Update main branch with TE 2.0 code, update version to 2.1.0.dev0

Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

tests/paddle/recompute_tests/recompute_transformer_encoder.py

-# Copyright (c) 2022-2025, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
-#
-# See LICENSE for license information.
-"""Test TransformerLayer encoder recompute"""
-
-import sys
-import paddle
-import transformer_engine.paddle as te
-
-
-class Net(paddle.nn.Layer):
-    """Network use for recompute testing"""
-
-    def __init__(self, layers):
-        super().__init__()
-        self.layers = layers
-
-    def forward(self, inp, mask, enable_recompute, use_reentrant):
-        for layer in self.layers:
-            if enable_recompute:
-                out = te.recompute(layer, inp, mask, use_reentrant=use_reentrant)
-            else:
-                out = layer(inp, mask)
-        return out
-
-
-def main():
-    """Main function"""
-    paddle.seed(10)
-    batch_size = 16
-    hidden_size = 4096
-    num_heads = 32
-    ffn_hidden_size = 16384
-    q_seqlen = 512
-    kv_seqlen = 512
-    num_layers = 4
-    enable_recompute = int(sys.argv[1])
-    use_reentrant = int(sys.argv[2])
-
-    layers = paddle.nn.LayerList(
-        [
-            te.TransformerLayer(
-                hidden_size,
-                ffn_hidden_size,
-                num_heads,
-                layer_type="encoder",
-            )
-            for _ in range(num_layers)
-        ]
-    )
-    model = Net(layers)
-
-    optimizer = paddle.optimizer.AdamW(learning_rate=0.001, parameters=model.parameters())
-
-    for _ in range(10):
-        inp = paddle.uniform([batch_size, q_seqlen, hidden_size])
-        inp.stop_gradient = False
-        mask = paddle.zeros(shape=(batch_size, 1, q_seqlen, kv_seqlen), dtype="bool")
-        with te.fp8_autocast(enabled=True):
-            out = model(inp, mask, enable_recompute, use_reentrant)
-        loss = out.mean()
-        loss.backward()
-        optimizer.step()
-        optimizer.clear_grad()
-
-    print("Loss: ", float(loss))
-    print("Peak memory: ", paddle.device.cuda.max_memory_allocated(0))
-
-
-if __name__ == "__main__":
-    main()

tests/paddle/test_install.py

-# Copyright (c) 2022-2025, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
-#
-# See LICENSE for license information.
-"""Test basic installation of Paddle extensions"""
-
-
-def test_import():
-    """
-    Test if Paddle extension can be imported normally
-    """
-    import transformer_engine.paddle  # pylint: disable=unused-import

tests/pytorch/custom_ort_ops/.gitignore

-build
-onnxruntime
-libcustom_ort_ops.so