Merge pull request #2280 from nouiz/import_fix

theano/sandbox/cuda/__init__.py

@@ -9,11 +9,29 @@ import sys
 import theano
 from theano.compat import get_unbound_function
 from theano.compile import optdb
+from theano.gof import EquilibriumDB, SequenceDB
 from theano.gof.cmodule import get_lib_extension
 from theano.gof.compilelock import get_lock, release_lock
 from theano.configparser import config, AddConfigVar, StrParam, BoolParam
 import nvcc_compiler
 
+# ignore_newtrees is to speed the optimization as this is the pattern
+# we use for optimization. Otherwise, we can iterate 100s of time on
+# the graph and apply only a few optimizations each time.
+gpu_optimizer = EquilibriumDB(ignore_newtrees=False)
+gpu_seqopt = SequenceDB()
+
+
+def register_opt(*tags, **kwargs):
+    def f(local_opt):
+        name = (kwargs and kwargs.pop('name')) or local_opt.__name__
+        gpu_optimizer.register(name, local_opt, 'fast_run', 'fast_compile',
+                               'gpu', *tags)
+        return local_opt
+    return f
+
+
+
 _logger_name = 'theano.sandbox.cuda'
 _logger = logging.getLogger(_logger_name)
 

theano/sandbox/cuda/dnn.py

@@ -2,7 +2,7 @@ import os
 
 import theano
 from theano import Apply, gof, tensor
-from theano.gof import Optimizer
+from theano.gof import Optimizer, local_optimizer
 from theano.gof.type import CDataType
 from theano.compat import PY3
 from theano.tensor.nnet import SoftmaxGrad
@@ -13,7 +13,7 @@ from theano.sandbox.cuda.basic_ops import (as_cuda_ndarray_variable,
 from theano.sandbox.cuda.blas import (GpuConv, GpuDownsampleFactorMax,
                                       GpuDownsampleFactorMaxGrad)
 from theano.sandbox.cuda.nnet import GpuSoftmax
-from theano.sandbox.cuda.opt import register_opt
+from theano.sandbox.cuda import gpu_seqopt, register_opt
 
 from theano.sandbox.cuda.nvcc_compiler import NVCC_compiler
 
@@ -1145,12 +1145,8 @@ err%(name)s = cudnnSoftmaxBackward(
 """
 
 
-# We need this since other stuff from opt is not importable.
-if cuda_available:
-
-    from theano.sandbox.cuda.opt import (
-        local_optimizer, gpu_optimizer, gpu_seqopt)
-
+# Intentation for history
+if True:
     #@register_opt('cudnn')  # this optimizer is registered in opt.py instead.
     @local_optimizer([GpuConv])
     def local_conv_dnn(node):

theano/sandbox/cuda/extra_ops.py

@@ -3,9 +3,8 @@ import copy
 from theano import Op
 from theano.gof import local_optimizer
 from theano.sandbox.cuda import cuda_available, GpuOp
-
+from theano.sandbox.cuda.basic_ops import GpuFlatten
 from theano.tensor.extra_ops import CumsumOp
-from theano.sandbox.cuda import GpuFlatten
 
 if cuda_available:
     from theano.sandbox.cuda import CudaNdarrayType

theano/sandbox/cuda/opt.py

@@ -13,7 +13,7 @@ from theano import config, tensor, gof
 import theano.ifelse
 
 from theano.compile import optdb
-from theano.gof import (local_optimizer, EquilibriumDB, SequenceDB, ProxyDB,
+from theano.gof import (local_optimizer, EquilibriumDB, ProxyDB,
                         Optimizer, toolbox)
 from theano.gof.python25 import all, any
 from theano.sandbox.cuda.basic_ops import (
@@ -42,6 +42,7 @@ from theano.sandbox.cuda.elemwise import SupportCodeError
 from theano.scalar.basic_scipy import Erfinv
 from theano.sandbox.cuda.elemwise import erfinv_gpu
 from theano.sandbox.cuda.var import CudaNdarrayConstant
+from theano.sandbox.cuda import gpu_optimizer, register_opt, gpu_seqopt
 from theano.scan_module import scan_utils, scan_op, scan_opt
 from theano.tensor.blas import _is_real_vector, _is_real_matrix
 from theano.tensor import nlinalg
@@ -56,12 +57,7 @@ except ImportError:
 
 #optdb.print_summary()  # shows what is currently registered
 
-#ignore_newtrees is to speed the optimization as this is the pattern
-#we use for optimization. Otherwise, we can iterate 100s of time on
-#the graph and apply only a few optimizations each time.
-gpu_optimizer = EquilibriumDB(ignore_newtrees=False)
 gpu_cut_copies = EquilibriumDB()
-gpu_seqopt = SequenceDB()
 gpu_seqopt.register('gpu_local_optimizations', gpu_optimizer, 1,
         'fast_run', 'fast_compile', 'inplace', 'gpu')
 gpu_seqopt.register('gpu_cut_transfers', gpu_cut_copies, 2,
@@ -84,14 +80,6 @@ gpu_optimizer.register('gpu_merge', theano.gof.opt.merge_optimizer,
                        'fast_run', 'fast_compile')
 
 
-def register_opt(*tags, **kwargs):
-    def f(local_opt):
-        name = (kwargs and kwargs.pop('name')) or local_opt.__name__
-        gpu_optimizer.register(name, local_opt, 'fast_run', 'fast_compile',
-                               'gpu', *tags)
-        return local_opt
-    return f
-
 #register local_track_shape_i at this level too
 #to make multi-level lift of shape work.
 register_opt()(theano.tensor.opt.local_track_shape_i)