[builder] unified cpu_optim fused_optim inferface (#2190)

colossalai/amp/naive_amp/_fp16_optimizer.py

@@ -3,19 +3,12 @@
 
 import torch
 import torch.distributed as dist
-
-try:
-    from colossalai._C import fused_optim
-except:
-    print('Colossalai should be built with cuda extension to use the FP16 optimizer')
-    from colossalai.kernel.op_builder.fused_optim import FusedOptimBuilder
-    fused_optim = FusedOptimBuilder().load()
-
 from torch.distributed import ProcessGroup
 from torch.optim import Optimizer
 
 from colossalai.context import ParallelMode
 from colossalai.core import global_context as gpc
+from colossalai.kernel import fused_optim
 from colossalai.logging import get_dist_logger
 from colossalai.utils import clip_grad_norm_fp32, copy_tensor_parallel_attributes, multi_tensor_applier
 

colossalai/kernel/__init__.py

-from .cuda_native import LayerNorm, FusedScaleMaskSoftmax, MultiHeadAttention
+from .cuda_native import FusedScaleMaskSoftmax, LayerNorm, MultiHeadAttention
 
-__all__ = ["LayerNorm", "FusedScaleMaskSoftmax", "MultiHeadAttention"]
+try:
+    from colossalai._C import fused_optim
+except:
+    from colossalai.kernel.op_builder.fused_optim import FusedOptimBuilder
+    fused_optim = FusedOptimBuilder().load()
+
+try:
+    from colossalai._C import cpu_optim
+except ImportError:
+    from colossalai.kernel.op_builder import CPUAdamBuilder
+    cpu_optim = CPUAdamBuilder().load()
+
+__all__ = ["fused_optim", "cpu_optim", "LayerNorm", "FusedScaleMaskSoftmax", "MultiHeadAttention"]

colossalai/nn/optimizer/fused_adam.py

@@ -65,11 +65,8 @@ class FusedAdam(torch.optim.Optimizer):
         self.adamw_mode = 1 if adamw_mode else 0
         self.set_grad_none = set_grad_none
         if multi_tensor_applier.available:
-            try:
-                from colossalai._C import fused_optim
-            except:
-                from colossalai.kernel.op_builder.fused_optim import FusedOptimBuilder
-                fused_optim = FusedOptimBuilder().load()
+            from colossalai.kernel import fused_optim
+
             # Skip buffer
             self._dummy_overflow_buf = torch.cuda.IntTensor([0])
             self.multi_tensor_adam = fused_optim.multi_tensor_adam

colossalai/nn/optimizer/fused_lamb.py

@@ -76,11 +76,7 @@ class FusedLAMB(torch.optim.Optimizer):
                         max_grad_norm=max_grad_norm)
         super(FusedLAMB, self).__init__(params, defaults)
         if multi_tensor_applier.available:
-            try:
-                from colossalai._C import fused_optim
-            except:
-                from colossalai.kernel.op_builder.fused_optim import FusedOptimBuilder
-                fused_optim = FusedOptimBuilder().load()
+            from colossalai.kernel import fused_optim
 
             self.multi_tensor_l2norm = fused_optim.multi_tensor_l2norm
             # Skip buffer

colossalai/nn/optimizer/fused_sgd.py

@@ -80,11 +80,8 @@ class FusedSGD(Optimizer):
         self.wd_after_momentum = wd_after_momentum
 
         if multi_tensor_applier.available:
-            try:
-                from colossalai._C import fused_optim
-            except:
-                from colossalai.kernel.op_builder import FusedOptimBuilder
-                fused_optim = FusedOptimBuilder().load()
+            from colossalai.kernel import fused_optim
+
             # Skip buffer
             self._dummy_overflow_buf = torch.tensor([0],
                                                     dtype=torch.int,

colossalai/nn/optimizer/hybrid_adam.py

@@ -76,13 +76,8 @@ class HybridAdam(NVMeOptimizer):
         default_args = dict(lr=lr, betas=betas, eps=eps, weight_decay=weight_decay, bias_correction=bias_correction)
         super(HybridAdam, self).__init__(model_params, default_args, nvme_offload_fraction, nvme_offload_dir)
         self.adamw_mode = adamw_mode
-        try:
-            from colossalai._C import cpu_optim, fused_optim
-        except ImportError:
-            from colossalai.kernel.op_builder import CPUAdamBuilder, FusedOptimBuilder
-            fused_optim = FusedOptimBuilder().load()
-            cpu_optim = CPUAdamBuilder().load()
 
+        from colossalai.kernel import cpu_optim, fused_optim
         self.cpu_adam_op = cpu_optim.CPUAdamOptimizer(lr, betas[0], betas[1], eps, weight_decay, adamw_mode)
 
         self.gpu_adam_op = fused_optim.multi_tensor_adam

colossalai/utils/common.py

@@ -4,28 +4,21 @@ import functools
 import os
 import random
 import socket
+from collections import defaultdict
+from contextlib import contextmanager
 from pathlib import Path
 from typing import Callable, Dict, List, Optional, Union
 
 import torch
+import torch.distributed as dist
 from torch._six import inf
 from torch.nn.parameter import Parameter
 
-try:
-    from colossalai._C import fused_optim
-except:
-    from colossalai.kernel.op_builder import FusedOptimBuilder
-    fused_optim = FusedOptimBuilder().load()
-
-from collections import defaultdict
-from contextlib import contextmanager
-
-import torch.distributed as dist
-
 from colossalai.constants import IS_TENSOR_PARALLEL, NUM_PARTITIONS, TENSOR_PARALLEL_ATTRIBUTES
 from colossalai.context.parallel_mode import ParallelMode
 from colossalai.core import global_context as gpc
 from colossalai.global_variables import tensor_parallel_env as env
+from colossalai.kernel import fused_optim
 from colossalai.tensor import ColoParameter, ProcessGroup
 
 from .multi_tensor_apply import multi_tensor_applier

colossalai/utils/multi_tensor_apply/multi_tensor_apply.py

@@ -14,7 +14,7 @@ class MultiTensorApply(object):
 
     def __init__(self, chunk_size):
         try:
-            import colossalai._C.fused_optim
+            from colossalai.kernel import fused_optim
             MultiTensorApply.available = True
             self.chunk_size = chunk_size
         except ImportError as err:

tests/test_optimizer/test_fused_adam_kernel.py

@@ -46,12 +46,7 @@ def torch_adam_update(
 @parameterize('p_dtype', [torch.float, torch.half])
 @parameterize('g_dtype', [torch.float, torch.half])
 def test_adam(adamw, step, p_dtype, g_dtype):
-    try:
-        import colossalai._C.fused_optim
-        fused_adam = colossalai._C.fused_optim.multi_tensor_adam
-    except:
-        from colossalai.kernel.op_builder import FusedOptimBuilder
-        fused_optim = FusedOptimBuilder().load()
+    from colossalai.kernel import fused_optim
     fused_adam = fused_optim.multi_tensor_adam
 
     dummy_overflow_buf = torch.cuda.IntTensor([0])