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 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 testShiftsWithNegativeLHS(self): dtype_list = [np.int8, np.int16, np.int32, np.int64] with self.test_session(use_gpu=True) as sess: for dtype in dtype_list: lhs = np.array([-1, -5, -3, -14], dtype=dtype) rhs = np.array([5, 0, 7, 11], dtype=dtype) left_shift_result, right_shift_result = sess.run( [bitwise_ops.left_shift(lhs, rhs), bitwise_ops.right_shift(lhs, rhs)]) self.assertAllEqual(left_shift_result, np.left_shift(lhs, rhs)) self.assertAllEqual(right_shift_result, np.right_shift(lhs, rhs))
def testShiftsWithNegativeLHS(self): dtype_list = [np.int8, np.int16, np.int32, np.int64] with self.session(use_gpu=True) as sess: for dtype in dtype_list: lhs = np.array([-1, -5, -3, -14], dtype=dtype) rhs = np.array([5, 0, 7, 11], dtype=dtype) left_shift_result, right_shift_result = sess.run( [bitwise_ops.left_shift(lhs, rhs), bitwise_ops.right_shift(lhs, rhs)]) self.assertAllEqual(left_shift_result, np.left_shift(lhs, rhs)) self.assertAllEqual(right_shift_result, np.right_shift(lhs, rhs))
def _shift_right_arithmetic_helper(x, y, name=None): """Performs an integer right arithmetic shift irrespective of input type.""" assert y.dtype == x.dtype dtype = x.dtype unsigned = dtype in _UNSIGNED_TO_SIGNED_TABLE if unsigned: signed_dtype = _UNSIGNED_TO_SIGNED_TABLE[dtype] x = math_ops.cast(x, signed_dtype) y = math_ops.cast(y, signed_dtype) output = bitwise_ops.right_shift(x, y, name=name) if unsigned: output = math_ops.cast(output, dtype) return output
def _shift_right_logical_helper(x, y, name=None): """Performs an integer right logical shift irrespective of input type.""" assert y.dtype == x.dtype dtype = x.dtype signed = dtype in _SIGNED_TO_UNSIGNED_TABLE if signed: unsigned_dtype = _SIGNED_TO_UNSIGNED_TABLE[dtype] x = math_ops.cast(x, unsigned_dtype) y = math_ops.cast(y, unsigned_dtype) output = bitwise_ops.right_shift(x, y, name=name) if signed: output = math_ops.cast(output, dtype) return output
def testImplementationDefinedShiftsDoNotCrash(self): dtype_list = [np.int8, np.int16, np.int32, np.int64] with self.test_session(use_gpu=True) as sess: for dtype in dtype_list: lhs = np.array([-1, -5, -3, -14], dtype=dtype) rhs = np.array([-2, 64, 101, 32], dtype=dtype) # We intentionally do not test for specific values here since the exact # outputs are implementation-defined. However, we should not crash or # trigger an undefined-behavior error from tools such as # AddressSanitizer. sess.run([bitwise_ops.left_shift(lhs, rhs), bitwise_ops.right_shift(lhs, rhs)])
def testImplementationDefinedShiftsDoNotCrash(self): dtype_list = [np.int8, np.int16, np.int32, np.int64] with self.session(use_gpu=True) as sess: for dtype in dtype_list: lhs = np.array([-1, -5, -3, -14], dtype=dtype) rhs = np.array([-2, 64, 101, 32], dtype=dtype) # We intentionally do not test for specific values here since the exact # outputs are implementation-defined. However, we should not crash or # trigger an undefined-behavior error from tools such as # AddressSanitizer. sess.run([bitwise_ops.left_shift(lhs, rhs), bitwise_ops.right_shift(lhs, rhs)])
def testShiftsWithPositiveLHS(self): dtype_list = [np.int8, np.int16, np.int32, np.int64, np.uint8, np.uint16, np.uint32, np.uint64] with self.session() as sess: for dtype in dtype_list: lhs = np.array([0, 5, 3, 14], dtype=dtype) rhs = np.array([5, 0, 7, 3], dtype=dtype) left_shift_result, right_shift_result = sess.run( [bitwise_ops.left_shift(lhs, rhs), bitwise_ops.right_shift(lhs, rhs)]) self.assertAllEqual(left_shift_result, np.left_shift(lhs, rhs)) self.assertAllEqual(right_shift_result, np.right_shift(lhs, rhs))