[legacy] clean up legacy code (#4743)

* [legacy] remove outdated codes of pipeline (#4692)

* [legacy] remove cli of benchmark and update optim (#4690)

* [legacy] remove cli of benchmark and update optim

* [doc] fix cli doc test

* [legacy] fix engine clip grad norm

* [legacy] remove outdated colo tensor (#4694)

* [legacy] remove outdated colo tensor

* [test] fix test import

* [legacy] move outdated zero to legacy (#4696)

* [legacy] clean up utils (#4700)

* [legacy] clean up utils

* [example] update examples

* [legacy] clean up amp

* [legacy] fix amp module

* [legacy] clean up gpc (#4742)

* [legacy] clean up context

* [legacy] clean core, constants and global vars

* [legacy] refactor initialize

* [example] fix examples ci

* [example] fix examples ci

* [legacy] fix tests

* [example] fix gpt example

* [example] fix examples ci

* [devops] fix ci installation

* [example] fix examples ci

colossalai/legacy/context/process_group_initializer/initializer_2d.py

@@ -0,0 +1,155 @@
+import math
+
+import torch.distributed as dist
+
+from colossalai.legacy.global_variables import tensor_parallel_env as env
+from colossalai.legacy.registry import DIST_GROUP_INITIALIZER
+
+from ..parallel_mode import ParallelMode
+from .process_group_initializer import ProcessGroupInitializer
+
+
+def _check_summa_env_var(summa_dim):
+    # check environment variable for SUMMA
+    env_summa_dim = env.summa_dim
+
+    if env_summa_dim:
+        assert int(env_summa_dim) == summa_dim, \
+            'SUMMA_DIM has been set in the current environment and ' \
+            'does not match with the value passed to this initialized'
+    else:
+        env.summa_dim = summa_dim
+
+
+class Initializer_2D_Row(ProcessGroupInitializer):
+    """2d tensor parallel initialization among rows.
+
+    Args:
+        num_group (int): The number of all tensor groups.
+        summa_dim (int): The dimension of SUMMA.
+        rank (int): The rank of current process.
+        world_size (int): Size of whole communication world.
+        config (Config): Running configuration.
+        data_parallel_size (int): Size of data parallel.
+        pipeline_parallel_size (int): Size of pipeline parallel.
+        tensor_parallel_size (int): Size of tensor parallel.
+    """
+
+    def __init__(self, num_group, summa_dim, *args, **kwargs):
+        super(Initializer_2D_Row, self).__init__(*args, **kwargs)
+        self.num_group = num_group
+        self.summa_dim = summa_dim
+
+    def init_dist_group(self):
+        """Initialize 2D tensor row parallel groups, and assign local_ranks and groups to each gpu.
+        Returns:
+            Tuple (local_rank, group_world_size, process_group, ranks_in_group, mode):
+                2D tensor row parallelism's information in a tuple.
+        """
+        local_rank = None
+        ranks_in_group = None
+        process_group = None
+        cpu_group = None
+        group_world_size = None
+        mode = ParallelMode.PARALLEL_2D_ROW
+
+        for i in range(self.num_group):
+            for j in range(self.summa_dim):
+                ranks = [i * self.tensor_parallel_size + j * self.summa_dim + k for k in range(self.summa_dim)]
+                group = dist.new_group(ranks)
+                group_cpu = dist.new_group(ranks, backend='gloo') if dist.get_backend() != 'gloo' else group
+
+                if self.rank in ranks:
+                    local_rank = ranks.index(self.rank)
+                    group_world_size = len(ranks)
+                    process_group = group
+                    cpu_group = group_cpu
+                    ranks_in_group = ranks
+
+        return local_rank, group_world_size, process_group, cpu_group, ranks_in_group, mode
+
+
+class Initializer_2D_Col(ProcessGroupInitializer):
+    """2d tensor parallel initialization among cols.
+
+    Args:
+        num_group (int): The number of all tensor groups.
+        summa_dim (int): The dimension of SUMMA.
+        rank (int): The rank of current process.
+        world_size (int): Size of whole communication world.
+        config (Config): Running configuration.
+        data_parallel_size (int): Size of data parallel.
+        pipeline_parallel_size (int): Size of pipeline parallel.
+        tensor_parallel_size (int): Size of tensor parallel.
+    """
+
+    def __init__(self, num_group, summa_dim, *args, **kwargs):
+        super(Initializer_2D_Col, self).__init__(*args, **kwargs)
+        self.num_group = num_group
+        self.summa_dim = summa_dim
+
+    def init_dist_group(self):
+        """Initialize 2D tensor row parallel groups, and assign local_ranks and groups to each gpu.
+
+        Returns:
+            Tuple (local_rank, group_world_size, process_group, ranks_in_group, mode):
+                2D tensor col parallelism's information in a tuple.
+        """
+        local_rank = None
+        ranks_in_group = None
+        process_group = None
+        cpu_group = None
+        group_world_size = None
+        mode = ParallelMode.PARALLEL_2D_COL
+
+        for i in range(self.num_group):
+            for j in range(self.summa_dim):
+                ranks = [i * self.tensor_parallel_size + j + k * self.summa_dim for k in range(self.summa_dim)]
+                group = dist.new_group(ranks)
+                group_cpu = dist.new_group(ranks, backend='gloo') if dist.get_backend() != 'gloo' else group
+
+                if self.rank in ranks:
+                    local_rank = ranks.index(self.rank)
+                    group_world_size = len(ranks)
+                    process_group = group
+                    cpu_group = group_cpu
+                    ranks_in_group = ranks
+
+        return local_rank, group_world_size, process_group, cpu_group, ranks_in_group, mode
+
+
+@DIST_GROUP_INITIALIZER.register_module
+class Initializer_2D(ProcessGroupInitializer):
+    """
+    Serve as the single entry point to 2D parallel initialization.
+
+    Args:
+        rank (int): The rank of current process.
+        world_size (int): Size of whole communication world.
+        config (Config): Running configuration.
+        data_parallel_size (int): Size of data parallel.
+        pipeline_parallel_size (int): Size of pipeline parallel.
+        tensor_parallel_size (int): Size of tensor parallel.
+    """
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.num_group = self.world_size // self.tensor_parallel_size
+        self.summa_dim = int(math.sqrt(self.tensor_parallel_size))
+
+        assert self.tensor_parallel_size == self.summa_dim ** 2, \
+            "2D summa dim should equal to tensor parallel size ^ 0.5"
+        _check_summa_env_var(self.summa_dim)
+
+        self.col_initializer = Initializer_2D_Col(self.num_group, self.summa_dim, *args, **kwargs)
+        self.row_initializer = Initializer_2D_Row(self.num_group, self.summa_dim, *args, **kwargs)
+
+    def init_dist_group(self):
+        """Initialize 2D tensor row and col parallel groups, and assign local_ranks and groups to each gpu.
+
+        Returns:
+            List[Tuple (local_rank, group_world_size, process_group, ranks_in_group, mode)]:
+                2D tensor parallelism's information in a list of tuples.
+        """
+        parallel_setting = [self.row_initializer.init_dist_group(), self.col_initializer.init_dist_group()]
+        return parallel_setting