chore: import upstream snapshot with attribution

test/auto_parallel/spmd_rules/test_c_embedding_rule.py

@@ -0,0 +1,150 @@
+# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import unittest
+from collections import OrderedDict
+
+from paddle.distributed.auto_parallel.static.dist_attribute import (
+    DistTensorSpec,
+    TensorDistAttr,
+)
+from paddle.distributed.fleet import auto
+from paddle.framework import core
+
+
+class TestEmbeddingSPMDRule(unittest.TestCase):
+    def setUp(self):
+        self.rule = core.get_phi_spmd_rule("c_embedding")
+
+    def test_c_embedding_infer_forward(self):
+        # forward setup
+        table_shape = [512, 768]  # [V,H]
+        x_shape = [4, 1024]  # [B,S]
+        process_mesh = auto.ProcessMesh(mesh=[[0, 1, 2, 3], [4, 5, 6, 7]])
+        table_tensor_dist_attr = TensorDistAttr()
+        table_tensor_dist_attr.process_mesh = process_mesh
+        self.table_dist_tensor_spec = DistTensorSpec(
+            table_shape, table_tensor_dist_attr
+        )
+        x_tensor_dist_attr = TensorDistAttr()
+        x_tensor_dist_attr.process_mesh = process_mesh
+        self.x_dist_tensor_spec = DistTensorSpec(x_shape, x_tensor_dist_attr)
+        self.attrs = OrderedDict([('start_index', 0), ('vocab_size', -1)])
+
+        # data parallel
+        self.table_dist_tensor_spec.set_dims_mapping([-1, -1])
+        self.x_dist_tensor_spec.set_dims_mapping([1, -1])
+        result_dist_attrs = self.rule.infer_forward(
+            self.table_dist_tensor_spec,
+            self.x_dist_tensor_spec,
+            self.attrs['start_index'],
+            self.attrs['vocab_size'],
+        )
+        inferred_input_dist_attrs = result_dist_attrs[0]
+        inferred_output_dist_attrs = result_dist_attrs[1]
+        self.assertEqual(len(result_dist_attrs), 2)
+        self.assertEqual(len(inferred_input_dist_attrs), 2)
+        self.assertEqual(len(inferred_output_dist_attrs), 1)
+        self.assertEqual(inferred_input_dist_attrs[0].dims_mapping, [-1, -1])
+        self.assertEqual(inferred_input_dist_attrs[1].dims_mapping, [1, -1])
+        self.assertEqual(
+            inferred_output_dist_attrs[0].dims_mapping, [1, -1, -1]
+        )
+
+        # table row-wise parallel
+        self.table_dist_tensor_spec.set_dims_mapping([1, -1])
+        self.x_dist_tensor_spec.set_dims_mapping([-1, -1])
+        result_dist_attrs = self.rule.infer_forward(
+            self.table_dist_tensor_spec,
+            self.x_dist_tensor_spec,
+            self.attrs['start_index'],
+            self.attrs['vocab_size'],
+        )
+        inferred_input_dist_attrs = result_dist_attrs[0]
+        inferred_output_dist_attrs = result_dist_attrs[1]
+        self.assertEqual(inferred_input_dist_attrs[0].dims_mapping, [1, -1])
+        self.assertEqual(inferred_input_dist_attrs[1].dims_mapping, [-1, -1])
+        self.assertEqual(
+            inferred_output_dist_attrs[0].dims_mapping, [-1, -1, -1]
+        )
+        self.assertEqual(inferred_output_dist_attrs[0]._is_partial(), True)
+        self.assertEqual(inferred_output_dist_attrs[0]._partial_dims(), {1})
+
+    def test_c_embedding_infer_backward(self):
+        # backward setup
+        process_mesh = auto.ProcessMesh(mesh=[[0, 1, 2, 3], [4, 5, 6, 7]])
+        table_shape = [512, 768]  # [V,H]
+        x_shape = [4, 1024]  # [B,S]
+        table_tensor_dist_attr = TensorDistAttr()
+        table_tensor_dist_attr.process_mesh = process_mesh
+        self.table_dist_tensor_spec = DistTensorSpec(
+            table_shape, table_tensor_dist_attr
+        )
+        x_tensor_dist_attr = TensorDistAttr()
+        x_tensor_dist_attr.process_mesh = process_mesh
+        self.x_dist_tensor_spec = DistTensorSpec(x_shape, x_tensor_dist_attr)
+        out_shape = [4, 1024, 768]  # [B,S,H]
+        out_tensor_dist_attr = TensorDistAttr()
+        out_tensor_dist_attr.process_mesh = process_mesh
+        self.out_dist_tensor_spec = DistTensorSpec(
+            out_shape, out_tensor_dist_attr
+        )
+        self.attrs = OrderedDict([('start_index', 0), ('vocab_size', -1)])
+
+        # table row-wise parallel
+        self.table_dist_tensor_spec.set_dims_mapping([1, -1])
+        self.x_dist_tensor_spec.set_dims_mapping([-1, -1])
+        self.out_dist_tensor_spec.set_dims_mapping([-1, -1, -1])
+        result_dist_attrs = self.rule.infer_backward(
+            self.table_dist_tensor_spec,
+            self.x_dist_tensor_spec,
+            self.out_dist_tensor_spec,
+            self.attrs['start_index'],
+            self.attrs['vocab_size'],
+        )
+        inferred_input_dist_attrs = result_dist_attrs[0]
+        inferred_output_dist_attrs = result_dist_attrs[1]
+        self.assertEqual(len(result_dist_attrs), 2)
+        self.assertEqual(len(inferred_input_dist_attrs), 3)
+        self.assertEqual(len(inferred_output_dist_attrs), 1)
+        self.assertEqual(inferred_input_dist_attrs[0].dims_mapping, [1, -1])
+        self.assertEqual(inferred_input_dist_attrs[1].dims_mapping, [-1, -1])
+        self.assertEqual(
+            inferred_input_dist_attrs[2].dims_mapping, [-1, -1, -1]
+        )
+        self.assertEqual(inferred_output_dist_attrs[0].dims_mapping, [1, -1])
+
+        # data parallel
+        self.x_dist_tensor_spec.set_dims_mapping([0, -1])
+        self.out_dist_tensor_spec.set_dims_mapping([0, -1, -1])
+        result_dist_attrs = self.rule.infer_backward(
+            self.table_dist_tensor_spec,
+            self.x_dist_tensor_spec,
+            self.out_dist_tensor_spec,
+            self.attrs['start_index'],
+            self.attrs['vocab_size'],
+        )
+        inferred_input_dist_attrs = result_dist_attrs[0]
+        inferred_output_dist_attrs = result_dist_attrs[1]
+        self.assertEqual(len(result_dist_attrs), 2)
+        self.assertEqual(len(inferred_input_dist_attrs), 3)
+        self.assertEqual(len(inferred_output_dist_attrs), 1)
+        self.assertEqual(inferred_input_dist_attrs[0].dims_mapping, [1, -1])
+        self.assertEqual(inferred_input_dist_attrs[1].dims_mapping, [0, -1])
+        self.assertEqual(inferred_input_dist_attrs[2].dims_mapping, [0, -1, -1])
+        self.assertEqual(inferred_output_dist_attrs[0].dims_mapping, [1, -1])
+
+
+if __name__ == "__main__":
+    unittest.main()