From 968edc93754bed31edd6198ca47c66e80454dac3 Mon Sep 17 00:00:00 2001 From: Ekaterina Aidova Date: Wed, 2 Aug 2023 08:38:34 +0400 Subject: [PATCH] [PT FE]: support aten::broadcast_to (#18899) --- src/frontends/pytorch/src/op_table.cpp | 1 + .../layer_tests/pytorch_tests/test_expand.py | 33 ++++++++++++++----- 2 files changed, 25 insertions(+), 9 deletions(-) diff --git a/src/frontends/pytorch/src/op_table.cpp b/src/frontends/pytorch/src/op_table.cpp index 537605282d4..ac0e66de932 100644 --- a/src/frontends/pytorch/src/op_table.cpp +++ b/src/frontends/pytorch/src/op_table.cpp @@ -236,6 +236,7 @@ const std::map get_supported_ops_ts() { {"aten::avg_pool1d", op::quantizable_op}, {"aten::avg_pool2d", op::quantizable_op}, {"aten::avg_pool3d", op::quantizable_op}, + {"aten::broadcast_to", op::translate_expand}, {"aten::baddbmm", op::translate_addmm}, {"aten::batch_norm", op::translate_batch_norm}, {"aten::bitwise_not", op::translate_bitwise_not}, diff --git a/tests/layer_tests/pytorch_tests/test_expand.py b/tests/layer_tests/pytorch_tests/test_expand.py index d8c306bf882..5848aca8fa8 100644 --- a/tests/layer_tests/pytorch_tests/test_expand.py +++ b/tests/layer_tests/pytorch_tests/test_expand.py @@ -11,50 +11,65 @@ class TestExpand(PytorchLayerTest): import numpy as np return (np.random.randn(1, 3).astype(np.float32),) - def create_model(self, dim): + def create_model(self, dim, op_type="expand"): import torch class aten_expand(torch.nn.Module): - def __init__(self, dims): + def __init__(self, dims, op_type="expand"): super(aten_expand, self).__init__() self.dims = dims + if op_type == "broadcast_to": + self.forward = self.forward_broadcast def forward(self, x): return x.expand(self.dims) + def forward_broadcast(self, x): + return x.broadcast_to(self.dims) + ref_net = None - return aten_expand(dim), ref_net, "aten::expand" + return aten_expand(dim, op_type), ref_net, f"aten::{op_type}" @pytest.mark.parametrize("dims", [(4, 3), (-1, -1), (1, 2, 3), (1, 2, 2, 3)]) + @pytest.mark.parametrize("op_type", ["expand", "broadcast_to"]) @pytest.mark.nightly @pytest.mark.precommit - def test_expand(self, dims, ie_device, precision, ir_version): - self._test(*self.create_model(dims), ie_device, precision, ir_version) + def test_expand(self, dims, op_type, ie_device, precision, ir_version): + self._test(*self.create_model(dims, op_type), ie_device, precision, ir_version) class TestExpandList(PytorchLayerTest): def _prepare_input(self, broadcast_shape): import numpy as np return (np.random.randn(1, 3).astype(np.float32), np.random.randn(*broadcast_shape).astype(np.float32)) - def create_model(self): + def create_model(self, op_type="expand"): import torch class aten_expand(torch.nn.Module): + def __init__(self, op_type="expand"): + super(aten_expand, self).__init__() + if op_type == "broadcast_to": + self.forward = self.forward_broadcast def forward(self, x, y): y_shape = y.shape return x.expand([y_shape[0], y_shape[1]]) + def forward_broadcast(self, x, y): + y_shape = y.shape + return x.broadcast_to([y_shape[0], y_shape[1]]) + ref_net = None - return aten_expand(), ref_net, ["aten::expand", "prim::ListConstruct"] + return aten_expand(op_type), ref_net, [f"aten::{op_type}", "prim::ListConstruct"] @pytest.mark.parametrize("dims", [(3, 3), (2, 3), (1, 3), [4, 3]]) + @pytest.mark.parametrize("op_type", ["expand", "broadcast_to"]) @pytest.mark.nightly @pytest.mark.precommit - def test_expand(self, dims, ie_device, precision, ir_version): - self._test(*self.create_model(), ie_device, precision, ir_version, kwargs_to_prepare_input={"broadcast_shape": dims}) + def test_expand(self, dims, op_type, ie_device, precision, ir_version): + self._test(*self.create_model(op_type), ie_device, precision, ir_version, kwargs_to_prepare_input={"broadcast_shape": dims}) class TestExpandAs(PytorchLayerTest):