flake8, docstring and small crash fix

theano/gpuarray/blas.py

@@ -170,7 +170,7 @@ class GpuGemm(BlasOp):
         beta = as_tensor_variable(beta)
 
         if not (A.dtype == B.dtype == C.dtype):
-            raise TypeError(Gemm.E_mixed,
+            raise TypeError(theano.tensor.blas.Gemm.E_mixed,
                             (A.dtype, B.dtype, C.dtype,
                              alpha.dtype, beta.dtype))
         if A.dtype == 'float16':
@@ -178,7 +178,7 @@ class GpuGemm(BlasOp):
         else:
             assert alpha.dtype == beta.dtype == A.dtype
         if not A.dtype.startswith('float'):
-            raise TypeError(Gemm.E_float, (A.dtype))
+            raise TypeError(theano.tensor.blas.Gemm.E_float, (A.dtype))
         assert alpha.ndim == 0
         assert beta.ndim == 0
         assert A.ndim == 2

theano/gpuarray/tests/test_blas.py

@@ -25,9 +25,9 @@ GpuGemvTester = makeTester(
     op=gemv_inplace, gpu_op=gpugemv_inplace,
     cases=dict(dot_vv=[rand(1), 1, rand(1, 2), rand(2), 0],
                dot_vm=[rand(3), 1, rand(3, 2), rand(2), 0],
-#               float16=[rand(3).astype('float16'), np.float32(1),
-#                        rand(3, 2).astype('float16'),
-#                        rand(2).astype('float16'), np.float32(0)],
+               # float16=[rand(3).astype('float16'), np.float32(1),
+               # rand(3, 2).astype('float16'),
+               # rand(2).astype('float16'), np.float32(0)],
                float32=[rand(3).astype('float32'), np.float32(1),
                         rand(3, 2).astype('float32'),
                         rand(2).astype('float32'), np.float32(0)],
@@ -42,6 +42,21 @@ GpuGemvTester = makeTester(
     )
 
 
+def test_gemv_float16():
+    float16 = [rand(3).astype('float16'),
+               np.asarray(1, dtype=np.float32),
+               rand(3, 2).astype('float16'),
+               rand(2).astype('float16'),
+               np.asarray(0.5, dtype=np.float32)]
+    float16 = [gpuarray_shared_constructor(val)
+               for val in float16]
+    o = gpugemv_no_inplace(*float16)
+    f = theano.function([], o)
+    y, alpha, A, x, beta = float16
+    out = f()
+    utt.assert_asclose(out, alpha * np.dot(A, x) + beta * y)
+
+
 class TestGpuSgemv(TestCase, BaseGemv, utt.TestOptimizationMixin):
     mode = mode_with_gpu
     dtype = 'float32'
@@ -68,9 +83,9 @@ GpuGemmTester = makeTester(
                test6=[rand(3, 4), 0.0, rand(3, 5), rand(5, 4), -1.0],
                test7=[rand(3, 4), -1.0, rand(3, 5), rand(5, 4), 0.0],
                test8=[rand(3, 4), -1.0, rand(3, 5), rand(5, 4), 1.1],
-#               float16=[rand(3, 4).astype('float16'), np.float32(-1.0),
-#                        rand(3, 5).astype('float16'),
-#                        rand(5, 4).astype('float16'), np.float32(-1.1)],
+               # float16=[rand(3, 4).astype('float16'), np.float32(-1.0),
+               # rand(3, 5).astype('float16'),
+               # rand(5, 4).astype('float16'), np.float32(-1.1)],
                float32=[rand(3, 4).astype('float32'), np.float32(-1.0),
                         rand(3, 5).astype('float32'),
                         rand(5, 4).astype('float32'), np.float32(-1.1)],

theano/gpuarray/type.py

@@ -25,13 +25,24 @@ _context_reg = {}
 
 
 def do_gpu_support(data):
+    """
+    Is the following data supported on the GPU?
+
+    Currently, only complex aren't supported.
+
+    Parameters
+    ----------
+    data : numpy.ndarray or TensorVariable
+           (it must have dtype and ndim parameter)
+    """
     return str(data.dtype) not in tensor.basic.complex_dtypes
 
+
 def move_to_gpu(data):
     """
     Do we want to move this computation to the GPU?
 
-    Currently, we don't move complex and scalar int.
+    Currently, we don't move complex and scalar.
 
     Parameters
     ----------