PyTorch 1.3+ build support (#135)

* add support for torch 1.3+ builds inside a docker build environment
* remove apex imports

deepspeed/pt/deepspeed_light.py

@@ -26,9 +26,6 @@ from deepspeed.pt.deepspeed_constants import ROUTE_TRAIN, ROUTE_PREDICT, \
 import deepspeed.pt.deepspeed_lr_schedules as lr_schedules
 from deepspeed.pt.deepspeed_csr_tensor import CSRTensor
 
-from apex import amp
-from apex.optimizers.fused_adam import FusedAdam
-
 MEMORY_OPT_ALLREDUCE_SIZE = 500000000
 SUMMARY_WRITER_DIR_NAME = "JobId"
 
@@ -458,6 +455,7 @@ class DeepSpeedLight(Module):
         if self.fp16_enabled() and 'max_grad_norm' in optimizer_parameters.keys():
             optimizer_parameters['max_grad_norm'] = 0.0
         if self.optimizer_name() == ADAM_OPTIMIZER:
+            from apex.optimizers.fused_adam import FusedAdam
             optimizer = FusedAdam(model_parameters, **optimizer_parameters)
         elif self.optimizer_name() == LAMB_OPTIMIZER:
             optimizer = FusedLamb(model_parameters, **optimizer_parameters)

setup.py

@@ -8,6 +8,7 @@ Create a new wheel via the following command: python setup.py bdist_wheel
 The wheel will be located at: dist/*.whl
 """
 
+import os
 import torch
 from deepspeed import __version__ as ds_version
 from setuptools import setup, find_packages
@@ -17,6 +18,30 @@ cmdclass = {}
 ext_modules = []
 cmdclass['build_ext'] = BuildExtension
 
+TORCH_MAJOR = int(torch.__version__.split('.')[0])
+TORCH_MINOR = int(torch.__version__.split('.')[1])
+
+if not torch.cuda.is_available():
+    # Fix to allow docker buils, similar to https://github.com/NVIDIA/apex/issues/486
+    print(
+        "[WARNING] Torch did not find cuda available, if cross-compling or running with cpu only "
+        "you can ignore this message. Adding compute capability for Pascal, Volta, and Turing "
+        "(compute capabilities 6.0, 6.1, 6.2)")
+    if os.environ.get("TORCH_CUDA_ARCH_LIST", None) is None:
+        os.environ["TORCH_CUDA_ARCH_LIST"] = "6.0;6.1;6.2;7.0;7.5"
+
+# Fix from apex that might be relevant for us as well, related to https://github.com/NVIDIA/apex/issues/456
+version_ge_1_1 = []
+if (TORCH_MAJOR > 1) or (TORCH_MAJOR == 1 and TORCH_MINOR > 0):
+    version_ge_1_1 = ['-DVERSION_GE_1_1']
+version_ge_1_3 = []
+if (TORCH_MAJOR > 1) or (TORCH_MAJOR == 1 and TORCH_MINOR > 2):
+    version_ge_1_3 = ['-DVERSION_GE_1_3']
+version_ge_1_5 = []
+if (TORCH_MAJOR > 1) or (TORCH_MAJOR == 1 and TORCH_MINOR > 4):
+    version_ge_1_5 = ['-DVERSION_GE_1_5']
+version_dependent_macros = version_ge_1_1 + version_ge_1_3 + version_ge_1_5
+
 ext_modules.append(
     CUDAExtension(name='fused_lamb_cuda',
                   sources=['csrc/fused_lamb_cuda.cpp',
@@ -24,9 +49,9 @@ ext_modules.append(
                   extra_compile_args={
                       'cxx': [
                           '-O3',
-                      ],
+                      ] + version_dependent_macros,
                       'nvcc': ['-O3',
-                               '--use_fast_math']
+                               '--use_fast_math'] + version_dependent_macros
                   }))
 
 setup(name='deepspeed',