Factor out the config flags for dnn to avoid errors.

theano/sandbox/cuda/dnn.py

@@ -10,7 +10,6 @@ from theano.gof import Optimizer, local_optimizer, COp
 from theano.gof.type import CDataType, Generic
 from theano.compile import optdb
 from theano.compile.ops import shape_i
-from theano.configparser import AddConfigVar, EnumStr
 from theano.tensor.nnet import SoftmaxGrad
 from theano.tensor.signal.downsample import (
     DownsampleFactorMax, MaxPoolGrad, AveragePoolGrad)
@@ -28,6 +27,8 @@ from theano.sandbox.cuda import gpu_seqopt, register_opt
 
 from theano.sandbox.cuda.nvcc_compiler import NVCC_compiler
 
+import theano.sandbox.dnn_flags
+
 
 def dnn_available():
     if dnn_available.avail is None:
@@ -62,8 +63,8 @@ if ((err = cudnnCreate(&_handle)) != CUDNN_STATUS_SUCCESS) {
             # exclusive mode, this cause bad detection.
             comp, out, err = NVCC_compiler.try_flags(
                 ["-l", "cudnn", "-I" + os.path.dirname(__file__),
-                 "-I" + os.path.join(theano.config.cuda.root, 'include'),
-                 "-L" + os.path.join(theano.config.cuda.root, 'lib64')],
+                 "-I" + config.dnn.include_path,
+                 "-L" + config.dnn.library_path],
                 preambule=preambule, body=body,
                 try_run=False, output=True)
 
@@ -141,7 +142,6 @@ if (%(err)s != CUDNN_STATUS_SUCCESS) {
     %(fail)s
 }
 }
-
         """ % dict(var=var, err=err, desc=desc, fail=fail)
 
 
@@ -359,37 +359,9 @@ class GpuDnnConvDesc(GpuOp):
     def c_code_cache_version(self):
         return (2, version())
 
-
-AddConfigVar('dnn.conv.workmem',
-             "This flag is deprecated; use dnn.conv.algo_fwd.",
-             EnumStr(''),
-             in_c_key=False)
-
-AddConfigVar('dnn.conv.workmem_bwd',
-             "This flag is deprecated; use dnn.conv.algo_bwd.",
-             EnumStr(''),
-             in_c_key=False)
-
-AddConfigVar('dnn.conv.algo_fwd',
-             "Default implementation to use for CuDNN forward convolution.",
-             EnumStr('small', 'none', 'large', 'fft', 'guess_once',
-                     'guess_on_shape_change', 'time_once',
-                     'time_on_shape_change'),
-             in_c_key=False)
-
-AddConfigVar('dnn.conv.algo_bwd',
-             "Default implementation to use for CuDNN backward convolution.",
-             EnumStr('none', 'deterministic', 'fft', 'guess_once',
-                     'guess_on_shape_change', 'time_once',
-                     'time_on_shape_change'),
-             in_c_key=False)
-
-
 # scalar constants
 _zero = constant(numpy.asarray(0.0, dtype='float32'))
 _one = constant(numpy.asarray(1.0, dtype='float32'))
-_ifour = constant(numpy.asarray(4, dtype='int32'))
-_ifive = constant(numpy.asarray(5, dtype='int32'))
 
 
 def ensure_float(val, default, name):
@@ -406,20 +378,6 @@ def ensure_float(val, default, name):
     return val
 
 
-def ensure_int(val, default, name):
-    if val is None:
-        return default.clone()
-    if not isinstance(val, Variable):
-        val = constant(val)
-    if hasattr(val, 'ndim') and val.ndim == 0:
-        val = as_scalar(val)
-    if not isinstance(val.type, theano.scalar.Scalar):
-        raise TypeError("%s: expected a scalar value" % (name,))
-    if not val.type.dtype == 'int32':
-        raise TypeError("%s: type is not int32" % (name,))
-    return val
-
-
 class GpuDnnConv(DnnBase, COp):
     """
     The forward convolution.

theano/sandbox/dnn_flags.py

+"""
+This module contains the configuration flags for cudnn support.
+
+Those are shared between the cuda and gpuarray backend which is why
+they are in this file.
+"""
+import os.path
+
+from theano.configparser import AddConfigVar, EnumStr, StrParam
+from theano import config
+
+AddConfigVar('dnn.conv.workmem',
+             "This flag is deprecated; use dnn.conv.algo_fwd.",
+             EnumStr(''),
+             in_c_key=False)
+
+AddConfigVar('dnn.conv.workmem_bwd',
+             "This flag is deprecated; use dnn.conv.algo_bwd.",
+             EnumStr(''),
+             in_c_key=False)
+
+AddConfigVar('dnn.conv.algo_fwd',
+             "Default implementation to use for CuDNN forward convolution.",
+             EnumStr('small', 'none', 'large', 'fft', 'guess_once',
+                     'guess_on_shape_change', 'time_once',
+                     'time_on_shape_change'),
+             in_c_key=False)
+
+AddConfigVar('dnn.conv.algo_bwd',
+             "Default implementation to use for CuDNN backward convolution.",
+             EnumStr('none', 'deterministic', 'fft', 'guess_once',
+                     'guess_on_shape_change', 'time_once',
+                     'time_on_shape_change'),
+             in_c_key=False)
+
+AddConfigVar('dnn.include_path',
+             "Location of the cudnn header (defaults to the cuda root)",
+             StrParam(lambda: os.path.join(config.cuda.root, 'include')))
+
+AddConfigVar('dnn.library_path',
+             "Location of the cudnn header (defaults to the cuda root)",
+             StrParam(lambda: os.path.join(config.cuda.root, 'lib64')))

theano/sandbox/gpuarray/dnn.py

@@ -10,7 +10,6 @@ from theano.gof.cmodule import GCC_compiler
 from theano.gof.type import CDataType, Generic
 from theano.compile import optdb
 from theano.compile.ops import shape_i
-from theano.configparser import AddConfigVar, EnumStr, StrParam
 from theano.tensor.nnet import SoftmaxGrad
 from theano.tensor.signal.downsample import (
     DownsampleFactorMax, MaxPoolGrad, AveragePoolGrad)
@@ -27,21 +26,7 @@ from .nnet import GpuSoftmax
 from .opt import gpu_seqopt, register_opt, conv_groupopt, op_lifter
 from .opt_util import alpha_merge, output_merge
 
-# This is to avoid conflict with the one in cuda/dnn.py
-if not hasattr(config, 'dnn'):
-    AddConfigVar('dnn.conv.workmem',
-                 "Default value for the workmem attribute of cudnn "
-                 "convolutions.",
-                 EnumStr('small', 'none', 'large'),
-                 in_c_key=False)
-
-AddConfigVar('dnn.include_path',
-             "Location of the cudnn header (defaults to the cuda root)",
-             StrParam(lambda: os.path.join(config.cuda.root, 'include')))
-
-AddConfigVar('dnn.library_path',
-             "Location of the cudnn header (defaults to the cuda root)",
-             StrParam(lambda: os.path.join(config.cuda.root, 'lib64')))
+from theano.sandbox import dnn_flags
 
 
 def dnn_available():
@@ -186,7 +171,6 @@ class DnnBase(COp):
 
 
 class DnnVersion(Op):
-
     __props__ = ()
 
     def c_headers(self):