This is an automated email from the ASF dual-hosted git repository. masahi pushed a commit to branch torchbench in repository https://gitbox.apache.org/repos/asf/tvm.git
commit 5aa6d7c25360ee5b339c42f8c9f5c655943a4333 Author: YJ Shi <yuanj...@octoml.ai> AuthorDate: Tue Sep 13 16:15:09 2022 -0700 fix rebase --- python/tvm/relay/frontend/pytorch.py | 12 ++++-------- tests/python/frontend/pytorch/test_forward.py | 7 +++---- 2 files changed, 7 insertions(+), 12 deletions(-) diff --git a/python/tvm/relay/frontend/pytorch.py b/python/tvm/relay/frontend/pytorch.py index 9255c42383..e2badaabf7 100644 --- a/python/tvm/relay/frontend/pytorch.py +++ b/python/tvm/relay/frontend/pytorch.py @@ -39,11 +39,7 @@ from ..loops import while_loop from ..prelude import Prelude, StaticTensorArrayOps from ..ty import Any, TensorType, TupleType from . import qnn_torch -<<<<<<< HEAD -from .common import AttrCvt, get_relay_op, gru_cell, logger, rnn_cell -======= -from .common import AttrCvt, fold_constant, get_relay_op, gru_cell, infer_shape, logger ->>>>>>> dfcf28b5d... add copy_ and embedding_bag +from .common import AttrCvt, fold_constant, get_relay_op, gru_cell, logger from .common import infer_shape as _infer_shape from .common import infer_value as _infer_value from .common import infer_value_simulated as _infer_value_simulated @@ -3415,7 +3411,7 @@ class PyTorchOpConverter: output = _op.random.multinomial(key, probs, num_samples) _, indices = _expr.TupleWrapper(output, 2) return indices - + def embedding_bag(self, inputs, _): assert len(inputs) == 9, "embedding_bag needs 9 arguments" ( @@ -3433,10 +3429,10 @@ class PyTorchOpConverter: assert scale_grad_by_freq == 0, "scale_grad_by_freq not supported in embedding_bag." assert padding_idx == None, "padding_idx not supported in embedding_bag." - assert len(infer_shape(indices)) == 1, "Expects 1D indices for aten::embedding_bag." + assert len(_infer_shape(indices)) == 1, "Expects 1D indices for aten::embedding_bag." offsets_const_fold = fold_constant(offsets_1d) - + print(offsets_const_fold) assert isinstance( offsets_const_fold, _expr.Constant ), "Only constant offsets are supported." diff --git a/tests/python/frontend/pytorch/test_forward.py b/tests/python/frontend/pytorch/test_forward.py index f9ff4a212c..58a4dfbe94 100755 --- a/tests/python/frontend/pytorch/test_forward.py +++ b/tests/python/frontend/pytorch/test_forward.py @@ -4608,7 +4608,6 @@ def test_mod(): verify_model(test_fn, [torch.tensor([1, 2, 3, 4, 5]), torch.tensor(-1.5)]) -<<<<<<< HEAD def test_softmax_fuse(): # https://github.com/apache/tvm/issues/12001 class Model(torch.nn.Module): @@ -4686,15 +4685,15 @@ def test_multinomial(): _test_multinomial(1), [torch.rand(size=[4, 5]).float()], cpu_only=True, - check_correctness=False, -======= + ) + + def test_embedding_bag(): embedding_matrix = torch.rand(10, 3) inp = torch.tensor([[1, 2, 4, 5], [4, 3, 2, 9], [6, 7, 8, 9]]) verify_model( F.embedding_bag, [inp, embedding_matrix], ->>>>>>> dfcf28b5d... add copy_ and embedding_bag )