[PYTHON] Better packaging

python/setup.py

@@ -63,19 +63,7 @@ class CMakeBuild(build_ext):
                       '-DBUILD_PYTHON_MODULE=ON',
                       '-DPYTHON_INCLUDE_DIRS=' + python_include_dirs,
                       '-DLLVM_CONFIG=' + find_llvm()]
-        # tensorflow compatibility
-        try:
-            import tensorflow as tf
-            tf_abi = tf.__cxx11_abi_flag__ if "__cxx11_abi_flag__" in tf.__dict__ else 0
-            tf_include_dirs = tf.sysconfig.get_include()
-            tf_libs = tf.sysconfig.get_link_flags()[1].replace('-l', '')
-            cmake_args += ['-DTF_INCLUDE_DIRS=' + tf_include_dirs,
-                        '-DTF_LIB_DIRS='     + tf.sysconfig.get_lib(),
-                        '-DTF_LIBS='         + tf_libs,
-                        '-DTF_ABI='          + str(tf_abi)]
-        except ModuleNotFoundError:
-            pass
-
+        # configuration
         cfg = 'Debug' if self.debug else 'Release'
         cfg = 'Release'
         build_args = ['--config', cfg]
@@ -104,8 +92,10 @@ find_llvm()
 directories = [x[0] for x in os.walk(os.path.join(os.path.pardir, 'include'))]
 data = []
 for d in directories:
-    files = glob.glob(os.path.join(d, '*.h'), recursive=False)
-    data += [os.path.relpath(f, os.path.pardir) for f in files]
+    for htype in ['h', 'hpp']:
+        files = glob.glob(os.path.join(d, f'*.{htype}'), recursive=False)
+        data += [os.path.relpath(f, os.path.pardir) for f in files]
+print(data)
 
 setup(
     name='triton',
@@ -114,7 +104,8 @@ setup(
     author_email='ptillet@g.harvard.edu',
     description='A language and compiler for custom Deep Learning operations',
     long_description='',
-    packages=['triton', 'triton/_C', 'triton/ops'],
+    packages=['triton', 'triton/_C', 'triton/ops', 'triton/nn'],
+    install_requires=['numpy', 'torch', 'sympy'],
     package_data={'': data},
     ext_modules=[CMakeExtension('triton', 'triton/_C/')],
     cmdclass=dict(build_ext=CMakeBuild),

python/triton/__init__.py

@@ -1,6 +1,7 @@
 from .kernel import *
 from .utils import *
 import triton.ops
+import triton.nn
 
 
 # clean-up libtriton resources

python/triton/ops/einsum.py

@@ -1,18 +1,21 @@
-import numpy as np
-import torch
 from math import ceil, log2
 from enum import IntEnum
-import triton
 from functools import reduce
 from operator import mul
-from sympy.parsing.sympy_parser import parse_expr
-import sympy as sp
 from collections import OrderedDict
 from collections import namedtuple
 import re
+import triton
+# torch
+import torch
+# numpy -- ideally removed in a future release
+import numpy as np
+# sympy -- ideally removed in a future release
+import sympy as sp
+from sympy.parsing.sympy_parser import parse_expr
 from sympy.printing.ccode import C89CodePrinter
 
-       
+
 class _einsum(torch.autograd.Function):
 
 
@@ -612,7 +615,7 @@ __global__ void {name}(
             TM, TN, TB, TZ = 64, 128, 1, 1
             self.macros =  {'TM': TM, 'TN': TN, 'TB': TB, 'TK': TK, 'TZ': TZ, 'TYPE': dtype}
             self.num_warps = [4]
-            if mask:
+            if mask is not None:
                 self.macros['MASK'] = '{0:#0{1}x}'.format(mask, 10)
             # save information on the operation
             self.expr_a = expr_a
@@ -696,7 +699,7 @@ __global__ void {name}(
         if ctx.needs_input_grad[2]:
             db = torch.empty_like(b)
             einsum(f'{expr_a},{expr_c}->{expr_b}', a, dy, db)
-        return None, da, db, None, None, None, None
+        return None, da, db, None, None, None, None, None
 
 
 def einsum(expr, a, b, output,