Update GpuDnnConvGradI to use new config flags

theano/sandbox/cuda/dnn.py

@@ -872,25 +872,44 @@ class GpuDnnConvGradI(DnnBase, COp):
     :param descr: the convolution descriptor
 
     """
-    __props__ = ('workmem', 'inplace',)
+    __props__ = ('algo', 'inplace',)
     __input_name__ = ('kernel', 'grad', 'output', 'descriptor', 'alpha', 'beta')
 
-    def __init__(self, inplace=False, workmem=None):
+    def __init__(self, inplace=False, workmem=None, algo=None):
+        """
+        :param workmem: *deprecated*, use param algo instead
+        :param algo: either 'none', 'deterministic', 'fft', 'guess_once' or
+        'guess_on_shape_change'.
+        Default is the value of :attr:`config.dnn.conv.algo_bwd`.
+        """
         COp.__init__(self, ["dnn_base.c", "dnn_conv_base.c", "dnn_gi.c"],
                      "APPLY_SPECIFIC(conv_gi)")
-        if workmem is None:
-            workmem = config.dnn.conv.workmem_bwd
-        self.workmem = workmem
+
+        if workmem is not None:
+            warnings.warn(("GpuDnnConvGradI: parameter 'workmem' is "
+                           "deprecated. Use 'algo' instead."), stacklevel=3)
+            assert algo == None
+            self.algo = workmem
+        else:
+            if algo is None:
+                algo = config.dnn.conv.algo_bwd
+            self.algo = algo
+
         self.inplace = inplace
         if self.inplace:
             self.destroy_map = {0: [2]}
-        assert self.workmem in ['none', 'deterministic', 'fft', 'guess',
-                                'guess_once']
+        assert self.algo in ['none', 'deterministic', 'fft', 'guess_once',
+                                'guess_on_shape_change']
 
     def __setstate__(self, d):
         self.__dict__.update(d)
-        if not hasattr(self, 'workmem'):
-            self.workmem = 'none'
+        if not hasattr(self, 'algo'):
+            if hasattr(self, 'workmem'):
+                self.algo = self.workmem
+            else:
+                self.algo = 'none'
+        if not hasattr(self, 'inplace'):
+            self.inplace = False
 
     def grad(self, inp, grads):
         kerns, top, output, desc, alpha, beta = inp
@@ -921,21 +940,21 @@ class GpuDnnConvGradI(DnnBase, COp):
             alg_def = ('CONV_ALGO', '0')
             alg_choose_def = ('CHOOSE_ALGO', '0')
         else:
-            if self.workmem == 'none':
+            if self.algo == 'none':
                 alg_def = ('CONV_ALGO', 'CUDNN_CONVOLUTION_BWD_DATA_ALGO_0')
                 alg_choose_def = ('CHOOSE_ALGO', '0')
-            elif self.workmem == 'deterministic':
+            elif self.algo == 'deterministic':
                 alg_def = ('CONV_ALGO', 'CUDNN_CONVOLUTION_BWD_DATA_ALGO_1')
                 alg_choose_def = ('CHOOSE_ALGO', '0')
-            elif self.workmem == 'fft':
+            elif self.algo == 'fft':
                 alg_def = ('CONV_ALGO', 'CUDNN_CONVOLUTION_BWD_DATA_ALGO_FFT')
                 alg_choose_def = ('CHOOSE_ALGO', '0')
-            elif self.workmem in ['guess', 'guess_once']:
+            elif self.algo in ['guess_once', 'guess_on_shape_change']:
                 # The convolution implementation should be choosen according
                 # to a heuristic
                 alg_def = ('CONV_ALGO', 'CUDNN_CONVOLUTION_BWD_DATA_ALGO_0')
                 alg_choose_def = ('CHOOSE_ALGO', '1')
-                if self.workmem == 'guess_once':
+                if self.algo == 'guess_once':
                     alg_choose_once_def = ('CHOOSE_ALGO_ONCE', '1')
 
         return inplace_def + [alg_def, alg_choose_def, alg_choose_once_def]