Update pytorch-metadata.json

source/pytorch-metadata.json

@@ -4086,6 +4086,9 @@
   {
     "name": "aten::list.t(t[] l) -> t[]"
   },
+  {
+    "name": "aten::list_with_default(int[] list, int[] defaults) -> int[]"
+  },
   {
     "name": "aten::log(Tensor self) -> Tensor"
   },
@@ -7050,6 +7053,9 @@
   {
     "name": "aten::zeros_like.out(Tensor self, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!)"
   },
+  {
+    "name": "cadence::quantize_per_tensor.out(Tensor input, float scale, int zero_point, int quant_min, int quant_max, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!)"
+  },
   {
     "name": "detectron2::nms_rotated(Tensor boxes, Tensor scores, float iou_threshold) -> Tensor"
   },
@@ -8378,6 +8384,9 @@
   {
     "name": "quantized_decomposed::dequantize_per_channel(Tensor input, Tensor scales, Tensor? zero_points, int axis, int quant_min, int quant_max, ScalarType dtype, *, ScalarType? out_dtype=None) -> Tensor"
   },
+  {
+    "name": "quantized_decomposed::dequantize_per_channel.out(Tensor input, Tensor scales, Tensor? zero_points, int axis, int quant_min, int quant_max, ScalarType dtype, *, ScalarType? out_dtype=None, Tensor(a!) out) -> Tensor(a!)"
+  },
   {
     "name": "quantized_decomposed::dequantize_per_channel_group(Tensor input, Tensor scales, Tensor? zero_points, int quant_min, int quant_max, ScalarType dtype, int group_size, ScalarType output_dtype) -> Tensor"
   },

tools/pytorch_script.py

@@ -57,11 +57,20 @@ known_legacy_schema_definitions = [
     "_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)", # noqa E501
     "_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)", # noqa E501
     "_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", # noqa E501
+    "aten::_cast_Char(Tensor self, bool non_blocking=False) -> Tensor",
+    "aten::_cast_Byte(Tensor self, bool non_blocking=False) -> Tensor",
+    "aten::_cast_Double(Tensor self, bool non_blocking=False) -> Tensor",
+    "aten::_cast_Float(Tensor self, bool non_blocking=False) -> Tensor",
+    "aten::_cast_Half(Tensor self, bool non_blocking=False) -> Tensor",
+    "aten::_cast_Int(Tensor self, bool non_blocking=False) -> Tensor",
+    "aten::_cast_Long(Tensor self, bool non_blocking=False) -> Tensor",
+    "aten::_cast_Short(Tensor self, bool non_blocking=False) -> Tensor",
     "aten::_cat.out(Tensor[] tensors, int dim=0, *, Tensor(a!) out) -> Tensor(a!)",
     "aten::_cat(Tensor[] tensors, int dim=0) -> Tensor",
     "aten::arange.start_out_(Scalar start, Scalar end) -> Tensor",
     "aten::fft(Tensor self, int signal_ndim, bool normalized=False) -> Tensor",
     "aten::grid_sampler.legacy(Tensor input, Tensor grid, int interpolation_mode, int padding_mode) -> Tensor", # noqa E501
+    "aten::list_with_default(int[] list, int[] defaults) -> int[]",
     "aten::rand_like.generator(Tensor self, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor", # noqa E501
     "aten::rand_like.generator_out(Tensor self, *, Generator? generator, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!)", # noqa E501
     "aten::randn_like.generator(Tensor self, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor", # noqa E501
@@ -71,6 +80,7 @@ known_legacy_schema_definitions = [
     "aten::randint_like.generator_with_low_dtype(Tensor self, SymInt low, SymInt high, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor", # noqa E501
     "aten::randint_like.generator_with_low_dtype_out(Tensor self, SymInt low, SymInt high, *, Generator? generator, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!)", # noqa E501
     "aqlm::code2x8_lut_matmat.out(Tensor input, Tensor codes, Tensor codebooks, Tensor scales, Tensor? bias, Tensor(a!) out) -> Tensor(a!)", # noqa E501
+    "cadence::quantize_per_tensor.out(Tensor input, float scale, int zero_point, int quant_min, int quant_max, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!)", # noqa E501
     "detectron2::nms_rotated(Tensor boxes, Tensor scores, float iou_threshold) -> Tensor", # noqa E501
     "detectron2::roi_align_rotated_forward(Tensor input, Tensor rois, float spatial_scale, int pooled_height, int pooled_width, int sampling_ratio) -> Tensor", # noqa E501
     "dim_order_ops::_clone_dim_order.out(Tensor self, *, bool non_blocking=False, int[]? dim_order=None, Tensor(a!)", # noqa E501
@@ -297,6 +307,7 @@ known_legacy_schema_definitions = [
     "quantized_decomposed::add.scalar(Tensor qa, float a_scale, int a_zero_point, int a_quant_min, int a_quant_max, ScalarType a_dtype, Scalar b, float out_scale, int out_zero_point, int out_quant_min, int out_quant_max, ScalarType out_dtype) -> Tensor", # noqa E501
     "quantized_decomposed::add_relu(Tensor a, float a_scale, int a_zero_point, int a_quant_min, int a_quant_max, Tensor b, float b_scale, int b_zero_point, int b_quant_min, int b_quant_max, float out_scale, int out_zero_point, int out_quant_min, int out_quant_max) -> Tensor qc", # noqa E501
     "quantized_decomposed::dequantize_per_channel(Tensor input, Tensor scales, Tensor? zero_points, int axis, int quant_min, int quant_max, ScalarType dtype, *, ScalarType? out_dtype=None) -> Tensor", # noqa E501
+    "quantized_decomposed::dequantize_per_channel.out(Tensor input, Tensor scales, Tensor? zero_points, int axis, int quant_min, int quant_max, ScalarType dtype, *, ScalarType? out_dtype=None, Tensor(a!) out) -> Tensor(a!)", # noqa E501
     "quantized_decomposed::fake_quant_per_channel(Tensor input, Tensor scales, Tensor zero_points, int axis, int quant_min, int quant_max) -> Tensor", # noqa E501
     "quantized_decomposed::quantize_per_channel(Tensor input, Tensor scales, Tensor zero_points, int axis, int quant_min, int quant_max, ScalarType dtype) -> Tensor", # noqa E501
     "quantized_decomposed::choose_qparams_symmetric.tensor(Tensor input, int quant_min, int quant_max, float eps, ScalarType dtype) -> (Tensor, Tensor)", # noqa E501