def testShapeInference(self):
dtype_list = [dtypes.int8, dtypes.int16, dtypes.int32, dtypes.int64,
dtypes.uint8, dtypes.uint16]
with self.test_session(use_gpu=True) as sess:
for dtype in dtype_list:
lhs = constant_op.constant([[0], [3], [5]], dtype=dtype)
rhs = constant_op.constant([[1, 2, 4]], dtype=dtype)
and_tensor = bitwise_ops.bitwise_and(lhs, rhs)
or_tensor = bitwise_ops.bitwise_or(lhs, rhs)
xor_tensor = bitwise_ops.bitwise_xor(lhs, rhs)
ls_tensor = bitwise_ops.left_shift(lhs, rhs)
rs_tensor = bitwise_ops.right_shift(lhs, rhs)
and_result, or_result, xor_result, ls_result, rs_result = sess.run(
[and_tensor, or_tensor, xor_tensor, ls_tensor, rs_tensor])
# Compare shape inference with result
self.assertAllEqual(and_tensor.get_shape().as_list(), and_result.shape)
self.assertAllEqual(and_tensor.get_shape().as_list(), [3, 3])
self.assertAllEqual(or_tensor.get_shape().as_list(), or_result.shape)
self.assertAllEqual(or_tensor.get_shape().as_list(), [3, 3])
self.assertAllEqual(xor_tensor.get_shape().as_list(), xor_result.shape)
self.assertAllEqual(xor_tensor.get_shape().as_list(), [3, 3])
self.assertAllEqual(ls_tensor.get_shape().as_list(), ls_result.shape)
self.assertAllEqual(ls_tensor.get_shape().as_list(), [3, 3])
self.assertAllEqual(rs_tensor.get_shape().as_list(), rs_result.shape)
self.assertAllEqual(rs_tensor.get_shape().as_list(), [3, 3])
def testShapeInference(self):
dtype_list = [dtypes.int8, dtypes.int16, dtypes.int32, dtypes.int64,
dtypes.uint8, dtypes.uint16]
with self.session(use_gpu=True) as sess:
for dtype in dtype_list:
lhs = constant_op.constant([[0], [3], [5]], dtype=dtype)
rhs = constant_op.constant([[1, 2, 4]], dtype=dtype)
and_tensor = bitwise_ops.bitwise_and(lhs, rhs)
or_tensor = bitwise_ops.bitwise_or(lhs, rhs)
xor_tensor = bitwise_ops.bitwise_xor(lhs, rhs)
ls_tensor = bitwise_ops.left_shift(lhs, rhs)
rs_tensor = bitwise_ops.right_shift(lhs, rhs)
and_result, or_result, xor_result, ls_result, rs_result = sess.run(
[and_tensor, or_tensor, xor_tensor, ls_tensor, rs_tensor])
# Compare shape inference with result
self.assertAllEqual(and_tensor.get_shape().as_list(), and_result.shape)
self.assertAllEqual(and_tensor.get_shape().as_list(), [3, 3])
self.assertAllEqual(or_tensor.get_shape().as_list(), or_result.shape)
self.assertAllEqual(or_tensor.get_shape().as_list(), [3, 3])
self.assertAllEqual(xor_tensor.get_shape().as_list(), xor_result.shape)
self.assertAllEqual(xor_tensor.get_shape().as_list(), [3, 3])
self.assertAllEqual(ls_tensor.get_shape().as_list(), ls_result.shape)
self.assertAllEqual(ls_tensor.get_shape().as_list(), [3, 3])
self.assertAllEqual(rs_tensor.get_shape().as_list(), rs_result.shape)
self.assertAllEqual(rs_tensor.get_shape().as_list(), [3, 3])
def testBinaryOps(self):
dtype_list = [dtypes.int8, dtypes.int16, dtypes.int32, dtypes.int64,
dtypes.uint8, dtypes.uint16]
with self.test_session(use_gpu=True) as sess:
for dtype in dtype_list:
lhs = constant_op.constant([0, 5, 3, 14], dtype=dtype)
rhs = constant_op.constant([5, 0, 7, 11], dtype=dtype)
and_result, or_result, xor_result = sess.run(
[bitwise_ops.bitwise_and(lhs, rhs),
bitwise_ops.bitwise_or(lhs, rhs),
bitwise_ops.bitwise_xor(lhs, rhs)])
self.assertAllEqual(and_result, [0, 0, 3, 10])
self.assertAllEqual(or_result, [5, 5, 7, 15])
self.assertAllEqual(xor_result, [5, 5, 4, 5])
def testBinaryOps(self):
dtype_list = [dtypes.int8, dtypes.int16, dtypes.int32, dtypes.int64,
dtypes.uint8, dtypes.uint16, dtypes.uint32, dtypes.uint64]
with self.session(use_gpu=True) as sess:
for dtype in dtype_list:
lhs = constant_op.constant([0, 5, 3, 14], dtype=dtype)
rhs = constant_op.constant([5, 0, 7, 11], dtype=dtype)
and_result, or_result, xor_result = sess.run(
[bitwise_ops.bitwise_and(lhs, rhs),
bitwise_ops.bitwise_or(lhs, rhs),
bitwise_ops.bitwise_xor(lhs, rhs)])
self.assertAllEqual(and_result, [0, 0, 3, 10])
self.assertAllEqual(or_result, [5, 5, 7, 15])
self.assertAllEqual(xor_result, [5, 5, 4, 5])
def bitwise_xnor(a, b):
# Need to do some dim expanding to handle batches.
a = tf.expand_dims(a, axis=1)
b = tf.expand_dims(b, axis=0)
ab = bitwise_ops.invert(bitwise_ops.bitwise_xor(a, b))
return ab
