_min_level, int rpn_post_nms_topN) -> (Tensor rois)"
"name": "_caffe2::CollectRpnProposals(Tensor[] input_list, int rpn_max_level, int rpn_min_level, int rpn_post_nms_topN, Tensor[]? _caffe2_preallocated_outputs=None) -> (Tensor rois)"
},
{
"name": "_caffe2::CopyCPUToGPU(Tensor input) -> Tensor"
"name": "_caffe2::CopyCPUToGPU(Tensor input, Tensor[]? _caffe2_preallocated_outputs=None) -> Tensor"
},
{
"name": "_caffe2::CopyGPUToCPU(Tensor input) -> Tensor"
"name": "_caffe2::CopyGPUToCPU(Tensor input, Tensor[]? _caffe2_preallocated_outputs=None) -> Tensor"
},
{
"name": "_caffe2::DistributeFpnProposals(Tensor rois, int roi_canonical_scale, int roi_canonical_level, int roi_max_level, int roi_min_level, bool legacy_plus_one) -> (Tensor rois_fpn2, Tensor rois_fpn3, Tensor rois_fpn4, Tensor rois_fpn5, Tensor rois_idx_restore_int32)"
"name": "_caffe2::DistributeFpnProposals(Tensor rois, int roi_canonical_scale, int roi_canonical_level, int roi_max_level, int roi_min_level, bool legacy_plus_one, Tensor[]? _caffe2_preallocated_outputs=None) -> (Tensor rois_fpn2, Tensor rois_fpn3, Tensor rois_fpn4, Tensor rois_fpn5, Tensor rois_idx_restore_int32)"
},
{
"name": "_caffe2::GenerateProposals(Tensor scores, Tensor bbox_deltas, Tensor im_info, Tensor anchors, float spatial_scale, int pre_nms_topN, int post_nms_topN, float nms_thresh, float min_size, bool angle_bound_on, int angle_bound_lo, int angle_bound_hi, float clip_angle_thresh, bool legacy_plus_one) -> (Tensor output_0, Tensor output_1)"
"name": "_caffe2::GenerateProposals(Tensor scores, Tensor bbox_deltas, Tensor im_info, Tensor anchors, float spatial_scale, int pre_nms_topN, int post_nms_topN, float nms_thresh, float min_size, bool angle_bound_on, int angle_bound_lo, int angle_bound_hi, float clip_angle_thresh, bool legacy_plus_one, Tensor[]? _caffe2_preallocated_outputs=None) -> (Tensor output_0, Tensor output_1)"
},
{
"name": "_caffe2::RoIAlign(Tensor features, Tensor rois, str order, float spatial_scale, int pooled_h, int pooled_w, int sampling_ratio, bool aligned) -> Tensor"
"name": "_caffe2::RoIAlign(Tensor features, Tensor rois, str order, float spatial_scale, int pooled_h, int pooled_w, int sampling_ratio, bool aligned, Tensor[]? _caffe2_preallocated_outputs=None) -> Tensor"
},
{
"name": "aten::Bool.Tensor(Tensor a) -> bool"
Expand Down
20 changes: 10 additions & 10 deletions tools/pytorch_script.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -44,16 +44,16 @@ def _write_metadata(value):

known_legacy_schema_definitions = [
# pylint: disable=line-too-long
'_caffe2::BBoxTransform(Tensor rois, Tensor deltas, Tensor im_info, float[] weights, bool apply_scale, bool rotated, bool angle_bound_on, int angle_bound_lo, int angle_bound_hi, float clip_angle_thresh, bool legacy_plus_one) -> (Tensor output_0, Tensor output_1)',
'_caffe2::BatchPermutation(Tensor X, Tensor indices) -> Tensor',
'_caffe2::BoxWithNMSLimit(Tensor scores, Tensor boxes, Tensor batch_splits, float score_thresh, float nms, int detections_per_im, bool soft_nms_enabled, str soft_nms_method, float soft_nms_sigma, float soft_nms_min_score_thres, bool rotated, bool cls_agnostic_bbox_reg, bool input_boxes_include_bg_cls, bool output_classes_include_bg_cls, bool legacy_plus_one) -> (Tensor scores, Tensor boxes, Tensor classes, Tensor batch_splits, Tensor keeps, Tensor keeps_size)',
'_caffe2::CollectAndDistributeFpnRpnProposals(Tensor[] input_list, int roi_canonical_scale, int roi_canonical_level, int roi_max_level, int roi_min_level, int rpn_max_level, int rpn_min_level, int rpn_post_nms_topN, bool legacy_plus_one) -> (Tensor rois, Tensor rois_fpn2, Tensor rois_fpn3, Tensor rois_fpn4, Tensor rois_fpn5, Tensor rois_idx_restore_int32)',
'_caffe2::CollectRpnProposals(Tensor[] input_list, int rpn_max_level, int rpn_min_level, int rpn_post_nms_topN) -> (Tensor rois)',
'_caffe2::CopyCPUToGPU(Tensor input) -> Tensor',
'_caffe2::CopyGPUToCPU(Tensor input) -> Tensor',
'_caffe2::DistributeFpnProposals(Tensor rois, int roi_canonical_scale, int roi_canonical_level, int roi_max_level, int roi_min_level, bool legacy_plus_one) -> (Tensor rois_fpn2, Tensor rois_fpn3, Tensor rois_fpn4, Tensor rois_fpn5, Tensor rois_idx_restore_int32)',
'_caffe2::GenerateProposals(Tensor scores, Tensor bbox_deltas, Tensor im_info, Tensor anchors, float spatial_scale, int pre_nms_topN, int post_nms_topN, float nms_thresh, float min_size, bool angle_bound_on, int angle_bound_lo, int angle_bound_hi, float clip_angle_thresh, bool legacy_plus_one) -> (Tensor output_0, Tensor output_1)',
'_caffe2::RoIAlign(Tensor features, Tensor rois, str order, float spatial_scale, int pooled_h, int pooled_w, int sampling_ratio, bool aligned) -> Tensor',
'_caffe2::BBoxTransform(Tensor rois, Tensor deltas, Tensor im_info, float[] weights, bool apply_scale, bool rotated, bool angle_bound_on, int angle_bound_lo, int angle_bound_hi, float clip_angle_thresh, bool legacy_plus_one, Tensor[]? _caffe2_preallocated_outputs=None) -> (Tensor output_0, Tensor output_1)',
'_caffe2::BatchPermutation(Tensor X, Tensor indices, Tensor[]? _caffe2_preallocated_outputs=None) -> Tensor',
'_caffe2::BoxWithNMSLimit(Tensor scores, Tensor boxes, Tensor batch_splits, float score_thresh, float nms, int detections_per_im, bool soft_nms_enabled, str soft_nms_method, float soft_nms_sigma, float soft_nms_min_score_thres, bool rotated, bool cls_agnostic_bbox_reg, bool input_boxes_include_bg_cls, bool output_classes_include_bg_cls, bool legacy_plus_one, Tensor[]? _caffe2_preallocated_outputs=None) -> (Tensor scores, Tensor boxes, Tensor classes, Tensor batch_splits, Tensor keeps, Tensor keeps_size)',
'_caffe2::CollectAndDistributeFpnRpnProposals(Tensor[] input_list, int roi_canonical_scale, int roi_canonical_level, int roi_max_level, int roi_min_level, int rpn_max_level, int rpn_min_level, int rpn_post_nms_topN, bool legacy_plus_one, Tensor[]? _caffe2_preallocated_outputs=None) -> (Tensor rois, Tensor rois_fpn2, Tensor rois_fpn3, Tensor rois_fpn4, Tensor rois_fpn5, Tensor rois_idx_restore_int32)',
'_caffe2::CollectRpnProposals(Tensor[] input_list, int rpn_max_level, int rpn_min_level, int rpn_post_nms_topN, Tensor[]? _caffe2_preallocated_outputs=None) -> (Tensor rois)',
'_caffe2::CopyCPUToGPU(Tensor input, Tensor[]? _caffe2_preallocated_outputs=None) -> Tensor',
'_caffe2::CopyGPUToCPU(Tensor input, Tensor[]? _caffe2_preallocated_outputs=None) -> Tensor',
'_caffe2::DistributeFpnProposals(Tensor rois, int roi_canonical_scale, int roi_canonical_level, int roi_max_level, int roi_min_level, bool legacy_plus_one, Tensor[]? _caffe2_preallocated_outputs=None) -> (Tensor rois_fpn2, Tensor rois_fpn3, Tensor rois_fpn4, Tensor rois_fpn5, Tensor rois_idx_restore_int32)',
'_caffe2::GenerateProposals(Tensor scores, Tensor bbox_deltas, Tensor im_info, Tensor anchors, float spatial_scale, int pre_nms_topN, int post_nms_topN, float nms_thresh, float min_size, bool angle_bound_on, int angle_bound_lo, int angle_bound_hi, float clip_angle_thresh, bool legacy_plus_one, Tensor[]? _caffe2_preallocated_outputs=None) -> (Tensor output_0, Tensor output_1)',
'_caffe2::RoIAlign(Tensor features, Tensor rois, str order, float spatial_scale, int pooled_h, int pooled_w, int sampling_ratio, bool aligned, Tensor[]? _caffe2_preallocated_outputs=None) -> Tensor',
'aten::_cat.out(Tensor[] tensors, int dim=0, *, Tensor(a!) out) -> Tensor(a!)',
'aten::_cat(Tensor[] tensors, int dim=0) -> Tensor',
'aten::adaptive_avg_pool1d.out(Tensor self, int[1] output_size, *, Tensor(a!) out) -> Tensor(a!)',
Expand Down

0 comments on commit 28ab781

Please sign in to comment.