Update PyTorch script

lutzroeder · lutzroeder · commit ec426976f875 · 2024-12-07T19:45:17.000-08:00
diff --git a/source/pytorch-metadata.json b/source/pytorch-metadata.json
@@ -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"
diff --git a/tools/pytorch_script.py b/tools/pytorch_script.py
@@ -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!)',
@@ -103,9 +103,10 @@ def _parse_schemas():
         schemas[key] = definition
     for schema in known_legacy_schema_definitions:
         key = _identifier(schema)
-        if key in schemas:
-            raise KeyError(key)
-        schemas[key] = schema
+        if key not in schemas:
+            schemas[key] = schema
+        else:
+            pass # raise KeyError(key)
     return schemas
 
 def _filter_schemas(schemas, types):

Original file line number	Diff line number	Diff line change
`@@ -32,34 +32,34 @@`
`32`	`32`	`]`
`33`	`33`	`},`
`34`	`34`	`{`
`35`		`- "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)"`
	`35`	`+ "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)"`
`36`	`36`	`},`
`37`	`37`	`{`
`38`		`- "name": "_caffe2::BatchPermutation(Tensor X, Tensor indices) -> Tensor"`
	`38`	`+ "name": "_caffe2::BatchPermutation(Tensor X, Tensor indices, Tensor[]? _caffe2_preallocated_outputs=None) -> Tensor"`
`39`	`39`	`},`
`40`	`40`	`{`
`41`		`- "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)"`
	`41`	+ "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)"
`42`	`42`	`},`
`43`	`43`	`{`
`44`		`- "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)"`
	`44`	`+ "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)"`
`45`	`45`	`},`
`46`	`46`	`{`
`47`		`- "name": "_caffe2::CollectRpnProposals(Tensor[] input_list, int rpn_max_level, int rpn_min_level, int rpn_post_nms_topN) -> (Tensor rois)"`
	`47`	`+ "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)"`
`48`	`48`	`},`
`49`	`49`	`{`
`50`		`- "name": "_caffe2::CopyCPUToGPU(Tensor input) -> Tensor"`
	`50`	`+ "name": "_caffe2::CopyCPUToGPU(Tensor input, Tensor[]? _caffe2_preallocated_outputs=None) -> Tensor"`
`51`	`51`	`},`
`52`	`52`	`{`
`53`		`- "name": "_caffe2::CopyGPUToCPU(Tensor input) -> Tensor"`
	`53`	`+ "name": "_caffe2::CopyGPUToCPU(Tensor input, Tensor[]? _caffe2_preallocated_outputs=None) -> Tensor"`
`54`	`54`	`},`
`55`	`55`	`{`
`56`		`- "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)"`
	`56`	`+ "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)"`
`57`	`57`	`},`
`58`	`58`	`{`
`59`		`- "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)"`
	`59`	`+ "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)"`
`60`	`60`	`},`
`61`	`61`	`{`
`62`		`- "name": "_caffe2::RoIAlign(Tensor features, Tensor rois, str order, float spatial_scale, int pooled_h, int pooled_w, int sampling_ratio, bool aligned) -> Tensor"`
	`62`	`+ "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"`
`63`	`63`	`},`
`64`	`64`	`{`
`65`	`65`	`"name": "aten::Bool.Tensor(Tensor a) -> bool"`