我们从Python开源项目中，提取了以下5个代码示例，用于说明如何使用theano.tensor.and_()。
def test_and(self): mode = theano.compile.get_default_mode().including('canonicalize') x = T.scalar('x', dtype='int8') for zero, one in [(numpy.int8(0), numpy.int8(1)), (0, 1)]: f = theano.function([x], T.and_(x, zero), mode=mode) self.assert_eqs_const(f, 0) f = theano.function([x], T.and_(zero, x), mode=mode) self.assert_eqs_const(f, 0) f = theano.function([x], T.and_(x, one), mode=mode) if f.outputs[0].variable.dtype == x.dtype: self.assert_identity(f) f = theano.function([x], T.and_(one, x), mode=mode) if f.outputs[0].variable.dtype == x.dtype: self.assert_identity(f)
def and_(self, l, r): return T.and_(l, r)
def sylu(gain=10, spread=0.1): return lambda x: switch(T.ge(x, (1 / spread)), gain, 0) + \ switch(T.and_(T.gt((1 / spread), x), T.gt(x, -(1 / spread))), gain * spread * x, 0) + \ switch(T.le(x, -(1 / spread)), -gain, 0) # Exponential Linear Unit
def test_elemwise(self): # float Ops mats = theano.tensor.matrices('cabxy') c, a, b, x, y = mats s1 = T.switch(c, a, b) s2 = T.switch(c, x, y) for op in (T.add, T.sub, T.mul, T.true_div, T.int_div, T.floor_div, T.minimum, T.maximum, T.gt, T.lt, T.ge, T.le, T.eq, T.neq, T.pow): g = optimize(FunctionGraph(mats, [op(s1, s2)])) assert str(g).count('Switch') == 1 # integer Ops mats = theano.tensor.imatrices('cabxy') c, a, b, x, y = mats s1 = T.switch(c, a, b) s2 = T.switch(c, x, y) for op in (T.and_, T.or_, T.xor, T.bitwise_and, T.bitwise_or, T.bitwise_xor): g = optimize(FunctionGraph(mats, [op(s1, s2)])) assert str(g).count('Switch') == 1 # add/mul with more than two inputs u, v = theano.tensor.matrices('uv') s3 = T.switch(c, u, v) for op in (T.add, T.mul): g = optimize(FunctionGraph(mats + [u, v], [op(s1, s2, s3)])) assert str(g).count('Switch') == 1
