import float8_experimental only when fp8 is enabled and install it in CI (#464)

make sure to only import float8_experimental when fp8 is enabled

for 4 gpu CI, make sure we can import float8_experimental correctly in
CI

`python -m pip install
git+https://github.com/pytorch-labs/float8_experimental.git`

Author: weifengpy

.github/workflows/integration_test_4gpu.yaml

@@ -39,5 +39,6 @@ jobs:
 
         python -m pip install --force-reinstall --pre torch --index-url https://download.pytorch.org/whl/nightly/cu121
         python -m pip install --pre torchdata --index-url https://download.pytorch.org/whl/nightly/
+        python -m pip install git+https://github.com/pytorch-labs/float8_experimental.git
         mkdir artifacts-to-be-uploaded
         python ./test_runner.py artifacts-to-be-uploaded --ngpu 4

torchtitan/float8_linear.py

@@ -15,18 +15,17 @@
 import contextlib
 from typing import Optional
 
-import float8_experimental.config as config
-
 import torch
 import torch.nn as nn
-from float8_experimental.float8_linear import TensorScalingType
 
 from torchtitan.config_manager import JobConfig
 from torchtitan.logging_utils import logger
 
 
 @contextlib.contextmanager
 def set_enable_fsdp_fp8_all_gather(enable_fsdp_fp8_all_gather: bool):
+    import float8_experimental.config as config
+
     prev = config.enable_fsdp_fp8_all_gather
     torch.distributed.barrier()
     config.enable_fsdp_fp8_all_gather = enable_fsdp_fp8_all_gather
@@ -51,6 +50,7 @@ def build_fp8_linear(
         job_config.training.enable_fsdp_fp8_all_gather and dp_enabled
     )
     try:
+        from float8_experimental.float8_linear import TensorScalingType
         from float8_experimental.float8_linear_utils import (
             swap_linear_with_float8_linear,
         )

train.py

@@ -19,7 +19,6 @@
 
 import torch
 import torch.nn.functional as F
-from float8_experimental.fsdp_utils import precompute_float8_dynamic_scale_for_fsdp
 from torch.distributed import destroy_process_group
 from torch.distributed.checkpoint.stateful import Stateful
 from torch.distributed.elastic.multiprocessing.errors import record
@@ -404,6 +403,10 @@ def loss_fn(pred, labels):
                 and job_config.training.enable_fsdp_fp8_all_gather
                 and job_config.training.precompute_float8_dynamic_scale_for_fsdp
             ):
+                from float8_experimental.fsdp_utils import (
+                    precompute_float8_dynamic_scale_for_fsdp,
+                )
+
                 # calculate float8 dynamic amax/scale for all-parameter for FSDP2
                 # it issues a single all-reduce for all parameters at once for better performance
                 precompute_float8_dynamic_scale_for_fsdp(model)