Add impl for torchvision.nms and support multiple batch dim for convolution. #8291
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This is partial progress to support MaskRCNN.
ManfeiBai
reviewed
Oct 21, 2024
| @@ -109,6 +109,8 @@ def _aten_add(x, y, *, alpha=1): | |||
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| assert x.dtype == y.dtype, (x.dtype, y.dtype) | |||
| """ | |||
| if isinstance(x, torch.Tensor) or isinstance(y, torch.Tensor): | |||
| import pdb; pdb.set_trace() | |||
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do we want to keep this here?
does these two line will block code running?
ManfeiBai
reviewed
Oct 21, 2024
| query, key, value, attn_mask=None, | ||
| dropout_p=0.0, is_causal=False, scale=None) -> torch.Tensor: | ||
| def _sdpa_reference(query, key, value, attn_mask=None, dropout_p=0.0, | ||
| is_causal=False, scale=None, enable_gqa=False) -> torch.Tensor: |
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thanks, do we have short description for enable_gpa?
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yes: https://pytorch.org/docs/stable/generated/torch.nn.functional.scaled_dot_product_attention.html
this is newly added in torch 2.5
ManfeiBai
reviewed
Oct 21, 2024
| @@ -166,14 +166,20 @@ def tolist(self): | |||
| def debug_accuracy(func, args, kwargs, current_output): | |||
| args_torch, kwargs_torch, out_torch = torch_pytree.tree_map_only( | |||
| torch.Tensor, lambda x: j2t(x._elem), (args, kwargs, current_output)) | |||
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| if func == torch.ops.aten._native_batch_norm_legit_no_training: | |||
| import pdb; pdb.set_trace() | |||
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thanks, do we want to keep this code here?
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This is partial progress to support MaskRCNN (#8116).
Fixes: #8278