Remove non-ported code

theano/sandbox/gpuarray/tests/test_nnet.py

@@ -160,90 +160,3 @@ def test_GpuCrossentropySoftmax1HotWithBiasDx():
 
         assert False, "numpy.allclose(cpu_out, gpu_out, rtol=%s, atol=%s)" % (
                 rtol, atol)
-
-
-def test_softmax_with_bias():
-    """
-    This is basic test for GpuSoftmaxWithBias
-
-    We check that we loop when their is too much block
-
-    TODO: check that we loop when their is too much thread.(THIS IS
-    NOT IMPLEMENTED)
-    """
-    x = T.fmatrix('x')
-    # We can't use zeros_like(x[0,::]) as this don't allow to test with
-    # 0 shape.
-    z = T.nnet.softmax_with_bias(x, T.arange(x.shape[1] * 2,
-                                             dtype='float32')[::2])
-
-    f = theano.function([x], z, mode=mode_without_gpu)
-    f_gpu = theano.function([x], z, mode=mode_with_gpu)
-    assert f.maker.fgraph.toposort()[-1].op == T.nnet.softmax_with_bias
-    assert isinstance(f_gpu.maker.fgraph.toposort()[-2].op,
-                      cuda.nnet.GpuSoftmaxWithBias)
-
-    def cmp(n, m):
-        #print "test_softmax",n,m
-        data = numpy.arange(n * m, dtype='float32').reshape(n, m)
-        out = f(data)
-        gout = f_gpu(data)
-        assert numpy.allclose(out, gout), numpy.absolute(out - gout)
-
-    cmp(2, 5)
-    #we need to test n>32*1024 to check that we make the block loop.
-    cmp(2 << 15, 5)
-    cmp(4074, 400)
-    cmp(0, 10)
-    cmp(784, 784)
-    cmp(4, 1000)
-    cmp(4, 1024)
-    cmp(4, 2000)
-    cmp(4, 2024)
-    #GTX285 don't have enough shared mem for this case.
-    cmp(4, 4074)
-    # The GTX580, 680 and kepler don't have enough shared memory.
-    cmp(2, 10000)
-    cmp(128, 16 * 1024)
-    cmp(128, 64 * 1024)
-
-
-def test_softmax():
-    """
-    This is basic test for GpuSoftmax
-
-    We check that we loop when their is too much block
-    We use slower code when there isn't enough shared memory
-    """
-    x = T.fmatrix('x')
-
-    z = T.nnet.softmax(x)
-    f = theano.function([x], z, mode=mode_without_gpu)
-    f_gpu = theano.function([x], z, mode=mode_with_gpu)
-    assert f.maker.fgraph.toposort()[-1].op == T.nnet.softmax
-    assert isinstance(f_gpu.maker.fgraph.toposort()[-2].op,
-                      cuda.nnet.GpuSoftmax)
-
-    def cmp(n, m):
-        #print "test_softmax",n,m
-        data = numpy.arange(n * m, dtype='float32').reshape(n, m)
-        out = f(data)
-        gout = f_gpu(data)
-        assert numpy.allclose(out, gout), numpy.absolute(out - gout)
-
-    #we need to test n>32*1024 to check that we make the block loop.
-    cmp(2, 5)
-    cmp(2 << 15, 5)
-    cmp(4074, 400)
-    cmp(0, 10)
-    cmp(784, 784)
-    cmp(4, 1000)
-    cmp(4, 1024)
-    cmp(4, 2000)
-    cmp(4, 2024)
-    # The GTX285 don't have enough shared memory.
-    cmp(4, 4074)
-    # The GTX580, 680 and kepler don't have enough shared memory.
-    cmp(2, 10000)
-    cmp(128, 16 * 1024)
-    cmp(128, 64 * 1024)